Overview Current Status of our Mapping Project Program Current Protocol for creating map of Nyaya Health Clinic OPD Visits Data Current Needs

Overview

Mapping of disease prevalence and healthcare utilization plays an important role in planning public health programs and medical services. Such maps, however, are typically not readily available at a local, community level in resource-denied settings where they are needed most. We will create a dynamic map that will improve access to and effective use of medical services in rural western Nepal where our organization operates. The main data points for this map will be continuously input by lay community health workers who serve as the frontline providers at the village level. The map will serve the following primary functions: 

• understand the distribution of access to core clinical services in western Nepal;
• determine how to optimally deploy mobile medical teams to best meet the healthcare of disperse populations;
• determine the impact of these teams on access to core services in the region;
• improve logistics planning of health services by tracking pharmaceutical utilization;
• implement syndromic surveillance of presenting symptoms and diagnoses to rapidly and effectively address local disease patterns;
• provide citizens with accessible and up-to-date data so that they are empowered to lobby the government and NGOs for improved and expanded services;
• plan for the future construction of new health clinics to optimize efficiency, access, and equity.

We will prototype this map in the district of Achham, Nepal, where we have been scaling up public health infrastructure. We employ the only physician in a district of 250,000 people whose healthcare services have been ravaged by a decade-long civil war, long-standing government neglect, and severe poverty. Our program will serve as a model for local monitoring of disease and healthcare utilization patterns in impoverished, rural areas with minimal health infrastructure. All maps, code, and protocol will be freely accessible and open-source. 

Current Status of our Mapping Project

See our current google earth map.  The numbers correspond to the OPD visits in each village development committee during the first six months of clinical services.  You may need the google earth plugin to view this  

Program

We aim to construct a dynamic set of map layers to depict ongoing health services utilization in rural Achham. There is both a technical and human resource aspect to the program; we are developing a model for both data input (via our health worker network) and for data presentation (via our map prototype). The project is a practical undertaking for which we have already established much of the human capacity required to obtain the data inputs. Our data sources include:

• existing electronic patient database of the Nyaya Health clinic, the largest provider of primary and acute care services in Achham;
• community health worker database, collected by mobile workers using GPS-enabled handheld electronic devices;
• government health posts, which provide data via the public data reporting system.

This information is centralized in an Access database which we maintain through regular uploading from the handhelds carried by our mobile health workers. The map will consist of the following layers, with data inputs localized at the village level and tracked over time:

• access to and utilization of core clinical services;
• pharmaceutical prescribing patterns of public-sector clinics;
• distribution of syndromes and disease cluster

Our prototype will be based on data from 15 sub-districts known as village development committees (VDCs) that are located near to the heart of Nyaya Health’s clinical operations. Each of these VDCs are covered by 2 community health workers and in total consist of a population of approximately 50,000 people. We have already implemented each of these layers for data from our clinic; with funding from this grant, we will layer on the community health worker and government health post data sources, add a time-dynamic component, and improve the user interface to be useful to healthcare managers.

Current Protocol for creating map of Nyaya Health Clinic OPD Visits Data

Resources: downloadable from http://www.sgrillo.net/googleearth/gegraph.htm

SharedNyaya\Clinic\Grants\Google GeoChallenge

Download and open SBMC.mdb

Open the OPD query

Export the OPD query to excel spreadsheet

Cut and paste the contents of the exported query into the "query" sheet of "achham settlements GPS.xls"

Go to the pivot table in the "pivot" sheet.  Copy the relevant numbers to the "GE graph input.csv" file.

Open GE Graph.  Go to File>>Load Options>>nyaya_services.ggo

File>>Open txt(csv)>>"GE graph input.csv"

Click run and create the desired KML or KMZ file

Upload new maps to maps.google.com via ID: nyayahealth

These get embedded into the wiki via the google earth plug in:

http://www.takitwithme.com/geembed.html

Current Needs

Correct the SBMC.mdb file with the proper names found in the "achham settlements GPS.xls" file. [Have requested from Chhitij]

Once that is done, create automated sheet to generate the .csv file.  See "msupply_pharmoutput.xls" in SharedNyaya\Clinic\Data as one example.

Determine how to represent these data month-to-month in a meaningful way on Google Earth.  That is, incorporate time-dynamic element into the static layer described above.

Add static items to the layers, such as location of Nyaya Health Clinic, Mangalsen Hospital, and area health posts.

Once a good system is achieved for the above:

Create similar strategy for pharmaceutical and HMIS disease code data, again using data solely from the clinic

Create a more fine-grain geographical analysis by breaking down the VDCs by ward (i.e., "settlement")

Incorporate the three layers (OPD visits, pharmaceutical utilization, and HMIS disease code) into a single, straightforward interface.

Final steps:

Incorporate similar data from CHWs and from government.

Improve the interface to be useful to the Nyaya team for data analysis and program planning.