Health Data Management Practice and Associated Factors Among Health Professionals Working at Public Health Facilities in Resource Limited Settings

"We don't trust all data coming from all facilities": factors influencing the quality of care network data quality in Ethiopia

BACKGROUND

Good quality data are a key to quality health care. In 2017, WHO has launched the Quality of Care Network (QCN) to reduce maternal, newborn and stillbirth mortality via learning and sharing networks. Guided by the principle of equity and dignity, the network members agreed to implement the programme in 2017-2021.

OBJECTIVE

This paper seeks to explore how QCN has contributed to improving data quality and to identify factors influencing quality of data in Ethiopia.

METHODS

We conducted a qualitative study in selected QCN facilities in Ethiopia using key informant interview and observation methods. We interviewed 40 people at national, sub-national and facility levels. Non-participant observations were carried out in four purposively selected health facilities; we accessed monthly reports from 41 QCN learning facilities. A codebook was prepared following a deductive and inductive analytical approach, coded using Nvivo 12 and thematically analysed.

RESULTS

There was a general perception that QCN had improved health data documentation and use in the learning facilities, achieved through coaching, learning and building from pre-existing initiatives. QCN also enhanced the data elements available by introducing a broader set of quality indicators. However, the perception of poor data quality persisted. Factors negatively affecting data quality included a lack of integration of QCN data within routine health system activities, the perception that QCN was a pilot, plus a lack of inclusive engagement at different levels. Both individual and system capabilities needed to be strengthened.

CONCLUSION

There is evidence of QCN's contribution to improving data awareness. But a lack of inclusive engagement of actors, alignment and limited skill for data collection and analysis continued to affect data quality and use. In the absence of new resources, integration of new data activities within existing routine health information systems emerged as the most important potential action for positive change.

Influence of Basic Health Care Provision Fund in improving primary Health Care in Kano state, a descriptive cross-sectional study

BACKGROUND

The Basic Health Care Provision Fund (BHCPF) is a direct financial investment that funds Primary Healthcare (PHC) to improve the quality of services. This study assessed the influence of the BHCPF in improving PHC services.

METHODS

A descriptive cross-sectional study was conducted among PHC workers in 100 facilities randomly selected from the 484 designated PHCs for implementing the BHCPF project in Kano state. Using multiple sampling methods, 200 healthcare workers in PHC facilities were selected and assisted by trained data collectors to respond to the questionnaires. Chi-square analysis was used to show associated factors, while binary regression analysis was used to determine the relationship between factors influencing the BHCPF implementation in PHC.

RESULT

The findings showed healthcare workers had higher awareness (61.7%) and good utilization (57.1%) of BHCPF. Challenges of the BHCPF implementation were insufficiently skilled health professionals (85%), lack of data management capacity (52.6%), low community participation and awareness (52.0%), delay in releasing funds (60.7%), poor infrastructure (87.8%), and weak financial management and accountability system (58.2%). Healthcare professionals having a diploma were four times more likely to have the National Health Management Information System (NHMIS) in their facilities (AOR = 4.955, 95% CI = 1.120-21.036; P-value 0.035) than those without. Primary healthcare facilities were two times more likely to have the NHMIS (AOR = 2.549, 95% CI = 1.167-5.566: P-value 0. 019) than health post.

CONCLUSION

The factors that influenced PHC facilities to promote the implementation of BHCPF included: periodic evaluation of the facilities, availability of functional storage facilities, and improving the standard of care in PHC facilities. There is a need for retraining healthcare workers and creating more community awareness of the BHCPF.

What, Where, and How to Collect Real-World Data and Generate Real-World Evidence to Support Drug Reimbursement Decision-Making in Asia: A reflection Into the Past and A Way Forward

BACKGROUND

Globally, there is increasing interest in the use of real-world data (RWD) and real-world evidence (RWE) to inform health technology assessment (HTA) and reimbursement decision-making. Using current practices and case studies shared by eleven health systems in Asia, a non-binding guidance that seeks to align practices for generating and using RWD/RWE for decision-making in Asia was developed by the REAL World Data In ASia for HEalth Technology Assessment in Reimbursement (REALISE) Working Group, addressing a current gap and needs among HTA users and generators.

METHODS

The guidance document was developed over two face-to-face workshops, in addition to an online survey, a face-to-face interview and pragmatic search of literature. The specific focus was on what, where and how to collect RWD/ RWE.

RESULTS

All 11 REALISE member jurisdictions participated in the online survey and the first in-person workshop, 10 participated in the second in-person workshop, and 8 participated in the in-depth face-to-face interviews. The guidance document was iteratively reviewed by all working group members and the International Advisory Panel. There was substantial variation in: (a) sources and types of RWD being used in HTA, and (b) the relative importance and prioritization of RWE being used for policy-making. A list of national-level databases and other sources of RWD available in each country was compiled. A list of useful guidance on data collection, quality assurance and study design were also compiled.

CONCLUSION

The REALISE guidance document serves to align the collection of better quality RWD and generation of reliable RWE to ultimately inform HTA in Asia.