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

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

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)

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

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

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

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)

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

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.

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

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

Integrated standard dataset 1.Person 2.Address 3.Death 4.Card 5.Drugallergy 6.Home 7.Service 8.Appointment 9.Accident 10.Diagnosis_OPD 11.Drug_OPD 12.Procedure_OPD 13.Charge_OPD 14.Admission 15.Diagnosis_IPD 16.Drug_IPD 17.Procedure_IPD 18.Charge_IPD 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 36.Community_service 37.Disability 38.ICF 39.Functional 40.Rehabilitation People Patient Service OPD IPD House P&PNCD Community service Disability &Rehab 41.Village 42.Community_activity 43.Provider Community Provider

NCD dataset 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 ChronicFU -Hospital code -Personal ID -Date of visit -Weight/height -Waist circumference -Blood pressure -Complication examination LabFU -Hospital code -Personal ID -Date of investigation -Lab investigation -Lab result ScreeningRegistration History of visit

Data center at Provincial level Health center Hospital OPD IPD PCU PHO MoPHNHSO Data center DHO

Matrix of HIS Mortality Morbidity Health service Determinant Health care Cost & expend. VitalRegistrationRoutineReportPatientRecordsDiseaseSurveillanceHH.SurveyFacilitydata Health resource

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Data for monitoring People Patient Funders Providers Utilize & pay Provide service Pay Register & Inform Pay Benefit 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

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

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

Efficiency People Patient Funders Providers Utilize & pay Provide service Pay Register & Inform Efficiency of system -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 -Type & level of providers -Cost of service Individual patient data Facility data Household survey

Equity People Patient Funders Providers Utilize & pay Provide service Pay Register & Inform Equity of system -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 Household survey Facility data Household survey

Thank you very much