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RATIONALISING HEALTH INFORMATION SYSTEMS TO IMPROVE HEALTH OUTCOMES Public Health Services Queensland Health Australia 1998-2000. Dr Magnolia Cardona Coordinating Epidemiologist MB.BS, MPH, Grad DAE, CHEcon. Objectives of this lecture.
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RATIONALISING HEALTH INFORMATION SYSTEMS TO IMPROVE HEALTH OUTCOMES Public Health Services Queensland Health Australia 1998-2000
Dr Magnolia Cardona Coordinating EpidemiologistMB.BS, MPH, Grad DAE, CHEcon
Objectives of this lecture • Provide an overview of information system types and potential uses • Increase awareness on need to balance amount of data with cost and confidentiality concerns • Present case scenarios to set up and enhance information systems
Characteristics of Good Health Surveillance Systems • Clear objectives • administration • routine documentation • monitoring • research/evaluation • Simple (MDS) • Standard item format • Justification and validation of items
Characteristics of Good Health Surveillance Systems (cont) • Relevant to users • Minimum burden to providers • Amenable to modification • Provision for security/confidentiality • Associated reporting system • Feedback to collectors • Linked to action
Options • Paper-based centralised • Sentinel/selected surveillance • Computerised stand alone • Single site • Multicentre
Options • Computerised networked • Encrypted data transfer • Combination • Paper-based notifications • electronic entry at central location
Setting up a Health Information System Which option is best?
SCENARIO: Cholera epidemic in Africa • No routine surveillance • Poorly kept clinical records • Understaffed facilities • Unreliable communications • No ongoing funding • No computers
Cholera epidemic in Africa Example of a paper-based system that worked in an endemic area for at least 2 years
Occupational exposure to bloodborne illnesses among health staff • Hundreds of health facilities • Infrequent incidents • Non-compulsory recording • No ongoing funding • Confidentiality issues • Compensation issues
Nutritional Status Monitoring in a remote indigenous community • Routine surveillance of some conditions • Somehow comprehensive clinical records • Services staffed by community • Unreliable communications • Some funding available • Some computers usable
Major stakeholder’s concerns • How the data will be collected • How the data will be used • Who will have access to the data • Confidentiality issues • Perceived discrimination • Financial implications
Indigenous Community Health • Computerised system • Easy front-end • Complete patient information (alias/residence) • Promotes opportunistic P.H. action • Capability for health worker plans • Population based reporting system • Generates customised prevalence/incidence
Burden of depression at Medical Practitioners rooms • Non-standard recording practices • ? Availability of clinical records • Busy medical practices • Variable communication systems • Low computer coverage • Ethical issues • Incentives required for doctors
Doctors-based Sentinel Surveillance • Enables documentation of non-hospital data • Burden of disease measurement • Paper-based with weekly notifications • Limited patient information & # conditions • Selected Locations (self-selected doctors) • Inability to calculate prevalence/incidence
Example of project to maximise efficiency of existing health information systems Real case scenario
Improve health outcomes through enhancement of Public Health information systems Aim
Objectives • High quality /timely data • Minimise duplication/cost • Standard coding practices • Common table structures • Common operating environment • Shared hardware • Data Linkage
Inventory of Databases • Purpose/Scope /Contents • Size/Accessibility • Operating system/server/interface • Data tables • Remote access/re-development • Special requirements • Staff involved
Integration Protocols • Hardware /software • Data definitions {NHDD} • Reference tables • Data Entry & Transfer • Security /Confidentiality
Working Group • Discuss IT requirements • Re/development experience • Security Principles • Sharing of reference tables • Integration protocols • Recommendations
Integration Levels Business User interface Data use (structure) Database (execute instructions) Platforms (hardware) Network (WAN, LAN)
*BSR PSR Lead *NOCs VIVAS *MODDs Business Interface Data use Database Platforms Network
How does this improve Health Outcomes? • Outbreak response/timing • Immunisation rates • Prescription control • Standard Indigenous identifiers • Early cancer detection\QA
Summary • Relevance & cost-effectiveness • Consultation with users and data holders • Financial considerations • Ethical implications • Ultimate goal to improve health