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GIS as a tool for monitoring Health Management Information System


A GIS can help to focus the Health Management Information for the above groups and perform the following key functions:
  • Generate “thematic maps” (ranged colour maps on proportional symbal maps to denote the intensity of a mapped variable).
  • Allow for overlaying of different pieces of information.
  • Create buffer areas around selected features (eg. a radius of 10 Km around a health centre to denote a catchment area)
  • Calculate distances between two points
  • Permit dynamic link between databases and maps so that data updates are automatically reflected on maps.
  • Permit interactive queries of information contained within the map, table or graph.
Mark the Special Action Project areas (hill areas, tribal packets, coastal islands etc)

Fig. 5: Districtwise Prevalence Rates of Leprosy - An example for ranged pattern map


For any health management information in the Public Health, the data is collected at the PHC level and later consolidated at block level, Health Unit District level (HUD), District level and finally at state level. In the above example, distribution of Leprosy Cases by typewise in Rural and Urban areas of Ramnad district detected is simulated. Cases have been classified as Pauci Bacillary (PB) and Multi Bacillary (MB). In fig 1, the district map of Ramnad with the geographic data is shown. The distribution of cases at the HUD level (Fig 2), at the block level (Fig 3) and at PHC level (Fig 4) are depicted.

Next example is a ranged pattern map. (Fig. 5) It presents the prevalence rates of leprosy in the 29 districts at the start of the Multi Drug Therapy (MDT) during mid 80’s, at the time of integration of leprosy services with the Primary Health Care and during March 2001. The prevalence rate has reached to 3.7 leprosy affected individuals per 10,000 population in Mar 2001 against 117 per 10,000 as recorded in mid 80’s. While satisfactory progress continues to be made towards the elimination of leprosy as public health problem, a “Final push” is being given to reduce the prevalence below 1 per 10,000 population by the year 2004.

Summary and conclusion
GIS and maps are valuable in strengthening the whole process of HMIS and analysis. It serves as a common platform for convergence of multi-disease surveillance activities standardised georeferencing of epidemiological data facilitates standardised approaches to data management. The process provides an excellent means of analysing epidemiological data, revealing trends, dependencies and inter-relationships that would otherwise remain hidden in data shown only in tabular format. A GIS can serve as an entry point for integrating disease surveillance activities where appropriate.

Aknowledgement
I should not fail to acknowledge the encouragement provided by Ms.Nanda Paithankar, Monitoring Adviser, DANLEP, New Delhi. I gratefully thank the Deputy Director (Lep), Ramnad dist., Tamil Nadu for his assistance in marking the health facilities.

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