“We don’t trust all data coming from all facilities”: factors influencing the quality of care network data quality in Ethiopia

ABSTRACT

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.

KEYWORDS:

• Quality of care network
• data quality
• data reliability
• data learning
• data sharing

Responsible Editor Maria Nilsson

Responsible Editor Maria Nilsson

Acknowledgments

We are grateful to all individuals and organisations for the successful accomplishment of this work. We are greatly indebted to all the study participants, Ethiopian Public Health Institute, London School of Hygiene and Tropical Medicine, Ethiopian Ministry of Health, and Bill and Melinda Gates Foundation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Authors contribution

Conceptualization: AsebeAmenu Tufa, Geremew Gonfa, Anene Tesfa, Nehla Djellouli, Tim Colbourn, TanyaMarchant, SeblewengelLemma

Study design: Nehla Djellouli, TimColbourn, Tanya Marchant, Asebe Amenu Tufa, Seblewengel Lemma, GeremewGonfa, Anene Tesfa

Data collection: Asebe Amenu Tufa, Geremew Gonfa, Anene Tesfa, Theodros Getachew,Desalegn Bekele, Ftalew Dagnaw

Context of the paper

This paper is part of the main QCN Evaluation of the WHO- Network for Improving Quality of Care for Maternal, Newborn and Child Health. The overall research project tried to address: How does a multi-country, multilateral network focused on specific health care improvements evolve and what shapes its ability to achieve its goals? This evaluation study took place in Bangladesh, Ethiopia, Malawi and Uganda from 2019–2022. This manuscript is the country specific, focusing on the role of the network in improving the data quality and its influencing factors in Ethiopia.

Additional information

Funding

This study was conducted by the financial support from Bill and Melinda Gates Foundation [grant number/investment number is INV-007644] through London School of Hygiene and Tropical Medicine.