HEALTH TECHNOLOGY INTENSITY & PHYSICIAN EXPENDITURE: Methodology, Algorithms MCMASTER UNIVERSITY Mehrdad Roham rohamm@mcmaster.ca Anait Gabrielyan anaitgabrielyan@gmail.com SAS Health User Group Forum November 15, 2013
Growth in Total Health Expenditure Per Capita Source: Adapted from Organisation for Economic Co-operation and Development (2010), OECD Health Data, OECD Health Statistics (database). doi: 10.1787/data-00350-en (Accessed on 14 February 2011). Annual Growth 1980-2008 Canada 3.0% US 4.0% Japan 2.7% 1990-2008 Canada 2.5% US 3.3% Japan 2.8% 2000-2008 Canada 3.4% US 3.4% Japan 2.0%
Primary Drivers of Health Care Costs Technology Developers Return investment Patients and family members Significant benefits for health improvement Health care expenditure Health care providers Better health care services Payers (Governments) Stabilize and reduce cost
REDUCE PAIN AND DISABILITY HEALTH TECHNOLOGY BENEFITS for PATIENTS IMPROVE THE HEALTH HEALTH TECHNOLOGY BENEFITS EXTENDED LIFE CONTRIBUTION TO LONGER AND BETTER-QUALITY LIVES
Health Technology Definition Health technology (HT) is any intervention that may be used to promote health, prevent, diagnose or treat disease, or for rehabilitation or long-term care to the maintenance, restoration and promotion of health
HT KEY ELEMENTS Usually HT divided in two categories: devices, equipment, procedures, organizational systems and instruments used in the clinical and administrative delivery of health services, to the maintenance, restoration and promotion of health; and information and knowledge, which form the basis of the skills and expertise of health caregivers.
HTI COMPONENTS Health Technology Intensity (HTI) is founded in the idea, that the process of adoption of the technology in health care can be analyzed within three components Technological Complexity of intervention (or procedure) (qualitative) Knowledge of person using that technology (qualitative), Cost of technology (quantitative).
HTI COMPONENTS DESCRIPTION Key Attributes of Component Identification of Technology Low Medium High 1) Technological Complexity Description: Technological Intervention a) Complexity; b) cost of device, equipment. a) Simple; b) Low cost. Example: Consultation, Simple Injection. a) Medium complexity; b) Relative medium cost. Example: Nerve Block; a) High complexity b) High cost. Example: Computed Tomography (CT); Coronary Artery Repair. 2) Technological Knowledge Description: Physician Specialization and Qualification Additional a) specialization, b) skills, c) training needed No Yes- short term Yes- long term 3) Technology Cost Description: Fee for technological intervention Clustering fee for service Equation a (step 1.b2) Equation b (step 1.b2) Equation c (step 1b2)
HTI COMPONENTS EXAMPLE Family Physician A608 $38.05 Partial assessment Consultation A605 $157.00 Cardiology consultation Cardiologist A600 $300.70 Comprehensive consultation
DATA SOURCES AND RESEARCH STEPS
Number of Records for Analysis CCHS linked data Description Records N % Total Records 3,878,720 100.0 Excluding HP,DP and LAB 1,407,631 36.3 Shadow Billing 66,071 1.7 Adjustment to Previous Billing 185,008 4.8 Total Records for Analysis 2,220,010 57.2 OHIP data Description Records N % Total Records (1994-2004) 1,324,633,221 100 Exclusions: Out of Province 1,658,198 0.13 HP, DP and LAB 485,358,165 36.64 Shadow Billing 26,630,280 2.01 Age and Sex not Known 56,889 0.0 Records for Analysis 810,929,689 61.22
MOTIVATION The mixture of precise quantitative information (the fee) and imprecise qualitative information (physician specialty, intervention codes) provides the motivation for the use of a fuzzy system rulebased approach in HTI calculations and modeling Fuzzy logic plays a unique role in handling natural language inputs in addition to numerical data and is an effective tool for modeling in the absence of complete and precise information. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge, and has proved effective in representing inexact, incomplete, or corrupted data for approximate reasoning over uncertain knowledge. This means that raw data represented through such fuzzy labels as low, medium, and high does not lead to loss of information instead, fuzzy systems make it possible to deal with processes for which only a linguistic description is available, thereby allowing us to achieve a robust, secure, and reproducible automation of such tasks.
FUZZY SET A fuzzy set is an extension to a classical set theory, which has a problem of defining the border of the set and non-set A fuzzy set A is defined by a set or ordered pairs, a binary relation, Where A (x) A (x) is a function called membership function; species the grade or degree to which any element x in A belongs to the fuzzy set A.
HTI CALCULATION ALGORITHM Source: Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer."The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation", Health Economics 08/2013; DOI:10.1002 /hec.2979
FEE SCHEDULE CODES TECHNOLOGICAL COMPLEXITY (near 5600 ) Fee schedule code A000 A001 A002 A003 A004 A005 A006 A007 A008 A009 A013 A014 A015 A016 A023 A024 A025 A026 A033 A034 A035 A036 A043 A044 Fee schedule code description A000 - DESCRIPTION UNKNOWN MINOR ASSESS. - F.P./G.P. A002 - DESCRIPTION UNKNOWN GEN. ASSES. - F.P./G.P. ANNUAL HEALTH WITH DIAG. CODE 917 GEN. RE-ASSESS. - F.P./G.P. CONSULT. - F.P./G.P. RE-CONSULT. - F.P./G.P. INTERMED. ASSESS./WELL BABY CARE - F.P./G.P./PAED. MINI ASSESSMENT - F.P./G.P. OCULO-VIS. ASSESS. - F.P./G.P. SPECIFIC ASSESSMENT -ANAES. PARTIAL-ASSESSMENT - ANAES. CONSULT. - ANAES. RE-CONSULT. - ANAES. SPECIFIC ASSESS. - DERM. PARTIAL ASSESS. - DERM. CONSULTATION - DERM. REPEAT CONSULTATION - DERM. SPEC. ASSESS. - GEN. SURG. PARTIAL ASSESS. - GEN. SURG. CONSULTATION - GEN. SURG. REPEAT CONSULT. - GEN. SURG. SPECIFIC ASSESSMENT - NEUROSURG. PARTIAL ASSESSMENT - NEUROSURG. CONSULTATIONS AND VISITS
FEE SCHEDULE CODES (TECHNOLOGICAL COMPLEXITY) LOW MEDIUM HIGH CONSULATATIONS AND VISITS PULMONARY FUNCTION STUDIES NUCLEAR MEDICINE - IN VIVO CONSULTATIONS AND VISITS (EMERG. DEPT. PHYS.ON DUTY) COMPREHENSIVE GERIATRIC CONSULTATION CONSULTATIONS AND VISITS (PHONE) ASSISTANCE CHIROPRACTIC VISIT PREVENTIVE CARE MANAGEMENT PRONOUNCEMENT OF DEATH HOSP. MINOR ASSESS CERTIFICATION OF DEATH HOME CARE INTEGUMENTARY SYSTEM SURGICAL PROCEDURES MUSCULOSKELETAL SYSTEM SURGICAL PROCEDURES RESPIRATORY SURGICAL PROCEDURES HAEMATIC AND LYMPHATIC SURGICAL PROCEDURES DIGESTIVE SYSTEM SURGICAL PROCEDURES UROGENITAL AND URINARY SURGICAL PROCEDURES MALE GENITAL SURGICAL PROCEDURES FEMALE GENITAL SURGICAL PROCEDURES ENDOCRINE SURGICAL PROCEDURES CHIROPRACTIC RADIOGRAPHIC RADIATION ONCOLOGY DIAGNOSTIC RADIOLOGY CLINICAL PROCEDURES ASSOCIATED WITH DIAGNOSTIC RADIOLOGICAL EXAMINATIONS MAGNETIC RESONANCE IMAGING (MRI) DIAGNOSTIC ULTRASOUND CARDIOVASCULAR SURGICAL PROCEDURES NEUROLOGICAL SURGICAL PROCEDURES OCULAR AND AURAL SURGICAL PROCEDURES SPINAL SURGICAL PROCEDURES OBSTETRICS DIAGNOSTIC AND THERAPEUTIC PROCEDURES* DIAGNOSTIC AND THERAPEUTIC PROCEDURES* DIAGNOSTIC AND THERAPEUTIC PROCEDURES*
PHYSICIAN SPECIALTY SP CODE LOW SP CODE MEDIUM SP CODE HIGH 05 COMMUNITY MEDICINE 01 ANAESTHESIA 60 CARDIOLOGY 00 GENERAL AND FAMILY PRACTICE 02 DERMATOLOGY 09 CARDIOVASCULAR & THORACIC SURGERY 07 GERIATRICS 12 EMERGENCY MEDICINE 33 DIAGNOSTIC RADIOLOGY 19 PSYCHIATRY 41 GASTROENTEROLOGY 64 GENERAL THORACIC SURGERY 03 GENERAL SURGERY 61 HAEMATOLOGY 13 INTERNAL MEDICINE 18 NEUROLOGY 20 OBSTETRICS & GYNAECOLOGY 04 NEUROSURGERY 24 OTOLARYNGOLOGY 63 NUCLEAR MEDICINE 26 PAEDIATRICS 23 OPHTHALMOLOGY 31 PHYSICAL MEDICINE 06 ORTHOPAEDIC SURGERY 47 RESPIRATORY DISEASE 08 PLASTIC SURGERY 48 RHEUMATOLOGY 34 THERAPEUTIC RADIOLOGY 35 UROLOGY
Validation Measure CLUSTERING VALIDATION The fuzzy GK algorithm reveals structure in data through a minimization of a quadratic objective function by utilizing the Mahalanobis distance 2.5 2 1.5 1 PC CE PI SI*10^3 XB*10^(-3) MPC MCE Most commonly used validation indexes include : Partition Coefficient (PC) Modified PC (MPC)); Classification ( sometimes called partition) Entropy (CE); Modified CE (MCE) ; Partition Index (PI); Separation Index (SI). 0.5 0 2 3 4 5 6 7 8 9 10 11 12 13 14 Number of Clusters Empirical studies suggest that a suitable number of clusters is the one that maximizes PC, MPC, and MCE and minimizes CE, PI, SI and XB. The value of the different cluster validity indices for different number of cluster The cluster centers after GK clustering algorithm for component x 3 - Cost of technology using in real 2002 dollars is following V 3 {70;1078;398}
PROPOSED ALGORITHM Stage 1.B1. Ranking centers for all clusters V { v, v, v } { v, v, v } {70;398;1078} 3 1 3 2 3 3 3 L 3 M 3 H 3 Stage 1.B2. Fuzzification Step 2. Determining components importance Step 3. Aggregation w1 0.5; w2 w. 3 0.25 N * HTI( x j. 1) wj Z ( x j.1) {1,0,0} j 1 HTI( x ) j. 2 {0.75,0,0.25} Fig. Membership Function for Linguistic Variable x3 - Cost of technology using Step 7. HTAI Linguistic Identification HTI( x ) j. 3 {0.25,0.5,0.25} HTI( x ) j. 4 {0.25,0,0.75} HTI( x ) j. 5 {0,0.03,0.97} Step 4. Defuzzification Fig. Membership Function for HTI. HTI N i 1 i z i max N i 1 i
SAS CODE EXAMPLE FUZZIFICATION /*******RECORDING PD TO CLASSIFICATION CLASS*********/ IF PD=0 then PD_CLASS=0; else if 0<PD<=179 then PD_CLASS=1; else if 179<PD<=289 then PD_CLASS=2; else if 289<PD<=625 then PD_CLASS=3; else if 625<PD<=851 then PD_CLASS=4; Else PD_CLASS=5; LABEL PD_CLASS='FEE PAID CLASSIFICATION'; /*****************************FUZZIFICATION*******************************/ /*MEMBERSHIP CALCULATION of PD "COST of TECHNOLOGY" */ / *********************LOW FEE PAID CALCULATION********************/ IF PD_CLASS=1 THEN PD_CLASS_LOW=1; ELSE IF PD_CLASS=2 THEN PD_CLASS_LOW=(289-PD)/(289-179); ELSE PD_CLASS_LOW=0; LABEL PD_CLASS_LOW='FEE PAID LOW TECHNOLOGY';
SAS CODE EXAMPLE FUZZIFICATION /***************************AGGREGATING*******************************************/ /*************OWA, ORDERED WEIGHTED OPERATOR*************************/ /*********LOW TECHNOLOGY CALCULATION**********/ TECHN_INDEX_LOW=0.5*FSC_CLASS_LOW+0.25*SP_CLASS_LOW+0.25*PD_CLASS_LOW; /*********MEDIUM TECHNOLOGY CALCULATION**********/ /*********HIGH TECHNOLOGY CALCULATION**********/ TECHN_INDEX_MEDIUM=0.5*FSC_CLASS_MEDIUM+0.25*SP_CLASS_MEDIUM+0.25*PD_CLASS_MEDIUM; /*MEMBERSHIP CALCULATION of PD "COST of INTERVENTION" */ TECHN_INDEX_HIGH=0.5*FSC_CLASS_HIGH+0.25*SP_CLASS_HIGH+0.25*PD_CLASS_HIGH; LABEL TECHN_INDEX_LOW='TECHNOLOGY INDEX FOR CALCULATION LOW'; LABEL TECHN_INDEX_MEDIUM='TECHNOLOGY INDEX FOR CALCULATION MEDIUM'; LABEL TECHN_INDEX_HIGH='TECHNOLOGY INDEX FOR CALCULATION HIGH' /*************************** *****************DEFUZZIFICATION********************************/ TECHN_INDEX=0.15*TECHN_INDEX_LOW+0.5*TECHN_INDEX_MEDIUM+0.9*TECHN_INDEX_HIGH; LABEL TECHN_INDEX='TECHNOLOGY INDEX'; /***************FOR TECHNOLOGY INDEX LEVEL CALCULATION FUZZY*************/ IF TECHN_INDEX >=0.70 THEN HTI_CLASS=3; ELSE IF 0.32<TECHN_INDEX<0.7 THEN HTI_CLASS=2; ELSE HTI_CLASS=1; LABEL HTI_CLASS='HTI CLASS IDENTIFICATION '; RUN;
ILLUSTRATIVE EXAMPLE Consultation with Family Physician, Visits (1) Is Additional Consultation with Specialist Needed? Yes Consultation with Specialist (2) Diagnostic Intervention (4) Yes Is Diagnostic Procedure Needed? No Special Treatment (3,5) Yes Is Special Treatment Needed? No END The process of receiving health technology by patient A.
ILLUSTRATIVE EXAMPLE CLAIM N FEE SCHEDULE CODE (Technological Complexity) FSC TI code PHYSICIAN SPECIALITY CLAIMED (SP) SP code Cost *, $ HTI a) DATA 1 CONSULTATION- FP/GP** A005 GENERAL AND FAMILY PRACTICE 0 51.37 0.1 2 CONSULTATION- CARDIOL A605 CARDIOLOGY 60 121.34 0.3 3 NERVE BLOCK- EPIDURAL BLOCK G216 NEUROSURGERY 4 68.77 0.5 4 COMPUTED TOMOGRAPHY (CT)-HEAD X400 DIAGNOSTIC RADIOLOGY 33 40.8 0.7 5 CORONARY ARTERY REPAIR R742 CARDIOLOGY 60 820.1 0.9 b) LINGUISTIC IDENTIFICATION 1 LOW LOW LOW LOW 2 LOW HIGH LOW MEDIUM 3 MEDIUM HIGH LOW MEDIUM 4 HIGH HIGH LOW HIGH 5 HIGH HIGH HIGH HIGH
KNOWLEDGE RULES IF For Technological Claim 1. Complexity (FSC) is Low, and Knowledge of person using that technology (SP) is Low, and Cost of technology using (P) is Low, THEN Health Technology Intensity (HTI) is Low. a) SP=LOW b) SP=MEDIUM c) SP=HIGH HTI Fig.. Knowledge base for HTI Step 6. HTI aggregation by class Number of Health Services Expenditure for HealthCare, 2002 Dollars LOW 1 51.4 4.7 MEDIUM 2 190.1 17.2 HIGH 2 860.9 78.1 ALL EXPENDITURE FOR PATIENT A 1102.4 100.0 Expenditure, %
3D Surface plot for FSC, SP and HTI P=Low (Claim 4) P=Medium P=High (Claim 5)
RESULTS We estimated Per person health expenditure, and Per person number of services used (number of procedures) for each year, age group, sex, technology intensity in health service. Annual growth rates in health care uses, expenditure, number of services by technology adoption were also estimated.
Physician health service provision, average number and share, by HTI, 1994 2004 Source: Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer."The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation", Health Economics 08/2013; DOI:10.1002 /hec.2979
Average Annual Percentage Change, % <1 1-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ ALL Annual Rates for Number of Services, by (HTI), 1994 2004 8 6 4 2 0-2 -4-6 -8-10 Age groups Low HTI Medium HTI High HTI
Physician health service provision, per capita expenditure and expenditure share, by HTI, 1994 2004 Source: Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer."The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation", Health Economics 08/2013; DOI:10.1002 /hec.2979
Average Annual Percentage Change, % <1 1-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ ALL Annual Rates for Physician Service Expenditures, by HTI, 1994 2004 6 4 2 0-2 -4-6 -8-10 Age groups Low HTI Medium HTI High HTI
Physician health service provision, average number of services, by HTI and Age Group Source: Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer."The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation", Health Economics 08/2013; DOI:10.1002 /hec.2979
Physician health service provision, average per capita expenditure, by HTI and Age Group Source: Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer."The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation", Health Economics 08/2013; DOI:10.1002 /hec.2979
GENDER DIFFERENCES
SUMMARY During ten years adoption of high technology grew significantly (4% annually). Increases in High HTI services was due to improvement in technology and medical devices used for diagnosis and treatment, allowing more and more patients to be treated. Females are more likely to have high technology treatment than males. This statement is true for all age groups (except Age Groups 0-14,80+) Elderly received high technology treatment more than non-elderly (1.8 for men and 1.4 for women) As age of patient increased, so did the expenditure paid for health care, This is true for all expenditure by technology adoption. Spending per person on high technology for elderly was significantly more than for nonelderly ( 4 times for men and 2 times for women)
Roham M, A.R. Gabrielyan, N. P. Archer, M.Grignon and B. G. Spencer. The Impact of Technological Intensity of Service Provision on Physician Expenditure: An Exploratory Investigation HEALTH ECONOMICS 08/2013; DOI:10.1002 /hec.2979
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APPENDIX
TO WHOM HTI IS IMPORTANT Details of the technology s Intensity into current practice add important information to the review of the provision and delivery of the health technology in Ontario for Government, Practicing medical experts, Insurance Companies and Industry.
WHY HTI IS IMPORTANT The research will help health policy analysts and researchers to understand the relations between aging population and distribution of spending on health care, with the analysis of the impact of the ageing of Canadian population on different categories of technology usage health expenditure (hospital, physician), changes in using the medical technology by age profile and also will help to produce better predictions on health care expenditures under various scenarios of the technology adoption.