HIS situation in Thailand

1. HIS situation in Thailand Dr.Pinij Faramnuayphol Health Information System Development Office

2. Structure of Organization Other Organization NSO, MOI MOPH Office of Permanent Secretary Departments Insurance UC, SSS, CSMBS Provincial Health Office Regional & General Hospital District Health Office District Hospital Health Center

3. Health Information System • Population-based Health Information System • Population and Housing Census (NSO) • Vital registration (Ministry of Interior) • Household surveys (NSO) • Health surveys (MoPH) • Facility-based Health Information System • Disease surveillance system (MoPH) • Disease registries (MoPH, University) • Routine reports from facilities (MoPH) • Electronic patient records (MoPH, NHSO) • Primary care health information (MoPH, NHSO) • Health resource information (MoPH) • National Health Account (IHPP)

4. Vital registration system Electronic file transfer monthly ICD-10 coding at MoPH(BPS) Ministry of Interior On-line system Death registration at district office or municipality Death certificate form (In-hospital) Death certificate form (Non-hospital) Death certificate by doctor Death notification by village head Death inside hospital Death outside hospital 35% 65%

5. Household surveys (NSO) • Health and Welfare survey • Out-of-pocket payment, Health care utilization • Illness, Chronic disease • Perceived health status • Health service coverage • Health behavior • Survey of Population Change • Disability survey • Smoking and Alcohol survey • Socio-economic survey

6. Health surveys (MoPH) • National Health Examination survey • History of chronic diseases and injuries • Health behavior : smoking, alcohol, exercise, food • Physical exam : weight/height, waist, BP • Blood exam : Blood sugar, cholesterol, CBC • Health service (screening) • Behavior Risk Factors Surveillance system • Chronic diseases (Known case) • Health behavior • Health service (screening) • Special surveys • Mental health, Oral health, Nutrition • Sex behavior, Exercise, EPI coverage

7. Disease surveillance system • Integrated disease surveillance system • 47 communicable diseases • 11 environmental-occupational diseases • AIDS surveillance reporting system • AIDS cases and OI cases (hospitals) • HIV sentinel sero-surveillance • Injury surveillance • Type of accident, severity, outcome (hospitals)

8. Routine reports • Groups of diseases report • OPD (21 ICD-10 groups) • IPD (75 ICD-10 groups) • Service utilization report • OPD visit and admission by insurance • Financial report • Causes of injury report

9. Databases for reimbursement • In-patient data (DRG-based) • For 3 schemes (UCS, CSMBS, SSS) • Out-patient data (Point system) • OP individual • PP service • Specific health service (Case-based) • ART for HIV/AIDS (NAP databases) • CA.cervix screening databases • Etc.

10. Electronic patient records • Standard dataset for hospitals (OPD, IPD) • IPD records for reimbursement from insurance scheme • ICD-10 for diagnosis and ICD-9-CM for procedures • DRG calculation for reimbursement • Additional dataset for each insurance scheme • Data use for morbidity and service utilization pattern • Database at Hospital • Outpatient data • Inpatient data • Diagnosis (ICD10,DRG) • Procedure • Cost of service Standard 1243 files

11. Primary care health information • Standard dataset for health centers and PCUs • Electronic data entry for catchment population • Health service provision at facilities • Coverage of prevention, promotion activities • Chronic disease management • Community health • Database at Health center & PCU • Population data, Insurance • Death, Chronic disease, Accident • Service, Diagnosis, Surveillance • Treatment, Cost • EPI, Nutrition, FP, MCH, ANC ,NCD, Dental, Disability, Community Standard 2143 files

12. Integrated standard dataset P&P NCD People Patient 1.Person 2.Address 3.Death 4.Card 5.Drugallergy 19.Surveillance 20.Women 21.FP 22.EPI 23.Nutrition 24.Prenatal 25.ANC 26.Labor 27.Postnatal 28.Newborn 29.Newborn_care 30.Dental 31.SpecialPP 32.NCDscreen 33.Chronic 34.ChronicFU 35.LabFU House 6.Home Community service 7.Service 8.Appointment Service 36.Community_service 9.Accident 10.Diagnosis_OPD 11.Drug_OPD 12.Procedure_OPD 13.Charge_OPD Disability &Rehab OPD 37.Disability 38.ICF 39.Functional 40.Rehabilitation 14.Admission 15.Diagnosis_IPD 16.Drug_IPD 17.Procedure_IPD 18.Charge_IPD IPD Community Provider 41.Village 42.Community_activity 43.Provider

13. NCD dataset History of visit ChronicFU -Hospital code -Personal ID -Date of visit -Weight/height -Waist circumference -Blood pressure -Complication examination Screening Registration NCDscreen -Hospital code -Personal ID -Date of service -Smoking/Alcohol -Family history -Weight/height -Waist circumference -Blood pressure -Blood sugar Chronic -Hospital code -Personal ID -Date of diagnosis -Diagnosis (ICD-10) -Discharge date -Current status LabFU -Hospital code -Personal ID -Date of investigation -Lab investigation -Lab result

14. Data center at Provincial level NHSO MoPH Data center PHO Hospital Health center DHO OPD PCU IPD

15. Matrix of HIS Vital Registration Routine Report Patient Records Disease Surveillance HH. Survey Facility data Mortality Morbidity Determinant Health service Health resource Health care Cost & expend.

16. Mortality Death Registration Intercensal survey by NSO Under-registration Survey of population change Completeness in 2006 = 98% IMR around 2 times difference Invalid causes of death 15 provinces 1998-99 Verbal autopsy Corresponding causes of death = 25%

17. Mortality Causes of death (death registration) 35% Inside hospital ICD10 training Diagnosis improvement Reduction of death from heart disease 65% Outside hospital 17 provinces 2000 Diagnosis by doctor (interview, medical record) Reduction of ill-defined causes from 48% to 28%

18. Improving in-hospital COD data • Training for medical doctors to define actual COD in medical death certificate • Reduce mode of death, un-specified causes, injury code • Reduce misclassification, wrong selection • Medical records and coding audit for better quality of diagnosis of diseases and causes of death (MoPH, NHSO)

19. Improving in-hospital COD data • Using medical death certificate for more information on COD (a, b, c, d) through web-based data entry from hospitals (managed by MoPH) • Using electronic in-patient records for defining COD • Principal diagnosis, co-morbidity, complication

20. Improving non-hospital COD data Prospective Retrospective Registrar office MoPH MOI Databases Databases With ICD-10 Health center personnel Providing COD using VA tool + medical history Registrar office Province Databases With ICD-10 Village head (Death notification form With COD) Village head (Death notification form) Health center personnel Investigating COD using VA tool + medical history 18 provinces Relatives Relatives

21. Morbidity Intra-hospital morbidity Aggregated data (groups of dis.) Routine report All diseases Standard databases (12,1843files) Reimbursement databases Hospital patient records Integrated disease surveillance Priority diseases Disease surveillance Around 70 diseases involved Separate for HIV, Accident Chronic diseases Cancer registration Disease registration

22. Morbidity Population-based morbidity NSO every 5 years  2 years Overall illness Health & Welfare survey Self reported illness (OP,IP) Choices, Spending, Compliance, Risk, Wealth data MoPH, HSRI every 5 years Priority diseases National Health Exam survey Chronic disease history, Risk, Physical exam, Blood exam

23. Health service Health service Aggregated data Routine report Hospital level Standard databases (1243files) Hospital patient records Aggregated data Routine report Primary care level Standard databases (1843files) Primary care population and patient records

24. Health resources Health care resources Annual health resources survey survey Health facilites & resources survey Personnel management system admin data Asset management system

25. Health expenditure Health expenditure SES, HWS Household expenditure Routine report Hospital expenditure National health account National health expenditure

26. Determinants Health behavior HIV, special groups Specific behavior survey Survey Major risk factors, province-based Integrated behavior survey Socio-economic SES, by NSO HH.survey HH.economic

27. Situation Poor aspect Good aspect Vital registration coverage ill-defined cause Routine report regularity no private sector reliability of data Disease regularity, timeliness private sector surveillance &reliability of data coverage Electronic patient data HH.survey community-based sub-national representative overlaps

28. Existing problems • Invalidity of data • Incompleteness of data • Lack of data from private sector • Overload and overlap of data collection • Overlapping between various surveys • Few utilization of information at local level • Lack of data linkage between data sources

29. Potential works • Defining health indicators • Defining standard dataset and coding • Strengthening capacity of local health information • system management through datacenter • Promoting local and national data analyses

30. Use of individual patient data Reimbursement Secondary use Service output monitoring Upper level Health system monitoring Health outcome monitoring Knowledge generation Service transaction Case management Hospital level Quality of care monitoring Coverage of service improvement Primary use Patient data exchange & referral

31. Benefit of individual patient data • Improve efficiency of service • Easy to search and display history • Easy to select patients by condition • Easy to analyze • Reduce workload of analysis • Easy to check quality of data • Able to analyze at all levels • Support data exchange between hospitals

32. Data for reimbursement Payment method Fee for service Fee schedule Case-based Per visit Capitation Utilization- adjusted Individual Individual Individual Individual Individual -Verify number of visits -Verify number of visits -Diagnosis -Service -Diagnosis -Procedure -Diagnosis -Service -Charge Summary Summary Summary Summary -Summary of Service provided -Number of visits -Number of visits -Summary of case and charge

33. Data for monitoring Utilize & pay People Patient Providers Provide service Register & Inform Pay Pay Benefit Funders Collective health care financing • Guarantee access to care when needed • Aim at effective coverage of service • Concern quality of care • Focus on efficiency of health care system • Promote equity of health care system

34. Accessibility Access to care Utilize & pay People Patient Providers • Seeking behavior • Compliance of insurance • Unmet need • Utilization rate • Continuity of care • Bypassing pattern • Cross-boundary pattern • Household expenditure • Out-of-pocket payment Benefit Funders • Coverage of insurance • Coverage of benefits • Choice of providers Individual patient data Household survey Registration

35. Quality Quality of care People Patient Providers Provide service Register & Inform • Patient outcome • Severity • Complication • Case-fatality, Survival • Remission • Re-admission • Continuity of care • Adverse events • Clinical practice quality • Waiting time • Satisfaction Pay Funders • Resources of providers • Service availability • Quality assurance • Cost of service Individual patient data Facility data Quality assurance data

36. Efficiency Efficiency of system Utilize & pay People Patient Providers Provide service Household survey Register & Inform Pay • Seeking pattern by type of provider • Proportion of service by level • Primary care vs Tertiary care • Provision pattern • Admission pattern • Case-mix pattern • Treatment modality • Referral pattern • Resource utilization Funders • Type & level of providers • Cost of service Individual patient data Facility data

37. Equity Equity of system Utilize & pay People Patient Providers Provide service Household survey Register & Inform Pay Funders • Seeking pattern by class • Coverage of service by class • Utilization by group of patient • Outcome by group of patient • Type and level of providers by area • Resources of provider by area • Cost of service by group of patient • Population outcome • Improved health of population • by class, group, area Individual patient data Facility data Household survey

38. Thank you very much