Btp endsem (1)

Part 1 of thesis

1. Study of the data flowline in healthcare system of india Purnanga Borah

2. Healthcare structure of India Understanding the structural hierarchy, working and management of the rural healthcare system in India . Three layers of Rural healthcare (controlled by the state govt.) Subcentres (SC) : First point of contact between a community and the system Public Health Centres (PHCs) : Overlooks 6 SCs Community Health centres (CHCs) : Overlooks 4 PHCs All are supposed to have specific number of officials, attendants, beds etc.

3. Literature Review Distributed Economics Distributed Economics is a regional approach to promote innovation by small and medium-sized enterprises, as well as sustainable development . REFERENCE MODEL 1 The future is Distributed – A vision of Sustainable economies REFERENCE MODEL 2 Distributed Treasure - Island Economics

4. Literature Review Healthcare management information system (HMIS) Healthcare management information system (HMIS) is where information systems meet healthcare to help optimize the acquisition, storage, retrieval and usage of information in healthcare

5. Literature Review Contextual reference model Healthcare information flow in rural India Identified the rural healthcare system and connected subsystems in India Learned how these subsystems are related to the data flow Identified gaps in the systems

6. Contextual Reference Model

7. Literature Review Decision making categories by using healthcare data Day to day management Medical and drug supply Formulating plans and policies Budget preparation and relocation Human Resource management Identifying emerging issues (Potential epidemics)

8. Problem Statement How might the stakeholders in the system collect, transfer and manage data so that the data can be effectively used for proper decision making, epidemic prevention and research purposes

9. Aim Design a system to improve the healthcare data flow in India

10. Objectives Current semester To understand the healthcare data flow system/sub-systems in rural India To identify all direct/indirect stakeholders and their roles Identify the roles of the stakeholders in the system To learn about the needs and problems of all the stakeholders Next Semester Identify design opportunities in the studied system Design solutions for efficient and effective healthcare data flow

11. Objectives Current semester To understand the healthcare data flow system/sub-systems in rural India To identify all direct/indirect stakeholders and their roles Identify the roles of the stakeholders in the system To learn about the needs and problems of all the stakeholders Next Semester Identify design opportunities in the studied system Design solutions for efficient and effective healthcare data flow

12. Primary research To validate the issues and problems identified through literature study Identify new problems & Issues Deeper Understanding of the current state of the art.

13. Primary research Primary research was done in the month of October by visiting 3 Sub- Centres of Kamrup District.

14. Analysis Analysis of the research were done using the following methods AEIOU Mapping Empathy Mapping

15. Analysis : AEIOU Mapping AEIOU mapping was done for two stakeholder in the Sub-Centre level: Auxiliary Nurse Mid-wife (ANM) and Male Health Worker (MHW). The AEIOU map represents all the activities performed by ANMs and MHWs on the Healthcare Data Management System . It also represents the interactions of ANMs and MHWs with other users and objects in environments where the activities are performed

16. Analysis : AEIOU Mapping : ANM

17. Analysis : AEIOU Mapping : MHW

18. Analysis : Empathy Mapping Empathy mapping was done to create empathy towards the users which will help us la

19. Findings Accounting for people/children who leaves the village When people/children of a place whose data has been collected previously suddenly leaves the village, the data at the top level gets corrupt and the performance of the ANM goes down for no fault of her.

20. Findings Data monitoring system on the ANMs Higher officials sometimes call the ANMs as the part of their monitoring process. They may ask about the details of some beneficiary of the area or about any recorded data. Since ANMs go for field visits frequently, it may happen that she do not have the data asked for through the calls and she answers from her memory or minimal data. This creates a constant mental fear on her about the call .

21. Findings Notion about large data collection The data collected by the ANMs are large and has multiple entries for every entity. Most ANMs felt that there is no use of collecting large data and minute data about every person. For example, for every child birth at a hospital, the names of doctors and nurses taking care are also noted. While 3 ANMs thought in this way, but 1 of them believed that all recorded data are important for higher purposes

22. Findings Registers for data collection ANMs need to regularly go for field visits where she has to carry her data collecting registers. The bulky size of the registers are not feasible for carrying and collecting data on regular field visits

23. Findings Motivation for ANMs ANMs are not aware about how their data collecting work are being used. The collected data are the backbone of all healthcare decisions, but there is no incentives or recognition program for the data collection. This leads to lack of motivation in ANMs on collecting these large data.

24. Findings Delay in receiving blood reports Blood samples of malaria symptoms are sent to the PHC for examination and reports are to be sent on the next day by the PHC. Due to large number of blood samples, examination delays. Plus sending reports back to the SC takes time and sometimes reports arrive after a week .

25. Findings Data transfer within the Sub-Centre There are numerous data transfer among the health workers of the Sub- centre . ASHA workers work hand in hand with ANMs and MHWs and some data like delivery cases are recorded by ASHA mostly, which are then communicated to the ANMs. Data of fever cases are also collected by all health workers which are communicated to the MHW, who compile all the data for the final deliverable format .

26. Findings Format changing at different levels The ANMs at the SCs collect data in registers, then compile them at the end of the month in a different format which they submit to their respective PHCs . The PHCs again re-compile the data in a different format and so on. The more the same data is being played with, more is the probability of making mistakes, also the workload increases due to repetition of work.

27. Timeline

28. Thank you