1. 7 October 20051 The Health Information Systems in Tanzania By Faraja Mukama

2. 7 October 20052 Presentation outline Health care structure and HMIS Collected information Working situation: Problems Problems: Effects to the HMIS HISP ideas

3. 7 October 20053 Health care stucture & The HMIS Flow of plans and resources Flow of information Governmental Hospitals, Health centers, Dispensaries Health facility level Private and NGOs Hospitals, Health centers, Dispensaries Village (community) level (VHW, TBA, CBD) National level (MoH) Regional level District level Flow of referral information Dispensary Health center District hospital Regional hospital Consultant hospital

4. 7 October 20054 Collected information Main source: Routine health care - Outpatients - Inpatients -Mother and Child Health (MCH): immunization, family planning, weighing, antenatal services -Community outreach: Working with Village Health Workers (VHW), Traditional Birth Attendants (TBA), Community Based Distributors (CBD) Additional: Survey data

5. 7 October 20055 Data collection and reporting Originating at the health facility level - Routine health care activities Using HMIS designed registers and forms -Twelve registers in total -Tally sheets: children vaccination Using Vertical programmes forms: e.g. TB, Dental care Reporting to the higher level in the hierarchy Manually at the health facility level, computerized at District (started in novemeber 2004), Regional and National level.

6. 7 October 20056 Report preparation – Health facility level

7. 7 October 20057 Report prepartion at the district level – Before computerization

8. 7 October 20058 Working Situation: Problems Lack of resources or disproportional distribution of resources - human -material: tools for data analysis, storage tools (folders) including transport Lack of data collection and managerial skills - No regular training Late receiving of data collection tool from the MoH Poor/lack of supervision and feedback

9. 7 October 20059 Problems: Effects to the HMIS gaps in data collection poor (minimal) analysis of data poor data quality Late reporting resulting in incompleteness of reports minimal use of information - Information flows reflecting the requirements of higher levels, without addressing the local level’s information needs

10. 7 October 200510 HISP ideas Support decentralization Build local information culture -addressing fragmantation of data -a software for data analysis and reporting -through training health workers

11. 7 October 200511 MCH section: Children Weighing

12. 7 October 200512 Dispensary Outpatient section: Patients in a queue

13. 7 October 200513 Data storage

14. 7 October 200514 Data storage

15. 7 October 200515 Thanks