Determinants for Healthcare Expenditure

Growth

Presented by LaToyia FloydWayne State University

Fall 2013

OverviewIntroduction

Health Care Trends

Literature Review

Data

Regression Model

Empirical results

Conclusion

IntroductionHealth care expenditure

Current trends vs growth rates: past vs future state

Health care reform in the USEquity Issues – who gets access to healthcare

Providing insurance for the uninsuredQuality issues – health outcomes

Quality of life; preventive careEfficiency Issues – best utilization of resources

Cost: front end investment vs back end exploitation

Re-organization of primary health careExpansion of Mid-level provider utilization

IntroductionRe-organization of primary health care

Improving quality checks and balancesCoordination post hospitalization

Helping the equity conundrum – who receives healthcareDistribute burden of service across resourcesLow overhead clinics which serve local communitiesMulti-payment structures

Re-introducing fee-for-service

% Change in spending downward slope

Health Care Trends

Average Annual Percent Change in National Health Expenditures, 1960-2010

Source: Kaiser Family Foundation calculations using NHE data from Centers for Medicare and Medicaid Services, Office of the Actuary, National Health Statistics Group, at http://www.cms.hhs.gov/NationalHealthExpendData/ (see Historical; National Health Expenditures by type of service and source of funds, CY 1960-2010; file nhe2010.zip).

Health Care TrendsBaby Boomers – increase dependence on health

care

Source: OECD health statistics database

Health Care Trends Distribution of National Health Expenditures, by

Type of Service (in Billions), 2010

Source: Kaiser Family Foundation calculations using NHE data from Centers for Medicare and Medicaid Services, Office of the Actuary, National Health Statistics Group, at http://www.cms.hhs.gov/NationalHealthExpendData/ (see Historical; National Health Expenditures by type of service and source of funds, CY 1960-2010; file nhe2010.zip).

Note: Other Personal Health Care includes, for example, dental and other professional health services, durable medical equipment, etc. Other Health Spending includes, for example, administration and net cost of private health insurance, public health activity, research, and structures and equipment, etc.

Health Care Trends% Distribution for source of spending

1970 2010

1970 2010

1970 2010 1970 2010

Hospital Care

Physician & Clinical Services

Retail Prescription Drugs

Nursing Care Facilities & Continuing Care

Retirement Communities

Literature ReviewBarros (1998) The Black Box of Health care

Expenditure Growth What contributes to the growth rate of health

expenditure – future expansion Contributions to level of health care expenditure –

current and past factors

Fuchs (1974) Who Shall Live Substitution of inputs – can this apply to healthcare

resources such as providers

Macinko, Starfield and Shi (2003) Contribution of Primary Care Systems to Health Outcomes for OECD Countries Strong relationship between strength of primary care

system and health outcomes

DataOECD Database

4 countries: USA, Canada, Norway and Australia

Sample sizes (~40 data points)

Difficulty finding variables that fit into model meaningfully

Data

DataDescriptive Statistics: NORWAY compared to US

VAR Sample size Mean Variance

Norway 39 2,036.92206 2,673,473.90896

 US 39 3,420.43427 5,853,666.01922

Summary

Degrees Of Freedom 67Hypothesized Mean

Difference 0.E+0

Test Statistics 2.95879 Pooled Variance 4,263,569.96409

Two-tailed distribution

p-level 0.00427 t Critical Value (5%) 1.99601

One-tailed distribution

p-level 0.00213 t Critical Value (5%) 1.66792       G-criterionTest Statistics 0.2124 p-level 0.00294

Critical Value (5%) 0.18367   

Pagurova criterionTest Statistics 2.95879 p-level 0.99572

Ratio of variances parameter 0.31353 Critical Value (5%) 0.02516

DataDescriptive Statistics: CANADA compared to US

VAR Sample size Mean VarianceCanada 39 1,918.69179 1,391,987.49144US 39 3,420.43427 5,853,666.01922

Summary

Degrees Of Freedom 55 Hypothesized Mean Difference 0.E+0

Test Statistics 3.48409 Pooled Variance 3,622,826.75533

Two-tailed distributionp-level 0.00098 t Critical Value (5%) 2.00404

One-tailed distributionp-level 0.00049 t Critical Value (5%) 1.67303       G-criterionTest Statistics 0.25225 p-level 0.00194Critical Value (5%) 0.18367    

Pagurova criterionTest Statistics 3.48409 p-level 0.99901

Ratio of variances parameter 0.19211 Critical Value (5%) 0.02518

DataDescriptive Statistics: AUSTRALIA compared to US

VAR Sample size Mean VarianceAustralia 39 1,580.52576 1,112,673.77351US 39 3,420.43427 5,853,666.01922

SummaryDegrees Of Freedom 52 Hypothesized Mean Difference 0.E+0Test Statistics 4.35338 Pooled Variance 3,483,169.89637

Two-tailed distributionp-level 0.00006 t Critical Value (5%) 2.00665

One-tailed distributionp-level 0.00003 t Critical Value (5%) 1.67469       G-criterionTest Statistics 0.32385 p-level 0.00015Critical Value (5%) 0.18367    

Pagurova criterionTest Statistics 4.35338 p-level 0.99994Ratio of variances parameter 0.15972 Critical Value (5%) 0.02519

Regression ModelDependent variable: Total health care

expenditure, per capita PPP

Independent variables:Administration and Health Insurance, per capita

PPPPharmaceuticals and non-durable medical goods,

per capita PPPTotal number of curative (acute) beds, per 1,000Preventative measures, per capita PPPHome care expenditures, per capita PPP

Regression ModelTime series regression, detrended

Country specific comparison

ModelTotal Expenditure on Healthcaret = 0 + 1 GDPt1 +

2(Administration)t1 + 3(Pharma)t3 + 4(tot. curative)t4 + 5(preventive)t5 + 6t + ut

Detrending accomplished by adding time trend variable, 6t

Empirical ResultsSignificant Variables

Empirical ResultsElasticities: logs of variables for USA

Increasing returns to scale for number of Curative beds

Regression ModelDependent variable: Total health care

expenditure, per capita PPP

Independent variables: Total of 10, discussing 5 todayPharmaceuticals and non-durable medical goods,

per capita PPPTotal number of curative (acute) beds, per 1,000Total hospital beds per million population

Limited data pointsPracticing physicians per 1,000 population

Regression Model

Regression Model

ConclusionNumber of Curative beds a factor in health care growth

Clue into organizational restructuring

Further studying on independent variablesNumber of hospitals

Could the decrease in the number of hospitals contribute to lower percentage growth of healthcare

Practicing physiciansNew medical schoolsLeverage mid-level providers

Co-integration between variablesEndogenous effects vs exogenous effects on model

Insurance structuringER expansion