Rationalising Health Information Systems to Improve Health Outcomes

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  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 Aim Improve health outcomes through enhancement of Public Health information systems 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 Business Levels 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