ArticleBMJ global health2022
'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.
Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 17 citations in OpenAlex.
- Health Misinformation in Ethiopia: Myths, Media Dynamics, Public Response, and Policy Implications: A Narrative Review.Public health challenges · 2026Review
- Impact analysis and evaluation of the Ethiopian Neonatal Network.BMJ global health · 2026Article
- Mapping multilevel barriers impacting the performance of Ethiopia's Community-Based Health Extension Program: A scoping review.PloS one · 2026Article
- Health system readiness for immediate Kangaroo Mother Care (iKMC) among network of care facilities in the Sidama region, Ethiopia: a mixed-method study.Gates open research · 2026Article
- Decline in malaria test positivity rates following capacity building and archiving of malaria rapid diagnostic test cassettes in Oyo State, Nigeria: a retrospective review of records.Malaria journal · 2025Article
- Article
- Integration of family planning into the primary health care in Ethiopia: results from national assessment.Reproductive health · 2024Article
- Stronger Evaluations are Needed for Interventions to Improve Health Worker Performance.The American journal of tropical medicine and hygiene · 2024Article
- Travelling numbers and broken loops: A qualitative systematic review on collecting and reporting maternal and neonatal health data in low-and lower-middle income countries.SSM - population health · 2024Review
- Health system barriers to the first dose of measles immunization in Ethiopia: a qualitative study.BMC public health · 2024Article
- Improvements in Obstetric and Newborn Health Information Documentation following the Implementation of the Safer Births Bundle of Care at 30 Facilities in Tanzania.Healthcare (Basel, Switzerland) · 2024Article
- "We don't trust all data coming from all facilities": factors influencing the quality of care network data quality in Ethiopia.Global health action · 2023Article
- 'The objective was about not blaming one another': a qualitative study to explore how collaboration is experienced within quality improvement collaboratives in Ethiopia.Health research policy and systems · 2023Article
- "Quality teaches you how to use water. It doesn't provide a water pump": a qualitative study of context and mechanisms of action in an Ethiopian quality improvement program.BMC health services research · 2023Article
- "Safer Births Bundle of Care" Implementation and Perinatal Impact at 30 Hospitals in Tanzania-Halfway Evaluation.Children (Basel, Switzerland) · 2023Article
- Understanding maternity care providers' use of data in Southern Tanzania.BMJ global health · 2023Article
- Feasibility, usability and acceptability of a novel digital hybrid-system for reporting of routine maternal health information in Southern Tanzania: A mixed-methods study.PLOS global public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHealth 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.
methodsWe 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.
resultsParticipants 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.
conclusionOur 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.