Assessing a computerized routine health information system in Mali using LQAS

Between 1987 and 1998 Save the Children conducted a child survival programme in Mali with the goal of reducing maternal and child morbidity and mortality. An integral part of this programme was a computerized demographic surveillance and health information system (HIS) that gathered data on individuals on an on-going basis.

To assess the overall coverage and quality of the data in the HIS, to identify specific health districts that needed improvements in data collection methods, and to determine particular areas of weakness in data collection.

Random samples of 20 mothers with children <5 years were selected in each of 14 health districts. Mothers were interviewed about pregnancies, live births, deaths of children <5, and children's growth monitoring and immunization status. The Lot Quality Assurance Method (LQAS) was used to identify districts in which records and interview results did not meet predetermined levels of acceptability. Data collected in the interviews were combined to estimate overall coverage and quality.

When all variables were analyzed, all 14 lots were rejected, and it was estimated that 52% of all events occurring in the community were registered in ProMIS. Much of this poor performance was due to immunization and growth monitoring data, which were not updated due to printer problems. Coverage of events increased (92%) when immunizations and growth monitoring were excluded, and no lots were rejected. When all variables were analyzed for quality of data recorded, six lots were rejected and the overall estimation was 83%. With immunizations and growth monitoring excluded, overall quality was 86% and no lots were rejected.

The comprehensive computerized HIS did not meet expectations. This may be due, in part, to the ambitious objective of complete and intensive monitoring of a large population without adequate staff and equipment. Future efforts should consider employing a more targeted and streamlined HIS so that data can be more complete and useful.