Causal Effect of Managed Care on Health Care Quality: Evidence from Cancer Screening Guideline Discontinuities Srikanth Kadiyala* Grant Miller** Harvard University Funding: *Sloan Foundation, **NIH

Dr. Sandy MacColl [one of the founders of GHC] wrote that he and his colleagues sought a “system of family care…directed towards a goal of good care, health maintenance and preventive services” Crowley,To serve the greatest number: A History of the GHC of Puget Sound

Managed Care Held Great Promise for Quality Improvements –Lower Cost –Appropriate Use of Medical Care Conventional View is that it has Failed We Contend Jury is Still Out

Previous Research Randomized Control Trial –Rand HI experiment (late 1970s) Cross-Sectional Studies –Selection problem since assignment to insurance type is NOT random –Control for observables –Findings Equivocal

New Empirical Strategy Discontinuity design using age-specific preventive service guidelines –Within plan comparisons of preventive service use across guideline thresholds difference out selection effects –Guidelines are “bright lines”-No discrete increase in cancer risk at these ages

Cancer Screenings Recommendations U.S Preventive Task Force (USPSTF) and American Cancer Society ( ACS) –Colorectal Cancer USPSTF & ACS – Both recommend screening for individuals age 40+ No recommendation on screening technology –Breast Cancer ACS-Recommended mammography for women ages 40+ since early 1980s USPSTF-Recently switched to 40+, previously 50+ Thus we look for changes over both the 40 and 50 year thresholds –Prostate Cancer USPSTF-Does not recommend PSA ACS-Physicians should offer PSA Screening is Recommended for these diseases ONLY for asymptomatic people above a certain age IOM/ Quality Chasm report: Cancer Screenings UNDERUSED

Natural Experiment Framework A B C D Pre- guideline Post Guideline Managed Care FFS E F G H Pre- guideline Post Guideline Difference-In-Difference-In-Difference = [ (D-B)-(C-A) ] – [(H-F)-(G-E)]

Regression Discontinuity Post Guideline Managed Care FFS Post Guideline F H Diff.-In-Diff.=[(D-B)] – [(H-F)] -This assumes that [(G-E)-(C-A)] is zero, which is a plausible assumption B D 50 49

Data National Health Interview Survey(NHIS): National Sample of Individuals Breast Cancer (N=6807,Years ) Colorectal Cancer (N=3426,Year 2000) Prostate Cancer(N=1543,Year 2000) Insurance Plan Types Group/Staff Models, IPA, POS, PPO, Fee-For- Service(FFS) Rich Set of Covariates –Income, Education, Race, Region, Marital Status Also MarketScan Data (these results not reported)

Colorectal Cancer: Any Screening in Last Year by Plan and Age NHIS Data-Year 2000

Breast Cancer: Mammogram Use in Last Year by Plan and Age NHIS Data:

Breast Cancer: Mammogram Use in Last Year by Plan and Age NHIS Data:

Prostate Cancer PSA Test Use in Last Year by Plan and Age NHIS DATA: Year 2000

Regression Discontinuity Estimate using Colorectal Cancer: Means by Plan and Age Group PlanAges45-49Ages50-54Diff.-In-Diff. Relative to FFS GHMO (N=171) 2.3% (.017) 36% (.07) [+33.7%] - [12.9%] = +20.8% IHMO (N=1369) 12% (.014) 21% (.018) [+9%] – [+12.9%] = - 3.9% PPO (N=745) 11% (.018) 22% (.022) [+11%] – [+12.9] = -1.9% FFS (N=619) 8.8% (.017) 21.7% (.027) +12.9% POS (N=520) 13.6% (.029) 17% (.027) [+3.4%] – [+12.9] = +9.5%

Regression Estimates of Screening Use PlanColorectalMam.(35-44)Mam.(45-54)PSA GHMO-.092(.027)-.086(.042).05(.05)-.079(.07) IHMO-.008(.021)-.055(.021).069(.026)-.054(.036) PPO-.021(.023)-.06 (.024).034(.030)-.01(.044) POS.001(.032)-.039(.027).017(.034)-.038(.047) GHMO*AGRP.24(.075).124(.065)-.012(.07).07(.11) IHMO*AGRP.022(.029).087(.026)-.014(.03)-.007(.048) PPO*AGRP.035(.033).103(.03).001(.036).075(.065) POS*AGRP-.032(.04).078(.037).025(.045)-.011(.07) N Standard Errors in parantheses. Bold indicates point estimate is significant at the 5% level. Italics means significant at the 10% level. Regression models adjust for age,sex,race, education, income,marital status, region and time where appropriate.

Results from Cross-Section Regressions PlanColorectalMam (35-44) GHMO.019 (.04)-.02 (.036) IHMO.003 (.02)-.009 (.02) PPO-.005 (.02)-.006 (.02) POS-.012 (.027).003 (.02) N Standard Errors in parantheses. Bold indicates point estimate is significant at the 5% level. Regression models adjust for age,sex,race, education, income,marital status, region and time where appropriate.

Interpretation of Results Change in Use across Age thresholds generally larger in Managed Care Plans –Large statistically significant differences for Colorectal and Breast Cancer screenings –No Statistically Significant differences for Prostate Cancer Screening –Strongest Results for the Group/Staff Managed Care Models

Supply or Demand Survey data indicates individuals don’t know the right age cutoffs We know whether people were offered screening services in the 2000 NHIS data –Using the same framework as above we find large statistically significant changes in Offer rates across the relevant age thresholds This indicates that supply side responses drive changes in use over the age thresholds.

Future Work How does Managed Care do it? –Plan Characteristics Health Effects Other treatments with Age Thresholds –Ex. Cholesterol Screening