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Public Health and Regional Informatics

Public Health and Regional Informatics. Mark Frisse November 18, 2008 see: http://sites.google.com/a/mfrisse.com/www/home/2008-11-18-bmif-300-lecture. what we will cover. What is public health? What is regional informatics? What are the common themes? What are the challenges?

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Public Health and Regional Informatics

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  1. Public Health andRegional Informatics Mark Frisse November 18, 2008 see: http://sites.google.com/a/mfrisse.com/www/home/2008-11-18-bmif-300-lecture

  2. what we will cover • What is public health? • What is regional informatics? • What are the common themes? • What are the challenges? • What are the research and service opportunities?

  3. differences and similarities • populations, not individuals • prevention more than diagnosis and treatment • government more than providers • same! my claim is that the informatics issues required to address public health are the same as those for many other pressing clinical problems

  4. the textbook answers three functions • Assessment involves monitoring and tracking the health status of populations. • Policy development utilizes the results of assessment activities in concert with local values and culture to recommend interventions and policies that improve health status. • Assurance refers to the mission public health agencies have to assure constituents that services necessary to achieve agree-upon goals are provided.

  5. big deals • unsuccessful siege of the Assyrians against Jerusalem (701 BCE) • guns, germs, and steel • the great influenza • HIV • drug-resistant TB, Staph, other stuff • immunizations

  6. more big deals • lack lung in miners • asbestos workers • back injury and other occupational-related disorders - $2.3 billion dollars • fluoridated water changed dentistry • seat belts • high fat foods • tobacco

  7. my view • relationships people have with one another • coordinated systems of prevention, detection and care • analysis and presentation of signals • interventions

  8. reporting • federal & state issues • completeness • accuracy • efficiency • latency • privacy and confidentiality

  9. federal (examples)

  10. not all are infections • Head injury • Lead poisoning • Motor vehicle injury • Sudden infant death syndrome • Suicide

  11. tennessee

  12. ph-1600

  13. completeness • automatic reporting of health conditions may lead to 4x the number of incidents • this means 4x as much work for public health professionals… • unless…you can give them access to a community-based record

  14. cool people and projects • McMurray, Kohane, Mandl • Grannis and Overhage • Mostashari • Wagner

  15. SPIN (McMurray et. al.)

  16. SPIN features • is self-scaling, voluntary and hence may be applicable to a national network • employs a distributed approach to data storage that they argue minimizes breach and hence protects privacy. • maintains institutional participation because of the autonomy relegated by a distributed approach. • provides oversight and transparency

  17. cdc public health informatics grid • a need for wide distribution of public health data. • rapid growth of public health data. • cultural, social and political impediments to data sharing. • significant and chronic financial constraints. • a dynamic and complex environment - global in scale. • an environment containing many redundant systems, as well as application and data silos. • an environment with a wide variety of complex requirements (disease surveillance, alerting, event detection, etc).

  18. surveillance: retail-style

  19. new ways

  20. analysis: signal vs. noise • Analysis • Case detection algorithms • Time-series methods • Combining multiple signals • Spatial and spatial-temporal clustering • Modeling

  21. markle principles • openness and transparency. • accountability and oversight • individual participation and control • purpose specification and minimization • collection limitation • use limitation • data integrity and quality • security safeguards and controls • legal and financial remedies for violations

  22. cholera

  23. whosissick.org

  24. memphis

  25. The MidSouth eHealth Alliance • Baptist Memorial Health Care Corp.(4 facilities) • Christ Community Health(4 primary care clinics) • Methodist Healthcare(7 facilities including Le Bonheur Children’s Medical Center) • The Regional Medical Center (The MED) • Saint Francis Hospital & St. Francis Bartlett (Tenet Healthcare) • St. Jude Children’s Research Hospital • Shelby County/Health Loop Clinics(11 primary care clinics) • UT Medical Group(300+ clinicians) • Memphis Managed Care/TLC (MCO)

  26. After 18 months of operation • Total # of encounter records:3.9 million • Total # of patients: 1,050,000 • Total # of patients with clinical data: 930,000 • Monthly Encounter Data: 140,000 • Monthly ICD-9 admission codes (Chief complaints): 34,000 • Monthly labs: 2,400,000 • Monthly microbiology reports: 26,000 • Monthly chest x-ray reports: 35,000 • Comprehensive privacy agreements • Costs to participants less that $50,000 per hospital • Overall annual operating cost – under $3 million

  27. Architecture Data is published from data source to the exchange Exchange receives data & manages data transformation Organizations will have a level of responsibility for management of data Data bank compiles and aggregates the patient Data at the regional level • Participation Agreement • Patient Data • Secure Connection • Batch / Real-Time • Mapping of Data • Parsing of Data • Standardization of Data • Queue Management • Compilation Algorithm • Authentication • Security • User Access • Issue Resolution • Data Integrity • Entities are responsible for managing their Data

  28. Use • > 400 users • Low in ED (< 5%) • Growing use in safety net clinics • hospitalists usage low • Increasing connectivity to ambulatory sites • Reduces redundant tests; impacts care

  29. visualization?

  30. public health / HIE issues • completeness • accuracy • efficiency • latency • privacy and confidentiality

  31. completeness • more data but more ways of managing information at the point of decision-making

  32. accuracy • clear data integrity checks because the data are the same used for clinical care

  33. efficiency • data are collected “on the margin.” • you no longer have separate systems, you have one, single, amorphous system whose use is dictated by need and authorization • everything becomes a marginal cost

  34. latency • detection? none…nada…zip • only the time it takes the brain to process and the system to intervene

  35. privacy - agreements • openness and transparency. • accountability and oversight • individual participation and control • purpose specification and minimization • collection limitation • use limitation • data integrity and quality • security safeguards and controls • legal and financial remedies for violations

  36. the real lesson • our health care system is broken • our health care system is fragmented • wherever you go - be it personal health, pay-for-performance, public health, information exchange, or public policy - you face the same issues • a unified approach based on a very simple, extensible technical and policy framework seems, in my mind, to be the only way informatics can help enable the health care system we all want and need.

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