OBJECTIVE: In developing countries, the poor quality of data derived from Health Information Systems constitutes a problem that limits use of these data and contributes to the recurrent difficulties of health system management. The low level of involvement of health workers directly responsible for data may contribute to this poor quality. This study documents a Health Information System collection tool design experience by health workers and assesses its effect on data quality. METHODS: Eighty health workers responsible for clinical statistics in public health centres participated in this study. The two tools used for clinical data collection were modified by a group of 6 volunteer health workers. Monitoring indicators, data entry time, percentage exhaustiveness and quality of data were assessed before and after using the new tools. Data were compared by Wilcoxon’s test for paired data and Mc Nemar’s chi-square test. RESULTS: Between the two assessments, the data entry time increased from 28.7 to 22.5 seconds by reported case (p=0.153), the exhaustiveness of the reports increased from 16% to 89% (p<0.001) and the proportion of reports with sufficient data quality increased from 18.8% to 45.8% (p=0.002). CONCLUSION: The positive course of the indicators shows that increased involvement of health workers in key stages such as the design of data collection tools can help improve data quality.
OBJECTIVE: In developing countries, the poor quality of data derived from Health Information Systems constitutes a problem that limits use of these data and contributes to the recurrent difficulties of health system management. The low level of involvement of health workers directly responsible for data may contribute to this poor quality. This study documents a Health Information System collection tool design experience by health workers and assesses its effect on data quality. METHODS: Eighty health workers responsible for clinical statistics in public health centres participated in this study. The two tools used for clinical data collection were modified by a group of 6 volunteer health workers. Monitoring indicators, data entry time, percentage exhaustiveness and quality of data were assessed before and after using the new tools. Data were compared by Wilcoxon’s test for paired data and Mc Nemar’s chi-square test. RESULTS: Between the two assessments, the data entry time increased from 28.7 to 22.5 seconds by reported case (p=0.153), the exhaustiveness of the reports increased from 16% to 89% (p<0.001) and the proportion of reports with sufficient data quality increased from 18.8% to 45.8% (p=0.002). CONCLUSION: The positive course of the indicators shows that increased involvement of health workers in key stages such as the design of data collection tools can help improve data quality.
Authors: Jieun Lee; Caroline A Lynch; Lauren Oliveira Hashiguchi; Robert W Snow; Naomi D Herz; Jayne Webster; Justin Parkhurst; Ngozi A Erondu Journal: BMJ Glob Health Date: 2021-06