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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]

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]

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 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 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 quantify the impact of two approaches (directed and query-based) to health information exchange (HIE) on potentially avoidable use of health care services.Data Sources/study Setting: Data on ambulatory care providers' adoption of HIE were merged with Medicare fee-for-service claims from 2008 to 2014. Providers were from 13 counties in New York served by the Rochester Regional Health Information Organization (RHIO).Study Design: Linear regression models with provider and year fixed effects were used to estimate changes in the probability of utilization outcomes for Medicare beneficiaries attributed to providers adopting directed and/or query-based HIE compared with beneficiaries attributed to providers who had not adopted HIE.Data Collection: Providers' HIE adoption status was determined through Rochester RHIO registration records. RHIO and claims data were linked via National Provider Identifiers.Principal Findings: Query-based HIE adoption was associated with a 0.2 percentage point reduction in the probability of an ambulatory care sensitive hospitalization and a 1.1 percentage point decrease in the likelihood of an unplanned readmission. Directed HIE adoption was not associated with any outcome.Conclusions: The Centers for Medicare & Medicaid Services' (CMS) EHR certification criteria includes requirements for directed HIE, but not query-based HIE. Pending further research, certification criteria should place equal weight on facilitating query-based and directed exchange. [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: The Medicare Modernization Act of 2004 allowed Medicare Advantage (MA) contracts to form provider networks in order to concentrate their patients among preferred providers. We focus on the skilled nursing facility (SNF) industry to assess patients' health when treating SNFs concentrate more patients from the same MA contract.Data Sources/study Setting: We use Medicare Beneficiary Summary File and Health, HEDIS, and the Minimum Data Set for patient attributes and OSCAR, LTCfocus.org, and Nursing Home Compare for SNF attributes. We include 1,069,436 MA enrollees newly admitted to SNF between 2012 and 2014.Study Design: Using a MA contract fixed-effect model, we examine the effect of prevalence of a patient's MA contract in the treating SNF on patient's health outcomes including 180-day survival, 30-day hospital readmission, 30-day home discharge, and nursing home length of stay. We use an Instrumental Variable (IV), the expected share of admissions in a SNF from patient's MA contract calculated using a McFadden choice model.Principal Findings: We find no relationship between SNF contract concentration and patients' outcomes after applying the IV.Conclusions: While MA plans appear to steer patients to specific SNFs, we do not observe significant returns to patient outcomes related to concentration. [ABSTRACT FROM AUTHOR]

Objective: Given the tremendous growth in assisted living (AL) over the past 20 years, it is important to understand how expansion has affected the demand for long-term care (LTC) provided in nursing homes (NHs). We estimated the effect of a change in county-level AL beds on the prevalence of private-pay residents and private-pay resident days at the NH-level.Data Sources: National census of large AL providers (25+ beds), and Minimum Data Set combined with Medicare enrollment records and claims from 2007 and 2014.Study Design: Retrospective longitudinal analysis of LTC markets.Principal Findings: Mean AL beds per county increased from 285 to 324, while NHs exhibited a decrease in private-pay residents (20.1 to 17.7 percent) and resident days (21.3 to 17.5 percent). An increase of 1,000 AL beds at the county level is associated with a reduction of 0.44 percentage points in private-pay resident days but is not significantly associated with percent of private-pay residents.Conclusions: These results suggest that increases in AL capacity have potentially allowed NH residents to delay or decrease their privately financed lengths of stay. As demand for AL continues to grow, it will be important to assess the effects on other LTC sectors. [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: 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 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 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]

The article argues that health information exchange and interoperability remain poor in both the inpatient and outpatient settings, despite progress in adoption of health information technology (HIT). It highlights need of investments in data normalization for using interoperability to improve clinical care, clinical decision support, and performance measurement.

Objective: To determine between-hospital variation in interventions provided to patients with do not resuscitate (DNR) orders.Data Sources/setting: United States Agency of Healthcare Research and Quality, Healthcare Cost and Utilization Project, California State Inpatient Database.Study Design: Retrospective cohort study including hospitalized patients aged 40 and older with potential indications for invasive treatments: in-hospital cardiac arrest (indication for CPR), acute respiratory failure (mechanical ventilation), acute renal failure (hemodialysis), septic shock (central venous catheterization), and palliative care. Hierarchical logistic regression to determine associations of hospital "early" DNR rates (DNR order placed within 24 hours of admission) with utilization of invasive interventions.Data Collection/extraction Methods: California State Inpatient Database, year 2011.Principal Findings: Patients with DNR orders at high-DNR-rate hospitals were less likely to receive invasive mechanical ventilation for acute respiratory failure or hemodialysis for acute renal failure, but more likely to receive palliative care than DNR patients at low-DNR-rate hospitals. Patients without DNR orders experienced similar rates of invasive interventions regardless of hospital DNR rates.Conclusions: Hospitals vary widely in the scope of invasive or organ-supporting treatments provided to patients with DNR orders. [ABSTRACT FROM AUTHOR]

Objective: To assess the impact of proxy survey responses on cancer care experience reports and quality ratings.Data Sources/study Setting: Secondary analysis of data from Cancer Care Outcomes Research and Surveillance (CanCORS). Recruitment occurred from 2003 to 2005.Study Design: The study was a cross-sectional observational study. The respondents were patients with incident colorectal or lung cancer or their proxies.Data Collection/extraction Methods: Analyses used linear regression models with an independent variable for proxy versus patient responses as well as study site and clinical covariates. The outcomes were experiences with medical care, nursing care, care coordination, and care quality rating. Multiple imputation was used for missing data.Principal Findings: Among 6,471 respondents, 1,011 (16 percent) were proxies. The proportion of proxy respondents varied from 6 percent to 28 percent across study sites. Adjusted proxy scores were modestly higher for medical care experiences (+1.28 points [95 percent CI:+ 0.05 to +2.51]), but lower for nursing care (-2.81 [95 percent CI: -4.11 to -1.50]) and care coordination experiences (-2.98 [95 percent CI: -4.15 to -1.81]). There were no significant differences between adjusted patient and proxy ratings of quality.Conclusions: Proxy responses have small but statistically significant differences from patient responses. However, if ratings of care are used for financial incentives, such differences could be exaggerated across practices or areas if proxy use varies. [ABSTRACT FROM AUTHOR]

Objectives: To determine how frequently patients revisit the emergency department after an initial encounter, and to describe revisit capture rates for the same hospital, health system, and geographic region.Data Sources/study Setting: Florida state data from January 1, 2010, to June 30, 2011, from the Healthcare Cost and Utilization Project.Study Design: This is a retrospective cohort study of emergency department return visits among Florida adults over an 18-month period. We evaluated pairs of index and 30-day return emergency department visits and compared capture rates for hospital, health system, and geographic units.Data Collection/extraction Methods: Data were obtained from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey Database.Principal Findings: Among 9,416,212 emergency department visits, 22.6 percent (2,124,441) were associated with a 30-day return. Seventy percent (1,477,772) of 30-day returns occurred to the same hospital. The 30-day return capture rates were highest within the same geographic area: county-level capture at 92 percent (IQR=86-96 percent) versus health system capture at 75 percent (IQR = 68-81 percent).Conclusions: Acute care utilization patterns are often independent of health system boundaries. Current population-based health care models that attribute patients to a single provider or health system may be strengthened by considering geographic patterns of acute care utilization. [ABSTRACT FROM AUTHOR]

Objective: Did mental health cost-sharing decrease following implementation of the Mental Health Parity and Addiction Equity Act (MHPAEA)?Data Source: Specialty mental health copayments, coinsurance, and deductibles, 2008-2013, were obtained from benefits databases for "carve-in" plans from a national commercial managed behavioral health organization.Study Design: Bivariate and regression-adjusted analyses compare the probability of use and (conditional) level of cost-sharing pre- and postparity. An interaction term is added to compare differential levels of pre- and postparity cost-sharing changes for plans that were and were not already at parity pre-MHPAEA.Findings: Controlling for employer/plan characteristics, MHPAEA is associated with higher intermediate care copayments ($15.9) but lower outpatient ($2.6) copayments among in-network-only plans. Among plans with in- and out-of-network benefits, MHPAEA is associated with lower inpatient ($23.2) and outpatient ($2.5) copayments, but increases in inpatient and intermediate in-network and out-of-network coinsurance (about 1 percentage point). Among the few plans not at parity pre-MHPAEA, changes in use and level of cost-sharing associated with MHPAEA were more dramatic.Conclusion: Mixed evidence that MHPAEA led to more generous mental health benefits may stem from the finding that many plans were already at parity pre-MHPAEA. Future policy focus in mental health may shift to slowing growth in cost-sharing for all health services. [ABSTRACT FROM AUTHOR]

Objective: (1) To evaluate the operational efficiency of various sampling methods for patient exit interviews; (2) to discuss under what circumstances each method yields an unbiased sample; and (3) to propose a new, operationally efficient, and unbiased sampling method.Study Design: Literature review, mathematical derivation, and Monte Carlo simulations.Principal Findings: Our simulations show that in patient exit interviews it is most operationally efficient if the interviewer, after completing an interview, selects the next patient exiting the clinical consultation. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings.Conclusion: Under the assumption that the order in which patients enter the consultation room is unrelated to the length of time spent with the clinician and the interviewer, selecting the next patient entering the consultation room tends to be the operationally most efficient unbiased sampling method for patient exit interviews. [ABSTRACT FROM AUTHOR]

Objective: To assess whether provider organizations exhibit distinct profiles of low-value service provision.Data Sources: 2007-2011 Medicare fee-for-service claims and enrollment data.Study Design: Use of 31 services that provide minimal clinical benefit was measured for 4,039,733 beneficiaries served by 3,137 provider organizations. Variation across organizations, persistence within organizations over time, and correlations in use of different types of low-value services within organizations were estimated via multilevel modeling, with adjustment for beneficiary sociodemographic and clinical characteristics.Principal Findings: Organizations provided 45.6 low-value services per 100 beneficiaries on average, with considerable variation across organizations (90th/10th percentile ratio, 1.78; 95 percent CI, 1.72-1.84), including substantial between-organization variation within hospital referral regions (90th/10th percentile ratio, 1.66; 95 percent CI, 1.60-1.71). Low-value service use within organizations was highly correlated over time (r, 0.98; 95 percent CI, 0.97-0.99) and positively correlated between 13 of 15 pairs of service categories (average r, 0.26; 95 percent CI, 0.24-0.28), with the greatest correlation between low-value imaging and low-value cardiovascular testing and procedures (r, 0.54).Conclusions: Use of low-value services in provider organizations exhibited substantial variation, high persistence, and modest consistency across service types. These findings are consistent with organizations shaping the practice patterns of affiliated physicians. [ABSTRACT FROM AUTHOR]

Objective: To understand the use of electronic health record (EHR) functionalities by physicians practicing in an underserved setting.Data Source/study Setting: A total of 333 Indian Health Service physicians (55 percent response rate) in August 2012.Study Design: Cross-sectional.Data Collection: The survey assessed routine use of EHR functionalities, perceived usefulness, and barriers to adoption.Principal Findings: Physicians routinely used a median 7 of 10 EHR functionalities targeted by the Meaningful Use program, but only 5 percent used all 10. Most (63 percent) felt the EHR improved quality of care. Many (76 percent) reported increased documentation time and poorer quality patient-physician interactions (45 percent). Primary care specialty and time using the EHR were positively associated with use of EHR functionalities, while perceived productivity loss was negatively associated.Conclusions: Significant opportunities exist to increase use of EHR functionalities and preserve physician-patient interactions and productivity in a resource-limited environment. [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 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: 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 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]

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]

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 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 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 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 compare methods of price measurement in health care markets.Data Sources: Truven Health Analytics MarketScan commercial claims.Study Design: We constructed medical prices indices using three approaches: (1) a "sentinel" service approach based on a single common service in a specific clinical domain, (2) a market basket approach, and (3) a spending decomposition approach. We constructed indices at the Metropolitan Statistical Area level and estimated correlations between and within them.Principal Findings: Price indices using a spending decomposition approach were strongly and positively correlated with indices constructed from broad market baskets of common services (r > 0.95). Prices of single common services exhibited weak to moderate correlations with each other and other measures.Conclusions: Market-level price measures that reflect broad sets of services are likely to rank markets similarly. Price indices relying on individual sentinel services may be more appropriate for examining specialty- or service-specific drivers of prices. [ABSTRACT FROM AUTHOR]

Objective: To determine if regions with high Medicare expenditures in a given setting remain high cost over time.Data Sources/study Setting: One hundred percent of national Medicare Parts A and B fee-for-service beneficiary claims data and enrollment for 1992-2010.Study Design: Patients are classified into regions. Claims are price-standardized. Risk adjustment is performed at the beneficiary level using the CMS Hierarchical Condition Categories model. Correlation analyses are conducted.Data Collection/extraction Methods: The data were obtained through a contract with CMS for a study performed for the Institute of Medicine.Principal Findings: High-cost regions in 1992 are likely to remain high cost in 2010. Stability in regional spending is highest in the home health, inpatient hospital, and outpatient hospital settings over this time period. Despite the persistence of a region's relative spending over time, a region's spending levels in all settings except home health tend to regress toward the mean.Conclusions: Relatively high-cost regions tend to remain so over long periods of time, even after controlling for patient health status and geographic price variation, suggesting that the observed effect reflects real differences in practice patterns. [ABSTRACT FROM AUTHOR]