IS TECHNOLOGICAL CHANGE IN

MEDICINE ALWAYS WORTH IT? THE

CASE OF ACUTE MYOCARDIAL

INFARCTION

“Waste and inefficiency are not inevitable by-products of technological

growth.”

Jonathan S. Skinner, Douglas O. Staiger and Elliott S. Fisher

5th April, 2016

Vibha Amblihalli

Sanjana Srinivasan

PREVIOUS RESEARCH

David Cutler et al. argue “the benefits from many

technological innovations more than justify the

rising costs of health care”

Rapid decline in mortality following Acute Myocardial

Infarction (AMI)

1984 to1998 - increase cost of Rx heart attack by

$10,000, and life expectancy rose by about 1 year

Elliott Fisher et al (Medicare)

Higher healthcare cost didn’t have better outcome, nor

did they gain better access to care or report greater

satisfaction

A state level data: –ve associative between quality of

care and healthcare spending!!

WHAT IS NEW ABOUT THIS PAPER?

Analysis on AMI mortality and spending

expanded data set that stretches from 1986 to 2003.

Questions to be answered

Did the observed survival gain in the earlier data continue

into the current century?

Have recent increases in health care costs still been worth it?

Did regions with rapid improvement in health outcomes also

experience rapid increases in costs?

Were there specific regional characteristics (low-cost, highly

effective Rx) which could be associated with better health-

outcome with unusual low spending increases?

STUDY DATA AND METHODS

Data:

Part A: hospital claims data from 1986–2003 were

merged with the Medicare Denominator File through

2003 to create a longitudinal cohort of fee for-service

(FFS) enrollees aged ≥65 who had new AMI - 2,872,050

valid AMI events found.

Spending data are available only through the end of

2003

One-year survival and spending data are analyzed from

1986 to 2002.

Part B spending data from 1993-2002: 5 % sample

from 1993–1997 and 20% sample for 1998–2002

PRIMARY AND SECONDARY ANALYSIS

Methods:

Primary analysis- on Part A data

Expenditures were corrected for inflation using US

implicit price deflator and expressed in 2003 dollars

Both spending and survival rates were determined for

the same 1-year horizon.

Secondary analysis on Part B data

Survival and spending data adjusted for

comorbidities, age, sex, race, and type of MI

The regression analysis of survival and spending

data as linear function of demographics and

comorbidities.

REGION SPECIFIC ANALYSIS

Done using data from 306 Hospital Referral Regions

(HRRs) across U.S. between 1986-2002

Region specific measure of annual survival and

spending were constructed

Regression analysis with adjustment for

comorbidities and demographics

Rationale : Analysis ensured that the results reflect

regional practice patterns rather than regional

differences in patient characteristics

Regions differed dramatically in their AMI treatment

strategies as well as reliance upon multiple physicians

per patient.

REGIONAL ANALYSIS

Research was focused on two region-level

dimensions of care.

1. Index of low-cost, highly effective treatments for AMI -

aspirin at discharge, beta-blockers at discharge, and

reperfusion within twelve hours of admission

quality measures were % patients in each region deemed idea

for Rx who actually did receive Rx

Quality measure range from 1 (<national median for all 3

measures) to 4 (>national median for all 3 measures)

2. Average no. of different physicians treating the patient

within one year of AMI, averaged across all patients in

the HRR in 1994-95.

REGIONAL ANALYSIS

Hypothesis

1. Regional differences in treatment strategies is

associated with survival gains and spending increases

during 1986 -2020

2. Regions where quality measures were adopted early

would experience the greatest improvement in survival

with small influences on Medicare spending.

3. Larger number of separate physicians should have

uncertain effects on survival but were likely to be

associated with more rapid spending increases during

the period.

THE CROSS-SECTIONAL EVIDENCE

There were very wide differences across regions

There was no evidence that higher spending levels were associated with

better outcomes, similar to previous researches.

THE TIME-SERIES EVIDENCE ON SURVIVAL

Flattening of mortality = no additional health benefits

Mid-1990s the diffusion of aspirin had begun to slow, while a

meta-analysis of stents during this period did not show significant mortality

effects

Flattening of mortality Flattening of Mortality

THE TIME-SERIES EVIDENCE ON SPENDING

1986 to 2002, Part A spending increased by $12,399 and one-year

survival raised by 9.8/100AMI pts.

Using the adjustments in Cutler study cost effectiveness ratio was

$20,086/life year – healthcare costs were “worth it”

1997

REGIONAL CHANGES IN SURVIVAL AND

EXPENDITURES

REGIONAL CHANGES IN SURVIVAL AND

EXPENDITURES

Increase in expenditures not associated with

increase in survival

If anything, there is a negative correlation between the

two

Statistical analysis shows that the correlation

coefficient between growth in spending and survival

is -0.21 (p < 0.001)

Changes in reimbursement rates across regions and in

the quality of care provided.

At best, no association between growth and

survival gains

FACTORS ASSOCIATED WITH CHANGES IN

REGIONAL MORTALITY AND EXPENDITURES

Exhibit 4 suggests large differences in regional

productivity

Highly productive regions = rapid growth in survival

rates, below-average growth in expenditures

Low productivity regions = below-average survival

gains, above-average growth in expenditures

Can the two variables from the 1994/1995 study –

quality index and average number of different

physicians predict high and low productivity

regions?

FACTORS ASSOCIATED WITH CHANGES IN

REGIONAL MORTALITY AND EXPENDITURES

FACTORS ASSOCIATED WITH CHANGES IN

REGIONAL MORTALITY AND EXPENDITURES

Exhibit 5a controls for average number of different

physicians, and Exhibit 5b holds the quality index at

a constant

Varying both the quality index and the average

number of different physicians yielded an effect that

was large in magnitude and highly significant

Highest productivity regions = best quality index AND

lowest average physicians

Predicted better survival growth (7.0/100 patients) and lower

cost increase (over $5000) than the lower productivity regions

DISCUSSION

Between 1986 and 2002

Average 1-year survival rate following AMI increased by

10 AMI patients

Estimated cost – less than $25,000 per life year saved

Huge amount of heterogeneity

very little improvement after 1996 despite growing

expenditures

Variation in survival gains across regions and times

Regional gains in survival were negatively related to

costs

So are increasing expenditures on medical care

“worth it” or not?

DISCUSSION

“Flat of the curve” – changes in patient outcomes

over time reflect valuable technological change, but

incremental spending provides little benefit or could

harm patients

Doesn’t explain the patterns found in this study

Overuse of treatments cannot explain why regions with

high spending are less likely to provide effective

treatment

This hypothesis is not consistent with findings that areas

with lower survival gains and higher cost lagged in

adopting low cost, non-invasive treatment

DISCUSSION

DISCUSSION

The proposed model reconciles the cross-sectional and

time series evidence

There is a negative correlation between spending and

survival – can be seen when comparing points B and C

On average, everyone is better off, but regional gains are not

correlated with regional expenditures

Assumption: uneven diffusion of cost-effective

innovations drives differences in patient costs and

outcomes

Use of low-cost and non-invasive treatments reduces the

incremental benefit of expensive, invasive treatments

Adoption of these low cost innovations may have caused

reduction in health care costs

POLICY IMPLICATIONS OF PROPOSED

APPROACH

Model does not preclude that cutting costs in the

low-efficiency, high-cost regions would impact

quality of care

Policies should focus on improving productivity – not

necessarily decreasing costs, but restructuring

resources to be spent on more efficient treatments or

processes

Does not suggest that focus be on “low-tech”

effective treatments. Preliminary results suggest

that “high-tech” options like surgery were not the

cause of expenditure growth between 1986 and

2002

AUTHORS’ CONCLUSIONS

Benefits of health care technology are substantial, but costs to consumers, producers and the government should be of real value to patients

Some regions in this study were able to implement technological innovations at low cost in an efficient fashion

Waste and high costs are not an inevitable by-product of technology

Keeping quality of care and efficiency in mind will help providers adopt low cost effective care, which may foster the growth of technological progress

THANK YOU!