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Information Communication Technology in Routine Health Information Systems
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Information Communication Technology in Routine Health Information Systems

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  • The concept is based on balancing the staff capacity, the resources, the detail in the data. If one area is unbalanced, the system becomes unstab
  • Transcript

    • 1. The cutting edge in ICT RHIS thinking
      Norah Stoops
      HISP South Africa
      4th International RHINO Conference Mexico
      March 2010
    • 2. Use of DHIS in Africa
      I have worked in the following countries
      Myanmar
      Liberia
      Swaziland
      Namibia
      DRC
      South Sudan
      Zimbabwe
      South Africa
    • 3. Common features
      Inappropriate use of Excel spread sheets
      Use of rigid databases – unable to change
      Collecting LOTS of data – poor reporting rates
      Unable to use almost all of the collected data
      Not collecting data that is really needed
      Vertical parallel programmes – no communication with anyone else
      HIS (sometimes) seen as not effective
      Very poor analysis of data
      Poor data quality – unable to run data quality checks
    • 4.
    • 5. Introduction of DHIS
      Standardised clinic/facility list
      Standardised data elements and definitions
      Country staff involved in customisation
      Able to see links between data elements/indicators and population in Pivot tables – see coverage rates
      Communication between various programmes
      Integration of parallel reporting systems
      ‘Why have we taken so long to introduce the DHIS’
      Revision of reporting systems and data flow
    • 6. Used only for TB data
    • 7. Myanmar
      Required a system for quarterly TB data
      Able now to make own changes to database in terms of facilities, population figures
      Able to view TB data over time instead of just for 1 year
    • 8.
    • 9. Zimbabwe
      Was using a non linked database
      Very limited reporting abilities
      Able to import all historical data
      MOH responsible for customisation of DHIS with off site support
    • 10.
    • 11. Liberia
      Excel being used for all programmes!!!!!
      Able to develop a National Essential Indicator Dataset
      Able to integrate ALL vertical programmes into 1 database
      Lots of training in definitions
      Lots of training in using the DHIS – capacity and skills transfer to local staff
    • 12.
    • 13. Democratic Republic of Congo
      Used for 1 project
      Use of both English and French in one database
      MOH interested in roll out in whole country
      MOH system unable to integrate provincial data files into 1 system – no country picture available
    • 14. The ability to switch languages for data element names
    • 15.
    • 16. South Sudan
      New state
      LOTS of INGOs and M&E staff
      Have NO system for routine data
      Disease surveillance in Excel
      Have LOTS of registers – BUT not printed
      Desperate for a comprehensive solution
      DHIS will be rollout in 4 states
    • 17. Results
      Ownership of system by all staff
      Encourage local staff to make alterations/adaptations
      Allows staff at lowest levels to analyse and use own information to improve health status and health service management.
    • 18. The cutting edge in RHIS(or how to move RHIS into the 21 century)
      Norah Stoops
      HISP South Africa
      4th International RHINO Conference Mexico
      March 2010
    • 19. Characteristics of a failed RHIS
      ‘Ownership’ of the data belonging to the HIS Unit
      Interpretation of data/information done by HIS (reports prepared without input of managers)
      Vertical programme management recording & reporting (duplicate data collection)
      Inflexibility of system to adapt to changes in information needs (paper forms/software)
      Demanding data without considering resources available
      Extensive use of Excel spreadsheets
      Use of databases that are not relationship based (i.e. tables not linked)
    • 20. Factors hindering a functional RHIS
      Applying research methodology in RHIS environment
      Data collection/tools (PMTCT)
      Longitudinal registers
      Donor demands (PEPFAR indicators)
      EVERYTHING is thrown into the Routine system
      No consideration of other data collection methods i.e.
      Record review, sentinel surveillance, surveys etc
      Data from different facility types not integrated – unable to determine the full district picture
    • 21. Defining an Essential Dataset. . . determine “must know” information needs
      Must Know
      Dangerous to know
      Should Know
      Nice to Know
    • 22. The fewer resources a country has – the more determined they are to waste them
      Collecting ‘Dangerous to know’ information
    • 23. Aim of a Routine Health Information System
      Health management strives to translate health policy into practice
      Health management information systems provide the mechanisms needed to monitor the translation of health policy into practice – this cascades down from ministry through provinces/regions/county/district and facility levels
      The RHIS enables counties to assess whether the goals, objectives, indicators and targets, based on both strategic & operational plans are being achieved
    • 24. High
      Detail in Data
      Low
      Information System
      Low
      Low
      Resources(time, people, h/w, s/w)
      Staff Capacity
      High
      High
    • 25. There are obstacles to a functional RHIS
    • 26. Sometimes you pick up free riders
      You may have to ‘dump’ some things (going nowhere)
    • 27. Sometimes you are not sure how something got into the system
      Occasionally you are given a warning that this road is not the right one
    • 28. Sometimes you are doing well and just need a bit of panel beating to be fully functional
    • 29. How do you get to be the best
      Be pro-active, out in front and responsive to changing information needs
      Make friends with all the programme managers
      Develop a ESSENTIAL INDICATOR DATA SET (indicators are analysed data – consist of numerator and denominator – this defines what you collect)
      Definitions for all data elements and indicators
      MDGs/National Objectives – have you included the most basic input, process, output, outcome, impact indicators that you need to measure these
      Say NO – donors/managers
      Rethink your M&E plan
      Plan for regular changes
      Appropriate computer software application – DHIS works
      Training, training and more training
    • 30. 30
      Ancient wisdom says that when you discover you are riding a dead horse, the best strategy is to dismount.
      In organizations, however, we often try many other strategies, including the following:
      1.  Changing riders.2.  Buying a stronger whip.3.  Falling back on. "This is the way we've always ridden."4.  Appointing a committee to study the horse.
    • 31. 31
      5.  Arranging a visit to other sites to see how they ride dead horses.
      6.  Appointing a committee to revive the dead horse.7.  Creating a training session to improve riding skills.8.  Hiring an outside consultant to show how a dead horse can be ridden.9.  Harnessing several dead horses together to increase speed.10.  Increasing funding to improve the horse's performance.
      11.  Doing a study to determine if outsourcing will reduce the cost of riding a dead horse.
    • 32. 32
      12.  Buying a computer program to enhance dead horse performance.13.  Declaring a dead horse less costly to maintain than a live one.14.  Forming a work group to find uses for dead horses.15.  Promoting the dead horse to a supervisory position.
      Is your RHIS a dead horse?
    • 33. We have a RHINO baby on the way

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