Predictive power of socio-demographic attributes of healthcare workers on data quality in Tanzanian regional referral hospitals
Rogate Phinias, Mikidadi Muhanga, Joshua Malago · 2025
Read Predictive power of socio-demographic attributes of healthcare workers on data quality in Tanzanian regional referral hospitals by Rogate Phinias, Mikidadi Muhanga, Joshua Malago (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12687510.txt.
Description
Rogate Phinias, Mikidadi Muhanga, and Joshua Malago studied health data quality in Tanzania in a 2025 paper. Good care depends on records that are accurate, complete, consistent, and on time, yet the workers who type in patient data can introduce errors. The team asked which traits of those workers predict better data.
They surveyed 336 data-entering health workers at eight regional referral hospitals between August and October 2024. Older workers produced more accurate, complete, and timely records. Sex and schooling also mattered, with education linked above all to accuracy and completeness. The authors suggest training and support should be shaped with these patterns in mind, since errors in patient data can put lives at risk.
Catalog record
| CREATOR | Rogate Phinias, Mikidadi Muhanga, Joshua Malago |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |