Preliminary validation of the PRImary care facility Management Evaluation tool (PRIME-Tool), a national facility management survey implemented in Ghana

The relationship between decision-making autonomy and training on facility-level management performance of primary health care facilities in Odisha, India

Background: Primary health care quality remains poor in many countries, despite its importance for universal health coverage. Evidence shows that better management of primary health care facilities improves service quality, and that facility managers’ autonomy and training levels can augment their management performance. In India, there is scant research in this area. Research questions include: 1) What is the effect of facility-level autonomy on management performance and is the effect modified by management training? 2) Which aspects of facility management are most sensitive to facility-level autonomy and is the effect augmented by management training?  Methods: Using a multi-stage, regionally representative survey of health facilities in Odisha (n=396), a validated tool was used to measure management performance. An “autonomy score” was created to understand which facility management decisions are within a manager’s capacity. Multivariable linear regressions were used to assess the association of decision-making autonomy and management training with performance scores.  Results: The mean performance score across all facilities was 0.657 (SD = 0.148) on a 0-1 scale; the mean autonomy score was 0.619 (SD = 0.305). Autonomy scores were not associated with a significant difference in performance scores; however, management training had an independent positive association with the human resources and monitoring domains of facility management.  Conclusion: In Odisha, India management training may improve management performance, and targeted training initiatives may strengthen a primary care facility’s ability to retain staff and monitor performance. Our data did not demonstrate a significant association between decision-making autonomy and management performance, highlighting a need for further study on how decision-making autonomy may augment a manager’s ability to leverage their skills to improve facility outcomes. In summary, neither management training nor decision-making autonomy alone will sufficiently improve primary care management but targeting the improvement of management training may improve a subset of performance outcomes.

Health facility management and primary health care performance in Uganda

Background

Primary health care is a critical foundation of high-quality health systems. Health facility management has been studied in high-income countries, but there are significant measurement gaps about facility management and primary health care performance in low and middle-income countries. A primary health care facility management evaluation tool (PRIME-Tool) was initially piloted in Ghana where better facility management was associated with higher performance on select primary health care outcomes such as essential drug availability, trust in providers, ease of following a provider’s advice, and overall patient-reported quality rating. In this study, we sought to understand health facility management within Uganda's decentralized primary health care system.

Methods

We administered and analyzed a cross-sectional household and health facility survey conducted in Uganda in 2019, assessing facility management using the PRIME-Tool.

Results

Better facility management was associated with better essential drug availability but not better performance on measures of stocking equipment. Facilities with better PRIME-Tool management scores trended towards better performance on a number of experiential quality measures. We found significant disparities in the management performance of primary health care facilities. In particular, patients with greater wealth and education and those living in urban areas sought care at facilities that performed better on management. Private facilities and hospitals performed better on the management index than public facilities and health centers and clinics.

Conclusions

These results suggest that investments in stronger facility management in Uganda may strengthen key aspects of facility readiness such as essential drug availability and potentially could affect experiential quality of care. Nevertheless, the stark disparities demonstrate that Uganda policymakers need to target investments strategically in order to improve primary health care equitably across socioeconomic status and geography. Moreover, other low and middle-income countries may benefit from the use of the PRIME-Tool to rapidly assess facility management with the goal of understanding and improving primary health care performance.

Adaptation of the Texas Christian University Organisational Readiness for Change Short Form (TCU-ORC-SF) for use in primary health facilities in South Africa

OBJECTIVES

The Texas Christian University Organisational Readiness for Change Scale (TCU-ORC) assesses factors influencing adoption of evidence-based practices. It has not been validated in low-income and middle-income countries (LMIC). This study assessed its psychometric properties in a South African setting with the aim of adapting it into a shorter measure.

METHODS

This study was conducted in 24 South African primary healthcare clinics in the Western Cape Province. The TCU-ORC and two other measures, the Organisational Readiness to Change Assessment (ORCA) and the Checklist for Assessing Readiness for Implementation (CARI) were administered. The questionnaire was readministered after 2 weeks to obtain data on test-retest reliability. Three hundred and ninety-five surveys were completed: 281 participants completed the first survey, and 118 recompleted the assessments.

RESULTS

We used exploratory factor analysis (EFA) to identify latent dimensions represented in the data. Cronbach's alpha for each subscale was assessed and we examined the extent to which the subscales and total scale scores for the first and retest surveys correlated. Convergent validity was assessed by the correlation coefficient between the TCU-ORC, ORCA and CARI total scale scores. EFA resulted in a three-factor solution. The three subscales proposed are Clinic Organisational Climate (8 items), Motivational Readiness for Change (13 items) and Individual Change Efficacy (5 items) (26 items total). Cronbach's alpha for each subscale was >0.80. The overall shortened scale had a test-retest correlation of r=0.80, p<0.01, acceptable convergent validity with the ORCA scale (r=0.56, p<0.05), moderate convergence with the CARI (r=39, p<0.05) and strong correlation with the original scale (r=0.79, p<0.05).

CONCLUSIONS

This study presents the first psychometric data on the TCU-ORC from an LMIC. The proposed shortened tool may be more feasible for use in LMICs.

TRIAL REGISTRATION NUMBER

Results stage. Project MIND trial. Pan-African Clinical Trials Registry. PACTR201610001825405.

Does decentralization of health systems translate into decentralization of authority? A decision space analysis of Ugandan healthcare facilities

Since the 1990s, following similar reforms to its general politico-administrative systems, Uganda has decentralized its public healthcare system by shifting decision-making power away from its central Ministry of Health and towards more distal administrative levels. Previous research has used decision space—the decision-making autonomy demonstrated by entities in an administrative hierarchy—to measure overall health system decentralization. This study aimed to determine how the decision-making autonomy reported by managers of Ugandan healthcare facilities (de facto decision space) differs from that which they are allocated by official policies (de jure decision space). Additionally, it sought to determine associations between decision space and indicators of managerial performance. Using quantitative primary healthcare data from Ugandan healthcare facilities, our study determined the decision space expressed by facility managers and the performance of their facilities on measures of essential drug availability, quality improvement and performance management. We found managers reported greater facility-level autonomy than expected in disciplining staff compared with recruitment and promotion, suggesting that managerial functions that require less financial or logistical investment (i.e. discipline) may be more susceptible to differences in de jure and de facto decision space than those that necessitate greater investment (i.e. recruitment and promotion). Additionally, we found larger public health facilities expressed significantly greater facility-level autonomy in drug ordering compared with smaller facilities, which indicates ongoing changes in the Ugandan medical supply chain to a hybrid ‘push-pull’ system. Finally, we found increased decision space was significantly positively associated with some managerial performance indicators, such as essential drug availability, but not others, such as our performance management and quality improvement measures. We conclude that increasing managerial autonomy alone is not sufficient for improving overall health facility performance and that many factors, specific to individual managerial functions, mediate relationships between decision space and performance.