patient satisfaction research paper

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Healthcare (Basel)
• PMC10048416

Measuring Patient Experience and Patient Satisfaction—How Are We Doing It and Why Does It Matter? A Comparison of European and U.S. American Approaches

Anna lena friedel.

1 Department of Neurosurgery and Spine Surgery, Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany

2 Institute for Medical Education, Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany

Sonja Siegel

Cedric fabian kirstein, monja gerigk.

3 Institute for Patient Experience, University Hospital Essen, University of Duisburg-Essen, Hohlweg 8, 45147 Essen, Germany

Ulrike Bingel

4 Department of Neurology, Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany

5 Digital Transformation Unit, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany

Oliver Steidle

6 Clinical Quality and Risk Management, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany

Steffen Haupeltshofer

Bernhard andermahr, witold chmielewski, ilonka kreitschmann-andermahr, associated data.

Not applicable.

(1) Background: Patients’ experiences and satisfaction with their treatment are becoming increasingly important in the context of quality assurance, but the measurement of these parameters is accompanied by several disadvantages such as poor cross-country comparability and methodological problems. The aim of this review is to describe and summarize the process of measuring, publishing, and utilizing patient experience and satisfaction data in countries with highly developed healthcare systems in Europe (Germany, Sweden, Finland, Norway, the United Kingdom) and the USA to identify possible approaches for improvement. (2) Methods: Articles published between 2000 and 2021 that address the topics described were identified. Furthermore, patient feedback in social media and the influence of sociodemographic and hospital characteristics on patient satisfaction and experience were evaluated. (3) Results: The literature reveals that all countries perform well in collecting patient satisfaction and experience data and making them publicly available. However, due to the use of various different questionnaires, comparability of the results is difficult, and consequences drawn from these data remain largely unclear. (4) Conclusions : Surveying patient experience and satisfaction with more unified as well as regularly updated questionnaires would be helpful to eliminate some of the described problems. Additionally, social media platforms must be considered as an increasingly important source to expand the range of patient feedback.

1. Introduction

Patients’ experiences of their own treatment and their satisfaction increasingly move into the focus as key quality indicators in many countries with highly developed healthcare systems. According to Bull [ 1 , 2 ], patient experience can be defined as “what” happened during an episode of care and “how” it happened from the patient’s perspective, whereas patient satisfaction rather captures the personal expectations and subjective opinions of the received care. Although both concepts are not interchangeable, they are complexly related, having a profound influence on each other and on treatment outcome [ 3 , 4 ]. Healthcare providers and researchers use patient experience and satisfaction scorings for general, indication-based, and disease-specific patient feedback [ 5 ] as tools to improve patient-centered healthcare or due to requirements by government or other regulatory authorities to conduct patient surveys on a regular basis. With respect to the evaluation of their impression of health service delivery, patients’ feedback on their treatment has also become an economic factor since reimbursement as well as the reputation of hospitals in some healthcare systems are also dependent on patients’ judgements of their received care [ 6 ].

To assess the patient view on received care, the treatment process, and related factors in a standardized way, patient-reported outcome measures (PROM) and patient-reported experience measures (PREM) are commonly used. Whereas PROM usually question specific aspects of treatment outcome by means of questionnaires, e.g., on health-related quality of life, PREM gather information on patient view of their health service experience and thus allow direct feedback to healthcare providers with the intention of improving the system and achieving integrative care [ 7 ]. However, there is a huge variety of approaches even in countries with high-quality healthcare, which is partly predefined by the different orientations and mandates of these systems. As a consequence, the already-existing PREM-surveys (e.g., HCAHPS, PPE-15, and PEQ) differ in validity and reliability [ 2 ].

In the face of this complex mix of issues, it is the aim of this review to describe and summarize the process of measuring, publishing, and utilizing patient experience and satisfaction data in countries with highly developed healthcare systems in Europe and the USA in order to identify possible leverage points for improving the collection of and consequences drawn from this important source of information.

2. Materials and Methods

Article search and selection strategy.

To incorporate the issues raised above, we opted for the preparation of a narrative review using the following approach: We studied healthcare rankings and reports (WHO report 2000 [ 8 , 9 ], KPMG report 2017 [ 10 ]; OECD report 2001 and 2019 [ 11 , 12 ]) in order to identify countries with highly developed healthcare systems that have a long history of measuring patient satisfaction on a regular basis but have different health system structures, reimbursement strategies, and access options for patients. These criteria, chosen to cover a wide spectrum of possibilities to implement the issue of patient satisfaction, resulted in the identification of the USA, UK, and Nordic countries (Norway, Sweden, and Finland). Therefore, studies from these countries were primarily selected for evaluation. Additionally, studies from the German healthcare system were included for comparison. Because the Internet has become one of the most important and easily accessible sources of information and feedback for patients, we also explicitly searched for studies reporting the issue of patient experience and patient satisfaction in social media.

The database search was conducted in PubMed ( Medline database primarily), Google Scholar , and Google in 2020–2021. Scientific articles, health reports, dissertations, and websites published between 2000 and 2021 in the English or German language were screened. Selected articles were also examined for references as an additional source for this review, leading to the inclusion of a few older articles. The following catchphrases were used during the database search: “patient”, “satisfaction”, “questionnaire”, “survey”, “patient experience”, “patient perspective, and “patient satisfaction” combined (“AND”) with “social media”, “hospital characteristics”, “socio-demographic characteristics”, “Germany”, “USA”, “UK”, “Scandinavia”, “Norway”, “Sweden”, or “Finland” and any combination (“AND”, “OR”) of the terms. The governmental healthcare surveys of the mentioned countries were used as additional search parameters for extracting information if available. A more detailed flow chart of the literature search with catchphrases for the different subsections as well as in- and exclusion criteria is provided as a flow chart as Supplementary Materials .

Inclusion and quality assessment were performed by interdisciplinary discussion among the authors of this article.

The results section starts with an overview on the most frequently used PREMS measuring patient experience and moves on to present data on this topic according to the countries mentioned above. We then provide the reader with an overview of studies on emerging new platforms of patient feedback, such as Internet databases, as well as studies analyzing the impact of sociodemographic and hospital characteristics. Whenever possible, we differentiated between the concept of patient experience and patient satisfaction. If the cited sources did not allow to make this distinction, we used both terms.

3.1. Surveys Measuring Patient Experience

In the countries focused on in this review, the most widely used instruments over the past 20 years are the Picker Patient Experience Questionnaire (PPE)-15 [ 13 ], the Hospital and Consumer Assessment of Healthcare Providers and Systems (HCAHPS) [ 14 ] (USA), the National Health Service Inpatient Survey (NHSIP) [ 15 ] (United Kingdom), and the Patient Experience Questionnaire (PEQ) (initially used in Norway) [ 16 , 17 ]. In Scandinavian countries, patient satisfaction is additionally measured with a variety of questionnaires tailored to country-specific healthcare aspects [ 18 , 19 ]. Since the numbers of patients investigated by these surveys are rather small, the instruments used are not described in more detail here. The four most widely used instruments for measuring patient experience of hospital treatment and their dimensions are described below. Their major characteristics are summarized in Table 1 .

Selected instruments capturing patient experience.

3.1.1. The Picker Patient Experience Questionnaire (PPE)-15

The PPE, as the first systematic assessment of patient experience, was developed and has been disseminated throughout the USA since 1987 and, since 1998, also in Europe [ 22 ]. The original instrument contained 40 items based on a systematic literature review, expert consultations, the conduction of patient focus groups, and in-depth interviews interrogating patient healthcare experiences. The current Picker Adult Inpatient Survey (PPE-15) [ 13 ], in use since 2002, is a revised and shortened version of the original PPE questionnaire. It now contains 15 items out of the original 40, querying issues from information and education to continuity and transition of healthcare. The questionnaire is intended to define problematic aspects of patients’ in-hospital stay that patients believe could be improved. Therefore, a dichotomous “problem score” indicating the presence or absence of a healthcare problem is derived from each item and used for statistical analysis. Based on their face validity, the items are grouped into eight dimensions (cf. Table 1 ) that have emerged as the most salient issues in patients’ experience of hospital care [ 23 ].

3.1.2. The Patient Experience Questionnaire (PEQ)

The PEQ was introduced as a new consultation-specific questionnaire of patient experiences in Norway in 2000 [ 17 ]. It was developed to improve the quality of care, with a special focus on the doctor–patient relationship in the inpatient setting and for national surveillance purposes [ 17 , 24 ]. The original survey includes 18 items questioning five dimensions that measure the satisfaction of patients during their stay in medical institutions (cf. Table 1 ). Initiated in 2005, a modified version of the PEQ was developed in Germany in cooperation with two large, national statutory health insurances (AOK [ 25 ] and BARMER [ 26 ]) and the Bertelsmann Foundation [ 27 ] and has been used for the measurement of patient experience there on a regular basis since November 2011 [ 28 , 29 ].

Since the release of the original PEQ, this questionnaire has been used mainly in the Scandinavian countries as a template to develop more specific questionnaires for certain patient groups or healthcare questions [ 19 ].

3.1.3. National Health Service Inpatient Survey (NHSIP)

In 2001, the U.K. implemented the systematic measurement of patient experience as an essential part of their healthcare system (the National Health Service, NHS [ 30 ]), with the aim to make NHS more patient-centered and responsive to patient feedback [ 31 ]. Patient experience with in-hospital treatment has been measured with the NHS inpatient survey (NHSIP) [ 32 ] since 2002 [ 33 ]. This instrument was derived from the early Picker Adult Inpatient Survey and adapted for use in the NHS based on the outcome of qualitative research measures (focus groups and cognitive interviews with patients) conducted by the Picker Institute Europe [ 20 ]. The inpatient survey is supplemented by surveys focusing on a variety of services and patient groups, including, for example, the experiences of children and adolescents or of patients in urgent and emergency care [ 34 ].

The current NHSIP consists of eight dimensions with 49 questions and is implemented on a nationwide basis through postal administration [ 15 ]. In contrast to other inpatient surveys, the NHSIP questions are reviewed and potentially revised each year to ensure their ongoing importance for patients and therefore for the NHS [ 35 ].

3.1.4. The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)

The HCAHPS survey is the first nationwide, standardized, publicly reported survey of patient perspectives on hospital care in the USA [ 36 ]. It was developed by the Agency for Healthcare Research and Quality and the Centers of Medicare and Medicaid Service (CMS) in 2002 in a process involving literature reviews, cognitive interviews, consumer focus groups, and stakeholder input [ 21 , 37 ]. The HCAHPS inpatient survey was rolled out in 2006 on a voluntary basis, and linkage to hospital payment followed in fiscal year 2008 [ 21 ]. It currently contains 29 items and 10 dimensions [ 37 ], which are described in more detail in Table 1 . Originally designed for improving hospital services and quality of care, HCAHPS results have been included in the Hospital Value-based Purchasing (VBP) program since 2012, which rewards acute-care hospitals with incentive payments for the quality of care provided in hospital settings [ 38 ].

3.2. Measuring Patient Experience in Selected Countries

3.2.1. united states of america (usa).

In the USA, the delivery of healthcare can be regarded as a consumer-driven industry. Most Americans obtain health insurance coverage through employers, private purchase, or government-based programs and the majority of healthcare facilities in the USA are privately owned. For those, high patient satisfaction translates into a competitive advantage in keeping old and attracting new patients. As mentioned above, hospital reimbursement rates are also linked to HCAHPS ratings [ 21 ].

The results of the 10 domains of the questionnaire are publicly reported on the HCAHPS website [ 39 ] and for individual hospitals on the Hospital Compare website of the CMS [ 40 ]. Annual reports describing scores according to geographic region, hospital type, and number of beds are also provided [ 41 ]. The HCAHPS reports from recent years indicate that there were no major changes in patient experience over time [ 39 ].

Despite the accountability of VBP for HCAHPS scores and the high public visibility of the questionnaire results, only few studies report patient experience of hospital treatments against a scientific background. In 2008, Jha and colleagues reported that a higher ratio of nurses to patient-days led to increased patient satisfaction, whereas other key hospital characteristics, such as profit or academic status, did not [ 42 ]. Thirteen years later, Seiler et al. [ 43 ] showed that the patients’ overall satisfaction with inpatient care provided by hospitalists and primary care physicians was nearly the same, with no differences among the specific domains of satisfaction, including communication skills, pain control, and physician behavior.

In summary, data collection concerning patient experience and satisfaction is well established in the United States through the predominant use of the HCAHPS. Nevertheless, apart from reimbursement policies, information on the practical implications of the data remains scarce.

3.2.2. United Kingdom (UK)

The public U.K. healthcare system, the NHS, is grounded in the principles of universality, equity, and being cost free at the point of delivery, paid for by central governmental funding to this day [ 44 ]. Healthcare providers with good patient experience and satisfaction rankings do not receive monetary incentives, but the surveys are a way of measuring progress, improving healthcare providers, and holding them accountable for their outcomes [ 45 ]. All surveys are documented on the NHS website to be reviewed by the public. The data about patient experience and satisfaction obtained by the surveys are used to give a score out of 10 to each hospital (the higher the better), giving more detailed insights about the ranking in each aspect of the questionnaire [ 46 ]. The 2021 survey on adult inpatient care found that the majority of patients gave positive reports about the communication with physicians and nurses, felt a sense of confidence and trust in their care, and were treated with dignity and respect. Patients also reported feeling included in conversations and understanding the answers to their questions. Topics in need for improvement included obtained help from the staff when needed, discharge management, and care at home [ 47 ]. Furthermore, data about the development of patient experience over a period of 10 years are provided [ 48 ].

Additionally, authors of various studies used the provided or collected additional data to perform secondary analyses of specific attributes. For example, Reeves and West analyzed the data of the NHSIPs from 2002 to 2013 in England, comprising 840.077 patients. They found improvement regarding obtaining copies of physician letters, gender-neutral accommodation on the wards, clinicians and general ward hygiene, as well as waiting times upon admission. The authors underline the need for consistency in investigating patient experience and satisfaction to detect changes over a long period since year-to-year changes might be small [ 49 ]. Another study questioning a sample of 2249 in-hospital patients in Scotland with the PPE found that important determinants of satisfaction were physical comfort, emotional support, and respect for patient preferences [ 50 ].

To summarize, there is a large amount of data collected in the U.K. mainly by the NHSIP regarding patient experience and patient satisfaction. These data are used in particular to ensure and improve quality of care and to provide information to patients without impacting reimbursement.

3.2.3. Norway, Sweden, and Finland

Healthcare systems in most Scandinavian countries (i.e., Finland, Sweden, and Norway) have followed a similar path. They are well established with regard to primary and preventive healthcare and also have highly developed hospitals, with all citizens having equal access to services. They are taxation based and locally administrated but require co-payments by patients for hospital care and medicines [ 51 ]. All Nordic countries have a history of measuring patient experience; however, much of this work was (or still is) done at the local level [ 52 ].

To improve comparability, the Nordic Patient Experiences Questionnaire (NORPEQ), a diagnostic instrument for assessing patient experiences of hospital care, was developed in the collaborative effort of Nordic countries [ 53 ]. The NORPEQ was validated in a Norwegian sample and subsequently translated and validated in other Nordic languages [ 52 ]. However, only few studies use the NORPEQ so far. Besides the NORPEQ, many other diagnostic instruments for patient experiences are used, including the PEQ [ 16 ], the PPE-15 [ 13 ], as well as a wide range of national surveys or instruments adapted to specific patient groups [ 19 ].

On the national level, Norway, Finland, and Sweden publish a wide range of epidemiological and aggregated medical data on governmental websites (Helsedata.no [ 54 ]; skr.se [ 55 ]; socialstyrelsen.se [ 56 ]; thl.fi [ 57 ]). However, some information is only accessible after registration with the user’s national bank identification number, which means that foreign website visitors are unable to see the information (helsenorge.no). Aggregated patient experience and/or satisfaction data are not easily accessible for international comparisons in all of these countries.

In Norway, the Norwegian Institute of Public Health is responsible for the monitoring of patient experiences. Since 2019, it has conducted an annual national survey on patient experience and satisfaction for the five following years [ 58 ]. Reports are available in Norwegian only [ 59 ].

Sweden started to annually collect patient experience data in 2001. Information about care providers has been made public in the “Vårdbarometer” (=care barometer) in Swedish [ 60 ]. In 2009, a standardized National Patient Survey, the Nationella Patientenkäten, was additionally introduced, collecting and facilitating comparability of patient experience and satisfaction data on the provider level and over time. The results are made available in Swedish and partially in English [ 61 ].

In Finland, healthcare providers are obliged to register healthcare visits into a national registry [ 62 ]. Apart from the registries, a national patient survey on health and well-being, including questions concerning patient experience, has been conducted since 2017 (FinSote, 2017–2020 [ 63 ]; since 2022, Healthy Finland Survey [ 64 ]). Full reports on the surveys are publicly available in Finnish [ 65 ], and indicator variables can be accessed and compared for regions and over time in English [ 66 ].

In Scandinavia, treatment continuity as well as enough time to listen, talk, and explain during the consultation were identified as important factors for patient satisfaction in primary care [ 67 , 68 ]. Waiting-time reduction is considered a key political challenge for health service improvement [ 69 ]. Surveys showed a high satisfaction with how patients were received by medical staff in primary care, while communication in areas concerning waiting times, side effects of medications, previous health status, and health-related warning signals were in need of improvement [ 70 ].

In summary, Norway, Sweden, and Finland are well positioned to collect data on patient experiences and to publish the results. The use of group-specific instruments and publications in the respective native languages hamper the comparability between different populations and time points.

3.2.4. Germany

The German public healthcare system is based on the principle of solidarity, where all people insured by statutory health insurance (SHI) receive the same ambulatory and hospital care regardless of their financial status. Approximately 87% of all German citizens fall under this statutory healthcare, whereas the rest has private health insurance (PHI) [ 71 ]. SHI or PHI has been mandatory for all citizens and permanent residents in Germany since 2009. The split into the two insurance types is unique among countries in the EU [ 72 ].

Since 2005, quality management reports, which address both quality of service and quality of care, have been mandatory in Germany and have to be published by all healthcare providers, private or public, to supply patients with information for benchmarking hospitals [ 73 , 74 ]. As part of these reports, patient satisfaction and patient experience are often surveyed as well. A summary of the results is published occasionally and can be accessed free of charge [ 75 ]. Recent results can also be found with various online search engines in German (e.g., “Weisse Liste” [ 76 ]) specifically designed to find information on hospitals operated, for example, by SH insurers. However, only the latest results can be found here, and longitudinal data on patient experience are not available.

Starting in 2011, various health insurance companies in cooperation with the “Weisse Liste” have been measuring patient satisfaction and experience nationwide with the PEQ [ 77 ]. Factors with particular importance for satisfaction from the patient perspective in Germany include interaction with the attending physicians and the nursing staff [ 78 ], which had by far the greatest influence on the patients’ willingness to recommend the hospital to others. These results are in line with corresponding results from the USA [ 42 ] and the U.K. [ 47 ]. Furthermore, the subjective success of the treatment, the kindness of nurses and physicians, general equipment and cleanliness, the admission procedure and food [ 78 , 79 ], a higher staffing per bed, higher process and outcome quality [ 80 ], and number of cases per physician [ 75 ] were associated with a positive patient experience or higher satisfaction, respectively.

In summary, Germany also performs well in collecting, analyzing, and publishing data on patient experience and patient satisfaction. However, data on overall consequences drawn from these assessments are hard to find.

3.3. Online Patient Ratings on Different Platforms

In recent years, patients increasingly use online platforms to express themselves about their medical treatment and hospital stay and to evaluate health service providers as a quick and easy way to voice an opinion. However, this advantage also gave these platforms the reputation of being unreliable and undifferentiated. In fact, they do not have the same methodological quality as validated PREM or PROM but do provide additional and useful information for studying patient experience and satisfaction. Patient rating platforms fall into two types: on the one hand, platforms such as RateMDs [ 81 ], Vitals.com [ 82 ], Healthgrades [ 83 ], and ZocDoc [ 84 ] were designed for the purpose of rating and giving feedback explicitly on hospitals and medical providers, whereas access to certain pages is not possible from all parts of the world (e.g., [ 83 ]). On the other hand, on social media platforms such as Facebook [ 85 ] or other platforms such as Yelp [ 86 ], people can express their opinions about a wide variety of topics. Several studies have compared online patient ratings with results from more traditional and established forms of patient ratings or other indicators of quality of care, such as unplanned readmission rates within 30 days after discharge from hospital. One study found that those hospitals with low readmission rates had higher ratings on Facebook [ 87 ], while others showed a positive association between the results of the subjective reviews (ratings and comments) on this platform or Yelp and the HCAHPS scores of the respective hospital [ 88 , 89 , 90 , 91 ]. Perez and Freedman (2018) found similar results when comparing reviews from Facebook, Yelp, and Google to patient experience measured with HCAHPS. They showed that in 50–60% of cases, the hospitals rated best on crowdsourcing sites were also the best hospitals according to HCAHPS patient experience ratings. In contrast, in about 20% of cases, the hospitals rated best on Facebook, Yelp, and Google were the worst according to patient experiences measured by HCAHPS [ 92 ].

In sum, the data suggest that subjective ratings on social media or other platforms can be used as a source of fair to good representation of patient experience and satisfaction. Since traditional surveys cover only a specific subset of aspects of patient satisfaction and experience, online formats can broaden the spectrum of patient feedback. A comparison of domains surveyed by the HCAHPS with the platform Yelp showed that the reviews on Yelp covered 12 additional domains not addressed by the HCAHPS, such as compassion of staff, quality of nursing, facilities, and amenities [ 91 ]. The U.K., for example, already enables patients and hospitals to complement their ratings on NHS Choices with narrative feedback, following the example of social media platforms [ 93 ]. Moreover, current advances in machine learning with improved automatized analysis of qualitative data—as reviews on online platforms are—are bound to facilitate the analysis of such narrative feedback modalities [ 94 ]. However, it must be kept in mind that users of online rating platforms may represent only a specific sociodemographic subgroup of patients and that the survey mode may affect response behavior and be susceptible to manipulation, thus limiting the generalizability of the conclusions obtained of such data [ 95 , 96 ].

3.4. Impact of Sociodemogaphic Characteristics

Numerous studies have shown that patients’ sociodemographic characteristics may influence patient experience and patient satisfaction [ 97 , 98 ]. Most of these studies focus on patient satisfaction; however, there are studies that also measure patient experience [ 78 , 99 ]. Further, the reviews concerning this topic often include studies that measure either satisfaction or experience or sometimes studies where this remains unclear [ 97 , 98 , 100 ].

Patients’ age represents the best-studied influencing sociodemographic factor with the most consistent results [ 97 , 100 ], indicating that older patients tend to be more satisfied with healthcare or showed a higher willingness for recommendation than youngers [ 75 , 101 , 102 ]. Stahl and colleagues [ 78 ] specified that older people were less critical in their interaction with physicians and with regard to the admission process and hospital food than younger ones. In contrast, they were more critical concerning the subjective assessment of the treatment success. Although the majority of study results point in the same direction, some studies found contrary effects. For example, Jaipaul and Rosenthal [ 103 ] showed that patient satisfaction increases with age until up to 80 years but then declines. However, the effect of age on patient experience and satisfaction in fact seems to be rather small [ 78 , 98 ].

Besides age, self-perceived health status is, in many studies, a significant positive predictor of patient experience or satisfaction [ 97 , 99 , 101 , 104 , 105 ]. However, the correlations between health status and satisfaction often are very small and only explain a small part of the variance [ 104 , 105 ]. For other sociodemographic characteristics (e.g., gender, education, race, social status, marital status, and religion), only few and ambiguous results are available [ 79 , 97 , 98 , 99 , 100 , 101 , 102 , 105 ].

In summary, the scarce data that exist so far indicate that sociodemographic characteristics do not appear to have a major impact or even a consistent effect on a person’s satisfaction with received healthcare [ 98 , 99 ]. However, sociodemographic characteristics should be taken into account when investigating patient satisfaction or patient experience to control their role as potential predictors or confounders [ 97 ].

3.5. Impact of Hospital Characteristics

Up to now, only few studies have examined the influence of hospital characteristics on patient experience and patient satisfaction [ 80 ]. As in the case of sociodemographic characteristics, both patient satisfaction [ 104 , 106 ] and patient experience [ 78 , 107 ] are measured in the related studies. A relevant factor seems to be the size of the hospital. The vast majority of studies revealed that patients were less satisfied or had a worse experience with a growing number of beds [ 75 , 78 , 80 , 105 ]. Furthermore, patients in not-for-profit hospitals were found to have a better experience and a higher willingness for recommendation than patients treated in for-profit hospitals [ 80 , 108 , 109 ]. Some other characteristics associated positively with patient satisfaction were, for example, specialty focus [ 110 ], system membership [ 108 ], and academic (versus general) status of the hospital [ 105 ], whereas inconsistent associations have been described between patient satisfaction or patient experience and teaching status of the hospital [ 6 , 104 , 107 ] as well as concerning urban versus rural region [ 75 , 106 ].

Overall, various hospital characteristics potentially influence patient experience and patient satisfaction. However, it is unclear how crucial this effect actually is since some associations were found to be inconsistent [ 6 ]. In addition, in some studies, the identified characteristics only explain a small part of the variance [ 105 ]. Nevertheless, given the potential influence of these hospital-associated features, care should be taken when using survey data concerning patient experience or patient satisfaction in quality management. The data should be evaluated keeping the potential effects of hospital characteristics in mind [ 78 ].

4. Discussion

The results of our review indicate that all countries studied have established routines for the measurement and publication of patient experience and satisfaction. The NHS appears to be currently leading the way in this regard not only because of the ongoing adaptation of their measurement tool NHSIP but also because of the integration of traditional quantitative and Internet-based narrative feedback possibilities and their publication on the NHS website. In addition, the Scandinavian countries selected for this overview have professionalized the collection and publication of patient experience and satisfaction data, especially in recent years, while the American approach to patient experience and satisfaction data has remained largely unchanged within the last decade. In Germany, on the other side, patient experience data are collected on a regular basis but only made available to the general population in a simplified form on a non-profit foundation website. Germany is, moreover, the only country of the ones studied here that does not provide annual or longitudinal statistical data on patient satisfaction and/or experience to the public.

Despite the individual countries’ efforts to measure and publish patient experience, consequences drawn from the patient feedback to improve national healthcare systems often remain unclear. The Scandinavian countries investigated here claim to incorporate the results of the PREM and PROM surveys into healthcare reforms, while the USA aims to control improvement processes via financial incentives. In the U.K. and Germany, on the other hand, it is up to healthcare providers and patients to draw conclusions from the data collected. However, despite extensive research, we did not find specific examples of how exactly patient experience and satisfaction measures are used to implement healthcare reforms in any of the countries studied.

Next to discussing how the different countries deal with the issue of patient experience and satisfaction, we also aimed to describe what is known to be important for patients in the individual countries. One factor that seems to be crucial for patient satisfaction across all countries mentioned is communication with physicians and nurses. On this aspect, patients in the U.K. seem to report the most positive experiences about their communication with healthcare professionals.

However, due to various methodological problems, the evaluation of these results on a cross-country level is difficult. In some of the countries studied in this review (i.e., Norway and Germany), survey results are only made available in national languages. The use of different surveys and country-specific modifications of existing questionnaires for subgroups make it difficult to compare findings with other health services or even within the same service over time.

Moreover, the construct validity of the inventories used varies considerably [ 2 ]. Many PREM (i.e., HCAHPS, PEQ) were developed years ago and are not updated on a regular basis. Some do not differentiate well between the constructs of patient experience and satisfaction but contain elements of both. However, the distinction between the two constructs is important: The measurement of patient experience is likely to uncover differences in the quality of care provided to individual populations, whereas aspects of patient satisfaction are more likely to be influenced by cultural differences in patient expectations or attitudes.

Further, sociodemographic data, which would allow a more differentiated analysis according to subgroups, are not systematically investigated. Yet, these are important when investigating patient satisfaction or patient experience to control their role as potential predictors or confounders.

Emerging and increasingly important sources of patient experience, such as website-based feedback from social media or discussion fora, are oftentimes viewed as unreliable sources of information. Nevertheless, studies show that these narrative data can be analyzed [ 94 ] and then yield important additional information such as the reference to additional and underrepresented dimensions of patient experience (i.e., compassion of staff, quality of nursing, facilities, and amenities) that are not yet captured in the conventional questionnaires [ 91 ]. Incorporating such domains into the existing measures could possibly improve the process of evaluating patient experience and satisfaction and provide important feedback to the respective hospitals [ 88 , 91 , 111 ].

Owing to the complexity of the topic and the sheer overwhelming amount of literature published, the present article was prepared as a narrative review rather than a systematic one. This approach constitutes a certain limitation because it obviously leads to a selection bias. We would, however, like this approach of data presentation to be understood as a starting point for further research and more in-depth study of certain aspects presented here.

5. Conclusions

In summary, with regard to patient experience, many countries are exemplary in one aspect or another, but all countries have potential for improvement. The present review presents insights beyond the national borders, aiming to provide a basis for improving the use of patient experience data to benefit healthcare systems. Our results suggest that international efforts to unify methods for measuring patient experience, as already initiated with the development of the NORPEQ, should be advanced further. While the distinction between patient experience and satisfaction is already an essential step towards its systematic assessment, questionnaires should be improved in terms of conceptual clarity and validity to reflect this distinction and to achieve better comparability of results.

Another consequence could be to establish mandatory and standardized recommendations for the collection and publication of patient experience data. Summarized results should be provided transparently for patients’ orientation, whereas more detailed cross-sectional and longitudinal data should be made easily accessible to researchers for national and international comparison.

Last but not least, at present, the consequences of patient experience surveys in the different countries are not easily discernible. We suggest implementing their results into change management structures, which have to be constantly adapted to altering healthcare challenges accounting for, e.g., multicultural social backgrounds and minority and marginalized groups. Planned and realized changes to improve patient care should be made easily accessible to the public. In our opinion, such an approach could bring about a vibrant culture of change in healthcare co-designed by patients and healthcare providers and give more comprehensive answers to the question of “how are we doing it and why does it matter”. We hope that the present review can be regarded, in this respect, as a starting point for further research and practical implementations.

Acknowledgments

While the compilation and writing of this article did not receive any external funding, the literature search was performed for a project funded by the University Medical Foundation of the University Hospital Essen.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/healthcare11060797/s1 , Figure S1: Detailed flow chart of literature search, in- and exclusion criteria.

Funding Statement

This manuscript received no external funding.

Author Contributions

A.L.F., S.S., C.F.K., S.H. and I.K.-A. performed the literature research. All authors discussed the results interdisciplinarily from their professional perspective and selected articles for inclusion into the review. A.L.F., S.S., C.F.K., S.H. and I.K.-A. drafted the first version of the manuscript. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

• Open access
• Published: 24 May 2022

Patient satisfaction with health care at a tertiary hospital in Northern Malawi: results from a triangulated cross-sectional study

• Frank Watson Sinyiza 1 ,
• Paul Uchizi Kaseka 1 ,
• Master Rodgers Okapi Chisale 2 , 3 ,
• Chikondi Sharon Chimbatata 1 ,
• Balwani Chingatichifwe Mbakaya 4 , 5 ,
• Pocha Samuel Kamudumuli 6 ,
• Tsung-Shu Joseph Wu 2 , 7 &
• Alfred Bornwell Kayira 1  

BMC Health Services Research volume  22 , Article number:  695 ( 2022 ) Cite this article

6817 Accesses

12 Citations

Metrics details

In 2016 the Malawi government embarked on several interrelated health sector reforms aimed at improving the quality of health services at all levels of care and attain Universal Health Coverage by 2030. Patient satisfaction with services is an important proxy measure of quality. We assessed patient satisfaction at a tertiary hospital in Northern Malawi to understand the current state.

We conducted exit interviews with patients aged ≥ 18 years using a 28 statement interviewer administered questionnaire. Patients were asked to express their level of agreement to each statement on a five-point Likert scale – strongly disagree to strongly agree, corresponding to scores of 1 to 5. Overall patient satisfaction was calculated by summing up the scores and dividing the sum by the number of statements. Mean score > 3 constituted satisfaction while mean score ≤ 3 constituted dissatisfaction. A χ 2 test was used to assess the association between overall patient satisfaction and demographic variables, visit type and clinic consulted at alpha 0.05. Patient self-rated satisfaction was determined from a single statement that asked patients to rate their satisfaction with services on a five-point Likert scale. We also asked patients to mention aspects of hospital care that they did not like. Responses were summarized into major issues which are presented according to frequencies.

Overall patient satisfaction was 8.4% (95% CI: 5.2 − 12.9%). Self-rated patient satisfaction was 8.9% (95% CI: 5.5 − 13.4%). There was no significant association between overall patient satisfaction and all predictor variables assessed. Patients raised six major issues that dampened their health care seeking experience, including health workers reporting late to work, doctors not listening to patients concerns and neither examining them properly nor explaining the diagnosis, shortage of medicines, diagnostics and medical equipment, unprofessional conduct of health workers, poor sanitation and cleanliness, and health worker behaviour of favouring relatives and friends over other patients.

Conclusions

We found very low levels of patient satisfaction, suggesting that quality of services in the public health sector is still poor. It is, therefore, critical to accelerate and innovate the Ministry of Health’s quality improvement initiatives to attain Malawi’s health goals.

Peer Review reports

Introduction

Malawi aspires to achieve Universal Health Coverage (UHC) by 2030 [ 1 ]. But a 2016 situation analysis of the health sector in Malawi identified low quality of care as a major setback to achieving UHC and improving population health outcomes [ 2 ]. Based on recommendations of this report the Malawi government has since 2016 been undertaking several health sector reforms to improve the quality of health services at all levels of care by improving and strengthening leadership and governance, human resource capacity, clinical practice, client safety, people-centered care and supply chain systems [ 1 ]. In 2018, the Ministry of Health and Population (MoHP) designated patient or client satisfaction with services as one of the main indicators for monitoring improvements in the quality of services in public health facilities in Malawi, and encourages the conduct of patient satisfaction surveys disaggregated by service type and facility type every two years [ 3 ]. The target is that by 2022 at least 80% of patients or clients seeking health care in public facilities should be satisfied with the health services provided [ 3 ].

Patient satisfaction, defined as the congruence between patient expectations of optimal care and the perception of the actual care received [ 4 ], is however not without limitations when used as an indicator for quality of care. According to the Donabedian quality of care model, health care quality encompasses the technical competencies of the providers as well as the interpersonal process through which that care is provided [ 5 ]. Technical quality of care is judged against the best in practice which is known or believed to produce the greatest improvements in health [ 5 ]. But Donabedian argues that due to limitation in medical knowledge most patients cannot competently assess the technical skills of their provider, and may therefore have low or no expectations on the technical quality of care [ 5 ]. As such, their satisfaction scores may only indicate the interpersonal skills of the provider and good health care outcomes. But even if the health care outcome is not good the quality of care given will still be judged as good if it conformed to best practice permitted by the science and technology of the day. Therefore satisfaction or dissatisfaction with care does not necessarily equate to receipt of good or bad quality of technical care.

Nonetheless, in recent decades, there has been a major shift in health care practice from the traditional way of defining quality of health care in terms of the technical standards to one that includes patient’s perception and judgement about the services received [ 6 ]. Patient perception about the quality of and trust in the health care services received has a huge bearing on their continued utilisation of health care and compliance with care regimens and suggested lifestyle modifications, which in turn affects treatment outcomes [ 7 ]. Donabedian, in his quality of care model, corroborates the importance of good interpersonal relationship between the provider and the patient because the interpersonal process serves as the vehicle by which technical care is implemented and on which its success depends [ 5 ]. Furthermore, beyond technical and interpersonal quality aspects of care, patient satisfaction has been reported to be influenced by availability and accessibility of health care providers, medicines and diagnostics; cost of services; and physical environment [ 8 , 9 , 10 ]. Studies have also demonstrated a direct connection between quality of services and patient satisfaction with services [ 11 , 12 , 13 ], making it an important indicator of health system performance improvement.

Four studies have previously assessed client or patient satisfaction in Malawi. All of them were done before the year 2016 and three of them reported satisfaction levels of more than 85% [ 14 , 15 , 16 ] which is higher than MoHP set target of 80% by the year 2022. The other study found that at least 75% of hospitalized stroke patients surveyed at discharge were satisfied with the care they received [ 17 ]. All four studies assessed satisfaction with either a specific service provided by a specific group of providers, one hospital unit or a specific group of patients, and mainly focused on the technical aspects of care. Perhaps this explains why MoHP set a target of 80% by the year 2022 knowing pretty well that studies done way earlier had demonstrated higher levels of client/patient satisfaction with the services. Motivated by these deficiencies and in responding to MoHP’s call for regular patient satisfaction surveys as a way of obtaining important feedback from clients and patients on the quality of services in public health facilities we assessed patient satisfaction with health care at a tertiary hospital in Northern Malawi.

Study design and setting

This was a descriptive cross-sectional study. It was carried out at Mzuzu Central Hospital (MCH) between January, 2021 and February, 2021 during the second surge of COVID-19 cases in the country. MCH is tertiary hospital located in Mzuzu City, Northern Malawi. It is a 410 bed capacity hospital and serves as the referral facility for six health districts that constitute the Northern Region and serving a population of 2,289,780 people [ 18 ]. Ideally the hospital provides specialist health services at the regional level. In practice, however, around 70% of the services it provides are either primary or secondary [ 19 ]. This is mainly due to unavailability of proper primary and secondary level health facilities in Mzuzu city and the surrounding areas and lack of a gate-keeping system [ 19 ]. Daily bed occupancy is at 410 and about 50 inpatients are discharged from hospital daily. Hospital records showed that the facility also treats about 500 patients daily on an outpatient basis.

Data collection, management and analysis

We conducted exit interviews with patients aged 18 years and above shortly after having been discharged from hospital (for inpatients) or after they had completed consultation and received treatment. Interviewer administered structured questionnaire was used to collect data from patients. The questionnaire was adapted from the Patient Satisfaction Questionnaire (PSQ-III) and the Patient Satisfaction Questionnaire Short Form (PSQ-18) (an abbreviated version of PSQ-III), both of which are validated and reliable tools for assessing patient satisfaction with medical care [ 20 , 21 ]. The adaption process involved rephrasing some statements to reflect the local context, dropping items that were not applicable locally, and substituting such items with those that were locally relevant. All new additions were based on literature. We engaged non-Mzuzu Central Hospital staff as interviewers to encourage free expression by patients. Interviewers had professional training in nursing and medicine. They were dressed in civilian clothes and interviews were conducted at a private place, away from identifiable hospital staff. Interviewers were trained in data collection tools and procedures before deployment.

The questionnaire consisted of 28 statements grouped into six domains of care: (1) Communication (4 statements), (2) Relational conduct (5 statements), (3) Technical skills/competence (5 statements), (4) Personal qualities/attributes (3 statements), (5) Availability and accessibility (6 statements), and (6) Physical environment (5 statements). Statements under communication domain solicited information from patients on whether health care providers provided adequate and patient tailored information on the investigations being done and eventual diagnosis, and adequately addressed patient concerns. Relation conduct domain comprised statements seeking information on whether patients were treated with respect by providers and were adequately involved in decision making. Statements under technical skills domain gathered information on whether providers demonstrated a masterly of their job. The personal attributes domain statements probed whether patients were treated courteously, and with privacy and empathy by providers. Statements under availability and accessibility domain solicited information on whether doctors were readily available and accessible to patients at the hospital and whether medicines, diagnostic services and functional medical equipment were also available. The physical environment domain asked patients to rate the adequacy, cleanliness and tidiness of sanitary facilities and hospital surroundings as well as the state of hospital infrastructure and room space.

Patients were asked to indicate their level of agreement to the statements on a five-point Likert scale: (1) Strongly disagree, (2) Disagree, (3) Not sure, (4) Agree, and (5) Strongly agree. The questionnaire contained a mix of statements expressing both positive and negative sentiments in a random order to minimize acquiescence bias. Together, the 28 statements provided a composite measure of satisfaction which we call Overall Patient Satisfaction. The questionnaire also contained one more question “ On the overall, how satisfied are you with the services you have received? ” with responses on a five-point Likert scale – very dissatisfied to very satisfied. The objective of this question was to solicit patients’ own subjective assessment of their health care seeking experience, herein referred to as Self-rated Satisfaction. The questionnaire further contained an open-ended question asking patients to mention any areas or aspects of care that needed improvement at the hospital. This question solicited inputs from patients so as to understand what constitutes quality health care from their perspective.

Data were entered in Microsoft excel 2016, cleaned and then imported into STATA V.13.0 (StataCorp) for analysis. But before any analysis could begin responses to all negatively framed statements were first re-coded so that all scores (1, 2, 3, 4, 5 corresponding to strongly disagree, disagree, not sure, agree and strongly agree) were in the same sense (i.e. the higher the score the higher the level of satisfaction). Overall patient satisfaction was calculated by summing up individual satisfaction scores across the six domains of care to get an overall score and then dividing this overall score by the total number of statements in the six domains. This calculation brought the overall scores back into the scale of 1 to 5. An overall mean score of more than 3 was treated as ‘Satisfied’ while an overall mean score of 3 or less was treated as ‘Unsatisfied’. This analysis was repeated for each domain to calculate domain specific overall satisfaction. Overall patient satisfaction was dichotomized because very few patients were satisfied with the care they received and splitting it further would have scattered the data even more, making it unlikely to observe any association between satisfaction and predictor variables.

For self-rated satisfaction responses very dissatisfied, dissatisfied and not sure constituted dissatisfaction whereas satisfied and very satisfied formed satisfaction. The response ‘Not sure’ was categorized on the dissatisfaction side because we felt that that was patients’ polite way of saying the services were not good. We believe if patients were happy with the services received they would not hesitate to say so. Patients’ responses to an open ended question were reviewed and summarized into major issues.

Descriptive statistics were performed to summarize patient characteristics. Overall patient satisfaction was the main outcome of analysis. A Chi square (χ 2 ) test of independence was used to test the association between overall patient satisfaction and demographic variables, visit type and hospital clinic/department consulted. A χ 2 test was performed for all cross tabulations where the sample size (n) was greater than the number of cells multiplied by 5 and where the expected value in 80% of the contingency cells was greater than 5 and no cell had the expected value of less than 3. Where this condition was not met a Fisher’s exact test was performed instead. A p-value of 0.05 or less was considered statistically significant. A binary logistic regression was not a good fit for the data at alpha 0.05 (i.e. Prob > chi2 was greater than 0.05) so we had to stick to the χ 2 .

A total of 225 patients were interviewed, representing 100% of the target sample size. Of these, 126 (56.0%) were female and the majority (38.7%) were in the 20–29 years age group. Half (50%) of the patients had completed secondary level education. The majority of patients resided in the Northern Region (77.8%), were treated as outpatients (58.7%) and were seen at the general outpatient department (44.4%) (Table  1 ).

Overall patient satisfaction was 8.4% (95% CI: 5.2 − 12.9%), but ranged from as low as 4.9% for health worker attributes to as high as 27.1% for availability and accessibility of health workers and health services. Self-rated patient satisfaction was 8.9% (95% CI: 5.5 − 13.4%) (Table  2 ).

A Chi square or Fishers’s exact test was used to explore associations between overall patient satisfaction and demographic characteristics of participants and other variables. None of the variables examined had a statistically significant association with overall patient satisfaction (Table  3 ).

The top six areas of improvement cited by patients are that health workers should report to work on time at 29.8% followed by a plea that doctors should listen to patients’ concerns, examine them thoroughly and explain their findings and diagnosis, including the reasons for doing blood tests and other examinations at 17.8% (Table  4 ). “Doctors should come to work on time and examine patients properly” , said a 27 year-old male when asked what he thought could have been done differently to improve his experience at the hospital. While a 35 year-old female had this to say “Doctors should pay attention to patients and examine them properly based on their complaints ”.

Third was an observation that the hospital should improve its stocks of essential medicines, diagnostics and medical furniture at 14.7%, which was followed by an earnest call that health workers must conduct themselves professionally at 12.9% (Table  4 ). “Doctors should minimize chatting with colleagues and on their phones when attending to us” said a 21 year-old woman when asked what should improve at the hospital to make her experience better. Another 20 year-old female responded “ Stock enough drugs in the pharmacy and provide more chairs on the outpatient queues so that we can observe social distance during this era of COVID-19” .

On fifth position, there was a call from 6.7% of patients that hospital management has to improve cleanliness in the hospital’s sanitary facilities and regularly maintain the physical infrastructure. Finally at number six, 4.0% of patients bemoaned the behaviour of some health workers who favour or prioritise their relatives and friends over other patients and pleaded that heath workers should change this discriminatory behaviour (Table  4 ). When asked what she thought should have been done differently in order to improve her experience at the hospital a 60 year old female said “improve sanitation in the toilets” while 63 year old woman said “stop prioritizing relatives and friends of health workers and treat us all equally”.

Seventy two patients (32%) contradicted their initial responses and said they were satisfied with the services they received when  prompted to suggest what could be improved at the hospital (Table  4 ). When asked to mention areas that needed improvement at the hospital so as to make their experience better next time they come to seek care a 42 year old male said “I’m satisfied with the services” . An 18 year old female said “The hospital should keep up the good work it is doing” while a 36 year old female said “There’s improvement on abuse of patients and that should continue”.

We assessed patient satisfaction in six domains of care (communication, rational conduct, technical competence, personal qualities, availability and accessibility, and physical environment) and calculated an overall measure of patient satisfaction. We also report patient self-rated satisfaction with the services they received and patient suggested areas of improvement for better service delivery at the hospital. To our knowledge this is the first study in Malawi to have taken a multi-pronged approach to assessing patient satisfaction, and to have assessed satisfaction holistically and not focussing on a specific service or hospital department.

Both overall patient satisfaction self-rated satisfaction were low (8.4% and 8.9% respectively), suggesting that the quality of services in public hospitals is still not satisfactory. If this study had included family members of patients who died in hospital the service ratings would have been even poorer considering the fact that patients who survive often tend to rate services as satisfactory [ 22 ]. It is encouraging to note, however, that our measured overall satisfaction was not different from patient self-rated satisfaction, giving confidence in the tool that we used to objectively assess patient satisfaction. Therefore, instituting improvements in the domains of care that we assessed may lead to increased satisfaction with care among patients.

Previous studies reported high levels of satisfaction with health care services in Malawi. In a study investigating client satisfaction with cervical cancer screening all women (100%) reported being satisfied with the services, with 68.3% reporting being very satisfied [ 14 ]. Creanga and colleagues found patient satisfaction levels of more than 85% with perinatal care [ 15 ]. 97% (97%) of women were satisfied with reproductive health services at Gogo Chatinkha Maternity Unit in Blantyre, Malawi [ 16 ] while more than 75% of stroke patients were said to be satisfied by the care they received in four tertiary hospitals in Malawi [ 17 ]. All of the above studies have fundamental differences from our study. While we attempted to assess the hospital as a system, encompassing as many dimensions of care that might lead to patient satisfaction (or otherwise) as possible, they focused on a specific service provided by specific staff in a particular unit or department of the hospital. Taking such a narrow approach one is likely to find higher levels of satisfaction. In Nigeria and Uganda studies that assessed a particular service or one aspect of care provided by the hospital or clinic reported higher levels of satisfaction (91.6% and 93.8% respectively) [ 23 , 24 ].

The hospital, however, is a much broader sand complex system. In navigating such a system patients may encounter several frustrations along the way, including having to interact with multiple providers with varying technical competencies and personal manners, and from different professional backgrounds. In resource constrained countries like Malawi patients are also faced with limited access to the doctor, frequent stock outs of essential medicines and limited diagnostics services. Studying patient experiences with the health care system from such a broader perspective one may find lower levels of satisfaction. In Ethiopia and Uganda, studies that took a similar approach to our own and measured patient satisfaction in a similar manner found lower levels of satisfaction with nursing care among hospitalized patients (40.7% and 49.2%) [ 25 , 26 ], inpatient services (46.2%) [ 27 ] and outpatient services (50.0%) [ 28 ]. Even though our results are still far lower than these the trend is apparent, and the observed discrepancies could be due differences in study sites. We are, therefore, of the view that when assessing patient satisfaction with hospital care taking a holistic approach is the best way to draw out true hospital ratings from the people it endeavors to serve better.

Further, this study was conducted in the midst of the COVID-19 pandemic. COVID-19 has had significant impact on the delivery of other essential health services in Sub-Saharan Africa, including Malawi. It led to shortage of human and material resources due to staff and money being redirected to tackle the epidemic [ 29 , 30 ]. COVID-19-related stressors such as physical exhaustion, alarming deaths of COVID-19 patients and the fear of contracting infection and subsequently passing it to family members took a huge toll on mental health of health workers [ 31 , 32 ], which in turn may have affected how providers related with patients. Globally, COVID-19 lockdowns disrupted supply chains and lead to acute shortage of medicines and other essential health commodities in Malawi [ 33 , 34 ]. In addition, the global scramble for essential health commodities such as masks and other protective equipment (PPE) led to severe shortages of these items in third world countries like Malawi [ 35 ]. Without appropriate and adequate PPE it was difficult for health workers to maintain good provider-patient interactions and discharge their duties comfortably. A combination of these factors may have plummeted health care provider and hospital ratings in the eyes of the patient.

We examined the association between overall patient satisfaction and independent variables listed in Table  1 using a Chi square or Fishers’s exact test, as appropriate. Initially, the plan was to fit a binary logistic regression but when we attempted to fit such a model with either of the variables individually or together the model itself was insignificant at alpha 0.05. As such we had to explore the association using basic statistical tests (Chi square or Fisher’s exact) which too did not reveal any association at 5% level of significance. Maseko et al. found no association between client satisfaction with cervical cancer screening and age, education level or marital status [ 36 ] while Nabbuye-Sekandi and colleagues reported higher levels of satisfaction among clients with primary or secondary education compared with those that had no formal education [ 28 ]. They also found greater levels of satisfaction among clients who attended certain specialized clinics (HIV treatment and research clinic) than among those who attended general outpatient clinics [ 28 ]. Sharew et al. reported the opposite of what Nabbuye-Sekandi et al. had reported. In their study they found that patients with at least primary education were 80% less satisfied compared with those without any formal education [ 26 ]. So, failure by our study to find any significant associations between satisfaction and demographic variables, visit type and department or clinic consulted could mean that indeed there is no association, or simply a failure by our study to detect these associations owing to few events (only 8.4% of patients were satisfied and therefore could not achieve adequate distribution for optimal comparison).

Patients raised various issues that dampened their health care seeking expereince at the hospital. Top on the list were health workers reporting late to work, that doctors do not listen to patients’ concerns and that they do not take time to examine patients thoroughly and explain the findings, shortage of medicines and diagnostics, and unprofessional conduct of health workers. Five of the top six items raised by patients were already included in the questionnaire we used to objectively assess patient satisfaction, giving reassuarance that the tool we used touched on issues that patients considered important. A small proportion of patients also raised some important issues that the hospital should consider improving if it is to appeal to its clientele. Concerns that health workers are favouring or prioritizing their relatives and friends over ordinary patients by aiding them to skip the queue, the revelation that some health workers are soliciting bribes from patients, and the need for adequate physical space so that patients can observe social distance while waiting on the queue during the COVID-19 pandemic must be seriously looked into. None of the issues raised were related to the technical aspects of quality of care. Nonetheless, these are the things that patients are able to observe and upon which they base their evaluation of the performance of the hospital. Therefore, while aiming to improve the technical quality of care particular attention must be paid to the nontechnical aspects of it as well.

When asked to mention areas that the hospital should improve to meet their expectations a substantial proportion of patients (32%) had nothing specific to point a finger at other than to contradict their earlier statements and say they were satisfied with the care they had received. Of these, 98.6% were not satisfied with the care they received by our measured overall satisfaction, and all of them (100%) reported not being satisfied in their self-rated satisfaction. Forty-two (58.3%) of them had completed at least secondary education. This contradictory result is interesting. We suspect that despite many of them having good education they still lacked knowledge on their rights with regard to health care, and therefore had no expectations of the quality of services they ought to receive. Without expectations it is difficult to judge the actual care received, and hence unable to point out a single thing that was not right in the services they received.

Patient satisfaction was very low, suggesting that patients were not happy with the quality of services they received. This is a strong message to policy makers and health managers to improve the quality of services and patient experience in public hospitals. To stay true to its commitment of improving population health outcomes and achieve UHC by 2030 through provision of quality services the Malawi government has to step up and accelerate current initiatives meant to improve quality of services or innovate its quality improvement approaches. Furthermore, the Malawi health system has to get better prepared for future pandemics because these tend to reverse the gains made in previous years. In addition, the Malawi government and development partners should consider sensitizing citizens on their rights and responsibilities enshrined in the Malawi service charter on patients’ and health service providers’ rights and responsibilities so that they know what to expect from and what is expected of them during a health care seeking encounter. Until there is congruence between expectations of ideal care and the actual care received it will be difficult for patients to rate the services as satisfactory or not. So even if the Malawi government is to make investments to improve quality of care and patient experience in its facilities future patient satisfaction surveys may still fail to detect changes in levels of satisfaction as patients may not be able to distinguish between optimal and suboptimal care.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Email: [email protected].

Abbreviations

Ministry of Health and Population

Universal Health Coverage

Personal Protective Equipment

Quality Management Policy for the Health Sector of Malawi. Vol. 1, Quality management policy. 2018 [cited 2021 Aug 7]. Available from: https://www.health.gov.mw/ Accessed on 01/11/2020

Ministry of Health. Situation Analysis of the Malawi Health Sector. 2016.

Malawi Ministry of Health and Population. Naonal Health Indicators Handbook for Monitoring Health Sector Performance. 2018; p. 62–7. [cited 2021 Aug 7] Available from: https://www.healthdatacollaborative.org/fileadmin/uploads/hdc/Documents/Country_documents/Malawi_National_Health_Indicators_FINAL_v11_clean_wt_sign_combo.pdf .

Risser NL, Batey V. Development of an instrument to measure patient satisfaction with nurses and nursing care in primary care settings. Nurs Res. 1975;24(1):45–52. [cited 2021 Aug 8] Available from: https://pubmed.ncbi.nlm.nih.gov/1038021/ .

Donabedian A. The Quality of Care: How Can It Be Assessed? JAMA J Am Med Assoc. 1988;260(12):1743–8.  [cited 2021 Sep 30] Available from: https://jamanetwork.com/journals/jama/fullarticle/374139 .

Cleary PD, Edgman-Levitan S, Roberts M, Moloney TW, McMullen W, Walker JD, et al. Patients evaluate their hospital care: A national survey. Health Aff. 1991;24(4):254–67.

Article   Google Scholar  

Reid RJ, Coleman K, Johnson EA, Fishman PA, Hsu C, Soman MP, et al. The group health medical home at year two: Cost savings, higher patient satisfaction, and less burnout for providers. Health Aff. 2010;29:835–43.  [cited 2021 Aug 2] Available from: https://pubmed.ncbi.nlm.nih.gov/20439869/ .

Jenkinson C, Coulter A, Bruster S, Richards N, Chandola T. Patients’ experiences and satisfaction with health care: Results of a questionnaire study of specific aspects of care. Qual Saf Heal Care. 2002;11(4):335–9.  [cited 2021 Aug 9] Available from: https://pubmed.ncbi.nlm.nih.gov/12468693/ .

Christman LP. Increasing Patient Satisfaction: A Guide for Nurses. Nursing Administration Quarterly. Springer Pub. Co; 1996.

Ware JE, Snyder MK, Wright WR, Davies AR. Defining and measuring patient satisfaction with medical care. Eval Program Plann. 1983;6(3–4):247–63. [cited 2022 Mar 31] Available from: https://pubmed.ncbi.nlm.nih.gov/10267253/ .

Pascoe GC. Patient satisfaction in primary health care: A literature review and analysis. Eval Program Plann. 1983;6(3–4):185–210.

Narayan KMV, Gregg EW, Fagot-Campagna A, Gary TL, Saaddine JB, Parker C, et al. Relationship between quality of diabetes care and patient satisfaction. J Natl Med Assoc. 2003;95(1):64. [cited 2021 Aug 9] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2594360/ .

Batbaatar E, Dorjdagva J, Luvsannyam A, Savino MM, Amenta P. Determinants of patient satisfaction: A systematic review. Perspect Public Health. 2017;137:89–101.  [cited 2021 Aug 9] Available from: https://pubmed.ncbi.nlm.nih.gov/27004489/ .

Maseko FC, Chirwa ML, Muula AS. Client satisfaction with cervical cancer screening in Malawi. BMC Health Serv Res. 2014;14(1). [cited 2022 Apr 4] Available from: https://pubmed.ncbi.nlm.nih.gov/25245860/ .

Creanga AA, Gullo S, Kuhlmann AKS, Msiska TW, Galavotti C. Is quality of care a key predictor of perinatal health care utilization and patient satisfaction in Malawi? BMC Pregnancy Childbirth. 2017;17(1). [cited 2021 Jul 27] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440969/ .

Changole J, Bandawe C, Makanani B, Nkanaunena K, Taulo F, Malunga E, et al. Patients’ satisfaction with reproductive health services at Gogo Chatinkha Maternity Unit, Queen Elizabeth Central Hospital, Blantyre, Malawi. Malawi Med J. 2010;22(1):5. [cited 2021 Jul 27] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3345683/ .

Chimatiro GL, Rhoda AJ, De Wit L. Stroke patients’ outcomes and satisfaction with care at discharge from four referral hospitals in Malawi: A cross-sectional descriptive study in limited resource. Malawi Med J. 2018;30(3):152–8. [cited 2021 Jul 27] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6307053/ .

National Statistical Office. 2018 Malawi Population and Housing Census Main Report. 2019 [cited 2021 Sep 30]. Available from: http://www.nsomalawi.mw/images/stories/data_on_line/demography/census_2018/2018 Malawi Population and Housing Census Main Report.pdf

Government of Malawi. Health Sector Strategic Plan II (2017–2022) [Internet]. 2017 [cited 2021 Oct 1]. p. 122. Available from: https://extranet.who.int/countryplanningcycles/sites/default/files/planning_cycle_repository/malawi/health_sector_strategic_plan_ii_030417_smt_dps.pdf .

Marshall GN, Hays RD, Sherbourne CD, Wells KB. The Structure of Patient Satisfaction With Outpatient Medical Care. Psychol Assess. 1993;5(4):477–83. [cited 2022 Apr 2] Available from: /record/1994-32042-001

Marshall GN, Hays RD. The Patient Satisfaction Questionnaire Short Form (PSQ-18). Santa Monica: RAND Corporation;

Kennedy GD, Tevis SE, Kent KC. Is there a relationship between patient satisfaction and favorable outcomes? In: Annals of Surgery. NIH Public Access; 2014; p. 592–600. [cited 2022 Apr 2] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159721/ .

Ezegwui, Okoye O, Aghaji A, Okoye O, Oguego N. Patients’ satisfaction with eye care services in a Nigerian teaching hospital. Niger J Clin Pract. 2014;17(5):585. [cited 2021 Jul 28] Available from: https://www.njcponline.com/article.asp?issn=1119-3077;year=2014;volume=17;issue=5;spage=585;epage=588;aulast=Ezegwui .

Ssengooba W, Kirenga B, Muwonge C, Kyaligonza S, Kasozi S, Mugabe F, et al. Patient satisfaction with TB care clinical consultations in Kampala: a cross sectional study. Afr Health Sci. 2016;16(4):1101. [cited 2021 Jul 28] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5448822/ .

Kasa AS, Gedamu H. Predictors of adult patient satisfaction with nursing care in public hospitals of Amhara region, Northwest Ethiopia. BMC Health Serv Res. 2019;19(1). [cited 2021 Jul 29] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341709/ .

Sharew NT, Bizuneh HT, Assefa HK, Habtewold TD. Investigating admitted patients’ satisfaction with nursing care at Debre Berhan Referral Hospital in Ethiopia: A cross-sectional study. BMJ Open. 2018;8(5):21107. Available from: http://bmjopen.bmj.com/ .

Asamrew N, Endris AA, Tadesse M. Level of Patient Satisfaction with Inpatient Services and Its Determinants: A Study of a Specialized Hospital in Ethiopia. J Environment Public Health. 2020;2020. [cited 2021 Jul 29] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443030/ .

Nabbuye-Sekandi J, Makumbi FE, Kasangaki A, Kizza IB, Tugumisirize J, Nshimye E, et al. Patient satisfaction with services in outpatient clinics at Mulago hospital, Uganda. Int J Qual Heal Care. 2011;23(5):516–23. [cited 2021 Jul 29] Available from: https://academic.oup.com/intqhc/article/23/5/516/1864829 .

Mohammed H, Oljira L, Roba KT, Yimer G, Fekadu A, Manyazewal T. Containment of COVID-19 in Ethiopia and implications for tuberculosis care and research. Infect Dis Poverty. 2020;9. [cited 2021 Oct 1] Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7492795/ .

Ongole JJ, Rossouw TM, Bernard Fourie P, Stoltz AC, Hugo J, Marcus TS. Sustaining essential healthcare in Africa during the COVID-19 pandemic. Int J Tuberculosis Lung Dis. 2020;24:643–5.

Kwobah EK, Mwangi A, Patel K, Mwogi T, Kiptoo R, Atwoli L. Mental Disorders Among Health Care Workers at the Early Phase of COVID-19 Pandemic in Kenya; Findings of an Online Descriptive Survey. Front Psychiatry. 2021;12:665611.

Htay MNN, Marzo RR, AlRifai A, Kamberi F, Radwa Abdullah EA, Nyamache JM, et al. Immediate impact of COVID-19 on mental health and its associated factors among healthcare workers: A global perspective across 31 countries. J Glob Health. 2020;10(2):1–6.  [cited 2021 Oct 1] Available from:  https://pubmed.ncbi.nlm.nih.gov/33214890/ .

Sharma A, Gupta P, Jha R. COVID-19: Impact on Health Supply Chain and Lessons to Be Learnt. J Health Manag. 2020;22(1):248–61.

Ranney ML, Griffeth V, Jha AK. Critical Supply Shortages — The Need for Ventilators and Personal Protective Equipment during the Covid-19 Pandemic. N Engl J Med. 2020;30(18):e41.

Medinilla A, Byiers B, Apiko P. African regional responses to COVID-19 [Internet]. 2020 [cited 2021 Oct 2]. Available from: www.ecdpm.org/dp272 .

Maseko FC, Chirwa ML, Muula AS. Client satisfaction with cervical cancer screening in Malawi. 2014 [cited 2021 Jul 27]; Available from: http://www.biomedcentral.com/1472-6963/14/420 .

Download references

Acknowledgements

The authors are sincerely grateful to Pingtung Christian Hospital and Luke International Norway (LIN) for funding this study.

The study was funded by Pingtung Christian Hospital, Taiwan through Luke International Norway (LIN), Malawi, Grant Number: PS-IR-108001. The funder played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and affiliations.

Mzuzu Central Hospital, Mzuzu City, Malawi

Frank Watson Sinyiza, Paul Uchizi Kaseka, Chikondi Sharon Chimbatata & Alfred Bornwell Kayira

Luke International, Mzuzu City, Malawi

Master Rodgers Okapi Chisale & Tsung-Shu Joseph Wu

Faculty of Sciences, Technology and Innovations, Biological Sciences Department, Mzuzu University, Mzuzu City, Malawi

Master Rodgers Okapi Chisale

Faculty of Applied Sciences, Department of Public Health, University of Livingstonia, Mzuzu City, Malawi

Balwani Chingatichifwe Mbakaya

Faculty of Health Sciences, Mzuzu University, Mzuzu City, Malawi

University of Maryland Global Initiative Corporation, Lilongwe City, Malawi

Pocha Samuel Kamudumuli

Pingtung Christian Hospital, Pingtung City, Taiwan

Tsung-Shu Joseph Wu

You can also search for this author in PubMed   Google Scholar

Contributions

FWS conceptualized and designed the study. TJW provided inputs to the manuscript and funding acquisition. PUK, MRC, CSC, BCM, PK and ABK refined the study design and contributed to the development of the study protocol. PUK supervised data collection. FWS, PUK, MRC, BCM and ABK devised the data analysis plan. ABK analysed and interpreted the data, and wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alfred Bornwell Kayira .

Ethics declarations

Ethics approval and consent to participate.

The study was approved by Mzuzu University Research and Ethics Committee (MZUNIREC). Permission to conduct the study was also obtained from Mzuzu Central Hospital Research Committee. Written informed consent was obtained from patients before interviews could proceed. For illiterate participants written informed consent was obtained from literate legal guardians. Patients were assured of confidentiality of information they provided and that this would have no bearing on the care they would receive at the hospital in future visits. Information obtained from patients was handled by authorized personnel only. All study methods were performed in accordance with MZUNIREC regulations and guidelines.

Consent for publication

This manuscript does not contain individual person’s data and therefore consent for publication was not required.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Sinyiza, F.W., Kaseka, P.U., Chisale, M.R. et al. Patient satisfaction with health care at a tertiary hospital in Northern Malawi: results from a triangulated cross-sectional study. BMC Health Serv Res 22 , 695 (2022). https://doi.org/10.1186/s12913-022-08087-y

Download citation

Received : 13 November 2021

Accepted : 12 May 2022

Published : 24 May 2022

DOI : https://doi.org/10.1186/s12913-022-08087-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Patient satisfaction
• Client satisfaction
• Quality of care
• Health care

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

ORIGINAL RESEARCH article

Covid-19 patient satisfaction and associated factors in telemedicine and hybrid system.

• 1 National Public Health Emergency Operation Center, Ethiopian Public Health Institute, Addis Ababa, Ethiopia
• 2 Saint Paul’s Hospital, Milennium Medical College, Addis Ababa, Ethiopia
• 3 Neurology Unit, Hospital Las Higueras, Talcahuano, Chile
• 4 Medical Program in Adult Neurology, School of Medicine, Universidad Católica de la Santísima Concepción, Concepción, Chile
• 5 National Training Center, Ethiopian Public Health Institute, Addis Ababa, Ethiopia
• 6 Ministry of Health of Ethiopia, Addis Ababa, Ethiopia

Background: The quality assessment of the home-based isolation and care program (HBIC) relies heavily on patient satisfaction and length of stay. COVID-19 patients who were isolated and received HBIC were monitored through telephone consultations (TC), in-person TC visits, and a self-reporting application. By evaluating patient satisfaction and length of stay in HBIC, healthcare providers could gauge the effectiveness and efficiency of the HBIC program.

Methods: A cross-sectional study design enrolled 444 HBIC patients who answered a structured questionnaire. A binary logistic regression model assessed the association between independent variables and patient satisfaction. The length of stay in HBIC was analyzed using Cox regression analysis. The data collection started on April (1–30), 2022, in Addis Ababa, Ethiopia.

Results: The median age was 34, and 247 (55.6%) were females. A greater proportion (313, 70.5%) of the participants had high satisfaction. Higher frequency of calls (>3 calls) (AOR = 2.827, 95% CI = 1.798, 4.443, p  = 0.000) and those who were symptomatic (AOR = 2.001, 95% CI = 1.289, 3.106, p  = 0.002) were found to be significant factors for high user satisfaction. Higher frequency of calls (>3 calls) (AHR = 0.537, 95% CI = 0.415, 0.696, p  = 0.000) and more in-person visits (>1 visit) (AHR = 0.495, 95% CI = 0.322, 0.762, p  = 0.001) had greater chances to reduce the length of stay in the COVID-19 HBIC.

Conclusion: 70.5% of the participants had high satisfaction with the system, and frequent phone call follow-ups on patients’ clinical status can significantly improve their satisfaction and length of recovery. An in-person visit is also an invaluable factor in a patient’s recovery.

1 Introduction

The global COVID-19 pandemic has had a significant impact on numerous countries, resulting in a staggering number of confirmed cases and deaths worldwide. Specifically, 774,771,942 confirmed cases and 7,035,337 deaths were reported globally. In Africa, approximately 9,576,309 confirmed cases and 175,500 deaths have been recorded, whereas Ethiopia alone has reported 501,157 confirmed cases and 7,574 deaths ( 1 ). Given the outbreak’s severity and the prevailing epidemiological situation, the Federal Ministry of Health of Ethiopia has taken swift action by developing, approving, and implementing a national guide on home-based isolation and care (HBIC). This guide is tailored for asymptomatic and mildly confirmed COVID-19 cases ( 2 ). Consequently, many patients have enrolled in the system, establishing a comprehensive telephone consultation (TC) service. Healthcare workers from health centers have been diligently monitoring the clinical condition of these patients through regular phone calls or in-person visits ( 2 ). The national or regional COVID-19 emergency centers are available for assistance to ensure that patients receive the necessary support and information. Patients facing challenges or requiring guidance on the system’s functioning, worsening symptoms, medication advice, or ambulance requests can reach these centers ( 2 ). This approach provides comprehensive care and support to individuals affected by COVID-19 in Ethiopia.

Several studies have emphasized the utilization of teleconsultations (TC) in Sub-Saharan Africa amid the COVID-19 outbreak. For instance, a study conducted at the Aga Khan Hospital in Dar es Salaam, Tanzania, revealed varying frequencies of TC calls over 3 months, with peaks observed at 7 weeks and lows at 13 weeks ( 3 ). In Uganda, the Ministry of Health rolled out TC services across multiple health centers simultaneously ( 4 ). Similarly, in Cameroon, many physicians resorted to TC consultations during the pandemic, often using WhatsApp applications ( 5 ). Despite the progress in telemedicine practices, assessing the quality of care provided through these methods is crucial. Quality indicators for telemedicine outcomes include mortality rates, average length of stay, and complication rates ( 6 ). The adoption of telemedicine has played a pivotal role in enhancing the quality of diagnosis and treatment in primary public hospitals ( 7 ). This is evident in the reduction of treatment duration, decrease in the average length of hospital stays, and decline in the percentage of critically ill patients ( 8 ). Moreover, telemedicine aids in improving personalized care and broadening the accessibility of medical services. Healthcare providers can deliver more efficient and effective patient care by harnessing telemedicine, particularly during crises such as the COVID-19 pandemic ( 9 , 10 ). Patient satisfaction is a significant indicator of the societal perception of healthcare services, particularly in telemedicine. The practical advantages of telemedicine further underscore its social reputation within primary healthcare facilities. First, Telemedicine plays a crucial role in alleviating the financial burden on patients and their families by eliminating expenses associated with transportation and accommodation ( 11 ). Second, the efficient nature of telemedicine expedites disease diagnosis and treatment, thereby mitigating patients’ suffering ( 11 ). Lastly, telemedicine’s unique “face-to-face” communication system fosters a novel connection between medical professionals and patients, ultimately enhancing the healthcare experience ( 12 , 13 ). Despite numerous studies, the findings remain inconclusive and conflicting. Some researchers suggested recruiting adaptable patients who embrace this new technology’s convenience ( 14 ). Conversely, others highlight limitations, such as the relative novelty of telehealth in medicine, which makes it challenging to compare its outcomes with those of more traditional interventions ( 15 ). In addition, patient satisfaction is a complex and multifaceted concept influenced by various factors. However, the factors influencing patient satisfaction in different settings or conditions remain debated ( 15 ).

Patient satisfaction and length of stay are crucial metrics for assessing the quality of healthcare programs. This study aimed to provide insights into the factors influencing the satisfaction and length of stay in HBIC of COVID-19 patients in Addis Ababa, Ethiopia. This study uses traditional care (TC) and hybrid (in-person-TC) approaches in different sub-city areas. By understanding these factors, policymakers can develop strategic plans to improve the quality of healthcare services, thereby ensuring high satisfaction levels and shorter medical residence stays. The findings of this study can also inform the National Public Health Emergency Operation Center and the Federal Ministry of Health in Ethiopia on how to intervene and strengthen the healthcare system. In addition, the results can contribute to expanding telemedicine services and adopting digital health technologies in the country’s healthcare sector.

2.1 Study area

This study focuses on Addis Ababa, primarily because of the significant burden of COVID-19 cases. Ethiopia alone has reported 501,157 confirmed cases and 7,574 deaths, with nearly 67% of these cases originating in Addis Ababa ( 1 ). Moreover, implementing the COVID-19 HBIC model in Addis Ababa surpasses other regions. Furthermore, the HBIC’s self-reporting and follow-up application is exclusively available in Addis Ababa, making it an ideal location for research. Addis Ababa is divided into 11 sub-cities [Addis Ketema, Akaky Kaliti, Arada, Bole, Gullele, Kirkos, Kolfe Keranio, Lideta, Nefas Silk-Lafto, Yeka, Lemi Kura (New)], all of which have adopted the HBIC system for COVID-19 patients since the initial case was identified. The digital follow-up tool was specifically launched in the Bole sub-city ( Figure 1 ).

Figure 1 . Addis Ababa district locations. This map of the 11 Addis Ababa sub-cities is included in this study. Lemi Kura is a new district and is not included in this map.

2.2 Study period

The study was conducted from 1 to 30 April 2022 in Addis Ababa, Ethiopia.

2.3 Telemedicine medical team and technology

Each sub-city is equipped with two to four health centers that serve as the base for the telemedicine medical team. A well-established system ensures that patient data is promptly transmitted to follow-up teams, enabling healthcare workers to initiate their follow-up procedures without delay. To support this initiative, the Ethiopian Public Health Institute and Addis Ababa Health Bureau allocated a tablet with complimentary airtime to each sub-city proportionate to the needs of the telemedicine medical team.

2.4 Population studied

This study encompasses all individuals diagnosed with COVID-19 who were isolated, received care at home, and met the criteria for inclusion. The study population consisted of confirmed COVID-19 cases admitted to HBIC from its inception, aged between 18 and 60, individuals who underwent regular follow-up assessments while at HBIC, and those whose contact information was documented in the registry.

2.5 Patient’s independent variables

Patients were classified based on the following criteria: Gender (male, female), Age (<30, 31–40, 41–50, 51–60 years), city of residence, education level (no education and elementary, secondary and diploma, degree and above), occupation (government employee, private employee, self-employee, not working), symptoms (asymptomatic, symptomatic), type of attention (only telephone call—TC, telephone call with in-person visits - in-person-TC), frequency of calls (≤2 calls, ≥3 calls), and frequency of in-person visits (no visits, ≤2 visits, ≥3 visits).

2.6 Study design

A cross-sectional research design assessed two primary variables: patient satisfaction and length of stay in HBIC in days. The formula for a single population proportion was applied to determine the required population size of 385 (with a Z-score of 1.96, an outcome proportion of 50%, and a marginal error of 5%). The technique of proportionate stratified sampling involved dividing the entire population into 11 strata or sub-cities. The total sample size was then distributed proportionally among each sub-city based on the burden of the disease. Study participants were selected from each stratum or sub-city using systematic probability sampling ( Figure 2 ).

Figure 2 . Data collection. Sampling technique from each sub-city in Addis Ababa, Ethiopia.

2.7 Data collection tools, techniques, and quality assurance

A validated patient satisfaction survey from the teleneurology program in Chile ( 13 ) employed a Likert scale to assess the extent of patient satisfaction. To ensure the accuracy and reliability of the data collected, a pretest was conducted on a random sample of 23 (5%) patients. Based on the findings from the pretest, necessary amendments were made to the data collection tool. Additionally, the collected data underwent daily reviews for clarity and completeness checks. Before analysis, the internal consistency of the questionnaire was evaluated using Cronbach’s alpha test ( 13 ). The local language was used during data collection to ensure the required information was collected with greater understanding. To facilitate this, the data collection questionnaire was first developed in English and then translated into Amharic, and the data collected were back-translated to English for consistency. The data collectors administered the questionnaire over the telephone, and responses were recorded on the individual datasheets. Training on the basics of the questionnaire and how to use it appropriately was given by the principal investigator for two BSc nurses for 2 days.

2.8 Patient satisfaction survey

The final questionnaire consisted of 17 closed-response questions, each assigned a numerical value ranging from 1 (totally disagree) to 5 (totally agree). The questions were categorized into four contextualized areas. The overall score on the questionnaire, with a maximum of 85 points, served as an indicator of patient satisfaction. The scoring system classified satisfaction levels as follows: very low (17 points or below), low (18–34 points), moderate (35–51 points), high (52–68 points), and very high (69–85 points). Following completion of the survey, patients were divided into two main groups based on their scores: (i) those with a score below 51 points, indicating moderate or low patient satisfaction, and (ii) those with a score over 52 points, indicating high or very high patient satisfaction ( Table 1 ).

Table 1 . Study questionnaire.

2.9 Data and outcomes analysis

Summary statistics, including frequency, percentage, median, and interquartile range, were utilized to summarize the characteristics of patients and other relevant information. This research aimed to assess the relationship between the independent variables and two primary outcomes: (i) the level of patient satisfaction and (ii) the length of stay in the HBIC. The binary logistic regression (Backwald) model was employed to examine the independent variables associated with patient satisfaction, and the findings were presented as odds ratios (OR). Cox regression (Backwald) analysis was conducted to evaluate the independent variables linked to the length of stay in HBIC, and the results were reported as hazard ratios (HR). To compare the means of length of stay in HBIC, a non-normal distribution, the Mann–Whitney U test for independent samples was employed, while the chi-square test was used for categorical variables. The significance level was set at p  < 0.05. All statistical analyses were performed using SPSS, version 26.

2.10 Ethical considerations

The study was conducted after obtaining ethical clearance from the Addis Ababa Health Bureau Public Health Research and Emergency Ethical Review Committee. Oral informed consent was obtained from the participants before any form of data collection. Participants’ contact information was obtained after a formal request was made to the Addis Ababa Health Bureau. Demographic data of all participants and survey responses were anonymously collected and entered. Access to the collected information was limited to the authors, and confidentiality was maintained throughout the project.

3.1 Data collection

A 17-question structured questionnaire was developed by reviewing similar studies ( Table 1 ) ( 13 ). Upon completing a reliability assessment of the survey, the internal reliability of the survey was robust, as evidenced by a Cronbach’s alpha coefficient of 0.96 (data not shown). The study included 509 patients, yielding a response rate of 87.2% ( n  = 444). Among the non-respondents ( n  = 65, 12.8%), the reasons provided for their lack of participation were as follows: 20% ( n  = 13) had incorrect contact information, and another 20% ( n  = 13) did not receive any follow-up, either in-person or through phone communication. The remaining 60% ( n  = 39) of participants displayed uncooperative behavior, as their phones were inactive, unreachable, or did not answer ( Figure 3 ).

Figure 3 . Patient’s response from telephone calls. Response rate and reasons for non-response include: (i) wrong phone number, (ii) no follow-up, and (iii) other.

3.2 Population description, patient satisfaction, and length of stay in HBIC

The descriptive statistics of the 444 patients who participated in the study are below. The median age was 34 ± 15 years, with an age distribution as follows: Age:<30 ( n  = 164, 36.9%); 31–40 ( n  = 141, 31.8%); 41–50 ( n  = 87, 19.6%); and 51–60 ( n  = 52, 11.7%). The gender distribution of the patients was as follows: Female 247 (55.6%) ( Table 2 ). We outline the performance of the HBIC system according to the patient satisfaction parameter. Due to the low frequency obtained in the lower user satisfaction groups (very low, low, and moderate), we grouped patients into two major groups according to the degree of user satisfaction: low or moderate and high or very high. patients with high or very high user satisfaction represent 313 (70.5%). When we break down this group by gender, we see that women have a slightly higher percentage of high or very high user satisfaction than men, with 177 (56.9%) females. However, no statistically significant differences are observed. Analyzing the distribution of patients with high and very high user satisfaction by age, we observe that more than 50% of patients are concentrated in a population under 40 years old ( Table 2 ). The length of stay for patients with high or very high satisfaction varied depending on certain variables. The average length of stay for females was 15 ± 5 days, while for males, it was 16 ± 5 days, and in terms of age groups, patients showed similar lengths between 14 and 16 days ( Table 2 ).

Table 2 . Patient’s demographic variables.

The distribution of patients according to sub-city of residence was found to be quite homogeneous, with some exceptions as detailed below: City: Addis Ketema (n = 62, 14.0%), Akaki Kality (n = 44, 9.9%), Arada (n = 43, 9.7%), Bole (n = 77, 17.3%), Gulele (n = 59, 13.3%), Kirkos (n = 11, 2.5%), Kolfe Keranyo (n = 44, 9.9%), Lideta (n = 36, 8.1%), Nefas Silk Lafto (n = 22, 5.0%), Yeka (n = 30, 6.8%), and Lemi Kura (n = 16, 3.6%). Patients with high or very high satisfaction were distributed according to sub-city of residence as follows: City: Addis Ketema (n = 48, 10.8%), Akaki Kality (n = 35), Arada (n = 32, 7.2%), Bole (n = 57, 12.8%), Gulele (n = 33, 7.4%, 7.9%), Kirkos (n = 6, 1.4%), Kolfe Keranyo (n = 33, 7.4%), Lideta (n = 23, 5.2%), Nefas Silk Lafto (n = 20, 4.5%), Yeka (n = 18, 4.1%), and Lemi Kura (n = 8, 1.8%) ( Table 2 ). Regarding the city of origin, the average length of stay varied as follows: Addis Ketema (17 ± 5), Akaki Kality (16 ± 8), Arada (16 ± 5), Bole (14 ± 3), Gulele (17 ± 4), Kirkos (17 ± 5), Kolfe Keranyo (16 ± 6), Lideta (14 ± 4), Nefas Silk Lafto (20 ± 7), Yeka (15 ± 7), and Lemi Kura (14 ± 7) ( Table 2 ).

The patient’s satisfaction and length of stay in HBIC can be influenced by various factors, including the patient’s level of education and occupation. The distribution of patients’ education level is as follows: 79 patients (17.8%) had no education or only completed elementary school, 174 patients (39.2%) had completed secondary school or obtained a diploma, and 191 patients (43.0%) had a degree or higher education. The distribution of patients’ occupation is as follows: 121 patients (27.3%) were government employees, 114 patients (25.7%) were private employees, 120 patients (25.0%) were self-employed, and 89 patients (20.0%) were not working ( Table 2 ). The majority of patients who showed high or very high user satisfaction have higher levels of education: Education: No Educ and Elementary ( n  = 45, 10.1%), Secondary and Diploma ( n  = 125, 28.2%), Degree and above ( n  = 143, 32.2%); however, the distribution was found to be more symmetrical according to the occupational level of these patients: Government employee ( n  = 80, 18.0%), Private employee ( n  = 85, 19.1%), Self-employee ( n  = 80, 18.1%), Not working ( n  = 68, 15.3%) ( Table 2 ). No significant differences were found in the duration length of stay in HBIC among patients concerning their level of education and occupation type. The respective data for education are as follows: No Education and Elementary 14 ± 7, Secondary and Diploma 15 ± 4, Degree and above 17 ± 5. Similarly, the data for occupation type were: Government employee 14 ± 5, Private employee 15 ± 5, Self-employee 16 ± 4, Not working 18 ± 7 ( Table 2 ).

Most patients who participated in this study were symptomatic, accounting for 275 (61.9%) with an average length of stay for HBIC of 16 (±6). Patients who displayed symptoms were more satisfied ( n  = 215, 48.5%) than those who were asymptomatic ( n  = 98, 22.1%). The length of stay in HBIC for asymptomatic patients (14 ± 5), was slightly lower than that of Symptomatic patients (16 ± 5). However, no statistically significant differences were observed (data not shown).

Next, we described the frequency of phone call follow-ups for patients during their stay at HBIC. The most common type of care was TC, with 330 patients (74.3%), followed by in-person and TC visits, with 114 patients (25.7%). The overall frequency of in-person visits was 1 ± 2 visits, and it can be further broken down as follows: no visits ( n  = 330, 48.9%), ≤2 visits ( n  = 84, 18.9%), and ≥ 3 visits ( n  = 30, 6.8%). The average frequency of phone call follow-ups was 3 ± 6 calls, and we observe that the distribution of calls appears to be symmetrical: TC was ≤2 calls ( n  = 221, 49.8%) and ≥ 3 calls ( n  = 223, 50.2%).

In terms of the mode of care, patients who were exclusively contacted through teleconsultation (TC) 217 (48.9%) were more satisfied than those receiving hybrid care with both TC and in-person visits 96 (21.6%). Consistent with the findings, patients exhibited higher user satisfaction with an increased frequency of calls in TC, as those patients with more than ≥3 calls ( n  = 184, 41.4%) expressed greater satisfaction compared to patients with less than or equal to ≤2 calls ( n  = 129, 29.1%) ( Table 2 ). Upon analyzing the frequency of in-person visits, patients with fewer visits reported higher user satisfaction: No visits ( n  = 217, 69.3%), 1 visit ( n  = 70, 22.0%), and ≥ 2 visits ( n  = 26, 8.3%).

It is important to mention that differences in patient length of stay were observed according to the type of care, as patients treated through the TC system 14 ± 5 stayed for a shorter period than those receiving hybrid care through TC and in-person visits 18 ± 6 ( p  < 0.05). As expected, patients with more calls stayed longer in the HBIC system as described below: Frequency of calls in TC: ≤2 calls 13 ± 3, and ≥ 3 calls 18 ± 6 ( p  < 0.05) ( Table 2 ).

3.3 Statistical analysis associated with patient satisfaction

A binary logistic regression analysis was utilized to explore the variables associated with high or very high patient satisfaction levels. The results revealed that individuals who placed more than three calls (OR = 2.827, 95% CI = 1.798, 4.443, p  = 0.000) and those displaying symptoms (OR = 2.001, 95% CI = 1.289, 3.106, p  = 0.002) were more inclined to report increased satisfaction. Nevertheless, no statistically significant relationships were found between user satisfaction and the other independent variables investigated ( p  > 0.05) ( Table 3 ).

Table 3 . Relevant demographic variables that influence patient satisfaction.

3.4 Statistical analysis associated with patient length of stay in HBIC

A Cox regression analysis was employed to examine the factors influencing the duration of hospital stays in patients who reported high levels of satisfaction. The findings revealed that patients who made more than three phone calls had a significantly lower hazard ratio (HR = 0.537, 95% CI = 0.415, 0.696, p  = 0.000), indicating a greater likelihood of reducing their length of stay. Similarly, patients with more in-person visits also exhibited a lower hazard ratio (HR = 0.495, 95% CI = 0.322, 0.762, p  = 0.001). However, no statistically significant associations were observed between the length of stay and the other independent variables analyzed ( p  > 0.05) ( Table 4 ).

Table 4 . Cox regression analysis to elucidate the demographic variables associated with the length of stay in HBIC and patients’ satisfaction.

3.5 Statistical analysis of the variables affecting patient satisfaction and length of stay in HBIC

Previously, we identified the following variables that significantly influence patient satisfaction and length of stay in HBIC: the presence of symptoms, the number of phone calls, and in-person follow-ups. Subsequently, we examined the relationship between symptoms and patient satisfaction with the number of phone calls and in-person follow-ups ( Table 5 ). It was noted that symptomatic patients with low or moderate satisfaction levels have an OR = 5.7 times higher likelihood of having a greater number of phone calls and 7.6 times higher likelihood of having in-person follow-ups. The length of stay in HBIC for these patients was notably longer for those with a higher number of phone calls. Conversely, patients with high or very high satisfaction levels have a 2.3 times higher likelihood of having a greater number of phone calls and in-person follow-ups. The length of stay in HBIC for these patients was significantly longer for those with in-person follow-up. Sig p  < 0.05 ( Table 5 ).

Table 5 . Analysis of the variables affecting patient satisfaction and length of stay in HBIC.

4 Discussion

This study aimed to evaluate the levels of patient satisfaction and length of stay in HBIC among COVID-19 patients while also examining the different factors that may impact these outcomes. Given the considerable number of COVID-19-positive instances and the limited bed availability at COVID-19-specific hospitals, the HBIC endorsed the practice of home isolation for COVID-19-affected persons. This directive was instituted because most COVID-19 patients were either asymptomatic or displayed mild symptoms. Such cases generally do not necessitate hospitalization at COVID-19-designated medical facilities and can be adequately managed at home with appropriate medical guidance and monitoring. The heightened level of patient satisfaction observed in symptomatic individuals treated by HBIC is supported by an associated investigation conducted through a survey-based study ( 10 , 16 – 18 ).

We identified a noteworthy connection between a high or very high satisfaction level and the frequency of phone call follow-ups in patients with COVID-19 symptoms. Essentially, for each increment of one in the frequency of phone call follow-ups, the chances of experiencing high or very high patient satisfaction rose by a factor of 2.8 (OR = 2.827, 95% CI = 1.798, 4.443, p  = 0.000). This tendency may be attributed to patients encountering difficulties during their healthcare facility stay, and regular communication with the follow-up team assists in addressing some of these challenges. As per the National HBIC Guideline, the frequency of phone call follow-ups escalates as the severity of the COVID-19 illness worsens, with follow-ups occurring once a week, every 3 days until discharge, and daily until discharge ( 19 ). Correspondingly, individuals exhibiting COVID-19 symptoms had 2.0 times greater odds of experiencing high or very high patient satisfaction than those with asymptomatic disease (OR = 2.001, 95% CI = 1.289, 3.106, p  = 0.002). Cox regression analysis uncovered a negative correlation between the length of stay in HBIC patients with high or very high satisfaction and the frequency of phone calls, follow-ups, and in-person visits. Specifically, the number of phone calls and in-person visits (with a minimum of two visits) emerged as significant factors impacting the length of stay. Upon adjusting for other variables, it was observed that with each additional phone call, the length of stay in the hospital-based isolation center (HBIC) decreased by 46.3% (HR = 0.537, 95% CI = 0.415, 0.696, p  = 0.000). Similarly, after accounting for other covariates, the length of stay among COVID-19 patients who had more than one in-person visit was 50.5% lower compared to patients with no in-person visits (HR = 0.495, 95% CI = 0.322, 0.762, p  = 0.001). Finally, this investigation determined that symptomatic patients with Low or Moderate satisfaction had a greater likelihood of experiencing a larger Number of Phone Calls, In-Person follow-ups, and a longer stay at HBIC compared to patients with high or very high satisfaction.

User satisfaction and length of stay have shown dissimilar results in different latitudes. A study conducted in general and university hospitals in the Netherlands found no evidence of a correlation between the average length of stay in hospital wards and patient satisfaction ( 20 ). Several studies conducted at the Nancy University Hospital Center in France and in training hospitals in Turkey and Japan ( 21 – 23 ) have found a connection between prolonged lengths of stay and decreased patient satisfaction. These studies have highlighted the importance of environmental factors in influencing patient satisfaction ( 24 ). However, a distinct study carried out in teaching hospitals in Turkey discovered that patients who stayed longer expressed higher satisfaction levels than those with shorter stays ( 25 ). Despite these variations, one can speculate about the reasons for higher user satisfaction in patients with greater follow-ups. Among these reasons, it can be argued that it is well-documented that telemedicine technology has the potential to enhance the quality of primary medical care, shorten the duration of treatment, and decrease the number of severe hospitalization cases ( 17 ). Telemedicine expands the availability of medical services and broadens the range of medical care, which is particularly crucial in Ethiopia, with a fragmented healthcare system and limited coverage ( 26 , 27 ). The sharing of medical resources is especially significant for rural or isolated areas, and telemedicine offers a greater abundance of advanced medical resources for primary hospital consultations in these vast rural regions, thereby enhancing the quality of medical and healthcare services ( 10 , 28 , 29 ).

The incorporation of telemedicine into the healthcare systems of low-and middle-income countries (LMICs), such as Ethiopia, has the potential to bring about cost savings and resource conservation in the long run. Consequently, this could alleviate the financial burden on individuals and enhance their access to affordable healthcare services ( 17 ). It is important to note that in many LMICs, a significant portion of overall health spending comes from out-of-pocket payments, as there is often no general health insurance available ( 30 ). Moreover, the COVID-19 pandemic has further strained the already fragile healthcare systems in LMICs ( 10 , 31 ). In this regard, telemedicine services could be crucial in relieving pressure on the healthcare system by saving time and resources and enhancing efficiency and accessibility. Additionally, telemedicine can facilitate social distancing measures and reduce the need for face-to-face interactions in hospitals and clinics, helping prevent the spread of infectious diseases like COVID-19 through physical contact ( 10 , 32 ). Furthermore, telemedicine can also be instrumental in providing counseling and specific advice to patients during the COVID-19 pandemic, such as guidance on prevention measures. Overall, the adoption of telemedicine in LMICs holds great potential for addressing healthcare challenges, reducing costs, and improving access to quality care. It can serve as a valuable tool in mitigating the impact of the COVID-19 pandemic and strengthening healthcare systems in these countries ( 33 ).

Throughout the initial three waves of the COVID-19 pandemic in Ethiopia, most patients seeking medical care were directed to the HBIC. This strategic decision is believed to have effectively alleviated the potential burden of cases and prevented burnout among the existing treatment facilities ( 2 ). The HBIC specifically caters to COVID-19 patients and represents our country’s pioneering national telehealth service. Therefore, it is crucial to examine its operational experiences thoroughly. The focus should be on integrating functionalities that encourage community acceptance of this telehealth modality. As COVID-19 patients continue to be enrolled in the HBIC, the findings from this study will serve as a valuable resource for the Ministry of Health and COVID-19 response teams in their efforts to enhance the healthcare system. The HBIC framework offers a practical solution for healthcare providers who aim to extend their services to patients residing in remote areas. Moreover, the growing acceptance and familiarity with telemedicine visits, driven by the pandemic, are likely to shape the future landscape of healthcare delivery for both patients and providers.

The study’s findings should be evaluated considering the strengths and limitations identified. The study’s strength lies in the thorough selection process of participants from various sub-cities throughout the entire duration of the service. The research questions were also carefully developed using a validated tool and assessed for internal consistency, ensuring their comprehensibility.

4.1 Limitations

It is important to acknowledge a limitation of the study, which is the potential recall bias introduced by enrolling most patients during the initial phase of the COVID-19 pandemic. Despite this limitation, this study is expected to pave the way for advancements in telemedical services in Ethiopia. Furthermore, it can potentially expand and incorporate other telemedicine care modalities, such as videoconferencing, in the future.

5 Conclusion

The investigation evaluated patient satisfaction and length of stay in telemedicine services. The findings revealed that most patients, accounting for over 70.5%, reported high or very high satisfaction with these services. Notably, patients who received frequent follow-up phone calls and exhibited symptomatic COVID-19 disease expressed higher satisfaction. Additionally, it was observed that a higher frequency of phone calls and in-person visits resulted in a shorter stay in the Hospital-Based Isolation Center (HBIC). Consequently, it is crucial to consider the aforementioned factors to enhance patient satisfaction and reduce the length of stay in HBIC or other telemedicine services. It is worth mentioning that the HBIC, which caters specifically to COVID-19 patients, represents the first large-scale national telemedicine service implemented in our country. Therefore, it is imperative to thoroughly examine the experiences gained from this service, with particular attention given to incorporating features that facilitate community acceptance and reimbursement of this mode of healthcare delivery. Meanwhile, as the enrollment of COVID-19 patients in the HBIC continues, the findings of this study will serve as a valuable resource for guiding the Ministry of Health, the Ethiopian Public Health Institute, and the COVID-19 response team in their efforts to improve the system.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by the Addis Ababa Health Bureau Public Health Research and Emergency Ethical Review Committee. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

DG: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. ZA: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. FC: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. FB: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. YT: Writing – review & editing, Writing – original draft, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. CM: Writing – review & editing, Writing – original draft, Supervision, Resources, Methodology, Investigation, Formal analysis, Data curation. JR: Writing – review & editing, Writing – original draft, Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation. CA-L: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

We offer our deepest gratitude to Tigist Workneh and Diribsa Tsegaye from Gamby Medical and Business College. We want to thank all the research participants and data collectors. We are very grateful for the support of the Biomedical Research Support Unit at Hospital Las Higueras (HHT), especially to the staff members Lorena, Karin, Jeannette, and Yosselyn.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2024.1384078/full#supplementary-material

1. World Health Organization . WHO coronavirus (COVID-19) dashboard | WHO coronavirus (COVID-19) dashboard with vaccination data . (2023). Available at: https://covid19.who.int/

Google Scholar

2. Ethiopian Public Health Institute . National implementation guide for COVID-19 home-based isolation and care [internet] Addis Ababa (2023) Available at: https://ephi.gov.et/images/novel_coronavirus/EPHI_PHEOC_COVID-19_Confirmed_Case_Home_Based_Isolation_and_Care_Guide_English.pdf .

3. Adebayo, PB, Jusabani, A, Mukhtar, M, and Zehri, AA. The changing trend of teleconsultations during COVID-19 era at a tertiary facility in Tanzania. Pan Afr Med J . (2020) 35:125. doi: 10.11604/pamj.supp.2020.35.2.24977

Crossref Full Text | Google Scholar

4. Kamulegeya, LH, Bwanika, JM, Musinguzi, D, and Bakibinga, P. Continuity of health service delivery during the covid-19 pandemic: the role of digital health technologies in Uganda. Pan Afr Med J . (2020) 35:1–3. doi: 10.11604/pamj.supp.2020.35.2.23115

5. Armand, K, Gaël, A, Marcien, N, Wilson, N, Reine, M, and Claude, N. Telemedicine and COVID-19: experience of medical doctors in Cameroon. Am J Heal Med Nurs Pract . (2021) 6:32–7. doi: 10.47672/ajhmn.666

6. Wan, S, Chen, Y, Xiao, Y, Zhao, Q, Li, M, and Wu, S. Spatial analysis and evaluation of medical resource allocation in China based on geographic big data. BMC Health Serv Res . (2021) 21:1–18. doi: 10.1186/s12913-021-07119-3

7. Constanzo, FM, Aracena-Sherck, P, Peña, L, Marrugo, M, Gonzalez, J, Vergara, G, et al. Characterization of the Teleneurology patients at the hospital Las Higueras de Talcahuano-Chile. Front Neurol . (2020) 11:1438. doi: 10.3389/fneur.2020.595577

8. Constanzo, F, Aracena-Sherck, P, Hidalgo, JP, Peña, L, Marrugo, M, Gonzalez, J, et al. Contribution of a synchronic teleneurology program to decrease the patient number waiting for a first consultation and their waiting time in Chile. BMC Med Inform Decis Mak . (2020) 20:20. doi: 10.1186/s12911-020-1034-2

PubMed Abstract | Crossref Full Text | Google Scholar

9. Scudeller, PG, Pereira, AJ, Cerri, GG, Jatene, FB, Bego, M, Amaral, TF, et al. Telemedicine in Brazil: teleconsultations at the largest University Hospital in the Country. Telemed Rep . (2023) 4:193–203. doi: 10.1089/tmr.2023.0012

10. Constanzo, F, Benavides, L, Garcés, J, Villalobos, R, Marrugo, M, Kuzmanic, K, et al. Changes in Televisit modalities due to the COVID-pandemic in Chile: a comparison of patient satisfaction. Cureus . (2024) 16:1–12. doi: 10.7759/cureus.55078

11. Paganoni, S, van de Rijn, M, Drake, K, Burke, K, Doyle, M, Ellrodt, AS, et al. Adjusted cost analysis of video televisits for the care of people with amyotrophic lateral sclerosis. Muscle Nerve . (2019) 60:147–54. doi: 10.1002/mus.26606

12. Centro Nacional de Sistemas de Salud (CENS) . Telemedicina durante la epidemia de COVID-19 en Chile: Guía de Buenas Prácticas y Recomendaciones . (2020). Available at: https://cens.cl/guia-de-buenas-practicas-y-recomendaciones-en-telemedicina/

13. Constanzo, F, Aracena-Sherck, P, Hidalgo, JP, Muñoz, M, Vergara, G, and Alvarado, C. Validation of a patient satisfaction survey of the Teleneurology program in Chile. BMC Res Notes . (2019) 12:359. doi: 10.1186/s13104-019-4358-1

14. Nguyen, M, Waller, M, Pandya, A, and Portnoy, J. A review of patient and provider satisfaction with telemedicine. Curr Allergy Asthma Rep . (2020) 20:72. doi: 10.1007/s11882-020-00969-7

15. Kruse, CS, Krowski, N, Rodriguez, B, Tran, L, Vela, J, and Brooks, M. Telehealth and patient satisfaction: a systematic review and narrative analysis. BMJ Open . (2017) 7:e016242. doi: 10.1136/bmjopen-2017-016242

16. Poitras, ME, Poirier, MD, Couturier, Y, T Vaillancourt, V, Cormier, C, Gauthier, G, et al. Chronic conditions patient’s perception of post-COVID-19 pandemic teleconsulting continuation in primary care clinics: a qualitative descriptive study. BMJ Open . (2022) 12:e066871. doi: 10.1136/bmjopen-2022-066871

17. Tiwari, BB, Kulkarni, A, Zhang, H, Khan, MM, and Zhang, DS. Utilization of telehealth services in low- and middle-income countries amid the COVID-19 pandemic: a narrative summary. Glob Health Action . (2023) 16:2179163. doi: 10.1080/16549716.2023.2179163

18. Vosburg, RW, and Robinson, KA. Telemedicine in primary care during the COVID-19 pandemic: provider and patient satisfaction examined. Telemed J . (2022) 28:167–75. doi: 10.1089/tmj.2021.0174

19. Mekonnen, H . COVID-19 in Ethiopia: assessment of how the Ethiopian government has executed administrative actions and managed risk communications and community engagement. Risk Manag Healthc Policy . (2020) 13:2803–10. doi: 10.2147/RMHP.S278234

20. Borghans, I, Kleefstra, SM, Kool, RB, and Westert, GP. Is the length of stay in hospital correlated with patient satisfaction? Int J Qual Heal Care . (2012) 24:443–51. doi: 10.1093/intqhc/mzs037

21. Nguyen Thi, PL, Briançon, S, Empereur, F, and Guillemin, F. Factors determining inpatient satisfaction with care. Soc Sci Med . (2002) 54:493–504. doi: 10.1016/S0277-9536(01)00045-4

22. Sahin, B, Yilmaz, F, and Lee, KH. Factors affecting inpatient satisfaction: structural equation modeling. J Med Syst . (2007) 31:9–16. doi: 10.1007/s10916-006-9038-8

23. Tokunaga, J, and Imanaka, Y. Influence of length of stay on patient satisfaction with hospital care in Japan. Int J Qual Heal Care. (2002) 14:493–502. doi: 10.1093/intqhc/14.6.493

24. Quintana, JM, González, N, Bilbao, A, Aizpuru, F, Escobar, A, Esteban, C, et al. Predictors of patient satisfaction with hospital health care. BMC Health Serv Res . (2006) 6:102. doi: 10.1186/1472-6963-6-102

25. Findik, UY, Unsar, S, and Sut, N. Patient satisfaction with nursing care and its relationship with patient characteristics. Nurs Health Sci . (2010) 12:162–9. doi: 10.1111/j.1442-2018.2009.00511.x

26. Rajkumar, E, Gopi, A, Joshi, A, Thomas, AE, Arunima, NM, Ramya, GS, et al. Applications, benefits and challenges of telehealth in India during COVID-19 pandemic and beyond: a systematic review. BMC Health Serv Res . (2023) 23:7. doi: 10.1186/s12913-022-08970-8

27. Desta, AA, Woldearegay, TW, Gebremeskel, E, Alemayehu, M, Getachew, T, Gebregzabiher, G, et al. Impacts of COVID-19 on essential health services in Tigray, northern Ethiopia: a prepost study. PLoS One . (2021) 16:e0256330. doi: 10.1371/journal.pone.0256330

28. Seto, E, Smith, D, Jacques, M, and Morita, PP. Opportunities and challenges of telehealth in remote communities: case study of the Yukon telehealth system. J Med Internet Res . (2019) 7:e11353. doi: 10.2196/11353

29. Cochrane Effective Practice and Organisation of Care GroupGonçalves-Bradley, DC, J Maria, AR, Ricci-Cabello, I, Villanueva, G, Fønhus, MS, et al. Mobile technologies to support healthcare provider to healthcare provider communication and management of care. Cochrane Database Syst Rev . (2020) 2020:CD012927. doi: 10.1002/14651858.CD012927.pub2,

30. Sallnow, L, Smith, R, Ahmedzai, SH, Bhadelia, A, Chamberlain, C, Cong, Y, et al. Report of the lancet commission on the value of death: bringing death back into life. Lancet . (2023) 399:837–84. doi: 10.1016/S0140-6736(21)02314-X

31. Asante, A, Price, J, Hayen, A, Jan, S, and Wiseman, V. Equity in health care financing in low- and middle-income countries: a systematic review of evidence from studies using benefit and financing incidence analyses. PLoS One . (2016) 11:e0152866. doi: 10.1371/journal.pone.0152866

32. Eslami Jahromi, M, and Ayatollahi, H. Utilization of telehealth to manage the Covid-19 pandemic in low- and middle-income countries: a scoping review. J Am Med Inform Assoc . (2023) 30:738–51. doi: 10.1093/jamia/ocac250

33. Kaeley, N, Choudhary, S, Mahala, P, and Nagasubramanyam, V. Current scenario, future possibilities and applicability of telemedicine in hilly and remote areas in India: a review protocol. J Fam Med Prim Care . (2021) 10:77. doi: 10.4103/jfmpc.jfmpc_1085_20

Keywords: patient satisfaction, COVID-19, home care, telehealth, telemedicine, digital health

Citation: Gashaw DG, Alemu ZA, Constanzo F, Belay FT, Tadesse YW, Muñoz C, Rojas JP and Alvarado-Livacic C (2024) COVID-19 patient satisfaction and associated factors in telemedicine and hybrid system. Front. Public Health . 12:1384078. doi: 10.3389/fpubh.2024.1384078

Received: 09 February 2024; Accepted: 20 March 2024; Published: 05 April 2024.

Reviewed by:

Copyright © 2024 Gashaw, Alemu, Constanzo, Belay, Tadesse, Muñoz, Rojas and Alvarado-Livacic. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dagmawit G. Gashaw, [email protected] ; Freddy Constanzo, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.