2009 Implementers Group Meeting Program Household Data

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<html><head><title></title></head><body>* How do we integrate OpenMRS with Household?

    • Health Information Systems Programme (HISP India) uses method of calling API from DHIS and then put data into OpenMRS.
    • Darius: Ideal case would be to fill out a form to contain both individual and household data.
  • Use Cases
    • MVP (Andy)
      • Primary Care System sends community workers to household visits.
      • Each community work is responsible for 200 households.
      • Data is sent through mobile phones.
      • Data collection includes issues on water and GPS coordinates of household.
      • Run reports for households for those specific patients.
      • Household is a place for catchment area. It’s more like a case (more than a house).
    • CDC (Roger)
      • CDC has been doing household surveys (longitudinal).
      • Some cases survey everyone (100%) and other cases are random sampling which workers are assigned to those households (record completion of the efforts).
      • Needs of expanding household definition to location, such as workplace, plane, ... , etc. which might be useful for outbreaks tracking and records keeping.
    • Haiti (James)
      • Data collection includes number of rooms, materials use for the house, types of roof, drinking water source, ... , etc. which store in Person Attributes in OpenMRS.
    • AMPATH (Paul)
      • Home-based Counseling and Testing Program
      • Community workers go to each of the household in the catchment area.
      • Data collection includes number of livestock/incomes on household, and medical related questions on individuals.
      • Definition of household is very ambiguous.
      • HCT ID stores as Person Attributes in OpenMRS which links to an external database which collects Household ID.
    • PIH Malawi
      • Community workers collect household data by visiting households.
      • Data colleciton includes economic data/key medical data.
      • Monthly follow-up visits.
      • Goals include monitoring the program/target community.
      • Definition of household: At least 3 nights a week in the same house.
    • Pakistan (Julia)
      • Data collection includes number of stoves and number of people eat together.
  • OpenHRS Group
    • Distinction of location and household.
    • Problem domain-demographic surveillance sites- interested where they reside, as time progress, would like to know births/deaths/migration.
    • Put bed nets and introduce new drugs regimens.
    • Need to know the denominators.
    • Modeling: Care about location and composition of household. Household is typically but not always in a location assigned. It is often true that we have separate records to associate with household and individual location. Some households are in several locations. With the compound structures, several households can be in the same location. Household is an abstract concept – groups of collection of individuals. Interested in knowing Person Days of Observations. Assign household to location. Households are mini-cohorts. Locations are points. Capability to link obs to household? Visit to a household is cross section – even if there is nothing happened, it’s still good information to collect.
    • List of problems:
      • Multiple wives – where are the locations even they are one household?
      • Partial residency of individual - do not want to double counts.
      • Movement – people move in and out of households.
      • Demographic Surveillance: Baseline, sampling household follow-up. Will share data model and put on wiki.
  • HISP
    • Each community worker visits each household of catchment area of 5000.
    • Activity worksheet and planner are given to community workers. Each activity worksheet/planner includes to-do list: a) facility information, b) household, and c) services patients receive.
    • Data collection includes Immunization, Family Planning, and ANC.
    • OpenMRS will store patient/health worker data. DHIS will store facility and household data.
    • Hope to answer questions like how many households get clean water or how many malaria cases in this catchment area?
    • Challenges: After linking both systems, how many households get unclean water?
    • Data Models for household and individuals are done.
    • Health workers are OpenMRS User which are providers which can be linked to individuals.
    • In India, a pregnant woman might receive treatment in one catchment area and then move to her mother’s catchment area in later months of pregnancy. This kind of temporary movements is very common in India.
    • Method of Household ID Generation: Random generation.
  • Data Model
    • HISP will provide data model to Ada to post on wiki.
    • OpenMRS Group will post data model on wiki.
  • What do we tell our implementers and when it might be ready (timeline)?
    • HISP: Ready by end of October 2009, testing in Nov/Dec 2009, and then roll-out by Jan 2010.
    • Roger: Needs for enriching definition of location. GIS should beyond coordinates, to include beds map of hospital.

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