Public Health and Regional Informatics
description
Transcript of Public Health and Regional Informatics
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Public Health andRegional Informatics
Mark FrisseNovember 18, 2008
see: http://sites.google.com/a/mfrisse.com/www/home/2008-11-18-bmif-300-lecture
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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?
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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
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the textbook answersthree 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.
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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
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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
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my view
• relationships people have with one another
• coordinated systems of prevention, detection and care
• analysis and presentation of signals• interventions
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reporting
• federal & stateissues• completeness• accuracy• efficiency• latency• privacy and confidentiality
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federal (examples)AIDSAmebiasisAnthraxAseptic meningitisAsthma, work-relatedBotulismChancroidChlamydia trachomatis genital infectionCholeraCoccidioidomycosisCryptosporidiosisCyclosporiasisDenguerDiphtheria
HIV InfluenzaKawasaki DiseaseLegionellosisLeptospirosisListeriosisLyme diseaseLymphogranuloma venereum (LGV)MalariaMeasles, totalMeningococcal diseaseMumpsNeurosyphilisNon-gonococcal urethritis (NGU)
PIDPertussisPlaguePoliomyelitisRabiesSalmonellosisShigellosisSilicosisSmallpoxSpinal cord injuryStrep. pneumoniae, invasive disease < 5 years Streptococcal disease, invasive, group AStreptococcal toxic-shock syndromeStreptococcus
pneumoniae, drug-resistantSyphilisTetanuToxic-shock syndrome (other than streptococcal)ToxoplasmosisTrichinellosisTuberculosisTularemiaTyphoid feverTyphus feverVancomycin-resistant Staphylococcus aureus (VRSA)Varicella
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not all are infections
• Head injury• Lead poisoning• Motor vehicle injury• Sudden infant death syndrome• Suicide
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tennessee
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ph-1600
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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
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cool people and projects
• McMurray, Kohane, Mandl• Grannis and Overhage• Mostashari• Wagner
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SPIN (McMurray et. al.)
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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
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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).
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surveillance: retail-style
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new ways
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analysis: signal vs. noise
• Analysis• Case detection algorithms• Time-series methods• Combining multiple signals• Spatial and spatial-temporal
clustering • Modeling
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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
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cholera
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whosissick.org
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memphis
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• 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)
The MidSouth eHealth Alliance
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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
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ArchitectureHealth Care
Entity InternalSystems
Vaults Regional Index
Volunteer eHealth Initiative Data Bank
Identifier Information- Patient Identifier numbers- Facility identifier- Patient name- Date of birth- Gender- Social security number
Data- Demographics- Lab- Orders
“Pharmacy”
Identifier Information- Patient Identifier numbers- Facility identifier- Patient name- Date of birth- Gender- Social security number
Data- Demographics- Lab- Orders
Clinic
Identifier Information- Patient Identifier numbers- Facility identifier- Patient name- Date of birth- Gender- Social security number
Data- Demographics- Lab- Transcribed reports- Pharmacy- Orders
Hospital
Identifier Information- Patient Identifier numbers- Facility identifier- Patient name- Date of birth- Gender- Social security number
Data- Demographics- Lab- Transcribed reports- Pharmacy- Orders
Person 1CompositeInformation
Link 1
Link n
Person 2CompositeInformation
Link 1
Link n
Person 3CompositeInformation
Link 1
Link n
::
Person nCompositeInformation
Link 1
Link n
“Laboratory”
Record Locator Service
Record Access Service
Parsing/Integration Engine
Publish Data
Publish Data
Publish Data
Printer
FAXServer
WebUser
Exchange receives data & manages data transformation
• Mapping of Data• Parsing of Data• Standardization of Data• Queue Management
Data is published from data source to the exchange• Participation Agreement• Patient Data• Secure Connection• Batch / Real-Time
Organizations will have a level of responsibility for management of data
• Issue Resolution• Data Integrity• Entities are responsible
for managing their Data
Data bank compiles and aggregates the patient Data at the regional level• Compilation Algorithm• Authentication
• Security• User Access
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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
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visualization?
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public health / HIE
issues• completeness• accuracy• efficiency• latency• privacy and confidentiality
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completeness
• more data but more ways of managing information at the point of decision-making
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accuracy
• clear data integrity checks because the data are the same used for clinical care
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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
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latency
• detection? none…nada…zip• only the time it takes the brain to
process and the system to intervene
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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
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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.