sábado, 22 de junio de 2013

The Oregon Experiment — Effects of Medicaid on Clinical Outcomes — NEJM

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The Oregon Experiment — Effects of Medicaid on Clinical Outcomes — NEJM

Special Article

The Oregon Experiment — Effects of Medicaid on Clinical Outcomes

Katherine Baicker, Ph.D., Sarah L. Taubman, Sc.D., Heidi L. Allen, Ph.D., Mira Bernstein, Ph.D., Jonathan H. Gruber, Ph.D., Joseph P. Newhouse, Ph.D., Eric C. Schneider, M.D., Bill J. Wright, Ph.D., Alan M. Zaslavsky, Ph.D., and Amy N. Finkelstein, Ph.D. for the Oregon Health Study Group
N Engl J Med 2013; 368:1713-1722May 2, 2013DOI: 10.1056/NEJMsa1212321
Citing Articles (1)
In 2008, Oregon initiated a limited expansion of its Medicaid program for low-income adults through a lottery drawing of approximately 30,000 names from a waiting list of almost 90,000 persons. Selected adults won the opportunity to apply for Medicaid and to enroll if they met eligibility requirements. This lottery presented an opportunity to study the effects of Medicaid with the use of random assignment. Earlier, nonrandomized studies sought to investigate the effect of Medicaid on health outcomes in adults with the use of quasi-experimental approaches.1-3 Although these approaches can be an improvement over observational designs and often involve larger samples than are feasible with a randomized design, they cannot eliminate confounding factors as effectively as random assignment. We used the random assignment embedded in the Oregon Medicaid lottery to examine the effects of insurance coverage on health care use and health outcomes after approximately 2 years.


Randomization and Intervention

Oregon Health Plan Standard is a Medicaid program for low-income, uninsured, able-bodied adults who are not eligible for other public insurance in Oregon (e.g., Medicare for persons 65 years of age or older and for disabled persons; the Children's Health Insurance Program for poor children; or Medicaid for poor children, pregnant women, or other specific, categorically eligible populations). Oregon Health Plan Standard closed to new enrollment in 2004, but the state opened a new waiting list in early 2008 and then conducted eight random lottery drawings from the list between March and September of that year to allocate a limited number of spots. Persons who were selected won the opportunity — for themselves and any household member — to apply for Oregon Health Plan Standard. To be eligible, persons had to be 19 to 64 years of age and Oregon residents who were U.S. citizens or legal immigrants; they had to be ineligible for other public insurance and uninsured for the previous 6 months, with an income that was below 100% of the federal poverty level and assets of less than $2,000. Persons who were randomly selected in the lottery were sent an application. Those who completed it and met the eligibility criteria were enrolled in the plan. Oregon Health Plan Standard provides comprehensive medical benefits, including prescription drugs, with no patient cost-sharing and low monthly premiums ($0 to $20, based on income), mostly through managed-care organizations. The lottery process and Oregon Health Plan Standard are described in more detail elsewhere.4

Data Collection

We used an in-person data-collection protocol to assess a wide variety of outcomes. We limited data collection to the Portland, Oregon, metropolitan area because of logistical constraints. Our study population included 20,745 people: 10,405 selected in the lottery (the lottery winners) and 10,340 not selected (the control group). We conducted interviews between September 2009 and December 2010. The interviews took place an average of 25 months after the lottery began. Our data-collection protocol included detailed questionnaires on health care, health status, and insurance coverage; an inventory of medications; and performance of anthropometric and blood-pressure measurements. Dried blood spots were also obtained.5 Depression was assessed with the use of the eight-question version of the Patient Health Questionnaire (PHQ-8),6 and self-reported health-related quality of life was assessed with the use of the Medical Outcomes Study 8-Item Short-Form Survey.7 More information on recruitment and field-collection protocols are included in the study protocol (available with the full text of this article at NEJM.org); more information on specific outcome measures is provided in the Supplementary Appendix (available at NEJM.org). Multiple institutional review boards approved the study, and written informed consent was obtained from all participants.

Statistical Analysis

Virtually all the analyses reported here were prespecified and publicly archived (see the protocol).8 Prespecification was designed to minimize issues of data and specification mining and to provide a record of the full set of planned analyses. The results of a few additional post hoc analyses are also presented and are noted as such in Tables 1 through 5. Analyses were performed with the use of Stata software, version 12.9 Adults randomly selected in the lottery were given the option to apply for Medicaid, but not all persons selected by the lottery enrolled in Medicaid (either because they did not apply or because they were deemed ineligible). Lottery selection increased the probability of Medicaid coverage during our study period by 24.1 percentage points (95% confidence interval [CI], 22.3 to 25.9; P<0 .001="" 0.25="" 1="" 25="" 4="" a="" able="" about="" affected="" and="" apply="" approach="" as="" assumed="" being="" by="" causal="" chance="" changing="" class="ref" comparable="" coverage.="" coverage="" did="" divided="" effect="" enrolled="" enrollment="" estimate="" for="" group="" high="" i.e.="" in="" increased="" instrument="" instrumental-variable="" insurance="" intuitively="" lottery.="" lottery="" medicaid.="" medicaid="" not="" of="" only="" outcomes="" overall="" percentage="" persons="" points="" selection="" simply="" since="" span="" standard="" subgroup="" that="" the="" therefore="" this="" times="" to="" ultimately="" used="" was="" we="" which="" who="" win="" winners="" yielded="">10
(See the Supplementary Appendix for additional details.) All analyses were adjusted for the number of household members on the lottery list because selection was random, conditional on household size. Standard errors were clustered according to household to account for intrahousehold correlation. We fitted linear probability models for binary outcomes. As sensitivity checks, we showed that our results were robust when the average marginal effects from logistic regressions for binary outcomes were estimated and when demographic characteristics were included as covariates (see the Supplementary Appendix). All analyses were weighted for the sampling and field-collection design; construction of the weights is detailed in the Supplementary Appendix.


Study Population

Characteristics of the respondents are shown in Table 1Table 1Characteristics of the 12,229 Survey Respondents.. A total of 12,229 persons in the study sample responded to the survey, for an effective response rate of 73%. There were no significant differences between those selected in the lottery and those not selected with respect to the response rates to either the full survey (0.28 percentage points higher in the group selected in the lottery, P=0.86) or specific survey measures, each of which had a response rate of at least 97% among people who completed any part of the survey. Just over half the participants were women, about a quarter were 50 to 64 years of age (the oldest eligible age group), and about 70% were non-Hispanic white. There were no significant differences between those selected in the lottery and those not selected with respect to these characteristics (F statistic, 0.20; P=0.99) or to the wide variety of prerandomization and interview characteristics examined (see the Supplementary Appendix).

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