Open Access Research article

Systemic factors of errors in the case identification process of the national routine health information system: A case study of Modified Field Health Services Information System in the Philippines

Shinsuke Murai1*, Leizel P Lagrada23, Julita T Gaite4 and Naruo Uehara1

Author Affiliations

1 Division of International Health (Quality and Health Systems), Graduate School of Medicine, Tohoku University, Sendai, Japan

2 Health Policy Development and Planning Bureau, Department of Health, Manila, Philippines

3 Division of Health Management and Planning, Department of Health Policy Science, Tokyo Medical & Dental University, Graduate School of Medical and Dental science, Tokyo, Japan

4 Provincial Health Office of Palawan, Puerto Princesa, Philippines

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BMC Health Services Research 2011, 11:271  doi:10.1186/1472-6963-11-271

Published: 14 October 2011



The quality of data in national health information systems has been questionable in most developing countries. However, the mechanisms of errors in the case identification process are not fully understood. This study aimed to investigate the mechanisms of errors in the case identification process in the existing routine health information system (RHIS) in the Philippines by measuring the risk of committing errors for health program indicators used in the Field Health Services Information System (FHSIS 1996), and characterizing those indicators accordingly.


A structured questionnaire on the definitions of 12 selected indicators in the FHSIS was administered to 132 health workers in 14 selected municipalities in the province of Palawan. A proportion of correct answers (difficulty index) and a disparity of two proportions of correct answers between higher and lower scored groups (discrimination index) were calculated, and the patterns of wrong answers for each of the 12 items were abstracted from 113 valid responses.


None of 12 items reached a difficulty index of 1.00. The average difficulty index of 12 items was 0.266 and the discrimination index that showed a significant difference was 0.216 and above. Compared with these two cut-offs, six items showed non-discrimination against lower difficulty indices of 0.035 (4/113) to 0.195 (22/113), two items showed a positive discrimination against lower difficulty indices of 0.142 (16/113) and 0.248 (28/113), and four items showed a positive discrimination against higher difficulty indices of 0.469 (53/113) to 0.673 (76/113).


The results suggest three characteristics of definitions of indicators such as those that are (1) unsupported by the current conditions in the health system, i.e., (a) data are required from a facility that cannot directly generate the data and, (b) definitions of indicators are not consistent with its corresponding program; (2) incomplete or ambiguous, which allow several interpretations; and (3) complete yet easily misunderstood by health workers.

Taking systemic factors into account, the case identification step needs to be reviewed and designed to generate intended data in health information systems.