Currently Viewing:
The American Journal of Managed Care January 2017
Alignment of Breast Cancer Screening Guidelines, Accountability Metrics, and Practice Patterns
Tracy Onega, PhD; Jennifer S. Haas, MD; Asaf Bitton, MD; Charles Brackett, MD; Julie Weiss, MS; Martha Goodrich, MS; Kimberly Harris, MPH; Steve Pyle, BS; and Anna N. A. Tosteson, ScD
The Challenge of Paying for Cost-Effective Cures
Patricia J. Zettler, JD, and Erin C. Fuse Brown, JD, MPH
An Expanded Portfolio of Survival Metrics for Assessing Anticancer Agents
Jennifer Karweit, MS; Srividya Kotapati, PharmD; Samuel Wagner, PhD; James W. Shaw, PhD, PharmD, MPH; Steffan W. Wolfe, BA; and Amy P. Abernethy, MD, PhD
The Social Value of Childhood Vaccination in the United States
Tomas J. Philipson, PhD; Julia Thornton Snider, PhD; Ayman Chit, PhD; Sarah Green, BA; Philip Hosbach, BA; Taylor Tinkham Schwartz, MPH; Yanyu Wu, PhD; and Wade M. Aubry, MD
Value-Based Payment in Implementing Evidence-Based Care: The Mental Health Integration Program in Washington State
Yuhua Bao, PhD; Thomas G. McGuire, PhD; Ya-Fen Chan, PhD; Ashley A. Eggman, MS; Andrew M. Ryan, PhD; Martha L. Bruce, PhD, MPH; Harold Alan Pincus, MD; Erin Hafer, MPH; and Jürgen Unützer, MD, MPH, MA
Patient-Centered Care: Turning the Rhetoric Into Reality
Joel S. Weissman, PhD; Michael L. Millenson, BA; and R. Sterling Haring, DO, MPH
Currently Reading
The Effect of Massachusetts Health Reform on Access to Care for Medicaid Beneficiaries
Laura G. Burke, MD, MPH; Thomas C. Tsai, MD, MPH; Jie Zheng, PhD; E. John Orav, PhD; and Ashish K. Jha, MD, MPH
Electronic Health Records and the Frequency of Diagnostic Test Orders
Ibrahim Hakim, BBA; Sejal Hathi, BS; Archana Nair, MS; Trishna Narula, MPH; and Jay Bhattacharya, MD, PhD
An Assessment of the CHIP/Medicaid Quality Measure for ADHD
Justin Blackburn, PhD; David J. Becker, PhD; Michael A. Morrisey, PhD; Meredith L. Kilgore, PhD; Bisakha Sen, PhD; Cathy Caldwell, MPH; and Nir Menachemi, PhD, MPH

The Effect of Massachusetts Health Reform on Access to Care for Medicaid Beneficiaries

Laura G. Burke, MD, MPH; Thomas C. Tsai, MD, MPH; Jie Zheng, PhD; E. John Orav, PhD; and Ashish K. Jha, MD, MPH
Although concerns remain that expanding insurance coverage may have a “crowding-out” effect, we saw no evidence of this for Medicaid beneficiaries in Massachusetts following statewide health reform.
Our analytic sample consisted of 127,532 beneficiaries in Massachusetts with 16,437 inpatient discharges in 2006 and 19,603 inpatient discharges in 2009. Control states had a total of 53,925 beneficiaries, with 9607 inpatient discharges in 2006 and 11,299 inpatient discharges in 2009. The proportion of beneficiaries who met each of the inclusion criteria in each state is presented in eAppendix Table A (eAppendices available at www.ajmc.com). The mean number of inpatient stays per beneficiary was similar across states, with the exception of New Hampshire, which had more than double the rate of admissions per beneficiary in both years in comparison with Massachusetts (0.35 admission per beneficiary in New Hampshire in 2009 vs 0.15 admission per beneficiary in Massachusetts). The demographic sample characteristics of our sample population of Medicaid beneficiaries in Massachusetts and control states are presented in Table 1.

Overall, Massachusetts had a higher percentage of white Medicaid beneficiaries relative to control states before health reform (53.8% vs 51.4%; P <.0001). The median age was slightly, but statistically, higher in Massachusetts than in control states (39.1 vs 38.2 years; P <.0001). The proportion of male beneficiaries was 30.3% in Massachusetts and 25.1% in control states (P <.0001). Massachusetts and control states differed with respect to the proportion of beneficiaries in each eligibility category. Massachusetts had a greater proportion of disabled beneficiaries (40.4% vs 35.2%; P <.0001) and of beneficiaries in the “other” category (41.0% vs 9.8%), which included primarily adults gaining coverage through Medicaid expansion waivers. Massachusetts had a lower proportion of beneficiaries (18.6% vs 55.0%) gaining coverage through the traditional “adult” eligibility categories (adult, adult poverty, unemployed adult). Mean total physician supply was 4.55 per 1000 population in Massachusetts and 3.36 per 1000 population in control states.

Preventable Hospitalization Rates in Massachusetts and Control States

We report unadjusted rates of PQIs by state in the pre- and postreform periods (eAppendix Table B). Massachusetts had a lower unadjusted rate of PQIs relative to control states in both years. Both Massachusetts and control states had increases in unadjusted rates of overall, acute, and chronic PQIs during the study period (Figure and eAppendix Table B). When we adjusted for age, race, gender, reason for eligibility, and physician supply, this increase persisted for overall and chronic PQIs in both Massachusetts and the control group of states, with no significant difference in the relative increase between the 2 groups for any of the PQI measures (Table 2). For example, among overall PQIs, Massachusetts had an increase of 73.6 admissions per 100,000 beneficiaries (from 557.4 to 631.0; P = .0049) whereas control states had an increase of 182.1 admissions per 100,000 beneficiaries (from 812.6 to 994.7; P = .0003). For chronic PQIs, the increases in Massachusetts and control states were 50.9 (from 314.6 to 365.6; P = .01) and 147.2 (from 501.7 to 649.0; P = .0002) admissions per 100,000 beneficiaries, respectively. There were no significant changes after health reform in the rate of acute PQIs in either Massachusetts or control states. There were no significant differences between Massachusetts and control states in the relative change between the 2 groups on any of the PQI measures using Poisson regression analysis (Table 2).

For control conditions, control states saw a trend toward an increase (59.3 admissions, from 359.7 to 419.1; P = .06) whereas Massachusetts saw a decrease (–19.1 admissions, from 305.2 to 286.1; P = .25), but it was not significant. The DID (–78.4; 95% CI, –148.1 to –8.8) was significant at P = .02. When we repeated the analyses using linear regression, the relative increase in PQIs was greater in control states than in Massachusetts for overall and chronic PQIs. For control conditions, Massachusetts saw a significant decrease, whereas control states saw a significant increase, with a significant DID between the two (eAppendix Table C).

 

Preventable Hospitalization Rates Within Massachusetts


We performed an analysis comparing PQI rates before and after health reform among counties in Massachusetts with a baseline insurance rate that was below the median (high-uptake counties) with those with a pre-reform insurance rate above the median (low-uptake counties) (Table 3). Prior studies have found that counties with the lowest rates of health insurance at baseline had, unsurprisingly, the greatest new uptake of health insurance; therefore, we hypothesized, they would have the largest crowding-out effect. We found that both high- and low-uptake Massachusetts counties experienced an increase in overall PQIs with no significant differences in the rate of change between the 2 groups (+97.3 vs +157.0 admissions per 100,000 beneficiaries, respectively; P = .42 for DID). Only high-uptake counties saw a significant increase in acute PQIs (+62.8 admissions per 100,000 beneficiaries; P = .03), but there was again no significant difference in the trend observed between the 2 groups (P = .16 for DID). For chronic PQIs, low-uptake counties had a significant increase that was greater than that observed for high-uptake counties (+148.0 vs +36.0; P = .045 for DID).

When we examined admissions for control conditions in high- and low-uptake counties (Table 3), overall admissions for control conditions decreased only in high-uptake counties (–56.4 admissions per 100,000 beneficiaries), but there was no significant differential change between the 2 groups (P = .16 for DID). A linear regression model produced similar findings (eAppendix Table D).

Preventable Hospitalization Rates by Race

Finally, because PQI rates differ by race, we looked specifically at rates of PQIs for African American beneficiaries in Massachusetts and in control states (Table 4). For overall and chronic PQIs, Massachusetts and control states saw a significant increase. For overall PQIs, Massachusetts had an increase of 156.1 PQI admissions per 100,000 beneficiaries (from 575.2 to 731.3; P = .002), and control states had an increase of 445.5 PQI admissions per 100,000 beneficiaries (from 963.5 to 1409.0; P =.002). For chronic PQIs, Massachusetts saw a significant increase of 117.4 PQIs per 100,000 beneficiaries (from 355.8 to 473.2; P = .025), and control states saw an increase of 339.1 PQIs per 100,000 beneficiaries (from 689.9 to 1029.1; P = .004). For acute PQIs, neither Massachusetts nor control states had a significant increase in PQIs for African American beneficiaries. We found no significant DID between Massachusetts and control states in any admission rates (PQI or control conditions) for African American beneficiaries following Massachusetts health reform, using either Poisson regression (Table 4) or linear regression.

DISCUSSION

In our study of Medicaid beneficiaries, Massachusetts, relative to control states, saw no increase in preventable admissions following health insurance expansion. When we stratified counties within Massachusetts by their rates of insurance uptake, high-uptake counties saw no greater increase in PQIs relative to low-uptake counties. Finally, when we looked at PQI rates for African Americans, we saw no differential change between Massachusetts and control New England states. Taken together, our findings suggest that there was no evidence of crowd-out in access to primary care for Medicaid beneficiaries as a result of Medicaid expansion from Massachusetts health reform.

Massachusetts health reform is a model for national health insurance expansion, a key component of which is Medicaid expansion in many states. Although insurance expansion has clear benefits for the newly insured, one persistent concern has been that reform efforts could jeopardize the care of individuals with existing health insurance and provider relationships via a crowd-out effect. Yet, we found no evidence of impaired primary care access among Medicaid beneficiaries who traditionally have had the greatest barriers to obtaining care. Our sample of beneficiaries in Massachusetts did have an increase in PQIs, but this trend was also seen in control states that did not undergo health reform during this time period.

We hypothesized that those counties with the lowest baseline rates of health insurance (ie, those with the greatest new uptake) would experience the largest impact of health insurance expansion and would be most likely to experience any negative spillover effect. Although these high-uptake counties did have increases in preventable admissions overall and for acute conditions, they did not experience a differential increase relative to low-uptake counties. In fact, for chronic PQIs, high-uptake counties saw less of an increase than low-uptake counties. These results suggest that the healthcare infrastructure in these communities was able to accommodate the increased demand for services associated with insurance expansion.

Our study complements the findings of previous work indicating that Massachusetts health reform had no adverse effects on preventable admissions among the Medicare population.6,7 This lack of observable deleterious effects among the elderly served as initial evidence that fears of a negative spillover effect of insurance expansion may be unfounded. However, Medicaid beneficiaries are thought to have even greater barriers to care because of historically low reimbursement rates. Now, the lack of an observable negative spillover effect in 2 separate vulnerable populations, Medicare and Medicaid beneficiaries, suggests that Massachusetts health reform did not result in clinically significant decrements in access to high-quality care for the previously insured. This should be reassuring for policy makers.

Although there may not have been a large, overall negative impact of health reform on access for those previously insured, one worries that certain particularly vulnerable populations, such as racial minorities, might have been affected. We found that Massachusetts—relative to other New England control states—did not have a differential change in preventable admissions for African Americans. However, African Americans continued to have higher PQIs than the overall population across both Massachusetts and control states, suggesting that we need to continue to focus on reducing disparities.

 
Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up