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This paper presents longitudinal data representing federal funding for health services research and discusses the observed trends in the larger context of overall funding for research and development in the United States. By putting into context public and private funding trends, the authors examine how these trends effect the supply and demand of the health services research workforce. [ABSTRACT FROM AUTHOR]

Objectives: To explore (1) differences in validity and feasibility ratings for geriatric surgical standards across a diverse stakeholder group (surgeons vs. nonsurgeons, health care providers vs. nonproviders, including patient-family, advocacy, and regulatory agencies); (2) whether three multidisciplinary discussion subgroups would reach similar conclusions.Data Source/study Setting: Primary data (ratings) were reported from 58 stakeholder organizations.Study Design: An adaptation of the RAND-UCLA Appropriateness Methodology (RAM) process was conducted in May 2016.Data Collection/extraction Methods: Stakeholders self-administered ratings on paper, returned via mail (Round 1) and in-person (Round 2).Principal Findings: In Round 1, surgeons rated standards more critically (91.2 percent valid; 64.9 percent feasible) than nonsurgeons (100 percent valid; 87.0 percent feasible) but increased ratings in Round 2 (98.7 percent valid; 90.6 percent feasible), aligning with nonsurgeons (99.7 percent valid; 96.1 percent feasible). Three parallel subgroups rated validity at 96.8 percent (group 1), 100 percent (group 2), and 97.4 percent (group 3). Feasibility ratings were 76.9 percent (group 1), 96.1 percent (group 2), and 92.2 percent (group 3).Conclusions: There are differences in validity and feasibility ratings by health professions, with surgeons rating standards more critically than nonsurgeons. However, three separate discussion subgroups rated a high proportion (96-100 percent) of standards as valid, indicating the RAM can be successfully applied to a large stakeholder group. [ABSTRACT FROM AUTHOR]

The United States is in the midst of a multifaceted public health crisis, marked by increasing midlife mortality rates among nearly all racial and ethnic groups.[[1]] The burden of this crisis has fallen most heavily among vulnerable populations, particularly individuals with lower levels of income and education.[[2]] Patterns of rising mortality - which vary across time, space, and causes of death - suggest a complex set of underlying causes, many of which may have been operative for decades.[2] How do the findings speak to the potential consequences of other trends in urban housing, in particular gentrification, whose relationship to evictions and health outcomes has thus far been shown to be mixed? America's declining well-being, health, and life expectancy: not just a white problem. 33 Fazel S, Geddes JR, Kushel M. The health of homeless people in high-income countries: descriptive epidemiology, health consequences, and clinical and policy recommendations. [Extracted from the article]

Objectives: To determine dementia prevalence and costs attributable to dementia using Veterans Health Administration (VHA) data with and without Medicare data.Data Sources: VHA inpatient, outpatient, purchased care and other data and Medicare enrollment, claims, and assessments in fiscal year (FY) 2013.Study Design: Analyses were conducted with VHA data alone and with combined VHA and Medicare data. Dementia was identified from a VHA sanctioned list of ICD-9 diagnoses. Attributable cost of dementia was estimated using recycled predictions.Data Collection: Veterans age 65 and older who used VHA and were enrolled in Traditional Medicare in FY 2013 (1.9 million).Principal Findings: VHA records indicated the prevalence of dementia in FY 2013 was 4.8 percent while combined VHA and Medicare data indicated the prevalence was 7.4 percent. Attributable cost of dementia to VHA was, on average, $10,950 per veteran per year (pvpy) using VHA alone and $6,662 pvpy using combined VHA and Medicare data. Combined VHA and Medicare attributable cost of dementia was $11,285 pvpy. Utilization attributed to dementia using VHA data alone was lower for long-term institutionalization and higher for supportive care services than indicated in combined VHA and Medicare data.Conclusions: Better planning for clinical and cost-efficient care requires VHA and Medicare to share data for veterans with dementia and likely more generally. [ABSTRACT FROM AUTHOR]

Objective: To develop outcome measures that are more sensitive than current measures for evaluating primary or transitional care after hospitalizations, emergency department (ED) visits, or observation stays.Data Sources: Medicare claims data from January 1, 2015, to October 31, 2017, for 1 261 707 Medicare fee-for-service beneficiaries served by (a) primary care practices participating in Track 1 of the Comprehensive Primary Care Plus (CPC+) initiative, and (b) their matched comparison practices.Study Design: Given the poor statistical power in many studies to detect effects on readmissions, we developed two novel claims-based measures of unplanned acute care (UAC) following an index acute care event. The first measure assesses the proportion of hospitalizations followed by an unplanned readmission, ED visit, or observation stay within 30 days of discharge; the second assesses the proportion of ED visits and observation stays followed by a hospitalization, ED visit, or observation stay within 30 days. We calculate minimum detectable effects (MDEs) for both measures and for a conventional measure of 30-day unplanned readmissions, using CPC+ data.Principal Findings: Repeat UAC events are common among Medicare beneficiaries served by the CPC+ practices. In 2017, 22% of discharges and 21% of ED visits and observation stays had a UAC event within 30 days. Readmissions were the most common UAC event following discharge, whereas ED visits were most common following index ED visits or observation stays. MDEs are 25%-40% lower for the new measures than for the standard 30-day readmissions measure, indicating better statistical power to detect impacts of primary or transitional care interventions.Conclusions: This study introduces two new claims-based measures to assess quality of care during a patient's vulnerable period following acute care. The new measures complement existing measures, covering a broader range of UAC events than the standard 30-day readmissions measure, and yielding greater statistical power. [ABSTRACT FROM AUTHOR]

Objective: We aim to assess whether system providers perform better than nonsystem providers under an alternative payment model that incentivizes high-quality, cost-efficient care. We posit that the payment environment and the incentives it provides can affect the relative performance of vertically integrated health systems. To examine this potential influence, we compare system and nonsystem hospitals participating in Medicare's Comprehensive Care for Joint Replacement (CJR) model.Data Sources: We used hospital cost and quality data from the Centers for Medicare & Medicaid Services linked to data from the Agency for Healthcare Research and Quality's Compendium of US Health Systems and hospital characteristics from secondary sources. The data include 706 hospitals in 67 metropolitan areas.Study Design: We estimated regressions that compared system and nonsystem hospitals' 2017 cost and quality performance providing lower joint replacements among hospitals required to participate in CJR.Principal Findings: Among CJR hospitals, system hospitals that provided comprehensive services in their local market had 5.8 percent ($1612) lower episode costs (P = .01) than nonsystem hospitals. System hospitals that did not provide such services had 3.5 percent ($967) lower episode costs (P = .14). Quality differences between system hospitals and nonsystem hospitals were mostly small and statistically insignificant.Conclusions: When operating under alternative payment model incentives, vertical integration may enable hospitals to lower costs with similar quality scores. [ABSTRACT FROM AUTHOR]

Background: Prior authorization of prescription medications is a policy tool that can potentially impact care quality and patient safety.Objective: To examine the effectiveness of a mandatory peer-review program in reducing antipsychotic prescriptions among Medicaid-insured children, accounting for secular trends that affected antipsychotic prescribing nationally.Data Source: Medicaid Analytical eXtracts (MAX) with administrative claims for health services provided between January 2006 and December 2011.Study Design: This retrospective, observational study examined prescription claims records from Washington State (Washington) and compared them to a synthetic control drawing from 20 potential donor states that had not implemented any antipsychotic prior authorization program or mandatory peer review for Medicaid-insured children during the study period. This method provided a means to control for secular trends by simulating the antipsychotic use trajectory that the program state would have been expected to experience in the absence of the policy implementation.Principal Findings: Before the policy implementation, antipsychotic use prevalence closely tracked those of the synthetic control (6.17 per 1000 in Washington vs. 6.21 in the synthetic control group). Within two years after the policy was implemented, prevalence decreased to 4.04 in Washington and remained stable in the synthetic control group (6.47), corresponding to an approximately 38% decline.Conclusion: Prior authorization program designs and implementations vary widely. This mandatory peer-review program, with an authorization window and two-stage rollout, was effective in moving population level statistics toward safe and judicious use of antipsychotic medications in children. [ABSTRACT FROM AUTHOR]

Objective: To understand the effect of physician payment incentives on the allocation of health care resources.Data Sources/study Setting: Review and analysis of the literature on physician payment incentives.Study Design: Analysis of current physician payment incentives and several ways to modify those incentives to encourage increased efficiency.Principal Findings: Fee-for-service payments can be incorporated into systems that encourage efficient pricing - prices that are close to the provider's marginal cost - by giving consumers information on provider-specific prices and a strong incentive to choose lower cost providers. However, efficient pricing of services ultimately will need to be supplemented by incentives for efficient production of health and functional status.Conclusions: The problem with current FFS payment is not paying a fee for each service, per se, but the way in which the fees are determined. [ABSTRACT FROM AUTHOR]

Objective: To assess the extent to which all-cause 30-day readmission rate varies by Medicare program within the same hospitals.Study Design: We used conditional logistic regression clustered by hospital and generalized estimating equations to compare the odds of unplanned all-cause 30-day readmission between Medicare Fee-for-Service (FFS) and Medicare Advantage (MA).Data Collection: Wisconsin Health Information Organization collects claims data from various payers including private insurance, Medicare, and Medicaid, twice a year.Principal Findings: For 62 of 66 hospitals, hospital-level readmission rates for MA were lower than those for Medicare FFS. The odds of 30-day readmission in MA were 0.92 times lower than Medicare FFS within the same hospital (odds ratio, 0.93; 95 percent confidence interval, 0.89-0.98). The adjusted overall readmission rates of Medicare FFS and MA were 14.9 percent and 11.9 percent, respectively.Conclusion: These findings provide additional evidence of potential variations in readmission risk by payer and support the need for improved monitoring systems in hospitals that incorporate payer-specific data. Further research is needed to delineate specific care delivery factors that contribute to differential readmission risk by payer source. [ABSTRACT FROM AUTHOR]

Objective: To evaluate episode-based payments for upper respiratory tract infections (URI) and perinatal care in Arkansas's Medicaid population.Study Setting: Upper respiratory infection and perinatal episodes among Medicaid-covered individuals in Arkansas and comparison states from fiscal year (FY) 2011 to 2014.Study Design: Cross-sectional observational analysis using a difference-in-difference design to examine outcomes associated with URI and perinatal episodes of care (EOC) from 2011 to 2014. Key dependent variables include antibiotic use, emergency department visits, physician visits, hospitalizations, readmission, and preventive screenings.Data Collection: Claims data from the Medicaid Analytic Extract for Arkansas, Mississippi, and Missouri from 2010 to 2014 with supplemental county-level data from the Area Health Resource File (AHRF).Principal Findings: The URI EOC reduced the probability of antibiotic use (marginal effect [ME] = -1.8, 90% CI: -2.2, -1.4), physician visits (ME = 0.6, 90% CI: -0.8, -0.4), improved the probability of strep tests for children diagnosed with pharyngitis (ME = 9.4, 90% CI: 8.5, 10.3), but also increased the probability of an emergency department (ED) visit (ME = 0.1, 90% CI: 0.1, 0.2), relative to the comparison group. For perinatal EOCs, we found a reduced probability of an ED visit during pregnancy (ME = 0.1, 90% CI: -0.2, -0.0), an increased probability of screening for HIV (ME = 6.2, 90% CI: 4.0, 8.5), chlamydia (ME = 9.5, 90% CI: 7.2, 11.8), and group B strep-test (ME = 2.6, 90% CI: 0.5, 4.6), relative to the comparison group. Predelivery and postpartum hospitalizations also increased (ME = 1.2, 90% CI: 0.4, 2.0; ME = 0.4, 90% CI: 0.0, 0.8, respectively), relative to the comparison group.Conclusion: Upper respiratory infection and perinatal EOCs for Arkansas Medicaid beneficiaries produced mixed results. Aligning shared savings with quality metrics and cost-thresholds may help achieve quality targets and disincentivize over utilization within the EOC, but may also have unintended consequences. [ABSTRACT FROM AUTHOR]

Objective: To quantify the effects of the Affordable Care Act Medicaid expansion on prescriptions for effective breast cancer hormonal therapies (tamoxifen and aromatase inhibitors) among Medicaid enrollees.Data Source/study Setting: Medicaid State Drug Utilization Database (SDUD) 2011-2018, comprising the universe of outpatient prescription medications covered under the Medicaid program.Study Design: Differences-in-differences and event-study linear models compare population rates of tamoxifen and aromatase inhibitor (anastrozole, exemestane, and letrozole) use in expansion and nonexpansion states, controlling for population characteristics, state, and time.Principal Findings: Relative to nonexpansion states, Medicaid-financed hormonal therapy prescriptions increased by 27.2 per 100 000 nonelderly women in a state. This implies a 28.8 percent increase from the pre-expansion mean of 94.2 per 100 000 nonelderly women in expansion states. The event-study model reveals no evidence of differential pretrends in expansion and nonexpansion states and suggests use grew to 40 or more prescriptions per 100 000 nonelderly women 3-5 years postexpansion.Conclusions: Medicaid expansion may have had a meaningful impact on the ability of lower-income women to access effective hormonal therapies used to treat breast cancer. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of nonphysician providers on measures of spatial access to primary care in Iowa, a state where physician assistants and advanced practice registered nurses are considered primary care providers.Data Sources: 2017 Iowa Health Professions Inventory (Carver College of Medicine), and minor civil division (MCD) level population data for Iowa from the American Community Survey.Study Design: We used a constrained optimization model to probabilistically allocate patient populations to nearby (within a 30-minute drive) primary care providers. We compared the results (across 10 000 scenarios) using only primary care physicians with those including nonphysician providers (NPPs). We analyze results by rurality and compare findings with current health professional shortage areas.Data Collection/extraction Methods: Physicians and NPPs practicing in primary care in 2017 were extracted from the Iowa Health Professions Inventory.Principal Findings: Considering only primary care physicians, the average unallocated population for primary care was 222 109 (7 percent of Iowa's population). Most of the unallocated population (86 percent) was in rural areas with low population density (< 50/square mile). The addition of NPPs to the primary care workforce reduced unallocated population by 65 percent to 78 252 (2.5 percent of Iowa's population). Despite the majority of NPPs being located in urban areas, most of the improvement in spatial accessibility (78 percent) is associated with sparsely populated rural areas.Conclusions: The inclusion of nonphysician providers greatly reduces but does not eliminate all areas of inadequate spatial access to primary care. [ABSTRACT FROM AUTHOR]

Objective: The 340B program allows safety-net hospitals to acquire discounted outpatient drugs and charge payers full price. We examined whether 340B participation increases safety-net engagement.Data Sources: 340B participation data, Medicare hospital cost reports, American Hospital Association Survey, and Schedule 990 nonprofit hospital tax returns.Study Design: Quasi-experimental difference-in-differences design comparing 340B hospitals (the "treatment" group) before and after participating to changes over time to three alternative "control" groups: all other nonprofit and public hospitals, hospitals that are not participating during our study, and hospitals that were not-yet-participating but started after 2015. Outcome measures include a range of safety-net care measures that are alternatives to the standard uncompensated care: charity care, community benefit spending, charity care policies, and low-profit service-line provision.Data Extraction: We extracted data on all nonprofit and public hospitals from 2011 to 2015. We linked 340B participation data to Medicare hospital cost reports and American Hospital Association data using Medicare hospital identifiers. 990 Data was linked on name and address.Principal Findings: New 340B participation was not associated with a change in uncompensated care, but was associated with a 28.9 percent increase in charity care spending (SE = 8.8), or about $880,000 per hospital. However, total community benefit spending (including charity care) did not change. 340B was associated with an increase in the probability of offering discounted care (4.3 percentage points, SE = 1.6) from 84 to 88 percent and an increase in the income eligibility limit for discounted care (18.9 percentage points, SE = 5.6) from 294 to 313 percent. Participation was not associated with the probability of offering low-profit medical care services.Conclusions: Alternative measures show that newly participating hospitals may increase charity care, potentially through offering more patients discounted care. However, increases appear to be fully offset by reductions in other community benefit programs. [ABSTRACT FROM AUTHOR]

Objective: To determine the correlation between hospital 30-day risk-standardized readmission rates (RSRRs) in elderly adults and those in nonelderly adults and children.Data Sources/study Setting: US hospitals (n = 1760 hospitals admitting adult patients and 235 hospitals admitting both adult and pediatric patients) in the 2013-2014 Nationwide Readmissions Database.Study Design: Cross-sectional analysis comparing 30-day RSRRs for elderly adult (≥65 years), middle-aged adult (40-64 years), young adult (18-39 years), and pediatric (1-17 years) patients.Principal Findings: Hospital elderly adult RSRRs were strongly correlated with middle-aged adult RSRRs (Pearson R2 .69 [95% confidence interval (CI) 0.66-0.71]), moderately correlated with young adult RSRRs (Pearson R2 .44 [95% CI 0.40-0.47]), and weakly correlated with pediatric RSRRs (Pearson R2 .28 [95% CI 0.17-0.38]). Nearly identical findings were observed with measures of interquartile agreement and Kappa statistics. This stepwise relationship between age and strength of correlation was consistent across every hospital characteristic.Conclusions: Hospital readmission rates in elderly adults, which are currently used for public reporting and hospital comparisons, may reflect broader hospital readmission performance in middle-aged and young adult populations; however, they are not reflective of hospital performance in pediatric populations. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of provider incentive policy on smoking status documentation.Data Sources: Primary data were extracted from structured electronic medical records (EMRs) from 15 community health centers (CHCs).Study Design: This was an observational study of data from 2006 to 2013, assessing changes in documentation of smoking status over time.Data Extraction Methods: We extracted structured EMR data for patients age 18 and older with at least one primary care visit.Principal Findings: Rates of documented smoking status rose from 30 percent in 2006 to 90 percent in 2013; the largest increase occurred from 2011 to 2012 following policy changes (21.3% [95% CI, 8.2%, 34.4%] from the overall trend). Rates varied by clinic and across patient subgroups.Conclusions: Documentation of smoking status improved markedly after introduction of new federal standards. Further improvement in documentation is still needed, especially for males, nonwhite patients, those using opioids, and HIV + patients. More research is needed to study whether changes in documentation lead to improvements in counseling, cessation, and patient outcomes. [ABSTRACT FROM AUTHOR]

Objective: To develop a model for identifying clinic performance at fulfilling next-day and walk-in requests after adjusting for patient demographics and risk.Data Source: Using Department of Veterans Affairs (VA) administrative data from 160 VA primary care clinics from 2014 to 2017.Study Design: Using a retrospective cohort design, we applied Bayesian hierarchical regression models to predict provision of timely care, with clinic-level random intercept and slope while adjusting for patient demographics and risk status. Timely care was defined as the provision of an appointment within 48 hours of any patient requesting the clinic's next available appointment or walking in to receive care.Data Collection/extraction Methods: We extracted 1 841 210 timely care requests from 613 263 patients.Principal Findings: Across 160 primary care clinics, requests for timely care were fulfilled 86 percent of the time (range 83 percent-88 percent). Our model of timely care fit the data well, with a Bayesian R2 of .8. Over the four years of observation, we identified 25 clinics (16 percent) that were either struggling or excelling at providing timely care.Conclusion: Statistical models of timely care allow for identification of clinics in need of improvement after adjusting for patient demographics and risk status. VA primary care clinics fulfilled 86 percent of timely care requests. [ABSTRACT FROM AUTHOR]

Objective: To examine the impact of Section 1115 waivers on Medicaid coverage and opioid agonist therapy (OAT) utilization among substance use treatment admissions.Data Source: Treatment Episode Data Set-Admissions (TEDS-A) (2001-2012).Study Design: We examined effects of 1115 waiver implementation on proportions of substance use treatment admissions with Medicaid and receiving OAT, using random intercept linear regression.Principal Findings: 1115 waiver implementation was associated with an average of a 6 percentage point increase in proportion of all admissions with Medicaid, and 4 percentage point increase among opioid outpatient admissions. Implementation was not associated with change in proportion of opioid outpatient admissions receiving OAT.Conclusions: 1115 waivers influence Medicaid coverage among substance use treatment admissions. The findings improve our understanding of how state policies impact substance use treatment utilization. [ABSTRACT FROM AUTHOR]

Objective: To assess the accuracy of nursing home self-report of major injury falls on the Minimum Data Set (MDS).Data Sources: MDS assessments and Medicare claims, 2011-2015.Study Design/methods: We linked inpatient claims for major injury falls with MDS assessments. The proportion of claims-identified falls reported for each fall-related MDS item was calculated. Using multilevel modeling, we assessed patient and nursing home characteristics that may be predictive of poor reporting. We created a claims-based major injury fall rate for each nursing home and estimated its correlation with Nursing Home Compare (NHC) measures.Principal Findings: We identified 150,828 major injury falls in claims that occurred during nursing home residency. For the MDS item used by NHC, only 57.5 percent were reported. Reporting was higher for long-stay (62.9 percent) than short-stay (47.2 percent), and for white (59.0 percent) than nonwhite residents (46.4 percent). Adjusting for facility-level race differences, reporting was lower for nonwhite people than white people; holding constant patient race, having larger proportions of nonwhite people in a nursing home was associated with lower reporting. The correlation between fall rates based on claims vs the MDS was 0.22.Conclusions: The nursing home-reported data used for the NHC falls measure may be highly inaccurate. [ABSTRACT FROM AUTHOR]

Objective: To compare different methods of indexing health care service prices for the commercially insured population across geographic markets.Data Sources: Health Care Cost Institute commercial claims data from 2012 to 2016.Study Design: We compare price indices computed using methods with differing levels of computational intensity: weighted-average versus regression-based methods. We separately compute indices of the prices paid for set of common inpatient and set of common outpatient services in different markets across the United States using each type of method. We subsequently examined the variation of and correlations between the resulting index values.Data Collection/extraction Methods: We computed health care service price indices separately using samples of inpatient and outpatient facility claims from 2012 to 2016 across 112 Core-Based Statistical Areas. Within each category of services, claims were limited to members under the age of 65 with employer-sponsored insurance. Both samples were limited to a common set of services that made up nearly 80 percent of the service use in the full sample every year.Principal Findings: We found that the methods studied produced highly correlated price indices (r > .94) with similar distributions across years for both inpatient and outpatient services.Conclusions: Our findings suggest that weighted-average methods, which are much less computationally intensive, will generate results similar to regression-based methods. [ABSTRACT FROM AUTHOR]

Objective: To estimate Prenatal Care Coordination's (PNCC) effect on birth outcomes for Wisconsin Medicaid-covered deliveries.Data Source: A longitudinal cohort of linked Wisconsin birth records (2008-2012), Medicaid claims, and state-administered social services.Study Design: We defined PNCC treatment dichotomously (none vs. any) and by service level (none vs. assessment/care plan only vs. service uptake). Outcomes were birthweight (grams), low birthweight (<2500 g), gestational age (completed weeks), and preterm birth (<37 weeks). We estimated PNCC's effect on birth outcomes, adjusting for maternal characteristics, using inverse-probability of treatment weighted and sibling fixed effects regressions.Data Collection/extraction Methods: We identified 136 224 Medicaid-paid deliveries, of which 33 073 (24.3 percent) linked to any PNCC claim and 22 563 (16.6 percent) linked to claims for PNCC service uptake.Principal Findings: Sibling fixed effects models-which best adjust for unobserved confounding and treatment selection-produced the largest estimates for all outcomes. For example, in these models, PNCC service uptake was associated with a 1.3 percentage point (14 percent) reduction and a 1.8 percentage point (17 percent) reduction in the probabilities of low birthweight and preterm birth, respectively (all P < .05).Conclusions: PNCC's modest but significant improvement of birth outcomes should motivate stronger PNCC outreach and implementation of similar programs elsewhere. [ABSTRACT FROM AUTHOR]

Objective: To estimate the impact of opting-out from Medicare supervision requirements for certified registered nurse anesthetists (CRNAs) on anesthesiologists' work patterns.Data Sources/study Setting: Secondary data from two national surveys of anesthesiologists and the Area Health Resource File.Study Design: We use a matching difference-in-difference regression which contrasts the change in work patterns for anesthesiologists in California, which dropped supervision requirements, to the change for similar anesthesiologists. Key outcome variables include the number of weekly hours worked, the type of work done, and type of care delivery teams.Data Collection/extraction Methods: Self-reported national survey data drawn from members of the American Society of Anesthesiologists.Principal Findings: Anesthesiologists in California saw no change in time spent working or time spent supervising CRNAs. There was a decrease in direct care clinical work hours along with a shift in working more in intraoperative care, a decrease in postoperative care, and an increase in the percentage of cases supervising residents.Conclusions: Anesthesiologists had small but real responses to California's decisions to opt-out of the physician supervision requirement for CRNAs, doing more work in intraoperative care and less outside of the operating room. Total hours worked saw no change. [ABSTRACT FROM AUTHOR]

Objective (or Study Question): To examine the association between hospitalists staffing levels and contract type with CMS Total Performance Score (TPS).Data Sources/study Setting: Total performance scores were obtained from CMS, hospital-level data from the 2015 American Hospital Association Annual Survey Database, and unemployment rates from the Area Resource Health File.Study Design: We used cluster analysis to classify hospitals based on the distribution of various hospitalist contracts, and we used regression analysis to examine the association between TPS and hospitalist staffing levels and contract distributions. Hospital-level predictors included hospitalists staffing levels, RN staffing levels, and Magnet status. Market-level variables were unemployment rates and competition.Principal Findings: Higher staffing levels of employed hospitalists or hospitalists with a group contract are associated with higher TPS (with coefficient estimates of 0.85 and 0.83, respectively, and the same standard error of 0.22). Higher staffing levels of hospitalists under individual contract are negatively associated with TPS (with coefficient estimate of -0.43 and standard error of 0.21). Based on the regression analysis using hospital clusters as independent variables, hospitals with individual contracts or without hospitalists providing care had significantly worse TPS compared to hospitals that predominantly employ hospitalists (with coefficient estimate of -1.80 and standard error of 0.61). Magnet status, RN staffing levels, and small and medium size were positively associated with TPS. Medicare share of inpatient days, teaching status, AMCs, and for-profit and public nonfederal ownership were negatively associated with TPS.Conclusions: Adequate hospitalist staffing level is important for hospitals to achieve better performance. Hospitals need to consider the mix of arrangements or contracts that they have with hospitalists. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of a voluntary pledge policy and a mandatory nonpayment policy on reducing early-term elective deliveries among privately insured and Medicaid-enrolled individuals.Data Sources/study Setting: Birth certificate data from 2009 to 2015, from South Carolina and 16 control states.Study Design: We use a difference-in-differences approach to test the impact of two different policy types. Outcomes include the probability of an early elective delivery, gestation time, and birthweight.Principal Findings: The voluntary pledge and mandatory nonpayment policy reduced overall EED rates from 13.1 to 11.4 (-12.7 percent, [P < .05]), and 10.9 ([-16.6 percent, P < .05]), respectively. Compared to the privately insured, we found greater relative decreases in Medicaid EED rate, the proportion of Medicaid births occurring before 39 weeks, and the proportion of Medicaid babies born with low birthweight.Conclusions: Both voluntary and mandatory nonpayment policies are effective in reducing the rate of EEDs, especially among Medicaid enrollees. Given the high costs and poor outcomes associated with EEDs, policy makers may consider using either tool as a way to improve care value. [ABSTRACT FROM AUTHOR]

Objective: To understand public attitudes about and recommendations to address antibiotic overuse by employing public deliberation (a method for eliciting informed input on value-laden issues).Data Sources/study Setting: Participants in 24 Community Deliberation groups (CD; n = 263), four Citizens' Panel groups (CP; n = 96), and a control group (n = 348). Data were collected in 2012 in four U.S.Locations: Study Design: Using mixed methods, we analyzed quantitative and qualitative data from a randomized control trial.Data Collection/extraction Methods: Using pre/postdeliberation surveys, we compared CD and CP participant attitude changes regarding antibiotic use to the control group. We analyzed deliberation transcripts using qualitative techniques to provide context for survey results.Principal Findings: Compared to control group participants, CD and CP participants had a larger postdeliberation shift in attitudes toward support of government limits on when doctors can prescribe antibiotics. Participants described unawareness about antibiotic overuse and called for education. When discussing prescription limits, participants debated tensions between preserving patient/doctor autonomy and protecting society from antibiotic-related harms. Participants saw patient, physician, and government roles in antibiotic stewardship policies/programs.Conclusion: When informed about individual and social consequences of antibiotic overuse, patients may be more receptive to antibiotic prescription limits. Community-physician-government partnerships are needed to create solutions. [ABSTRACT FROM AUTHOR]

Objective: To demonstrate rolling entry matching (REM), a new statistical method, for comparison group selection in the context of staggered nonuniform participant entry in nonrandomized interventions.Study Setting: Four Health Care Innovation Award (HCIA) interventions between 2012 and 2016.Study Design: Center for Medicare and Medicaid Innovation HCIA participants entering these interventions over time were matched with nonparticipants who exhibited a similar pattern of health care use and expenditures during each participant's baseline period.Data Extraction Methods: Medicare fee-for-service claims data were used to identify nonparticipating, fee-for-service beneficiaries as a potential comparison group and conduct REM.Principal Findings: Rolling entry matching achieved conventionally-accepted levels of balance on observed characteristics between participants and nonparticipants. The method overcame difficulties associated with a small number of intervention entrants.Conclusions: In nonrandomized interventions, valid inference regarding intervention effects relies on the suitability of the comparison group to act as the counterfactual case for the intervention group. When participants enter over time, comparison group selection is complicated. Rolling entry matching is a possible solution for comparison group selection in rolling entry interventions that is particularly useful with small sample sizes and merits further investigation in a variety of contexts. [ABSTRACT FROM AUTHOR]

Objective: To estimate health care utilization and costs incurred by homeless Veterans relative to nonhomeless Veterans and to examine the impact of a VA homelessness program on these outcomes.Data Sources/study Setting: Combined Department of Veterans Affairs (VA) administrative and Medicare claims data.Study Design: Observational study using longitudinal data from Veterans engaged with the VA system and enrolled in Medicare. Veterans with administrative evidence of homelessness at any point during 2006-2010 were matched on period of military service to Veterans with no evidence of homelessness.Principal Findings: Experience of homelessness was associated with 1.37 (95 percent CI = 1.34-1.40) and 0.16 (95 percent CI = 0.14-0.17) more outpatient encounters per quarter in VA and non-VA settings, respectively, and 1.31 (95 percent CI = 1.30-1.32) and 0.49 (95 percent CI = 0.48-0.49) more inpatient days per quarter in VA and non-VA hospitals, respectively. These were associated with higher costs. Relative to stably housed Veterans less than 65 years of age, those enrolled in a VA homelessness program had 94.4 percent (95 percent CI = 90.7 percent-98.1 percent) more VA outpatient visits but 5.5 percent (95 percent CI = 3.0 percent-7.9 percent) fewer Medicare outpatient visits.Conclusions: Homelessness was associated with an increase in VA and Medicare utilization and cost. A VA homelessness program decreased use of Medicare outpatient services. [ABSTRACT FROM AUTHOR]

Objective: To measure how much of the postdischarge cost and utilization attributable to methicillin-resistant Staphylococcus aureus (MRSA) health care-associated infections (HAIs) occur within the US Department of Veterans Affairs (VA) system and how much occurs outside.Data Sources/study Setting: Health care encounters from 3 different settings and payment models: (1) within the VA; (2) outside the VA but paid for by the VA (purchased care); and (3) outside the VA and paid for by Medicare.Study Design: Historical cohort study using data from admissions to VA hospitals between 2007 and 2012.Methods: We assessed the impact of a positive MRSA test result on costs and utilization during the 365 days following discharge using inverse probability of treatment weights to balance covariates.Principal Findings: Among a cohort of 152,687 hospitalized Veterans, a positive MRSA test result was associated with an overall increase of 6.6 (95 percent CI: 5.7-7.5) inpatient days and $9,237 (95 percent CI: $8,211-$10,262) during the postdischarge period. VA inpatient admissions, Medicare reimbursements, and purchased care payments accounted for 60.6 percent, 22.5 percent, and 16.9 percent of these inpatient costs.Conclusions: While most of the excess postdischarge health care costs associated with MRSA HAIs occurred in the VA, non-VA costs make up an important subset of the overall burden. [ABSTRACT FROM AUTHOR]

Objective: It remains unknown whether high-functioning teams can compensate for poor continuity of care to support important patient outcomes.Data Source: Linked VA administrative and Medicare claims data to measure the relationship of team-based care and continuity of care with high-cost utilization.Study Design: Retrospective cohort study of 1.2 million VA-Medicare dual eligible Veterans assigned to a VA primary care provider (PCP) in 2012. Continuity was the proportion of primary care visits to the assigned VA provider of care. Clinics were categorized as low, average, or high-team functioning based on survey data. Our primary outcomes were the number of all-cause hospitalizations, ambulatory care sensitive (ACSC) hospitalizations, and emergency department (ED) visits in 2013.Principal Findings: A 10-percentage point increase in continuity with a VA PCP was associated with 4.5 fewer hospitalizations (p < .001), 3.2 fewer ACSC hospitalizations (p < .001), and 2.6 more ED visits (p = .07) per 1,000 patients. Team-based care was not significantly associated with any high-cost utilization category. Associations were heterogeneous across VA-reliant and nonreliant Veterans. Finally, the interaction results demonstrated that the quality of team-based care functioning could not compensate for poor continuity on hospitalizations, ACSC hospitalizations, or ED visits.Conclusions: In Veterans who were reliant on the VA for services, increasing continuity with a VA PCP and high-functioning team-based care clinics was associated with fewer ED visits and hospitalizations. Furthermore, leveraging combined data from VA and Medicare allowed to better measure continuity and assess high-cost utilization among Veterans who are and are not reliant on the VA for services. [ABSTRACT FROM AUTHOR]

Objective: To assess differences in risk (measured by expected costs associated with sociodemographic and clinical profiles) between Veterans receiving outpatient services through two community care (CC) programs: the Fee program ("Fee") and the Veterans Choice Program ("Choice").Data Sources/study Setting: Administrative data from VHA's Corporate Data Warehouse in fiscal years (FY) 2014-2015.Study Design: We compared the clinical characteristics of Veterans across three groups (Fee only, Choice only, and Fee & Choice). We classified Veterans into risk groups based on Nosos risk scores and examined the relationship between type of outpatient utilization and risk within each CC group. We also examined changes in utilization of VHA and CC in FY14-FY15. We used chi-square tests, t tests, and ANOVAs to identify significant differences between CC groups.Principal Findings: Of the 1,400,977 Veterans using CC in FY15, 91.4 percent were Fee-only users, 4.4 percent Choice-only users, and 4.2 percent Fee & Choice users. Mean concurrent risk scores were higher for Fee only and Fee & Choice (1.9, SD = 2.7; 1.8, SD = 2.2) compared to Choice-only users (1.0, SD = 1.2) (p < .0001). Most CC users were "dual users" of both VHA and CC in FY14-FY15.Conclusions: As care transitions from VHA to CC, VHA should consider how best to coordinate care with community providers to reduce duplication of efforts, improve handoffs, and achieve the best outcomes for Veterans. [ABSTRACT FROM AUTHOR]

Objective: To examine the prevalence of concurrent Veterans Health Administration (VA) and non-VA prescriptions for opioids and sedative-hypnotic medications among post-9/11 veterans in Oregon.Data Sources: VA health care and prescription data were probabilistically linked with Oregon Prescription Drug Monitoring Program (PDMP) data.Study Design: This retrospective cohort study examined concurrent prescriptions among n = 19,959 post-9/11 veterans, by year (2014-2016) and by patient demographic and clinical characteristics. Veterans were included in the cohort for years in which they received VA outpatient care; those receiving hospice or palliative care were excluded. Concurrent prescriptions were defined as ≥1 days of overlap between outpatient prescriptions for opioids and/or sedative-hypnotics (categorized as benzodiazepines vs. non-benzodiazepines).Principal Findings: Among 5,882 veterans who filled opioid or sedative-hypnotic prescriptions at VA pharmacies, 1,036 (17.6 percent) filled concurrent prescriptions from non-VA pharmacies. Within drug class, 15.1, 8.8, and 4.6 percent received concurrent VA and non-VA opioids, benzodiazepines, and non-benzodiazepines, respectively. Veteran demographics and clinical diagnoses were associated with the likelihood of concurrent prescriptions, as was enrollment in the Veterans Choice Program.Conclusions: A considerable proportion of post-9/11 veterans receiving VA care in Oregon filled concurrent prescriptions for opioids and sedative-hypnotics. Fragmentation of care may contribute to prescription drug overdose risk among veterans. [ABSTRACT FROM AUTHOR]

Objective: To examine the association between medical home enrollment and receipt of recommended care for Medicaid beneficiaries with multiple chronic conditions (MCC).Data Sources/study Setting: Secondary claims data from fiscal years 2008-2010. The sample included nonelderly Medicaid beneficiaries with at least two of eight target conditions (asthma, chronic obstructive pulmonary disease, diabetes, hypertension, hyperlipidemia, seizure disorder, major depressive disorder, and schizophrenia).Study Design: We used linear probability models with person- and year-level fixed effects to examine the association between patient-centered medical home (PCMH) enrollment and nine disease-specific quality-of-care metrics, controlling for selection bias and time-invariant differences between enrollees.Data Collection Methods: This study uses a dataset that links Medicaid claims with other administrative data sources.Principal Findings: Patient-centered medical home enrollment was associated with an increased likelihood of receiving eight recommended mental and physical health services, including A1C testing for persons with diabetes, lipid profiles for persons with diabetes and/or hyperlipidemia, and psychotherapy for persons with major depression and persons with schizophrenia. PCMH enrollment was associated with overuse of short-acting β-agonists among beneficiaries with asthma.Conclusions: The PCMH model can improve quality of care for patients with multiple chronic conditions. [ABSTRACT FROM AUTHOR]

Objective: To assess the issue of nonrepresentative sampling in Medicare Advantage (MA) risk adjustment.Data Sources: Medicare enrollment and claims data from 2008 to 2011.Data Extraction: Risk adjustment predictor variables were created from 2008 to 2010 Part A and B claims and the Medicare Beneficiary Summary File. Spending is based on 2009-2011 Part A and B, Durable Medical Equipment, and Home Health Agency claims files.Study Design: A propensity-score matched sample of Traditional Medicare (TM) beneficiaries who resembled MA enrollees was created. Risk adjustment formulas were estimated using multiple techniques, and performance was evaluated based on R2 , predictive ratios, and formula coefficients in the matched sample and a random sample of TM beneficiaries.Principal Findings: Matching improved balance on observables, but performance metrics were similar when comparing risk adjustment formula results fit on and evaluated in the matched sample versus fit on the random sample and evaluated in the matched sample.Conclusions: Fitting MA risk adjustment formulas on a random sample versus a matched sample yields little difference in MA plan payments. This does not rule out potential improvements via the matching method should reliable MA encounter data and additional variables become available for risk adjustment. [ABSTRACT FROM AUTHOR]

Objective: Develop and validate a surveillance model to identify outpatient surgical adverse events (AEs) based on previously developed electronic triggers.Data Sources: Veterans Health Administration's Corporate Data Warehouse.Study Design: Six surgical AE triggers, including postoperative emergency room visits and hospitalizations, were applied to FY2012-2014 outpatient surgeries (n = 744,355). We randomly sampled trigger-flagged and unflagged cases for nurse chart review to document AEs and measured positive predictive value (PPV) for triggers. Next, we used chart review data to iteratively estimate multilevel logistic regression models to predict the probability of an AE, starting with the six triggers and adding in patient, procedure, and facility characteristics to improve model fit. We validated the final model by applying the coefficients to FY2015 outpatient surgery data (n = 256,690) and reviewing charts for cases at high and moderate probability of an AE.Principal Findings: Of 1,730 FY2012-2014 reviewed surgeries, 350 had an AE (20 percent). The final surveillance model c-statistic was 0.81. In FY2015 surgeries with >0.8 predicted probability of an AE (n = 405, 0.15 percent), PPV was 85 percent; in surgeries with a 0.4-0.5 predicted probability of an AE, PPV was 38 percent.Conclusions: The surveillance model performed well, accurately identifying outpatient surgeries with a high probability of an AE. [ABSTRACT FROM AUTHOR]

Objective: To characterize the nature and degree of hospitals' efforts to collaborate with skilled nursing facilities (SNFs) and associated patient outcomes.Data Sources/study Setting: Qualitative data were collected through 138 interviews with staff in 16 hospitals and 25 SNFs in eight markets across the United States in 2015. Quantitative data include Medicare claims data for the 290,603 patients discharged from those 16 hospitals between 2008 and 2015.Study Design/data Collection: Semi-structured interviews with hospital and SNF staff were coded and used to classify hospitals' collaboration efforts with SNFs into high versus low collaboration hospitals, and risk-adjusted, claims-based hospital readmission rates from SNF were compared.Principal Findings: Hospital collaboration efforts were defined as establishing SNF partners, transition management initiatives, and hospital staff visits to SNFs. High collaboration hospitals were more likely to send patients to SNFs (as opposed to home, home with home health, or other PAC settings), sent a higher share of patients to high quality SNFs, and had fewer hospital readmissions from SNF sooner than did low collaboration hospitals.Conclusions: Although collaboration with SNF requires significant administrative and clinical time investment, it is associated with positive patient outcomes. [ABSTRACT FROM AUTHOR]

Objective: To test the effectiveness of financial incentives for smoking cessation in the Medicaid population.Data Sources: Secondary data from the Medicaid Incentives for Prevention of Chronic Disease (MIPCD) program and Medicaid claims/encounter data from 2010 to 2015 for five states.Study Design: Beneficiaries were randomized into receipt or no receipt of financial incentives. We ran multivariate regression models testing the impact of financial incentives on the use of counseling services, smoking behavior, and Medicaid expenditures and utilization.Data Extraction: Participating states provided Medicaid eligibility, claims and encounters, program enrollment, and incentivized service use data.Principal Findings: Participants who received incentives were more likely to call the Quitline and complete counseling sessions. Incentive receipt was positively associated with self-reported quit attempts, self-reported quits, or passing cotinine tests of smoking cessation in most programs, although results were only statistically significant in a subset. There was no systematic evidence that incentives affected health care use or spending.Conclusions: Financial incentives are a promising policy lever to motivate behavioral change in the Medicaid population, but more evidence is needed regarding optimal incentive size, effectiveness of process-versus outcome-based incentives, targeting of incentives, and long-run cost-effectiveness. [ABSTRACT FROM AUTHOR]

Objective: The concept of shifting from volume (i.e., billing for as many patients and services as possible) to value (i.e., reducing costs while improving quality) has been a key underpinning of the development of accountable care organizations (ACOs), yet the cultural change necessary to make this shift has been previously unexplored.Data Sources/study Setting: Primary data collected through site visits to four private sector ACOs.Study Design: Cross-sectional, semi-structured interview study with analysis done at the ACO level to learn about ACO development.Data Collection: One hundred and forty-eight interviews recorded and transcribed verbatim followed by rigorous qualitative analysis using a grounded theory approach.Principal Findings: The importance of shifting organizational culture from volume to value was emphasized across sites and interviewees, particularly when defining an ACO; describing the shift in organizational focus to value; and discussing how to create value by emphasizing quality over volume. Value was viewed as more than cost-benefit, but rather encapsulated a paradigmatic cultural change in the way care is provided.Conclusions: We found that moving from volume to value is central to the culture change required of an ACO. Our findings can inform future efforts that aim to create a more effective value-based health care system. [ABSTRACT FROM AUTHOR]

Objective: To describe a new Veterans Health Administration (VHA) program to foster the learning health system paradigm by rigorously evaluating health care initiatives and to report key lessons learned in designing those evaluations.Principal Findings: The VHA's Quality Enhancement Research Initiative and its Health Services Research and Development Service are cooperating on several large, randomized program evaluations aimed at improving the care veterans receive and the efficiency with which it is delivered. The evaluations we describe involve collaborative design, outcomes assessment, and implementation science through partnerships between VHA operations and researchers. We review key factors to assess before committing to an evaluation. In addition to traditional design issues (such as ensuring adequate power and availability of data), these include others that are easily overlooked: the stability of intervention financing, means of controlling and commitment to adhering to randomized roll-out, degree of buy-in from key implementation staff, and feasibility of managing multiple veto points for interventions that span several programs, among others.Conclusions: Successful program implementation and rigorous evaluation require resources, specialized expertise, and careful planning. If the learning health system model is to be sustained, organizations will need dedicated programs to prioritize resources and continuously adapt evaluation designs. [ABSTRACT FROM AUTHOR]

Objective: To estimate the relative health risk of Medicare Advantage (MA) beneficiaries compared to those in Traditional Medicare (TM).Data Sources/study Setting: Medicare claims and enrollment records for the sample of beneficiaries enrolled in Part D between 2008 and 2015.Study Design: We assigned therapeutic classes to Medicare beneficiaries based on their prescription drug utilization. We then regressed nondrug health spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used coefficients from this regression to predict relative risk of both MA and TM beneficiaries.Principal Findings: Based on prescription drug utilization data, beneficiaries enrolled in MA in 2015 had 6.9 percent lower health risk than beneficiaries in TM, but differences based on coded diagnoses suggested MA beneficiaries were 6.2 percent higher risk. The relative health risk based on drug usage of MA beneficiaries compared to those in TM increased by 3.4 p.p. from 2008 to 2015, while the relative risk using diagnoses increased 9.8 p.p.Conclusions: Our results add to a growing body of evidence suggesting MA receives favorable, or, at worst, neutral selection. If MA beneficiaries are no healthier and no sicker than similar beneficiaries in TM, then payments to MA plans exceed what is warranted based on their health status. [ABSTRACT FROM AUTHOR]

Objective: To examine the cost-effectiveness of a community-based Diabetes Prevention Program (DPP) for Medicaid beneficiaries from the perspective of the health care sector.Data Sources/study Setting: A total of 847 Medicaid enrollees at high risk for type 2 diabetes participating in a community-based DPP.Study Design: Pre- and post clinical outcome and cost data were used as inputs into a validated diabetes simulation model. The model was used to evaluate quality-adjusted life years (QALYs) and health care costs over a 40-year time horizon from the perspective of the health care sector.Data Collection/extraction Methods: Clinical outcome and cost data were derived from a study examining the effect of financial incentives on weight loss.Principal Findings: Study participants lost an average of 4.2 lb (p < .001) and increased high-density lipoprotein cholesterol by 1.75 mg/dl (p = .002). Intervention costs, which included financial incentives for participation and weight loss, were $915 per participant. The incremental cost-effectiveness ratio was estimated to be $14,011 per QALY but was sensitive to the time horizon studied.Conclusions: Widespread adoption of community-based DPP has the potential to reduce diabetes and cardiovascular-related morbidity and mortality for low-income persons at high risk for diabetes and may be a cost-effective investment for Medicaid programs. [ABSTRACT FROM AUTHOR]

Objective: To assess frequency, type, and extent of behavioral health (BH) nonquantitative treatment limits (NQTLs) before and after implementation of the Mental Health Parity and Addiction Equity Act of 2008 (MHPAEA).Data Sources: Secondary administrative data for Optum carve-out and carve-in plans.Study Design: Cross-tabulations and "two-part" regression models were estimated to assess associations of parity period with NQTLs.Data Collection/extraction Methods: Optum provided four proprietary BH databases, including 2008-2013 data for 40 carve-out and 385 carve-in employers from Optum's claims processing databases and 2010 data from interviews conducted by Optum's parity compliance team with 49 carve-out employers.Principal Findings: Preparity, carve-out plans required preauthorization for in-network inpatient/intermediate care; otherwise coverage was denied. Postparity, 73 percent would review later by request and half charged no penalty for late authorization. Outpatient visit authorization requirements virtually disappeared. For carve-out out-of-network inpatient/intermediate care, and for carve-ins, plans changed penalties to match medical service policies, but this did not necessarily lead to fewer requirements or lower penalties.Conclusion: After 2011, MHPAEA was associated with the transformation of BH care management, including much less restrictive preauthorization requirements, especially for in-network care provided by carve-out plans. [ABSTRACT FROM AUTHOR]

Objective: To test whether underwriting modifies the effect of state-based incentives on individuals' purchase of long-term care insurance.Data Source: Health and Retirement Study (HRS), 1996-2012.Study Design: We estimated difference-in-difference regression models with an interaction of state policy indicators with individuals' probabilities of being approved for long-term care insurance.Data Extraction: We imputed probabilities of underwriting approval for respondents in the HRS using a model developed with underwriting decisions from two U.S. insurance firms. We measured the elasticity response to long-term care insurance price using changes in simulated after-tax price as an instrumental variable for premium price.Principal Findings: Tax incentives and Partnership programs increased insurance purchase by 3.62 percentage points and 1.8 percentage points, respectively, among those with the lowest risk (highest approval probability). Neither had any statistically significant effects among the highest risk individuals.Conclusions: We show that ignoring the effects of underwriting may lead to biased estimates of the potential state budget savings of long-term care insurance tax incentives. If the private market is to play a role in financing long-term care, policies need to address the underlying adverse selection problems. [ABSTRACT FROM AUTHOR]

Objective: To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending.Data Sources: 2011-2012 Truven MarketScan database.Study Design: I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression.Principal Findings: My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression.Conclusions: The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. [ABSTRACT FROM AUTHOR]

Objective: The Affordable Care Act and Medicare Access and CHIP Reauthorization Act are changing access to, and delivery of, health care in the United States, with potential implications for the field of health services research (HSR). We therefore investigated employers' perceptions of demand for individuals to conduct HSR, the competencies required for success, and implications for HSR training programs.Data Source: Interviews conducted in August 2016 with 21 key informants at a range of U.S.-based HSR organizations.Study Design: We conducted a semistructured, qualitative, telephone interview study to explore relevant topics.Data Collection/extraction Methods: Interviews with respondents were transcribed from recordings and then synthesized by respondent organization type and topic area.Principal Findings: Most respondents reported recently hiring health services researchers, and most anticipated hiring additional such researchers in the future. Most respondents emphasized the abilities to analyze data, work in teams, and engage with stakeholders. Finally, most respondents recommended that potential recruits gain real-world experience during their academic training.Conclusions: Our interviews indicated that current and future demand for health services researchers is strong. They also suggested that, as a field, HSR will continue to draw together individuals from a variety of backgrounds to inform a diverse array of decision makers. [ABSTRACT FROM AUTHOR]

Objective: This study examines the stock and supply including educational pipeline of health services researchers (HSRers) in the United States.Data Sources: National Institutes of Health Research Portfolio Online Reporting Tools, Agency for Healthcare Research and Quality Grants On-Line Database, Health Services Research Projects in Progress, PubMed, Integrated Postsecondary Education Data System, AcademyHealth membership database, and social networks.Study Design: Exploratory descriptive analysis of individuals involved in health services research (HSR) in the United States as of 2015/16.Principal Findings: The HSRer stock grew by 25 percent to 45 percent between 2007 and 2015/16, which was slower than the previous measurement period. The growth in the number of doctoral and master's degrees conferred in core HSR fields has been slowing in recent years. Minorities are underrepresented among HSRers, but this trend may improve over time given the diversity of the educational pipeline. Hispanics, however, were generally underrepresented in the educational pipeline.Conclusions: The average annual growth rate of HSRers appears to be within range of national recommendations. Additional work is needed to assess whether supply of HSRers is meeting demand and to ensure a competent and diverse educational pipeline that meets the needs of an evolving health system. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between cost and quality in Veterans Health Administration (VA) nursing homes (called Community Living Centers, CLCs) using longitudinal data.Data Sources/study Setting: One hundred and thirty CLCs over 13 quarters (from FY2009 to FY2012) were studied. Costs, resident days, and resident severity (RUGs score) were obtained from the VA Managerial Cost Accounting System. Clinical quality measures were obtained from the Minimum Data Set, and resident-centered care (RCC) was measured using the Artifacts of Culture Change Tool.Study Design: We used a generalized estimating equation model with facilities included as fixed effects to examine the relationship between total cost and quality after controlling for resident days and severity. The model included linear and squared terms for all independent variables and interactions with resident days.Principal Findings: With the exception of RCC, all other variables had a statistically significant relationship with total costs. For most poorer performing smaller facilities (lower size quartile), improvements in quality were associated with higher costs. For most larger facilities, improvements in quality were associated with lower costs.Conclusions: The relationship between cost and quality depends on facility size and current level of performance. [ABSTRACT FROM AUTHOR]

Objective: To compare the quality of care following admission to a nursing home (NH) with and without a dementia special care unit (SCU) for residents with dementia.Data Sources/study Setting: National resident-level minimum dataset assessments (MDS) 2005-2010 merged with Medicare claims and provider-level data from the Online Survey, Certification, and Reporting database.Study Design: We employ an instrumental variable approach to address the endogeneity of selection into an SCU facility controlling for a range of individual-level covariates. We use "differential distance" to a nursing home with and without an SCU as our instrument.Data Collection/extraction Methods: Minimum dataset assessments performed at NH admission and every quarter thereafter.Principal Findings: Admission to a facility with an SCU led to a reduction in inappropriate antipsychotics (-9.7 percent), physical restraints (-9.6 percent), pressure ulcers (-3.3 percent), feeding tubes (-8.3 percent), and hospitalizations (-14.7 percent). We found no impact on the use of indwelling urinary catheters. Results held in sensitivity analyses that accounted for the share of SCU beds and the facilities' overall quality.Conclusions: Facilities with an SCU provide better quality of care as measured by several validated quality indicators. Given the aging population, policies to promote the expansion and use of dementia SCUs may be warranted. [ABSTRACT FROM AUTHOR]

Objective: To develop a conceptual framework and preliminary item bank for childbirth-specific patient-reported outcome (PRO) domains.Data Sources: Women, who were U.S. residents, ≥18 years old, and ≥20 weeks pregnant, were surveyed regarding their childbirth values and preferences (V&P) using online panels.Study Design: Using community-based research techniques and Patient-Reported Outcomes Management Information System (PROMIS® ) methodology, we conducted a comprehensive literature review to identify self-reported survey items regarding patient-reported V&P and childbirth experiences and outcomes (PROs). The V&P/PRO domains were validated by focus groups. We conducted a cross-sectional observational study and fitted a multivariable logistic regression model to each V&P item to describe "who" wanted each item.Principal Findings: We identified 5,880 V&P/PRO items that mapped to 19 domains and 58 subdomains. We present results for the 2,250 survey respondents who anticipated a vaginal delivery in a hospital. Wide variation existed regarding each V&P item, and personal characteristics, such as maternal confidence and ability to cope well with pain, were frequent predictors in the models. The resulting preliminary item bank consisted of 60 key personal characteristics and 63 V&P/PROs.Conclusions: The conceptual framework and preliminary (PROMIS® ) item bank presented here provide a foundation for the development of childbirth-specific V&P/PROs. [ABSTRACT FROM AUTHOR]

Objective: To examine whether market competition is associated with improved health outcomes in hemodialysis.Data Sources: Secondary analysis of data from a national dialysis registry between 2001 and 2011.Study Design: We conducted one- and two-part linear regression models, using each hospital service area (HSA) as its own control, to examine the independent associations among market concentration and health outcomes.Data Collection: We selected cohorts of patients receiving in-center hemodialysis in the United States at the start of each calendar year. We used information about dialysis facility ownership and the location where patients received dialysis to measure an index of market concentration-the Hirschman-Herfindahl Index (HHI)-for HSA and year, which ranges from near zero (perfect competition) to one (monopoly).Principal Findings: An average reduction in HHI by 0.2 (one standard deviation in 2011) was associated with 2.9 fewer hospitalizations per 100 patient-years (95 percent CI, 0.4 to 5.4). If these findings were generalized to the entire in-center hemodialysis population, this would translate to 8,100 (95 percent CI 1,200 to 15,000) fewer hospitalizations in 2011. There was no association between change in market competition and mortality.Conclusions: Market competition in dialysis may lead to improved health outcomes. [ABSTRACT FROM AUTHOR]

Objective: To illustrate the impact of key quasi-experimental design elements on cost savings measurement for population health management (PHM) programs.Data Sources: Population health management program records and Medicaid claims and enrollment data from December 2011 through March 2016.Study Design: The study uses a difference-in-difference design to compare changes in cost and utilization outcomes between program participants and propensity score-matched nonparticipants. Comparisons of measured savings are made based on (1) stable versus dynamic population enrollment and (2) all eligible versus enrolled-only participant definitions. Options for the operationalization of time are also discussed.Data Collection/extraction Methods: Individual-level Medicaid administrative and claims data and PHM program records are used to match study groups on baseline risk factors and assess changes in costs and utilization.Principal Findings: Savings estimates are statistically similar but smaller in magnitude when eliminating variability based on duration of population enrollment and when evaluating program impact on the entire target population. Measurement in calendar time, when possible, simplifies interpretability.Conclusion: Program evaluation design elements, including population stability and participant definitions, can influence the estimated magnitude of program savings for the payer and should be considered carefully. Time specifications can also affect interpretability and usefulness. [ABSTRACT FROM AUTHOR]

Objective: To investigate magnitude and sources of discrepancy in quality metrics using claims versus electronic health record (EHR) data.Study Design: Assessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases.Data Collection/extraction: Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program-coded EHR extraction; manual review of selected EHRs.Principal Findings: Of 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD-9 codes, failure to submit claims, and others.Conclusions: Claims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. Use of claims data for these metrics is problematic. [ABSTRACT FROM AUTHOR]