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Objective: To forecast out-of-pocket health care spending among older adults. Long-term forecasts allow policy makers to explore potential impacts of policy scenarios, but existing microsimulations do not incorporate details of supplemental insurance coverage and income effects on health care spending.Data Sources: Dynamic microsimulation calibrated to survey and administrative data.Study Design: We augment Urban Institute's Dynamic Simulation of Income Model (DYNASIM) with modules that incorporate demand responses and economic equilibria, with dynamics driven by exogenous technological change. A lengthy technical appendix provides details of the microsimulation model and economic assumptions for readers interested in applying these techniques.Principal Findings: The model projects total out-of-pocket spending (point of care plus premiums) as a share of income for adults aged 65 and older. People with lower incomes and poor health fare worse, despite protections of Medicaid. Spending rises 40 percent from 2012 to 2035 (from 10 to 14 percent of income) for the median beneficiary, but it increases from 5 to 25 percent of income for low-income beneficiaries and from 23 to 29 percent for the near poor who are in fair/poor health.Conclusions: Despite Medicare coverage, near-poor seniors will face out-of-pocket spending that would render them, in practical terms, underinsured. [ABSTRACT FROM AUTHOR]

Objective: To study how differences in quality score adjustments across Medicare Advantage contracts change comparisons for individuals and contracts.Data Sources: Responses to the Medicare Advantage implementation of the Consumer Assessments of Healthcare Providers and Systems (CAHPS) survey from 2010 to 2014.Study Design: We fit national-and state-level hierarchical models to predict CAHPS scores for individuals and contracts, adjusted for self-reported education, general health, and mental health. We allow the effects of these variables on quality measures to vary across contracts with a hierarchical model.Data Collection/extraction Methods: We perform secondary data analysis.Principal Findings: For average consumers, standard adjustment is sufficient to represent variation in contract quality standardized to a common population. For people with characteristics far from average, personalized reporting using their characteristics and contract-specific coefficients can substantially change the expected quality measures across contracts. This effect is stronger when comparing among contracts within a state than across all contracts.Conclusions: Customized reporting may help consumers select the best Medicare Advantage plan, but policies should protect against unintended consequences. [ABSTRACT FROM AUTHOR]

Background: Little is known about real-world facility-level preferences for cardiac resynchronization therapy devices with (CRT-D) and without (CRT-P) defibrillator backup. We quantify this variation at the facility level and exploit this variation to compare outcomes of patients receiving these 2 devices.Methods and Results: Claims data from fee-for-service Medicare beneficiaries were used to identify new CRT-P and CRT-D implants, 2006 to 2012. We modeled factors associated with receipt of each device, and compared mortality, hospitalizations, and reoperations for patients receiving each using both logistic regression and instrumental variable analysis to account for confounding. Among 71 459 device recipients (CRT-P, 11 925; CRT-D, 59 534; 31% women), CRT-P recipients were older, more likely to be women, and had more comorbidities. Variation in device selection among facilities was substantial: After adjustment for patient characteristics, the odds of receiving a CRT-P (versus CRT-D) device were 7.6× higher for a patient treated at a facility in the highest CRT-P use quartile versus a facility in the lowest CRT-P use quartile. Logistic modeling suggested a survival advantage for CRT-D devices but with falsification end points indicating residual confounding. By contrast, in the instrumental variable analysis using facility variability as the proposed instrument, clinical characteristics and falsification end points were well balanced, and 1-year mortality in patients who received CRT-P versus CRT-D implants did not differ, while CRT-P patients had a lower probability of hospitalizations and reoperations in the year following implant.Conclusions: CRT-P versus CRT-D selection varies substantially among facilities, adjusted for clinical factors. After instrumental variable adjustment for clinical covariates and facility preference, survival was no different between the devices. Therefore, CRT-P may be preferred for Medicare beneficiaries considering new CRT implantation. [ABSTRACT FROM AUTHOR]