Transcript ความก้าวหน้าแผนงานพัฒนาร

HIS situation in Thailand
Dr.Pinij Faramnuayphol
Health Information System Development Office
Structure of Organization
Other Organization
NSO, MOI
Insurance
UC, SSS, CSMBS
MOPH
Office of Permanent Departments
Secretary
Provincial Health Office
District Health Office
Health Center
District Hospital
Regional &
General Hospital
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
Electronic file transfer monthly
Ministry of Interior
ICD-10 coding
at MoPH (BPS)
On-line system
Death registration at district office or municipality
Death certificate form
(In-hospital)
Death certificate by doctor
Death inside hospital 35%
Death certificate form
(Non-hospital)
Death notification by village head
Death outside hospital 65%
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
Standard 2143 files
•Service, Diagnosis, Surveillance
•Treatment, Cost
•EPI, Nutrition, FP, MCH, ANC ,NCD, Dental, Disability, Community
Integrated standard dataset
People 1.Person
Patient 2.Address
House
Service
OPD
IPD
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
P&P
NCD
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
Community service
36.Community_service
Disability &Rehab
37.Disability
38.ICF
39.Functional
40.Rehabilitation
Community
Provider
43.Provider
41.Village
42.Community_activity
NCD dataset
History of visit
ChronicFU
Screening
Registration
NCDscreen
Chronic
-Hospital code
-Personal ID
-Date of service
-Smoking/Alcohol
-Family history
-Weight/height
-Waist
circumference
-Blood pressure
-Blood sugar
-Hospital code
-Personal ID
-Date of diagnosis
-Diagnosis (ICD-10)
-Discharge date
-Current status
-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
Data center at Provincial level
NHSO
MoPH
PHO
Hospital
OPD
IPD
DHO
PCU
Data center
Health center
Matrix of HIS
Vital
Routine Patient Disease
HH.
Facility
Registration Report Records Surveillance Survey data
Mortality
Morbidity
Determinant
Health service
Health resource
Health care
Cost & expend.
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%
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%
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
Prospective
Registrar office
Retrospective
MOI
Databases
MoPH
Databases
With ICD-10
Health center personnel
Providing COD using VA tool
+ medical history
Village head
(Death notification form)
Registrar office
Village head
(Death notification form
With COD)
18 provinces
Relatives
Province
Relatives
Databases
With ICD-10
Health center personnel
Investigating COD
using VA tool
+ medical history
Morbidity
Intra-hospital morbidity
All diseases
Aggregated data (groups of dis.)
Routine report
Standard databases (12,1843 files)
Reimbursement databases
Hospital patient records
Priority diseases
Chronic diseases
Integrated disease surveillance
Disease surveillance
Around 70 diseases involved
Separate for HIV, Accident
Disease registration Cancer registration
Morbidity
Population-based morbidity
Overall illness
NSO every 5 years  2 years
Health & Welfare survey
Self reported illness (OP,IP)
Choices, Spending, Compliance, Risk,
Wealth data
Priority diseases
MoPH, HSRI every 5 years
National Health Exam survey
Chronic disease history, Risk,
Physical exam, Blood exam
Health service
Health service
Aggregated data
Routine report
Hospital level
Standard databases (1243 files)
Hospital patient records
Aggregated data
Primary care level
Routine report
Standard databases (1843 files)
Primary care population and
patient records
Health resources
Health care resources
survey
admin data
Annual health resources survey
Health facilites & resources survey
Personnel management system
Asset management system
Health expenditure
Health expenditure
SES, HWS
Household expenditure
Routine report
Hospital expenditure
National health account
National health expenditure
Determinants
Health behavior
HIV, special groups
Specific behavior survey
Survey
Socio-economic
HH.survey
Major risk factors, province-based
Integrated behavior survey
SES, by NSO
HH.economic
Situation
Good aspect
Poor aspect
Vital registration
coverage
ill-defined cause
Routine report
regularity
no private sector
reliability of data
Disease
regularity, timeliness
surveillance &
reliability of data
Electronic patient data
private sector
coverage
HH.survey
sub-national
representative
overlaps
community-based
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
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
Use of individual patient data
Secondary use
Upper level
Reimbursement
Service output monitoring
Health system monitoring
Health outcome monitoring
Knowledge generation
Service transaction
Case management
Hospital level
Primary use
Quality of care monitoring
Coverage of service improvement
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
Individual
Individual
Individual
Individual
-Diagnosis
-Service
-Diagnosis
-Procedure
-Verify
number of
visits
Individual
-Verify
number of
visits
Summary
Summary
-Number
of visits
-Number
of visits
-Diagnosis
-Service
-Charge
Summary
-Summary of
case and charge
Case-based
Summary
-Summary of
Service provided
Per visit
Capitation
Utilizationadjusted
Data for monitoring
People
Patient
Benefit
Utilize & pay
Providers
Provide service
Pay
Register
& Inform
Pay
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
Accessibility
People
Patient
Utilize & pay
Providers
Benefit
Funders
-Coverage of insurance
-Coverage of benefits
-Choice of providers
Registration
Access to care
Individual
patient data
-Seeking behavior
-Compliance of insurance
-Unmet need
-Utilization rate
-Continuity of care
-Bypassing pattern
-Cross-boundary pattern
-Household expenditure
-Out-of-pocket payment
Household
survey
Quality
People
Patient
-Patient outcome
-Severity
-Complication
-Case-fatality, Survival
-Remission
-Re-admission
-Continuity of care
-Adverse events
-Clinical practice quality
-Waiting time
-Satisfaction
Quality of care
Providers
Provide service
Register
& Inform
Pay
Funders
-Resources of providers
-Service availability
-Quality assurance
-Cost of service
Individual
patient data
Quality assurance data
Facility
data
Efficiency
People
Patient
Household
survey
-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
Efficiency of system
Utilize & pay
Providers
Provide service
Register
& Inform
Pay
Funders
-Type & level of providers
-Cost of service
Individual
patient data
Facility
data
Equity
Equity of system
Utilize & pay
People
Patient
Providers
Provide service
Household
survey
Register
& Inform
-Seeking pattern by class
-Coverage of service by class
-Utilization by group of patient
-Outcome by group of patient
Individual
patient data
Pay
Funders
-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
Household survey
Facility
data
Thank you very much