Quality of routine health data collected by health workers using smartphone at primary health care in Ethiopia

Background: Mobile phone based applications are considered by many as potentially useful for addressing challenges and improving the quality of data collection in developing countries. Yet very little evidence is available supporting or refuting the potential and widely perceived benefits on the use of electronic forms on smartphones for routine patient data collection by health workers at primary health care facilities.

Methods: A facility based cross sectional study using a structured paper checklist was prepared to assess the completeness and accuracy of 408 electronic records completed and submitted to a central database server using electronic forms on smartphones by 25 health workers. The 408 electronic records were selected randomly out of a total of 1772 maternal health records submitted by the health workers to the central database over a period of six months. Descriptive frequencies and percentages of data completeness and error rates were calculated.

Results: When compared to paper records, the use of electronic forms significantly improved data completeness by 209 (8%) entries. Of a total 2622 entries checked for completeness, 2602 (99.2%) electronic record entries were complete, while 2393 (91.3%) paper record entries were complete. A very small percentage of error rates, which was easily identifiable, occurred in both electronic and paper forms although the error rate in the electronic records was more than double that of paper records (2.8% vs. 1.1%). More than half of entry errors in the electronic records related to entering a text value.

Conclusions: With minimal training, supervision, and no incentives, health care workers were able to use electronic forms for patient assessment and routine data collection appropriately and accurately with a very small error rate. Minimising the number of questions requiring text responses in electronic forms would be helpful in minimizing data errors. (C) 2017 Elsevier B.V. All rights reserved.