Causes and Consequences of Regional Variations in Health Care Resources in Thérèse A. Stukel, Ph.D. DA Alter, R Saskin, DM Rothwell Institute for Clinical Evaluative Sciences, Health Services Restructuring Conference Queen s University November 2005 Health System Alignment The basic objective of most publicly funded health care systems is rational planning and optimal allocation of health care resources based on population health care need. Health system alignment occurs when patients are treated using the resources & in the setting where returns are highest in terms of clinical outcomes & financial efficiency. Components of a Health Care System Outcomes Mortality Quality of life Readmissions Complications Resources Health human resources Beds Equipment Supplierinduced Demand Evidencebased Use Population Need Use of Services Hospital admissions Physician visits Diagnostic testing Home care Predictors of Need? 1
Geography of Health Care: Local Health Integration Networks (LHINs) Why Create Regions? Allows rational, population needs-based health care planning, management and accountability. Study effects of health system resources (hospital beds, physicians, diagnostic test equipment) on health care utilization & outcomes of populations. Health Care Resources How does one measure resource supply to a population? What is the right rate? How many resources do we need? Allocation of Health Care Resources to LHINs Hospital beds (acute, chronic, rehab). Physician supply (primary care, specialists). Cardiac technology (CATH labs). Allocate resources used by population in region, regardless of where services are provided. Compute LHIN resources on a per capita basis. 2
Hospital Bed Allocation Method LHIN 1 LHIN 2 Hospital Patient-Days to LHIN 1 Population: 3,500 Hospital Patient-Days to LHIN 2 Population: 2,500 50 Beds 3,000 500 2,000 500 10 Beds 30 +5=35 Allocated Beds 20 + 5 = 25 Allocated Beds Hospital Beds per 1,000 (In-Area) Mississauga Oakville 0 1 2 3 Rate per 1,000 Hospital Beds per 1,000 (Allocated) 0.0 0.5 1.0 1.5 2.0 2.5 Rate per 1,000 3
Cardiac Catheterization Labs per 100,000 (In-Area) 0.0 0.5 1.0 1.5 Cardiac Catheterization Labs per 100,000 (Allocated) 0.0 0.2 0.4 0.6 0.8 Relationship Between Total Inpatient Days and Hospital Bed Supply INPATIENT DAY RATE PER 1,000 500 600 700 800 R2 = 0.87 (R2 = 0.42) 1.4 1.6 1.8 2.0 2.2 2.4 2.6 HOSPITAL BEDS PER 1,000 4
Hip Fracture Admission Rates 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Rate per 1,000 AMI Admission Rates 0 1 2 3 4 Rate per 1,000 COPD Admission Rates 0 1 2 3 4 Rate per 1,000 5
Primary Care Physician Supply per 100,000 0 20 40 60 80 100 Anti-Hypertensive Prescribing Rates (Age 65+) 0 1 2 3 4 5 6 Rate (per capita) Cardiologist Supply per 100,000 0 1 2 3 4 5 6 6
Relationship Between AMI Admission Rates and Cardiologist Supply AMI ADMISSION RATE PER 1,000 1.8 2.0 2.2 2.4 2.6 2.8 3.0 R2 = 0.3 (R2 = 0.21) 2 3 4 5 AGE-SEX ADJUSTED ALLOCATED CARDIOLOGISTS (FTEs) PER 100,000 Relationship Between Cardiac Catheterization Rates and Cardiologist Supply CARDIAC CATHETER RATE PER 1,000 3.5 4.0 4.5 5.0 5.5 6.0 6.5 R2 = 0.01 (R2 = 0.01) 2 3 4 5 AGE-SEX ADJUSTED ALLOCATED CARDIOLOGISTS (FTEs) PER 100,000 Paediatrician Supply per 100,000 0 5 10 15 20 7
Psychiatrist Supply per 100,000 0 10 20 30 40 Benchmarking Physician Supply per 100,000 Specialty Non-billing (%) U.S. U.S. HMO Primary Care 74.7 13 70.9 52.4 General Pediatrics 6.8 30 18.5 9.9 Cardiology 3.8 4 5.9 2.7 General Surgery 4.3 8 11.0 5.0 Anesthesiology 7.4 11 10.6 8.8 OB/GYN 5.0 9 12.7 9.8 Orthopedic Surgery 3.1 8 7.7 5.1 Psychiatry 13.2 9 13.9 3.3 Radiology 7.3 3 9.6 10.0 Cohort Study Longitudinal Cohort Study Chronic Disease Cohorts: AMI, hip fracture, GIB, respiratory cancer. Incident cases, first admission. Followed up to 5 years for mortality, readmissions, PC visits. Censored if died, moved from LHIN. 8
Models Demographic, SES characteristics. Comorbidities. Clinical presentation, MI location (AMI). Pre-admission functional status (AMI). Hospital characteristics (volume, teaching status). Chronic Disease Cohorts Were the populations similar at baseline? Predicted one-year mortality Predicted One-Year Mortality (%) 30 25 20 15 10 5 0 AMI GI Bleed Hip Fracture Respiratory Ca Circum SW Regions SE North Chronic Disease Cohorts Were they treated differently? Mean annual hospital re-admissions 20 AMI GI Bleed Hip Fracture Respiratory Ca Mean Re-admissions 15 10 5 0 Circum SW SE North Regions 9
Chronic Disease Cohorts Were they treated differently? Mean annual primary care visits Mean Primary Care Visits 10 8 6 4 2 0 AMI GI Bleed Hip Fracture Respiratory Ca Circum SW Regions SE North Adjusted Relative Mortality Rates in Chronic Disease Cohorts Across Regions Regions Bed Supply per 1,000 AMI 1.61 1.00 (reference) Circum- 1.40 1.04 (1.00, 1.08) SW 1.55 1.14 (1.10, 1.18) SE 1.59 1.09 (1.05, 1.14) Northern 2.27 1.22 (1.17, 1.27) Hip Fracture GI Bleed 1.00 (reference) 1.00 (reference) 1.09 (1.04, 1.14) 0.91 (0.85, 0.99) 1.19 (1.14, 1.24) 0.97 (0.90, 1.04) 1.18 (1.12, 1.23) 0.95 (0.88, 1.04) 1.22 (1.16, 1.28) 0.93 (0.86, 1.02) Respiratory Cancer 1.00 (reference) 1.00 (0.95, 1.05) 1.13 (1.07, 1.19) 0.95 (0.90, 1.01) 1.09 (1.03, 1.16) Healthcare Resource Supply vs. U.S. Fewer resources per capita (hospital beds, CATH labs, specialists). Regional variations smaller when rational allocation occurs (hospital bed supply, PC physician supply, cardiac surgery). Variations large when health system unmanaged (specialist supply; location of specialists w.r.t. need; diagnostic equipment). Strong relationships between supply and use. 10
Managing s Healthcare Resources Manage supply so as to match resources to population need with a view to clinical & financial efficiency Measure supply at population (per capita) level, accounting for migration Benchmark supply to that of other efficient, high quality health care systems Relationships between supply/use and outcomes? Or regional differences in practice patterns? Vulnerable populations (North, old elderly, low SES). 11