'The false reporter will get a praise and the one who reported truth will be discouraged': a qualitative study on intentional data falsification by frontline maternal and newborn healthcare workers in two regions in Ethiopia.

INTRODUCTION: Health Management Information Systems (HMIS) are vital to ensure accountability and for making decisions including for tracking the Sustainable Development Goals. The Ethiopia Health Sector Transformation Plan II includes preventing data falsification as a major strategic initiative and our study aimed to explore the reasons why healthcare providers intentionally falsify maternal and newborn health (MNH) data in two regions of Ethiopia. METHODS: We conducted a qualitative study in two hospitals, four health centres and their associated health posts in Oromia and Amhara regions. We conducted 45 in-depth interviews with health facility managers, quality improvement (QI) focal persons, health information technicians, MNH care providers, Health Extension Workers and QI mentors. Data were collected in local languages and transcribed in English. During analysis we repeatedly read the transcripts, coded them inductively using NVivo V.12, and categorised the codes into themes. RESULTS: Participants were hesitant to report personal data falsification but many reported that falsification is common and that they had experienced it in other facilities or had been told about it by other health workers. Falsification was mostly inflating the number of services provided (such as deliveries). Decreasing the number of deaths or reclassifying neonatal death into stillbirths was also reported. An overarching theme was that the health system focuses on, and rewards, the number of services provided over any other metric. This focus led to both system and individual level incentives for falsification and disincentives for accurate reporting. CONCLUSION: Our finding suggests that to reduce facility level data falsification policy makers might consider disentangling reward and punishments from the performance reports based on the routine HMIS data. Further studies examining the high-level drivers of falsification at regional, national and global levels and effective interventions to address the drivers of data falsification are needed.