Responsiveness of services rendered at primary healthcare facilities of Bharatpur, Nepal: a cross-sectional study

Introduction

The WHO Health Report 2000 has considered health system responsiveness (HSR) as the inherent goal of health system and is considered as an important aspect of effective health system.1 Responsiveness is defined by WHO as ‘how well the health system meets the legitimate expectations of population for non-health enhancing aspects of the health system’.2 3 As the responsiveness is derived from a variety of disciplines it can be described as the overall experience of an individual when interacting with the health system, including things like the way they are treated and the quality of the environment in which they are treated.1 2 This includes eight domains: dignity, autonomy, privacy and confidentiality, prompt attention, adequate quality of basic amenities, communication, access to social networks, family and community support and choice of medical providers.4

Moreover, WHO has recognised primary healthcare (PHC) as a crucial aspect of health service delivery, as outlined in the Alma Ata Declaration of 1978 and Astana Declaration of 2018, reigniting the worldwide effort to enhance PHC with the goal of enhancing the responsiveness and readiness of a nation’s healthcare system.2 5 When functioning at the highest level, primary care serves as a gateway to the health system and delivers seamless, coordinated health services to individuals at an affordable price.6

Despite the development of a widespread PHC network over the past few decades that covers both rural and urban areas of the country, there are numerous obstacles to its efficient operation.7 Numerous studies have indicated that healthcare institutions suffer from insufficient funding, inadequate supply of health workforce, inadequately trained and motivated health workforce and inadequate logistical support.8 Patients frequently encounter inappropriate behaviour from healthcare providers, such as disrespect, abuse, neglect and even denial of care.8 Furthermore, this circumstance is aggravated by health service quality, a lack of consideration for sociocultural factors that influence client perceptions and expectations, and the health systems’ incapacity to cultivate more favourable care environments.9–14

According to the Constitution of Nepal 2015, access to basic health service is a fundamental right of every individual, and it is crucial for achieving overall health and well-being.15 To facilitate the journey towards universal health coverage (UHC) in low and middle-income countries (LMICs), improving PHC through health system strengthening is essential.16 However, the responsiveness of the health system to the needs of patients can vary greatly, especially in LMICs, which are facing significant challenges in its health system.4 17

In Nepal, PHC is provided through a network of health posts (HP), primary healthcare centres (PHCC) and other health facilities.18 These facilities under the local government are responsible for providing basic health services to the people.19 Despite the central role of PHC facilities in ensuring the health and well-being of populations, there is limited understanding of the responsiveness of the critical components of health systems. This lack of data represents a significant gap in our understanding of responsiveness of services and hinders the development of effective strategies to improve the quality of healthcare services provided by PHC facilities. Therefore, this study aimed to assess the responsiveness of services and identify associated factors at PHC facilities of Bharatpur, Nepal.

Materials and methods

Sample size and sampling

While calculating the sample size, allowable error was kept at 5%, confidence level as 95% and prevalence data as 67%.21 The sample size for the outpatients to participate in the study was computed using the Cochran formula22:

=339.75ᵙ340

The required sample size for calculating the finite population is calculated by considering the infinite population correction factor.

Finite population (N)=6048, which is the total outpatient visits in the previous months in the PHC facilities.

=321.908ᴝ322

Adding non-response rate of 10%,

n=357.77ᴝ358

The total number of the outpatient visits in the previous month (May) was obtained from the Public Health Promotion Section of BMC. Required total sample size was calculated using Cochran formula for finite population.

Out of 40 PHC facilities this study was conducted among the PHCCs and HPs, out of which (14; 1 PHCC and 13 HPs) six health facilities were selected through simple random sampling. The final sample size was split across the six health facilities (Shivanagar PHCC, Gitanagar HP, Bharatpur HP, Saradhanagar HP, Gunjanagar HP and Mangalpur HP) by using probability proportion to size sampling. Finally, patients visiting outpatient department (OPD) from six selected health facilities were interviewed by convenience sampling (figure 1). Exit interviews with these patients were carried out as they were on their way home after receiving services.

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Figure 1

Sampling procedure. HP, health post; PHCC, primary healthcare centre.

Patients who received healthcare services at the time of the study as an outpatient in the selected PHC facilities were included in the study, whereas patients below 18 years and who could not communicate verbally were excluded from the study. Patients who visited health facility other than PHCC and HPs were excluded from the study.

Data collection tools and variables

The interview schedule (online supplemental material) mainly encompassed sociodemographic variables (age, sex, ethnicity, religion, marital status, educational status, occupation and health insurance), individual-related factors (perceived satisfaction, perceived quality of care and patient health quality), health service accessibility-related factors (time to reach health facility, out-of-pocket expenditure for transport and visit to traditional healer) and WHO responsiveness assessment questionnaires. Closed-ended interview questionnaires adapted from WHO multicountry studies were employed to evaluate responsiveness.23 The questions for patient satisfaction were adopted from Patient Satisfaction Questionnaire 18 and for perceived quality of life questions from SERVQUAL (Service Quality) model.24 25 Also, patient health quality was assessed by nine depression questions adopted from Patient Health Questionnaire 9.26

Responsiveness of the services was the dependent variable and which was assessed by 15 items customised from WHO multicountry studies.23 The 15 items were divided among seven domains: autonomy (2), choice (1), communication (3), confidentiality (2), dignity (2), quality of basic amenities (2) and prompt attention (3). The domain ‘access to social support network’ was not included as it is used to evaluate the inpatient.

The 15 items were measured in a 4-point Likert scale (1 ‘Never’ to 4 ‘Always’), then the items were computed and then dichotomised as ‘good’ and ‘poor’ by the demarcation formula as27:

  

The overall responsiveness score is the sum of the respondents’ ratings (ranging from 1 to 4) across the 15 indicators, encompassing all seven domains

Here, the total highest score signifies the highest cumulative score across all domains by a respondent, while the total lowest score denotes the lowest cumulative score across all domains by a respondent. The final cut-off point obtained through this formula was 27.5. Those above and including the cut-off point to determine ‘Good’ performance, while below scores, were considered ‘Poor’.

Similarly, all the seven domains were added separately and grouped as good and poor by the above formula. Above and including the cut-off point to determine ‘Good’ performance, below scores, was considered ‘Poor’ for each domain independently.

Perceived satisfaction was measured using 5-point Likert scale with five response categories (1 ‘strongly disagree’ to 5 ‘strongly agree’). It was also grouped using the demarcation threshold formula. Above and including the cut-off point (13.5) was considered as ‘Satisfied’ and below ‘dissatisfied’. Similarly, perceived quality was measured using 5-point Likert scale with five response categories (1 ‘Strongly disagree’ to 5 ‘Strongly agree’). It was also grouped using the demarcation threshold formula. Above the cut-off point (25.5) was considered as ‘High’ and below ‘Low’. Patient health quality was assessed by nine questions ranging from 1 ‘always’ to 4 ‘not at all’. It was also grouped using the demarcation threshold formula. Above and including the cut-off point18 was considered as ‘Good’ and below ‘Poor’.

The operational definitions for some of the variables and terms are provided in table 1.

Table 1

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Operational definitions

Also, the internal consistencies of Cronbach’s alpha values for all domains of responsiveness were 0.91. Similarly, the Cronbach’s alpha values for perceived satisfaction, perceived quality of care and patient health quality were 0.89, 0.92 and 0.76, respectively.

The questionnaire form was developed in ODK platform and ODKCollect application was used for the data entry purpose.

The conceptual framework provides a condensed overview of various elements for investigating factors connected to responsiveness encompassing sociodemographic characteristics, individual-related factors and health service accessibility-related factors. The framework itself has been derived and adapted from diverse literature27–29 (figure 2).

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Figure 2

Conceptual framework of the study.

Results

Discussion

This study aimed to assess the responsiveness of services and to identify the factor associated with it among outpatients visiting PHC facilities of Bharatpur, Nepal. Findings of this research highlighted that almost three-quarters of the respondents (74.2%) reported a responsive health service. The finding of this study aligns with a prior study conducted in Iran, which indicated a responsiveness rate of 72.6%.30 However, a study in Germany demonstrated a higher responsiveness score (85%), surpassing the finding of the current research.31 This discrepancy might be due to the type of care accessed; the study in Germany focused on outpatients visiting mental health facilities, which could have influenced the results.

However, some of the studies showed relatively lower responsiveness. For instance, two studies from Ethiopia discovered that the health service was responsive to 66.2% and 68.3% of the service users.27 28 Similar results were seen in the Asian countries, India (62%) and Bangladesh (67%), where the level of responsiveness was reported to be relatively lower than this study.21 32 Similarly, this study demonstrated that the responsiveness of the services was higher than African countries like Nigeria (47.0%) and Ghana (47.1%).33 The variation in the responsiveness could be due to the Nepal’s local governments’ ongoing efforts such as insuring the presence of competent health workers, implementing training programmes and workshops and upgrading infrastructures to enhance the quality of primary health service and enhance the efficiency of health service delivery.19

This study has uncovered variations in the level of service responsiveness across different areas. According to this study, the majority of respondents reported positive experiences in domains such as communication, confidentiality, dignity, prompt attention and quality, with ratings ranging from 84.9% to 97.2%. In this study, the highest were seen among the dignity (97.2%) and communication (91.6%) which aligns with a study conducted in Iran.34 Confidentiality was one of the high-performing domains in this study with 84.9%. One possible reason for these results could be the implementation of minimum service standards (MSS), which emphasise the importance of maintaining patient privacy.35 This finding aligns with a study conducted in Tanzania, where confidentiality (86.7%) and dignity (81.4%) were the domains that received the highest scores in terms of responsiveness.36 Similarly, studies conducted in Iran and Ethiopia also reported favourable results for confidentiality and dignity as high-performing domains.27 37 In contrast to previous studies conducted in Ethiopia, South Africa, Nigeria and Tanzania, this study revealed prompt attention (88.8%) and quality (77.4%) as domains with good performance.17 27 38 39 This discrepancy in findings can be attributed to several factors. First, the relatively low number of patients in the HPs included in this study may have contributed to reduced waiting times, allowing for prompt attention to be provided. Additionally, the implementation of MSS in the health facilities may have played a role in the improved performance of the quality domain. These standards likely outline specific guidelines and protocols for delivering high-quality care, leading to better service provision and patient experiences in terms of quality.35

This study revealed that choice was the least performing domain, with only 22.6% of respondents reporting a good experience. This finding is consistent with a study conducted in Brazil, which reported the lowest performance (24.4%) in the choice domain.40 Studies conducted in Iran and Ethiopia also yielded similar results, with the good performance of choice being reported as 35.8% and 37%, respectively.27 37 This can be attributed to a lack of awareness among patients regarding the specific specialisations of healthcare workers. Additionally, the limited presence of healthcare workers with distinct specialisations further restricts the options and choices available to patients. Similarly, autonomy was also one of the low-performing domains after choice with only 67%. This result was higher than the result of the similar study conducted in Ethiopia where the autonomy was 54.9%.27

The findings of this study revealed that, except age, no sociodemographic variables showed significant association with responsiveness. Specifically, the older age group (≥50 years) was 4.1 times more likely to experience a higher responsiveness of services compared with 18–29 years age group. This finding aligns with a previous study conducted in Ethiopia where the likelihood of responsiveness among respondents aged 50 years and above was 2.48 times higher compared with the younger individuals.41 This finding is consistent with a previous study conducted in Germany42 and Thailand43 which identified a significant association between age and the responsiveness. This may be due to accumulated life experiences and expectations among older individuals; specifically older individuals may have had more encounters with healthcare systems and developed certain expectations regarding responsiveness. However, contrasting results were observed in a study conducted in Tanzania, where older age, sex and marital status were negatively associated with responsiveness, while high income and educational status were positively associated.39 Likewise, a study in Nigeria revealed that gender, educational status and income were significantly associated with responsiveness.3 These findings highlight the complexity and variability of the relationship between sociodemographic factors and responsiveness across different settings and populations. It suggests that cultural, economic and social factors contribute to the divergent results observed in different studies. Further research is needed to understand how sociodemographic variables influence the responsiveness in various contexts.

Several studies have emphasised the positive association between perceived satisfaction and responsiveness of services.28 43 44 This study also supports this concept by demonstrating a positive association between responsiveness and perceived satisfaction. Notably, a study conducted in Ghana revealed that perceived satisfaction was a significant predictor of responsiveness.44 Similarly, studies from Thailand and Ethiopia found that perceived satisfaction was positively linked to responsiveness.28 43 A cross-sectional study involving PHC facility patients in Ethiopia discovered that those who reported higher satisfaction with their care were nearly ten times more likely to experience responsiveness compared with dissatisfied individuals.27 Moreover, WHO proposed that satisfaction exhibited a positive and significant association with all domains of HSR.45 Thus, the available evidence strongly suggests a positive link between perceived satisfaction and responsiveness, indicating that patient satisfaction can serve as a valuable indicator of service responsiveness. When patients are satisfied with their care, it suggests that the healthcare system is meeting their needs and responding effectively.

According to the findings of this study, individuals who perceive a high quality of care are significantly more likely to experience responsiveness in their healthcare. This is supported by a similar study conducted in Ethiopia, which found that an increase of one unit in perceived quality of care led to 0.5% increase in the responsiveness score.28 One possible reason for this might be when individuals perceive that their healthcare providers are committed to delivering high-quality care, it may enhance their trust and satisfaction, leading to a greater perception of responsiveness. However, a separate study conducted in Ethiopia discovered no association between perceived quality of care and responsiveness.27

In the realm of healthcare assessment, responsiveness, perceived quality of care and satisfaction play pivotal roles in understanding and evaluating the patient experience. The interconnectedness between these concepts is intricate and symbiotic.46 47 Responsive healthcare systems, adept at addressing patients’ non-clinical needs, often contribute positively to the perceived quality of care. Elements such as effective communication, respectful treatment and consideration of patient preferences enhance the overall quality perception. Moreover, the perceived quality of care significantly influences satisfaction, as patients are more likely to be satisfied when they believe they have received high quality of care.46 47 Recognising the interdependencies between responsiveness, perceived quality and satisfaction is imperative for healthcare providers and policymakers seeking to optimise the holistic experience for patients.47

The responsiveness of services is influenced by various factors, including financial aspects of healthcare.48 This study revealed that respondents who did not have to make out-of-pocket payments for transport to reach the health facility had 4.63 times higher odds of perceiving higher responsiveness of services. This result aligns with a similar study conducted in Ethiopia where people who had out-of-pocket expenditure for transport experienced a poor responsiveness of services.27 Accordingly, another study demonstrated that improved financial fairness in healthcare led to higher service responsiveness score.28

Our study highlights the need for targeted interventions to improve responsiveness of services. There is a need for the government to allocate resources more efficiently by addressing specific domains identified for the improvement. Additionally, the study sheds light on various factors associated with responsiveness, emphasising the importance of strategic investments in these areas to effectively improve service responsiveness.

Conclusion

The PHC facilities of Bharatpur, Nepal demonstrated nearly three-quarters of the respondents reporting good responsiveness of services at OPD. Dignity received the highest scores, indicating a culture of respect for patients. However, choice had the lowest scores, suggesting a need for improvement in providing patients with options. Respondents above or including 50 years, satisfied clients, those perceiving high-quality care and those not paying for transport experienced better responsiveness than their counterparts. These findings can help local authorities improve health services, and the study provides a foundation for further research and interventions. Recommendations include strengthening the referral mechanism, empowering patients in decision-making and focusing on patient-centred care and quality improvement.