Health In an implementation of openIMIS used to manage health financing mechanisms (such as insurance systems) capture a wealth of data on individuals, their families, their treatment, their health care costs, diagnosis patterns, medication prescribing behavior, cost of service provision, etc . Such systems take a is captured. This puts openIMIS unique position in the landscape of IT solutions dedicated to supporting various functions within a health care system. With openIMIS we would like to explore the use of such data from various perspectives to explore ways in which this data could contribute to strengthening health care systems. We encourage you to contribute to this discussion by providing us your ideas and inputs. You can do so by adding to the table below. You can also share (by uploading on this page below the table) relevant documentation on this topic like publications, consultation summaries, etc. and adding a summary of your documentation to the table in form of a use case in the table below that you would derived from the shared document.
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Tracking of infectious diseases/ Disease outbreak investigations
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- Demographics on individuals are useful for picking out disease patterns
- Claims data including diagnosis is relevant and an insurer actively scrutinizing (does diagnosis makes sense looking across trends, etc.), leads to the claim data having better quality diagnosis reported
- If claims payment mechanism requires facilities to report claims regularly (daily or even monthly), it could be a source of real time information
- The system could provide flags to disease surveillance teams to track abnormal patterns.
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- Quality of diagnosis made might be low (not an insurance specific problem but low quality professionals in health system)
- Provider payment mechanism might also influence reporting behaviour (eg. fixed payments monthly reimbursement based on head count might lead to lower empathizes on reporting correct diagnosis)
- Tracking is not appropriate for highly infectious "Notifiable Diseases" (for eg. Ebola outbreaks) which require dedicated structures and systems in place
- openIMIS can only flag potential outbreaks (eg. Influenza outbreak) and dedicated investigations teams are still needed to undertake further investigations and tracking through their own dedicated systems and structures
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- Establish link between multiple visits/claims for the same illness episode by the same person
- Tracking of referral cases - links between claims coming from different level of facilities of an individual for the same illness episode as part of referral chain
- Development of algorithms/logic to track standard patterns in data and subsequently link to disease surveillance system (an actor who is not a direct stakeholder of the system but part of dedicated disease surveillance team in country)
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- Demographics on individuals are useful for picking out disease patterns
- Claims data including diagnosis is relevant and an insurer actively scrutinizing (does diagnosis makes sense looking across trends, etc.), leads to the claim data having better quality diagnosis reported
- System has both longitudinal and cross sectional data on diseases diagnosed and hence useful for tracking disease patterns
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- Quality of diagnosis made might be low (not an insurance specific problem but low quality professionals in health system)
- Provider payment mechanism might also influence reporting behaviour (eg. fixed payments monthly reimbursement based on head count might lead to lower empathizes on reporting correct diagnosis)
- openIMIS can only be source for this data for cross verification/triangulation for disease data reported in national health information systems
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- Link to national health information systems used for tracking disease patterns
- Capturing location of where family lives and where claims are reported from to allow visualization of data on maps
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- Diagnosis against type of drugs and quantity of drugs prescribed could help flag high use of antibiotics
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- Provider payment mechanism might also influence reporting behaviour (eg. fixed payments monthly reimbursement based on head count might lead to lower empathizes on reporting correct diagnosis)
- openIMIS can only act as a flag and further investigations, verification, tracking and improvement measures are to be undertaken by other actors
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- Link to national health information systems used in a country by the dedicated team/structure tracking anti microbial resistance
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- data could be linked to vaccination coverage dataset to indicate outcome of vaccination programme efforts
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- disease profile pointing to chronic conditions for eg. could lead to better planning of preventive services or better targeted health promotion programmes
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Currently, openIMIS provides two ways to analyze this wealth of data - through standard Reports and through DHIS2-based dashboards. As every implementation is unique in terms of data collected and the analysis needs, both methods require initial configuration/customization to ensure that the indicators available in the reports and dashboards are of significance to the specific implementation. The default indicators, reports, and dashboards in openIMIS are presented and discussed below.
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