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The article reflects on advancements and services offered by the periodical since 50 years. It mentions a section of special issue that was drawn on by doctoral training programs in health services research and health policy analysis. It also highlights the challenges faced by the medical journal editors and efforts to tackle head on the issue of authorship.

Objective: To examine state and community factors that contributed to geographic variation in qualified health plan selection during the first open enrollment period.Data Sources/study Setting: Administrative data on qualified health plan selections at the ZIP code area merged with survey estimates from the American Community Survey.Study Design: Descriptive and regression analyses.Data Collection/extraction Methods: Data were generated by healthcare.gov and from a household survey.Principal Findings: Thirty-one percent of the variation in qualified health plan selection ratios resulted from between-state differences, and the rest was driven by local area differences. Education, language, age, gender, and the ethnic composition of communities contributed to disparate levels of plan selection. Medicaid expansion states had a qualified health plan selection ratio that was 4.4 points lower than non-Medicaid expansion states, controlling for covariates.Conclusions: Our results suggest community-level differences in the intensity or receptiveness to outreach and enrollment activities during the first open enrollment period. [ABSTRACT FROM AUTHOR]

Background: Extensive evidence documents geographic variation in spending, but limited research assesses geographic variation in quality, particularly among commercially insured enrollees.Objective: To measure geographic variation in quality measures, correlation among measures, and correlation between measures and spending for commercially insured enrollees.Data Source: Administrative claims from the 2007-2009 Truven MarketScan database.Methods: We calculated variation in, and correlations among, 10 quality measures across 306 Hospital Referral Regions (HRRs), adjusting for beneficiary traits and sample size differences. Further, we created a quality index and correlated it with spending.Results: The coefficient of variation of HRR-level performance ranged from 0.04 to 0.38. Correlations among quality measures generally ranged from 0.2 to 0.5. Quality was modestly positively related to spending.Conclusion: Quality varied across HRRs and there was only a modest geographic "quality footprint." [ABSTRACT FROM AUTHOR]

Objective: To examine the relative influence of hospital and skilled nursing facilities (SNFs) on 30-day rehospitalization.Data Sources/settings: Elderly Medicare beneficiaries newly admitted to a SNF following hospitalization.Study Design: We ranked hospitals and SNFs into quartiles based on previous years' adjusted rehospitalization rates (ARRs) and examined how rehospitalizations from a given hospital vary depending upon the admitting SNF ARR quartile. We examined whether the availability of SNFs with low rehospitalization rates influenced hospitals' SNF readmission rates and whether changes in a hospital's ARR over 3 years is associated with changes in the SNFs to which they discharge.Principal Findings: Hospital readmission rates from SNFs varied 5 percentage points between patients discharged to SNFs in the lowest and the highest rehospitalization quartiles. Low rehospitalization rate hospitals sent a larger fraction of their patients to the lowest rehospitalization SNFs available in the area. A 10 percent increase in hospital's share of discharges to the lowest rehospitalization quartile SNFs is associated with a 1 percentage point reduction in hospital's ARR.Conclusions: The SNF rehospitalization rate has greater influence on patients' risk of rehospitalization than the discharging hospital. Identifying high-performing SNFs may be a powerful strategy for hospitals to reduce rehospitalizations. [ABSTRACT FROM AUTHOR]

Objective: To examine the influence of physician and hospital market structures on medical technology diffusion, studying the diffusion of drug-eluting stents (DESs), which became available in April 2003.Data Sources/study Setting: Medicare claims linked to physician demographic data from the American Medical Association and to hospital characteristics from the American Hospital Association Survey.Study Design: Retrospective claims data analyses.Data Collection/extraction Methods: All fee-for-service Medicare beneficiaries who received a percutaneous coronary intervention (PCI) with a cardiac stent in 2003 or 2004. Each PCI record was joined to characteristics on the patient, the procedure, the cardiologist, and the hospital where the PCI was delivered. We accounted for the endogeneity of physician and hospital market structure using exogenous variation in the distances between patient, physician, and hospital locations. We estimated multivariate linear probability models that related the use of a DES in the PCI on market structure while controlling for patient, physician, and hospital characteristics.Principal Findings: DESs diffused faster in markets where cardiology practices faced more competition. Conversely, we found no evidence that the structure of the hospital market mattered.Conclusions: Competitive pressure to maintain or expand PCI volume shares compelled cardiologists to adopt DESs more quickly. [ABSTRACT FROM AUTHOR]

Objective: To measure variation in payment rates under Medicare's Inpatient Prospective Payment System (IPPS) and identify the main payment adjustments that drive variation.Data Sources/study Setting: Medicare cost reports for all Medicare-certified hospitals, 1987-2013, and Dartmouth Atlas geographic files.Study Design: We measure the Medicare payment rate as a hospital's total acute inpatient Medicare Part A payment, divided by the standard IPPS payment for its geographic area. We assess variation using several measures, both within local markets and nationally. We perform a factor decomposition to identify the share of variation attributable to specific adjustments. We also describe the characteristics of hospitals receiving different payment rates and evaluate changes in the magnitude of the main adjustments over time.Data Collection/extraction Methods: Data downloaded from the Centers for Medicare and Medicaid Services, the National Bureau of Economic Research, and the Dartmouth Atlas.Principal Findings: In 2013, Medicare paid for acute inpatient discharges at a rate 31 percent above the IPPS base. For the top 10 percent of discharges, the mean rate was double the IPPS base. Variations were driven by adjustments for medical education and care to low-income populations. The magnitude of variation has increased over time.Conclusions: Adjustments are a large and growing share of Medicare hospital payments, and they create significant variation in payment rates. [ABSTRACT FROM AUTHOR]

Objective: To explore the influence of varying degrees of remoteness on practice-level electronic medical record (EMR) adoption, including whether the effect differs across practice specialty.Data Sources: Survey data on over 270,000 office-based physician practices (representing over 1,250,000 providers) collected by SK&A information services during 2012.Study Design: This study examined differences in EMR adoption by practices located across the nine-category rural-urban continuum. Logistic regressions and associated marginal effects are used to assess how much a move up or down the rural-urban continuum code impacts the likelihood of EMR adoption, after controlling for characteristics likely to affect EMR adoption such as practice size and specialty.Principal Findings: Overall practice-level EMR adoption rates generally increase with the degree of rurality and range from 47 percent in the most urban counties to over 60 percent in the most rural. Moving from the most urban county to the most rural corresponded to a 7 percent increase in the likelihood of EMR adoption (p < .01).Conclusions: EMR adoption rates do vary significantly across nonmetropolitan counties, and they generally increase as a practice becomes more rural. From a policy perspective, this suggests that urban practices may in fact be the lowest hanging remaining fruit for increasing EMR adoption rates. [ABSTRACT FROM AUTHOR]

Objective: This study examines nurse-related clinical nonlicensed personnel (CNLP) in U.S. hospitals between 2010 and 2014, including job categories, trends in staffing levels, and the possible relationship of substitution between this group of workers and registered nurses (RNs) and/or licensed practical nurses (LPNs).Data Source: We used 5 years of data (2010-2014) from an operational database maintained by Premier, Inc. that tracks labor hours, hospital units, and facility characteristics.Study Design: We assessed changes over time in the average number of total hours worked by RNs, LPNs, and CNLP, adjusted by total patient days. We then conducted linear regressions to estimate the relationships between nurse and CNLP staffing, controlling for patient acuity, volume, and hospital fixed effects.Principal Findings: The overall use of CNLP and LPN hours per patient day declined from 2010 to 2014, while RN hours per patient day remained stable. We found no evidence of substitution between CNLP and nurses during the study period: Nurse-related CNLP hours were positively associated with RN hours and not significantly related to LPN hours, holding other factors constant.Conclusions: Findings point to the importance of examining where and why CNLP hours per patient day have declined and to understanding of the effects of these changes on outcomes. [ABSTRACT FROM AUTHOR]

Objective: To identify and describe new roles for medical assistants (MAs) in innovative care models that improve care while providing training and career advancement opportunities for MAs.Data Sources/study Setting: Primary data collected at 15 case study sites; 173 key informant interviews and de-identified secondary data on staffing, wages, patient satisfaction, and health outcomes.Study Design: Researchers used snowball sampling and screening calls to identify 15 organizations using MAs in new roles. Conducted site visits from 2010 to 2012 and updated information in 2014.Data Collection/extraction Methods: Thematic analysis explored key topics: factors driving MA role innovation, role description, training required, and wage gains. Categorized outcome data in patient and staff satisfaction, quality of care, and efficiency.Principal Findings: New MA roles included health coach, medical scribe, dual role translator, health navigator, panel manager, cross-trained flexible role, and supervisor. Implementation of new roles required extensive training. MA incentives and enhanced compensation varied by role type.Conclusions: New MA roles are part of a larger attempt to reform workflow and relieve primary care providers. Despite some evidence of success, spread has been limited. Key challenges to adoption included leadership and provider resistance to change, cost of additional MA training, and lack of reimbursement for nonbillable services. [ABSTRACT FROM AUTHOR]

Objective: To describe the distribution of Veterans in areas of the United States where there are potentially inadequate supplies of health professionals, and to explore opportunities suggested by this distribution for fostering health workforce flexibility.Data Sources: County-level data from the 2015-2016 Health Resources and Services Administration's (HRSA's) Area Health Resources Files (AHRF) were used to estimate Veteran populations in HRSA-designated health professional shortage areas (HPSAs). This information was then linked to 2015 VA health facility information from the Department of Veterans Affairs.Study Design: Potential Veteran populations living in Shortage Area Counties with no VHA facilities were estimated, and the composition of these populations was explored by Census division and state.Principal Findings: Nationwide, approximately 24 percent of all Veterans and 23 percent of Veterans enrolled in VHA health care live in Shortage Area Counties. These estimates mask considerable variation across states.Conclusions: An examination of Veterans residing in Shortage Area Counties suggests extensive maldistribution of health services across the United States and the continued need to find ways to improve health care access for all Veterans. Effective avenues for doing so may include increasing health workforce flexibility through expansion of nurse practitioner scopes of practice. [ABSTRACT FROM AUTHOR]

Objective: To assess how medical staffing mix changed over time in association with the adoption of electronic health records (EHRs) in community health centers (CHCs).Study Setting: Community health centers within the 50 states and Washington, DC.Study Design: Estimated how the change in the share of total medical staff full-time equivalents (FTE) by provider category between 2007 and 2013 was associated with EHR adoption using fractional multinomial logit.Data Collection: 2007-2013 Uniform Data System, an administrative data set of Section 330 federal grant recipients; and Readiness for Meaningful Use and HIT and Patient Centered Medical Home Recognition Survey responses collected from Section 330 recipients between December 2010 and February 2011.Principal Findings: Having an EHR system did significantly shift the share of workers over time between physicians and each of the other categories of health care workers. While an EHR system significantly shifted the share of physician and other medical staff, this effect did not significantly vary over time. CHCs with EHRs by the end of the study period had a relatively greater proportion of other medical staff compared to the proportion of physicians.Conclusions: Electronic health records appeared to influence staffing allocation in CHCs such that other medical staff may be used to support adoption of EHRs as well as be leveraged as an important care provider. [ABSTRACT FROM AUTHOR]

Objective: To understand factors affecting specialty heterogeneity in physician migration.Data Sources/study Setting: Physicians in the 2009 American Medical Association Masterfile data were matched to those in the 2013 file. Office locations were geocoded in both years to one of 293 areas of the country. Estimated utilization, calculated for each specialty, was used as the primary predictor of migration. Physician characteristics (e.g., specialty, age, sex) were obtained from the 2009 file. Area characteristics and other factors influencing physician migration (e.g., rurality, presence of teaching hospital) were obtained from various sources.Study Design: We modeled physician location decisions as a two-part process: First, the physician decides whether to move. Second, conditional on moving, a conditional logit model estimates the probability a physician moved to a particular area. Separate models were estimated by specialty and whether the physician was a resident.Principal Findings: Results differed between specialties and according to whether the physician was a resident in 2009, indicating heterogeneity in responsiveness to policies. Physician migration was higher between geographically proximate states with higher utilization for that specialty.Conclusions: Models can be used to estimate specialty-specific migration patterns for more accurate workforce modeling, including simulations to model the effect of policy changes. [ABSTRACT FROM AUTHOR]

Objective: The median time required to perform a surgical procedure is important in determining payment under Medicare's physician fee schedule. Prior studies have demonstrated that the current methodology of using physician surveys to determine surgical times results in overstated times. To measure surgical times more accurately, we developed and validated a methodology using available data from anesthesia billing data and operating room (OR) records.Data Sources: We estimated surgical times using Medicare 2011 anesthesia claims and New York Statewide Planning and Research Cooperative System 2011 OR times. Estimated times were validated using data from the National Surgical Quality Improvement Program. We compared our time estimates to those used by Medicare in the fee schedule.Study Design: We estimate surgical times via piecewise linear median regression models.Principal Findings: Using 3.0 million observations of anesthesia and OR times, we estimated surgical time for 921 procedures. Correlation between these time estimates and directly measured surgical time from the validation database was 0.98. Our estimates of surgical time were shorter than the Medicare fee schedule estimates for 78 percent of procedures.Conclusions: Anesthesia and OR times can be used to measure surgical time and thereby improve the payment for surgical procedures in the Medicare fee schedule. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effects of state insurance mandates requiring insurance plans to cover Pap tests, the standard screening for cervical cancer that is recommended for nearly all adult women.Data Sources: Individual-level data on 600,000 women age 19-64 from the CDC's Behavioral Risk Factor Surveillance System.Study Design: Twenty-four states adopted state mandates requiring private insurers in the state to cover Pap tests from 1988 to 2000. We performed a difference-in-differences analysis comparing within-state changes in Pap test rates before and after adoption of a mandate, controlling for the associated changes in other states that did not adopt a mandate.Principal Findings: Difference-in-differences estimates indicated that the Pap test mandates significantly increased past 2-year cervical cancer screenings by 1.3 percentage points, with larger effects for Hispanic and non-Hispanic white women. These effects are plausibly concentrated among insured women.Conclusions: Mandating more generous insurance coverage for even inexpensive, routine services with already high utilization rates such as Pap tests can significantly further increase utilization. [ABSTRACT FROM AUTHOR]

Objective: To examine the role of patient, hospital, and community characteristics on racial and ethnic disparities in in-hospital postsurgical complications.Data Sources: Healthcare Cost and Utilization Project, 2011 State Inpatient Databases; American Hospital Association Annual Survey of Hospitals; Area Health Resources Files; Centers for Medicare & Medicaid Services Hospital Compare database.Methods: Nonlinear hierarchical modeling was conducted to examine the odds of patients experiencing any in-hospital postsurgical complication, as defined by Agency for Healthcare Research and Quality Patient Safety Indicators.Principal Findings: A total of 5,474,067 inpatient surgical discharges were assessed using multivariable logistic regression. Clinical risk, payer coverage, and community-level characteristics (especially income) completely attenuated the effect of race on the odds of postsurgical complications. Patients without private insurance were 30 to 50 percent more likely to have a complication; patients from low-income communities were nearly 12 percent more likely to experience a complication. Private, not-for-profit hospitals in small metropolitan or micropolitan areas and higher nurse-to-patient ratios led to fewer postsurgical complications.Conclusions: Race does not appear to be an important determinant of in-hospital postsurgical complications, but insurance and community characteristics have an effect. A population-based approach that includes improving the socioeconomic context may help reduce disparities in these outcomes. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between distance to dialysis provider and patient selection of dialysis modality, informed by the absolute distance from a patient's home and relative distance of alternative modalities.Data Sources: U.S. Renal Data System.Study Design: About 70,131 patients initiating chronic dialysis and 4,795 dialysis facilities in 2006. The primary outcome was patient utilization of peritoneal dialysis (PD). Independent variables included absolute distance between patients' home and the nearest hemodialysis (HD) facility, relative distance between patients' home and nearest PD versus nearest HD facilities, and their interaction. Logistic regression was used to model distance on PD use, controlling for patient and market characteristics.Principal Findings: Nine percent of incident dialysis patients used PD in 2006. There was a positive, nonlinear relationship between absolute distance to HD services and PD use (p < .0001), with the magnitude of the effect increasing at greater distances. In terms of relative distance, odds of PD use increased if a PD facility was closer or the same distance as the nearest HD facility (p = .006). Interaction of distance measures to dialysis facilities was not significant.Conclusions: Analyses of patient choice between alternative treatments should model distance to reflect all relevant dimensions of geographic access to treatment options. [ABSTRACT FROM AUTHOR]

Objectives: To estimate (1) family-centered care (FCC) and shared decision-making (SDM) prevalence, and (2) associations of FCC and SDM (FCC/SDM) with health care outcomes among U.S. children.Data Source: The Medical Expenditure Panel Survey Household Component (MEPS-HC), a nationally representative survey of the noninstitutionalized, civilian population.Study Design: Secondary analyses of prospectively collected data on 15,764 U.S. children were conducted to examine FCC/SDM prevalence in year 1 and associations of FCC/SDM in year 1 with health services utilization, medical expenditures, and unmet health care needs in year 2.Data Collection/extraction Methods: We combined four MEPS-HC longitudinal files from 2007 to 2011.Principal Findings: FCC/SDM prevalence in year 1 varied from 38.6 to 93.7 percent, and it was lower for composites with more stringent scoring approaches. FCC/SDM composites with stringent scoring approaches in year 1 were associated with reduced unmet needs in year 2. FCC/SDM, across all year 1 composites, was not associated with health services utilization or medical expenditures in year 2. FCC/SDM year 1 subcomponents describing consensus building and mutual agreement were consistently associated with unmet health care needs in year 2.Conclusions: FCC/SDM composites with stringent scoring approaches measuring consensus building and mutual agreement may have the greatest utility for pediatric health care quality improvement efforts. [ABSTRACT FROM AUTHOR]

Objective To identify roles physicians assumed as part of new health care delivery models and related strategies that facilitated physician engagement across 21 Health Care Innovation Award ( HCIA) programs. Data Sources Site-level in-depth interviews, conducted from 2014 to 2015 ( N = 672) with program staff, leadership, and partners (including 95 physicians) and direct observations. Study Design NORC conducted a mixed-method evaluation, including two rounds of qualitative data collected via site visits and telephone interviews. Data Collection/Extraction Methods We used qualitative thematic coding for data from 21 programs actively engaging physicians as part of HCIA interventions. Principal Findings Establishing physician champions and ensuring an innovation-values fit between physicians and programs, including the strategies programs employed, facilitated engagement. Among engagement practices identified in this study, tailoring team working styles to meet physician preferences and conducting physician outreach and education were the most common successful approaches. Conclusions We describe engagement strategies derived from a diverse range of programs. Successful programs considered physicians' values and engagement as components of process and policy, rather than viewing them as exogenous factors affecting innovation adoption. These types of approaches enabled programs to accelerate acceptance of innovations within organizations. [ABSTRACT FROM AUTHOR]

Objective: To identify lessons learned from the experience of the Agency for Healthcare Research and Quality (AHRQ) Patient Safety and Medical Liability (PSML) Demonstration Program.Data Sources/study Setting: On September 9, 2009, President Obama directed the Secretary of Health and Human Services to authorize demonstration projects that put "patient safety first" with the intent of reducing preventable adverse outcomes and stemming liability costs. Seven demonstration projects received 3 years of funding from AHRQ in the summer of 2010, and the program formally came to a close in June 2015.Study Design: The seven grantees implemented complex, broad-ranging innovations addressing both patient safety and medical liability in "real-world" contexts. Some projects featured novel approaches, while others implemented adaptations of existing models. Each project was funded by AHRQ to collect data on the impact of its interventions. In addition, AHRQ funded a cross-cutting qualitative evaluation focused on lessons learned in implementing PSML interventions.Data Collection/extraction Methods: Site visits and follow-up interviews supplemented with material abstracted from formal project reports to AHRQ.Principal Findings: The PSML demonstration projects focused on three broad approaches: (1) improving communication around adverse events through disclosure and resolution programs; (2) preventing harm through implementation of clinical "best practices"; and (3) exploring alternative methods of settling claims. Although the demonstration contributed to accumulating evidence that these kinds of interventions can positively affect outcomes, there is also evidence to suggest that these interventions can be difficult to scale.Conclusions: In addition to producing at least preliminary positive outcomes, the demonstration also lends credence to the idea that targeted interventions that improve some aspect of patient safety or malpractice performance may also contribute more broadly to institutional culture and the alignment of all parties around reducing risk and preventing harm. However, more empirical work needs to be carried out to quantify the effect of such interventions. [ABSTRACT FROM AUTHOR]

Objective: To explore predictors of gaps between observed and best possible Hospital Compare scores in U.S. hospitals.Data Sources: American Hospital Association Annual Survey; Area Resource Files; Centers for Medicare and Medicaid Services Medicare Provider and Analysis Review; and Hospital Compare data.Study Design: Using Stochastic Frontier Analysis and secondary cross-sectional data, gaps between the best possible and actual scores of Hospital Compare quality measures were estimated. Poisson regressions were used to ascertain financial, organizational, and market predictors of those gaps.Data Extraction: Data were cleaned and matched based on hospital Medicare IDs. All U.S. hospitals that matched on analysis variables in 2007 were in the study (1,823-2,747, depending upon gap variable).Principal Findings: Most hospitals have a greater than 10 percent gap in quality indicators. Payer mix, registered nurse staffing, size, case mix index, accreditation, being a teaching hospital, market competition, urban location, and region were strong predictors of gaps, although the direction of the association with gaps was not uniform across outcomes.Conclusions: A significant percentage of hospitals have gaps between their best possible and observed quality scores. It may be better to use gap scores than observed scores in payments systems. More SFA research is needed to know how to lower gaps through changes in hospital and market characteristics. [ABSTRACT FROM AUTHOR]

Objective: To profile the sick leave landscape in the United States.Data Sources: The 2011 Leave Supplement of the American Time Use Survey.Study Design: Bivariate and multivariate analyses to identify (i) employees without sick pay coverage and (ii) employees who attend work sick.Principal Findings: Sixty-five percent of full-time employees have sick pay coverage. Coverage rates are below 20 percent for employees with hourly wages below $10, part-time employees, and employees in the hospitality and leisure industry.Conclusion: Each week, up to 3 million U.S. employees go to work sick. Females, low-income earners, and those aged 25 to 34 years have a significantly elevated risk of presenteeism behavior. [ABSTRACT FROM AUTHOR]

Objectives: To test whether a care management program could replicate its success in an earlier trial and determine likely explanations for why it did not.Data Sources/setting: Medicare claims and nurse contact data for Medicare fee-for-service beneficiaries with chronic illnesses enrolled in the trial in eastern Pennsylvania (N = 483).Study Design: A randomized trial with half of enrollees receiving intensive care management services and half receiving usual care. We developed and tested hypotheses for why impacts declined.Data Extraction: All outcomes and covariates were derived from claims and the nurse contact data.Principal Findings: From 2010 to 2014, the program did not reduce hospitalizations or generate Medicare savings to offset program fees that averaged $260 per beneficiary per month. These estimates are statistically different (p < .05) from the large reductions in hospitalizations and spending in the first trial (2002-2010). The treatment-control differences in the second trial disappeared because the control group's risk-adjusted hospitalization rate improved, not because the treatment group's outcomes worsened.Conclusion: Even if demonstrated in a randomized trial, successful results from one test may not replicate in other settings or time periods. Assessing whether gaps in care that the original program filled exist in other settings can help identify where earlier success is likely to replicate. [ABSTRACT FROM AUTHOR]

Objective: To determine associations between need, enabling, and predisposing factors with mental health service use among National Guard soldiers in the first year following a combat deployment to Iraq or Afghanistan.Data Sources/study Setting: Primary data were collected between 2011 and 2013 from 1,426 Guard soldiers representing 36 units.Study Design: Associations between Guard soldier factors and any mental health service use were assessed using multivariable logistic regression models in a cross-sectional study. Further analysis among service users (N = 405) assessed VA treatment versus treatment in other settings.Principal Findings: Fifty-six percent of Guard soldiers meeting cutoffs on symptom scales received mental health services with 81 percent of those reporting care from the VA. Mental health service use was associated with need (mental health screens and physical health) and residing in micropolitan communities. Among service users, predisposing factors (middle age range and female gender) and enabling factors (employment, income above $50,000, and private insurance) were associated with greater non-VA services use.Conclusion: Overall service use was strongly associated with need, whereas sector of use (non-VA vs. VA) was insignificantly associated with need but strongly associated with enabling factors. These findings have implications for the recent extension of veteran health coverage to non-VA providers. [ABSTRACT FROM AUTHOR]

Objectives: To conduct a systematic literature review of selected major provisions of the Affordable Care Act (ACA) pertaining to expanded health insurance coverage. We present and synthesize research findings from the last 5 years regarding both the immediate and long-term effects of the ACA. We conclude with a summary and offer a research agenda for future studies.Study Design: We identified relevant articles from peer-reviewed scholarly journals by performing a comprehensive search of major electronic databases. We also identified reports in the "gray literature" disseminated by government agencies and other organizations.Principal Findings: Overall, research shows that the ACA has substantially decreased the number of uninsured individuals through the dependent coverage provision, Medicaid expansion, health insurance exchanges, availability of subsidies, and other policy changes. Affordability of health insurance continues to be a concern for many people and disparities persist by geography, race/ethnicity, and income. Early evidence also indicates improvements in access to and affordability of health care. All of these changes are certain to ultimately impact state and federal budgets.Conclusions: The ACA will either directly or indirectly affect almost all Americans. As new and comprehensive data become available, more rigorous evaluations will provide further insights as to whether the ACA has been successful in achieving its goals. [ABSTRACT FROM AUTHOR]

Objective: To examine the extent to which accountable care organizations (ACOs) formally incorporate postacute care providers.Data Sources: The National Survey of ACOs (N = 269, response rate 66 percent).Study Design: We report statistics on ACOs' formal inclusion of postacute care providers and the organizational characteristics and clinical capabilities of ACOs that have postacute care.Principal Findings: Half of ACOs formally include at least one postacute service, with inclusion at higher rates in ACOs with commercial (64 percent) and Medicaid contracts (70 percent) compared to ACOs with Medicare contracts only (45 percent). ACOs that have a formal relationship with a postacute provider are more likely to have advanced transition management, end of life planning, readmission prevention, and care management capabilities.Conclusions: Many ACOs have not formally engaged postacute care, which may leave room to improve service integration and care management. [ABSTRACT FROM AUTHOR]

Objectives: To understand hospital- and county-level factors for rural obstetric unit closures, using mixed methods.Data Sources: Hospital discharge data from Healthcare Cost and Utilization Project's Statewide Inpatient Databases, American Hospital Association Annual Survey, and Area Resource File for 2010, as well as 2013-2014 telephone interviews of all 306 rural hospitals in nine states with at least 10 births in 2010. Via interview, we ascertained obstetric unit status, reasons for closures, and postclosure community capacity for prenatal care.Study Design: Multivariate logistic regression and qualitative analysis were used to identify factors associated with unit closures between 2010 and 2014.Principal Findings: Exactly 7.2 percent of rural hospitals in the study closed their obstetric units. These units were smaller in size, more likely to be privately owned, and located in communities with lower family income, fewer obstetricians, and fewer family physicians. Prenatal care was still available in 17 of 19 communities, but local women would need to travel an average of 29 additional miles to access intrapartum care.Conclusions: Rural obstetric unit closures are more common in smaller hospitals and communities with a limited obstetric workforce. Concerns about continuity of rural maternity care arise for women with local prenatal care but distant intrapartum care. [ABSTRACT FROM AUTHOR]

Objective: To examine the effect of a change in U.S. Preventive Services Task Force (USPSTF) screening guidelines on mammography rates in the United States.Principal Findings: In 2010, the year following the change in guidelines, 12-month mammography prevalence among women aged 40-49 years fell by 2.09 percentage points (95 percent confidence interval [CI]: -2.87 to -1.31) from 54.63 percent in 2008. For women aged 50-74 years, and aged 75 years and older, 12-month screening rates were 2.21 (95 percent CI: -2.65 to -1.77) and 3.60 (95 percent CI: -4.48 to -2.70) percentage points lower than those in 2008. In 2012, for women aged 40-49 years, 12-month prevalence fell to 52.51 percent, a decline of 2.12 percentage points (95 percent CI: -2.79 to -1.32) relative to screening rates prior the USPSTF announcement. For women aged 50-74 years and aged 75 years and older screening rates were 2.45 (95 percent CI: -2.96 to -2.07) and 5.71 (95 percent CI: -6.61 to -4.81) percentage points lower, respectively, in 2012 than in 2008.Conclusion: This study demonstrates an immediate and lasting reduction in the rates of breast cancer screening among women of all age groups after the 2009 revision of screening guidelines by the USPSTF. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects on hospitals of early California actions to expand insurance coverage for low-income uninsured adults after passage of the Affordable Care Act.Data Sources/study Setting: Data from the California Office of Statewide Health Planning and Development and the California Department of Health were merged with U.S. census data for 294 short-term general hospitals during the period 2009-2012.Study Design: A difference-in-difference analysis was conducted with hospitals in counties that did not implement insurance expansions used as a comparison group. Variables examined included payer mix, costs of unreimbursed care, and hospital operating margin. Sensitivity analyses were conducted as well as a triple difference analysis. Effects were estimated for hospitals overall and by ownership type.Principal Findings: California insurance expansions primarily benefited for-profit hospitals, with these facilities experiencing significant decreases in self-pay patients, increases in county-covered patients, and reductions in charity care. Most models yielded no significant change in payer mix and conflicting changes in unreimbursed care for nonprofit hospitals.Conclusions: California hospitals that treated the most uninsured prior to insurance expansions did not as a group experience substantial benefit in terms of reduced uninsured burden or better financial performance after program expansions occurred. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects of past Medicaid eligibility expansions to parents on coverage, access to care, out-of-pocket (OOP) spending, and mental health outcomes, and consider implications for the Affordable Care Act (ACA) Medicaid expansion.Data Sources: Person-level data from the National Health Interview Survey (1998-2010) is used to measure insurance coverage and related outcomes for low-income parents. Using state identifiers available at the National Center for Health Statistics Research Data Center, we attach state Medicaid eligibility thresholds for parents collected from a variety of sources to NHIS observations.Study Design: We use changes in the Medicaid eligibility threshold for parents within states over time to identify the effects of changes in eligibility on low-income parents.Principal Findings: We find that expanding Medicaid eligibility increases insurance coverage, reduces unmet needs due to cost and OOP spending, and improves mental health status among low-income parents. Moreover, our findings suggest that uninsured populations in states not currently participating in the ACA Medicaid expansion would experience even larger improvements in coverage and related outcomes than those in participating states if they chose to expand eligibility.Conclusions: The ACA Medicaid expansion has the potential to improve a wide variety of coverage, access, financial, and health outcomes for uninsured parents in states that choose to expand coverage. [ABSTRACT FROM AUTHOR]

Objective: To examine the impact of a 2007 redesign of West Virginia's Medicaid program, which included an incentive and "nudging" scheme intended to encourage better health care behaviors and reduce Emergency Department (ED) visits.Data Sources: West Virginia Medicaid enrollment and claims data from 2005 to 2010.Study Design: We utilized a "differences in differences" technique with individual and time fixed effects to assess the impact of redesign on ED visits. Starting in 2007, categorically eligible Medicaid beneficiaries were moved from traditional Medicaid to the new Mountain Health Choices (MHC) Program on a rolling basis, approximating a natural experiment. Members chose between a Basic plan, which was less generous than traditional Medicaid, or an Enhanced plan, which was more generous but required additional enrollment steps.Data Collection: Data were obtained from the West Virginia Bureau for Medical Services.Principal Findings: We found that contrary to intentions, the MHC program increased ED visits. Those who selected or defaulted into the Basic plan experienced increased overall and preventable ED visits, while those who selected the Enhanced plan experienced a slight reduction in preventable ED visits; the net effect was an increase in ED visits, as most individuals enrolled in the Basic plan. [ABSTRACT FROM AUTHOR]

Objective: Limited consumer use of health care report cards may be due to the large amount of information presented in report cards, which can be difficult to understand. These limitations may be overcome with summary measures. Our objective was to evaluate consumer response to summary measures in the setting of nursing homes.Data Sources/study Setting: 2005-2010 nursing home Minimum Data Set and Online Survey, Certification and Reporting (OSCAR) datasets.Study Design: In December 2008, Medicare converted its nursing home report card to summary or star ratings. We test whether there was a change in consumer demand for nursing homes related to the nursing home's star rating after the information was released.Principal Findings: The star rating system was associated with a significant change in consumer demand for low- and high-scoring facilities. After the star-based rating system was released, 1-star facilities typically lost 8 percent of their market share and 5-star facilities gained over 6 percent of their market share.Conclusions: The nursing home star rating system significantly affected consumer demand for high- and low-rated nursing homes. These results support the use of summary measures in report cards. [ABSTRACT FROM AUTHOR]

Objective: To improve the predictions provided by Medicare's Hospital Compare (HC) to facilitate better informed decisions regarding hospital choice by the public.Data Sources/setting: Medicare claims on all patients admitted for Acute Myocardial Infarction between 2009 through 2011.Study Design: Cohort analysis using a Bayesian approach, comparing the present assumptions of HC (using a constant mean and constant variance for all hospital random effects), versus an expanded model that allows for the inclusion of hospital characteristics to permit the data to determine whether they vary with attributes of hospitals, such as volume, capabilities, and staffing. Hospital predictions are then created using directly standardized estimates to facilitate comparisons between hospitals.Data Collection/extraction Methods: Medicare fee-for-service claims.Principal Findings: Our model that included hospital characteristics produces very different predictions from the current HC model, with higher predicted mortality rates at hospitals with lower volume and worse characteristics. Using Chicago as an example, the expanded model would advise patients against seeking treatment at the smallest hospitals with worse technology and staffing.Conclusion: To aid patients when selecting between hospitals, the Centers for Medicare and Medicaid Services (CMS) should improve the HC model by permitting its predictions to vary systematically with hospital attributes such as volume, capabilities, and staffing. [ABSTRACT FROM AUTHOR]

Objective: To examine whether racial, gender, and ethnic salary disparities exist in the physician assistant (PA) profession and what factors, if any, are associated with the differentials.Data Sources/study Setting: We use a nationally representative survey of 15,105 PAs from the American Academy of Physician Assistants (AAPA).Study Design: We use bivariate and multivariate statistics to analyze pay differentials from the 2009 AAPA survey.Principle Findings: Women represent nearly two-thirds of the profession but receive approximately $18,000 less in primary compensation. The differential reduces to just over $9,500 when the analysis includes a variety of other variables. According to AAPA survey, minority PAs tend to make slightly higher salaries than White PAs nationally, although the differences are not statistically significant once the control variables are included in the analysis.Conclusions: Despite the rough parity in primary salary, PAs of color are vastly underrepresented in the profession. The salaries of women lag in comparison to their male counterparts. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between Magnet recognition, an indicator of nursing excellence, and patients' experience with their hospitalization reported in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey.Data Sources: This secondary analysis includes cross-sectional data from the 2010 HCAHPS survey, the American Hospital Association, and the American Nurses Credentialing Center.Study Design: We conducted a retrospective observational study.Data Collection: Using common hospital identifiers, we created a matched set of 212 Magnet hospitals and 212 non-Magnet hospitals.Principal Findings: Patients in Magnet hospitals gave their hospitals higher overall ratings, were more likely to recommend their hospital, and reported more positive care experiences with nurse communication.Conclusions: Magnet recognition is associated with better patient care experiences, which may positively enhance reimbursement for hospitals. [ABSTRACT FROM AUTHOR]

Objective: To estimate the impact of different forms of Medicaid managed care (MMC) delivery on racial and ethnic disparities in utilization.Data Source: Longitudinal, administrative data on 101,649 children in Kentucky continuously enrolled in Medicaid between January 1997 and June 1999. Outcomes considered are monthly professional, outpatient, and inpatient utilization.Study Design: We apply an intent-to-treat, instrumental variables analysis using the staggered geographic implementation of MMC to create treatment and control groups of children.Principal Findings: The implementation of MMC reduced monthly professional visits by a smaller degree for non-whites than whites (3.8 percentage points vs. 6.2 percentage points), thereby helping to equalize the initial racial/ethnic disparity in utilization. The Passport MMC program in the Louisville-centered region statistically significantly reduced disparities for professional visits (closing the gap by 8.0 percentage points), while the Kentucky Health Select MMC program in the Lexington-centered region did not. No substantive impact on disparities was found for either outpatient or inpatient utilization in either program.Conclusions: We find evidence that MMC has the possibility to reduce racial/ethnic disparities in professional utilization. More work is needed to determine which managed care program characteristics drive this result. [ABSTRACT FROM AUTHOR]

Objective: To examine the impacts of job insecurity during the recession of 2007-2009 on health care utilization among a panel of U.S. employees.Data Sources/study Setting: Linked administrative and claims datasets on a panel of continuously employed, continuously insured individuals at a large multisite manufacturing firm that experienced widespread layoffs (N = 9,486).Study Design: We employed segmented regressions to examine temporal discontinuities in utilization during 2006-2012. To assess the effects of job insecurity, we compared individuals at high- and low-layoff plants. Because the dataset includes multiple observations for each individual, we included individual-level fixed effects.Principal Findings: We found discontinuous increases in outpatient (3.5 visits/month/10,000 individuals, p = .002) and emergency (0.4 visits/month/10,000 individuals, p = .05) utilization in the panel of all employees. Compared with individuals at low-layoff plants, individuals at high-layoff plants decreased outpatient utilization (-4.0 visits/month/10,000 individuals, p = .008), suggesting foregone preventive care, with a marginally significant increase in emergency utilization (0.4 visits/month/10,000 individuals, p = .08).Conclusions: These results suggest changes in health care utilization and potentially adverse impacts on employee health in response to job insecurity during the latest recession. This study contributes to our understanding of the impacts of economic crises on the health of the U.S. working population. [ABSTRACT FROM AUTHOR]

Objective: To assess the coverage effects of California's 2011 Low-Income Health Program (LIHP), enacted as an "early expansion" under the Affordable Care Act (ACA), and to demonstrate the feasibility of using Census data to measure county-level coverage changes.Data Sources/study Setting: 2008-2012 American Community Survey (ACS). The sample contained California adults ages 19-64 years (n = 237,876) and children 0-18 years (n = 113,159) with incomes below 200 percent of the federal poverty level.Study Design: Differences-in-differences analysis comparing public coverage, private insurance, and the uninsured rate in counties that expanded the LIHP in 2011 versus California counties not expanding during this time. Additional analyses tested for heterogeneous impacts of the LIHP and spillover effects on children.Principal Findings: Compared to nonexpansion counties, public coverage for adults increased by 1.8 percentage points (p = .02) in expanding counties, while the uninsured rate declined by 2.1 percentage points (p = .01). There was no significant change in private coverage. Public coverage gains were largest for Latinos and those with limited English proficiency. The expansion produced a positive spillover effect on children's Medicaid enrollment.Conclusions: California's 2011 expansion produced significant increases in public coverage for low-income individuals, particularly Latinos. Substate coverage analyses with the ACS can add valuable detail to future assessments of the ACA. [ABSTRACT FROM AUTHOR]

Objective: To examine the association between non-adherence to clinical practice guidelines (CPGs) and time to return to work (RTW) for patients with workplace injuries.Data Sources/study Setting: Secondary analysis of medical billing and disability data for 148,199 for shoulder and back injuries from a workers' compensation insurer.Study Design: Cox proportional hazard regression is used to estimate the association between time to RTW and receipt of guideline-discordant care. We test the robustness of our findings to an omitted confounding variable.Data Collection: Collected by the insurer from the time an injury was reported, through recovery or last follow-up.Principal Findings: Receiving guideline-discordant care was associated with slower RTW for only some guidelines. Early receipt of care, and getting less than the recommended amount of care, were correlated with faster RTW. Excessive physical therapy, bracing, and injections were associated with slower RTW.Conclusions: There is not a consistent relationship between performance on CPGs and RTW. The association between performance on CPG and RTW is difficult to measure in observational data, because analysts cannot control for omitted variables that affect a patient's treatment and outcomes. CPGs supported by observational studies or randomized trials may have a more certain relationship to health outcomes. [ABSTRACT FROM AUTHOR]

Objective: To analyze health care disparities in pediatric quality of care measures and determine the impact of data imputation.Data Sources: Five HEDIS measures are calculated based on 2012 administrative data for 145,652 children in two public insurance programs in Florida.Methods: The Bayesian Improved Surname and Geocoding (BISG) imputation method is used to impute missing race and ethnicity data for 42 percent of the sample (61,954 children). Models are estimated with and without the imputed race and ethnicity data.Principal Findings: Dropping individuals with missing race and ethnicity data biases quality of care measures for minorities downward relative to nonminority children for several measures.Conclusions: These results provide further support for the importance of appropriately accounting for missing race and ethnicity data through imputation methods. [ABSTRACT FROM AUTHOR]

Research Objective: This study examines small area variations in readmission rates to assess whether higher readmission rate in an area is associated with higher clusters of patients with multiple chronic conditions.Study Design: The study uses hospital discharge data of adult (18+) patients in 6 U.S. states for 2009 from the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality, linked to contextual and provider data from Health Resources and Services Administration. A multivariate cross sectional design at primary care service area (PCSA) level is used.Principal Findings: Adjusting for area characteristics, the readmission rates were significantly higher in PCSAs having higher proportions of patients with 2-3 chronic conditions and those with 4+ chronic conditions, compared with areas with a higher concentration of patients with 0-1 chronic conditions.Conclusions: Using small area analysis, the study shows that areas with higher concentration of patients with increased comorbid conditions are more likely to have higher readmission rates. [ABSTRACT FROM AUTHOR]

Research Objective: Coronavirus disease 2019 (COVID‐19), a global pandemic, has disproportionately inflicted deaths and affected the US economy. With the recent emergency use authorization of COVID‐19 vaccines, ongoing non‐pharmaceutical interventions (NPIs) could be lifted in the future. Our objective was to quantify the impact of the timing of the lifting of NPIs on COVID‐19 infections and deaths. Study Design: We developed a dynamic transmission model with Susceptible‐Exposed‐Infectious‐Recovered (SEIR) compartments to simulate the evolution of COVID‐19 over time in the United States from March 2020 to December 2021. We accounted for heterogeneity by including seven age groups and four contact mixing domains (school, work, household, and other locations) relevant to SARS‐CoV‐2 transmission. We extracted model parameters from published studies, available databases, and via calibration. We also calibrated the effect of NPIs (e.g., restriction on businesses, mask mandates, limited indoor gathering) on contact rates within each mixing domain. The model was calibrated to reproduce COVID‐19 deaths, reported infections and hospitalizations from March–December. We introduced the COVID‐19 vaccine from January 2021, assuming an uptake rate of 15 million individuals per month and a prioritization schedule as defined by the Centers for Disease Control and Prevention. We assumed a vaccine efficacy of 70–90% (base case: 90%) for protection against developing COVID‐19 symptoms, and we assumed 25% (relative to vaccine efficacy) of the protection against COVID‐19 infection. We projected the total numbers of COVID‐19 infections (diagnosed and undiagnosed), hospitalizations, and deaths in 2021 if NPIs are lifted in August, September, October, November, and not lifted in 2021. Population Studied: US Population. Principal Findings: Maintaining all NPIs in the US throughout 2021 is predicted to result in 36,300 deaths (22,700 deaths in age 70+), 11.19 million total COVID‐19 infections (6.20 million diagnosed; and 2.11 million moderate/severe), 84,000 intensive care unit (ICU) admissions. TABLE shows the difference in outcomes if NPIs are lifted (compared with maintaining NPIs throughout 2021) in August, September, October, and November. All scenarios of the lifting of NPIs would result in additional deaths, infections, and hospitalizations. Sensitivity analysis showed that with the vaccine efficacy of 70%, the difference in outcomes would increase further. OutcomeJan‐Dec 2021Excess Outcomes with NPIs Lifting in:Maintain NPIs in 2021Aug‐2021Sep‐2021Oct‐2021Nov‐2021Deaths: total36,340+262,956+125,536+28,708+3360age 0–1971+1299+774+221+30age 20–6913,572+89,067+44,546+10,711+1371age 70+22,697+172,591+80,215+17,776+1959Infections: total11.19 M+165.88 M+110.10 M+35.14 M+5.29 Mundiagnosed4.99 M+84.63 M+58.08 M+19.31 M+2.96 Mdiagnosed6.20 M+81.24 M+51.98 M+15.82 M+2.33 MInfections: moderate/severe2.11 M+21.31 M+13.48 M+4.09 M+0.60 MInfections: asymptomatic/mild9.07 M+144.56 M+96.58 M+31,051,361+4,691,031Hospitalizations224,247+2,179,487+1,394,693+455,218+69,833ICU admissions83,967+738,179+427,519+121,676+16,888 Conclusions: Even though COVID‐19 vaccines are being deployed through emergency use approvals in the US, the time at which NPIs are lifted will still have a substantial influence on COVID‐19 mortality during 2021. Implications for Policy or Practice: Social distancing and restrictions on businesses are needed, potentially throughout 2021, to mitigate COVID‐19 hospitalizations and deaths in the United States before immunity through vaccination programs can become effective. Primary Funding Source: Janssen. [ABSTRACT FROM AUTHOR]

Research Objective: To compare the outcomes of post‐acute care between home health (HH) and skilled nursing facilities (SNFs) following hospitalization among Medicare beneficiaries with dementia. Despite the fact that both post‐acute care use and dementia are highly prevalent in the Medicare population, very few studies have compared the outcomes of different post‐acute care settings for patients with dementia, leaving patients, caregivers, and clinicians uncertain how to make optimal decisions around hospital discharge. Study Design: Retrospective analysis of secondary data using an instrumental variable design to compare outcomes of HH versus SNF following an acute hospitalization. We used a 100% sample of Medicare inpatient, outpatient, and post‐acute care claims and assessment data from January 1, 2015 to December 31, 2016 and used differential distance between home health and SNF as the instrumental variable to account for nonrandom allocation of patients (F‐statistic: 26.5). Outcomes included unplanned 30‐day readmission, 30‐ and 100‐day mortality, and a composite measure of readmission and mortality to address competing risks. Our analysis adjusted for beneficiary characteristics and year of analysis, included fixed effects for hospital and year, and adjusted for clustering at the hospital level. Population Studied: We used MedPAR to identify hospitalizations and Minimum Data Set and Outcome and Assessment Information Set assessments to identify SNF and HH stays following hospital discharge. We excluded beneficiaries younger than age 65, admitted to the hospital from a nursing home, or were enrolled in hospice. We identified dementia using validated diagnostic codes with a three‐year look‐back. We also measured demographics, comorbidities, characteristics of the index hospital stay, prior health care utilization, and both cognitive and physical function on admission to post‐acute care. Principal Findings: Our sample included 1,369,192 beneficiaries with a diagnosis of dementia; 404,539 (29.5%) received HH, while 964,653 (70.5%) went to SNF. The cohort was older (mean age 83), approximately 70% were cognitively impaired on SNF admission, and only 30.4% of patients were independent in Activities of Daily Living. Overall, 16.1% were readmitted to the hospital and 5.9% died within 30 days, while 19.5% died within 100 days of hospital discharge. In the instrumental variable analysis, there were no differences in any outcome between the two post‐acute care settings. These findings were similar when the analysis was stratified by degree of cognitive impairment. Conclusions: In a sample of more than 1.6 million Medicare beneficiaries discharged to post‐acute care following hospitalization, use of home health services and SNF were equivalent in terms of unplanned readmissions and 30‐ and 100‐day mortality. These are important findings given more than 7 in 10 Medicare beneficiaries with dementia are currently discharged to SNF for post‐acute care at much higher cost than HH, and the prevalence of both dementia and post‐acute care use are increasing in the United States. Implications for Policy or Practice: Our findings suggest HH may provide similar outcomes at lower cost following hospitalization for Medicare beneficiaries with a diagnosis of dementia, and that home‐based models of care may provide increased post‐acute care value. Primary Funding Source: University of Pennsylvania Institute on Aging. [ABSTRACT FROM AUTHOR]

Objective: To determine how access to percutaneous coronary intervention (PCI) is distributed across demographics.Data Sources: Secondary data from the 2011 American Hospital Association (AHA) survey data combined with 2010 Census.Study Design: We calculated prehospital times from 32,370 ZIP codes to the nearest PCI center. We used a multivariate logit model to determine the odds of untimely access by the ZIP code's concentration of vulnerable populations.Data Collection: We used ZIP code-level data on community characteristics from the 2010 Census and supplemented it with 2011 AHA survey data on service-line availability of PCI for responding hospitals.Principal Findings: For approximately 306 million Americans, the median prehospital time to the nearest PCI center is 33 minutes. While 84 percent of Americans live within one hour of a PCI center, the odds of untimely access are higher in low-income (OR: 3.00; 95 percent CI: 2.39, 3.77), rural (8.10; 95 percent CI: 6.84, 9.59), and highly Hispanic communities (2.55; 95 percent CI: 1.86, 3.49).Conclusions: While the majority of Americans live within 60 minutes of a PCI center, rural, low-income, and highly Hispanic communities have worse PCI access. This may translate into worse outcomes for patients with acute myocardial infarction. [ABSTRACT FROM AUTHOR]

Objective: To evaluate whether aligning the Part D low-income subsidy and Medicaid program enrollment pathways in 2010 increased Medicaid participation among new Medicare beneficiaries.Data Sources: Medicare enrollment records for years 2007-2011.Study Design: We used a multinomial logistic model with state fixed effects to examine the annual change in limited and full Medicaid enrollment among new Medicare beneficiaries for 2 years before and after the reforms (2008-2011).Data Extraction Methods: We identified new Medicare beneficiaries in the years 2008-2011 and their participation in Medicaid based on Medicare enrollment records.Principal Findings: The percentage of beneficiaries enrolling in limited Medicaid at the start of Medicare coverage increased in 2010 by 0.3 percentage points for individuals aging into Medicare and by 1.3 percentage points for those qualifying due to disability (p < .001). There was no significant difference in the size of enrollment increases between states with and without concurrent limited Medicaid eligibility expansions.Conclusions: Our findings suggest that streamlining financial assistance programs may improve Medicare beneficiaries' access to benefits. [ABSTRACT FROM AUTHOR]

Objective: To detect the presence of racial and ethnic pay disparities between minority and white hospital RNs using a national sample.Data Sources/study Setting: The National Sample Survey of Registered Nurses, 2008, which is representative at both the state and national level.Study Design: Cross-sectional data were analyzed using multivariate regression and regression decomposition. Differences between groups were decomposed into differences in the possession of characteristics and differences in the value of the same characteristic between different groups, the latter being a commonly used measure of wage discrimination.Data Collection/extraction Methods: As the majority of minority hospital RNs are employed within the most densely populated (central) counties of metropolitan statistical areas (MSAs), only hospital RNs employed in the central counties of MSAs were selected.Principal Findings: Regression decomposition found that black and Hispanic RNs earned less than whites and Asians, while Asian RNs earned more than white RNs. The majority of pay variation between white RNs, versus Asian, black, or Hispanic RNs was due to unexplained differences in the value of the same characteristic between groups.Conclusions: Differences in earnings between underrepresented and overrepresented hospital RNs is suggestive of discrimination. [ABSTRACT FROM AUTHOR]

Objective: To compare total annual costs for Medicare beneficiaries receiving primary care in federally funded health centers (HCs) to Medicare beneficiaries in physician offices and outpatient clinics.Data Sources/study Settings: Part A and B fee-for-service Medicare claims from 14 geographically diverse states. The sample was restricted to beneficiaries residing within primary care service areas (PCSAs) with at least one HC.Study Design: We modeled separately total annual costs, annual primary care costs, and annual nonprimary care costs as a function of patient characteristics and PCSA fixed effects.Data Collection: Data were obtained from the Centers for Medicare & Medicaid Services.Principal Findings: Total median annual costs (at $2,370) for HC Medicare patients were lower by 10 percent compared to patients in physician offices ($2,667) and by 30 percent compared to patients in outpatient clinics ($3,580). This was due to lower nonprimary care costs in HCs, despite higher primary care costs.Conclusions: HCs may offer lower total cost practice style to the Centers for Medicare & Medicaid Services, which administers Medicare. Future research should examine whether these lower costs reflect better management by HC practitioners or more limited access to specialty care by HC patients. [ABSTRACT FROM AUTHOR]

Objective: To synthesize new findings from the THRIVE Research Collaborative (The Research Initiative Valuing Eldercare) related to the Green House (GH) model of nursing home care and broadly consider their implications.Data Sources: Interviews and observations conducted in GH and comparison homes, Minimum Data Set (MDS) assessments, Medicare data, and Online Survey, Certification and Reporting data.Study Design: Critical integration and interpretation of findings based on primary data collected 2011-2014 in 28 GH homes (from 16 organizations), and 15 comparison nursing home units (from 8 organizations); and secondary data derived from 2005 to 2010 for 72 GH homes (from 15 organizations) and 223 comparison homes.Principal Findings: Implementation of the GH model is inconsistent, sometimes differing from design. Among residents of GH homes, adoption lowers hospital readmissions, three MDS measures of poor quality, and Part A/hospice Medicare expenditures. Some evidence suggests the model is associated with lower direct care staff turnover.Conclusions: Recommendations relate to assessing fidelity, monitoring quality, capitalizing opportunities to improve care, incorporating evidence-based practices, including primary care providers, supporting high-performance workforce practices, aligning Medicare financial incentives, promoting equity, informing broad culture change, and conducting future research. [ABSTRACT FROM AUTHOR]

Objective: Despite the proliferation of databases with increasingly rich patient data, prediction of medication adherence remains poor. We proposed and evaluated approaches for improved adherence prediction.Data Sources: We identified Medicare beneficiaries who received prescription drug coverage through CVS Caremark and initiated a statin.Study Design: A total of 643 variables were identified at baseline from prior claims and linked Census data. In addition, we identified three postbaseline predictors, indicators of adherence to statins during each of the first 3 months of follow-up. We estimated 10 models predicting subsequent adherence, using logistic regression and boosted logistic regression, a nonparametric data-mining technique. Models were also estimated within strata defined by the index days supply.Results: In 77,703 statin initiators, prediction using baseline variables only was poor with maximum cross-validated C-statistics of 0.606 and 0.577 among patients with index supply ≤30 days and >30 days, respectively. Using only indicators of initial statin adherence improved prediction accuracy substantially among patients with shorter initial dispensings (C = 0.827/0.518), and, when combined with investigator-specified variables, prediction accuracy was further improved (C = 0.842/0.596).Conclusions: Observed adherence immediately after initiation predicted future adherence for patients whose initial dispensings were relatively short. [ABSTRACT FROM AUTHOR]

Objectives: To assess the feasibility of using existing claims-based algorithms to identify community-dwelling Medicare beneficiaries with disability based solely on the conditions for which they are being treated, and improving on these algorithms by combining them in predictive models.Data Source: Data on 12,415 community-dwelling fee-for-service Medicare beneficiaries who first responded to the Medicare Current Beneficiary Survey (MCBS) in 2003-2006.Study Design: Logistic regression models in which six claims-based disability indicators are used to predict self-reported disability. Receiver operating characteristic (ROC) curves were used to assess the performance of the predictive models.Principal Findings: The predictive performance of the regression-based models is better than that of the individual claims-based indicators. At a predicted probability threshold chosen to maximize the sum of sensitivity and specificity, sensitivity is 0.72 for beneficiaries age 65 or older and specificity is 0.65. For those under 65, sensitivity is 0.54 and specificity is 0.67. The findings also suggest ways to improve predictive performance for specific disability populations of interest to researchers.Conclusions: Predictive models that incorporate multiple claims-based indicators provide an improved tool for researchers seeking to identify people with disabilities in claims data. [ABSTRACT FROM AUTHOR]

Objective: To compare standardized estimates of the true resource costs of outpatient health care to the allowable and billed charges for that care among Medicare Fee for Service (FFS) beneficiaries.Data Sources/study Setting: Medicare Carrier and Outpatient Standard Analytic (SAF) files linked to participant data in the Study of Osteoporotic Fractures from 2004 through 2010. Participants were 3,435 female Medicare Fee for Service enrollees age 80 and older recruited in one rural and three metropolitan areas of the United States.Study Design: We estimated standardized costs for Carrier and OP-SAF claims using Medicare payment weights, and compared them to allowable and billed charges for those claims. We used semilog linear regression to estimate the associations of age, race, bone mineral density, prior fracture, and geriatric depression scale score with allowable charges, billed charges, and standardized costs.Results: Estimated associations of patient characteristics with standardized costs were not statistically different than the associations with allowable charges (chi-squared [χ(2)]: 8.6, p = .13) but were different from associations with billed charges (χ(2): 25.5, p < .001).Conclusion: Allowable charges for outpatient utilization in the Carrier file and OP-SAF may be good surrogates for standardized costs that reflect patient medical and surgical acuity. [ABSTRACT FROM AUTHOR]