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Establishing care with primary care and specialist clinicians is critical for Medicare beneficiaries with complex care needs. However, beneficiaries with disabilities may struggle to access ambulat...

BACKGROUND: Rural Americans have less access to care than urban Americans. Preventable acute care use is a marker of unmet ambulatory healthcare needs, but little is known about how such utilization has differed between rural and urban areas over time. OBJECTIVE: Compare preventable emergency department (ED) visit and hospitalization rates among rural versus urban residents over the past decade. DESIGN: Observational study using a validated algorithm to compute age-sex-adjusted rates per 100,000 individuals of preventable ED visits and hospitalizations. Differences in overall, annual, and condition-specific rates for rural versus urban residents were assessed and linear regression was used to assess 10-year trends. SETTING: Nationwide Emergency Department Sample, National Inpatient Sample, and US Census, 2008–2017. PARTICIPANTS: US adults, an annual average of 241.3 million individuals. MEASUREMENTS: Preventable ED visits and hospitalizations. RESULTS: Compared to urban residents, rural residents had 45% higher rates of preventable ED visits in 2008 (3003 vs. 2070 per 100,000, adjusted difference [AD]: 933; 95% CI: 928–938) and 44% higher rates of preventable ED visits in 2017 (3911 vs. 2708 per 100,000, AD: 1202; 95% CI: 1196–1208). Rural residents had 26% higher rates of preventable hospitalizations in 2008 (2104 vs. 1666 per 100,000, AD: 439; 95% CI: 434–443) and 13% higher rates in 2017 (1634 vs. 1440 per 100,000, AD: 194; 95% CI: 190–199). Preventable ED visits increased more in absolute terms in rural versus urban residents, but the percentage increase was similar (30% vs. 31%) because rural residents started at a higher baseline. Preventable hospitalizations decreased at a faster rate (22% vs. 14%) among rural versus urban residents. LIMITATIONS: Observational study; unable to infer causality. CONCLUSIONS: Rural disparities in acute care use are narrowing for preventable hospitalizations but have persisted for all preventable acute care use, suggesting unmet demand for high-quality ambulatory care in rural areas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06532-4.

This study used a claims-based frailty index to investigate outcomes of frail patients with heart failure (HF).Medicare value-based payment programs financially reward and penalize hospitals based on HF patients' outcomes. Although programs adjust risks for comorbidities, they do not adjust for frailty. Hospitals caring for high proportions of frail patients may be unfairly penalized. Understanding frail HF patients' outcomes may allow improved risk adjustment and more equitable assessment of health care systems.Adapting a claims-based frailty index, the study assigned a frailty score to each adult in the National in-patient Sample (NIS) from 2012 through September 2015 with a primary diagnosis of HF and dichotomized frailty by using a cutoff value established in the general NIS population. Multivariate regression models were estimated, controlling for comorbidities and hospital characteristics, to investigate relationships between frailty and outcomes.Of 732,932 patients, 369,298 were frail. Frail patients were more likely than nonfrail patients to die during hospital stay (3.57% vs. 2.37%, respectively; adjusted odds ratio [aOR]: 1.67; 95% confidence interval [CI]: 1.61 to 1.72; p 0.001); were less likely to be discharged to home (66.5% vs. 79.3%, respectively; aOR: 0.58; 95% CI: 0.57 to 0.58; p 0.001); were hospitalized for more days (5.89 vs. 4.63 days, respectively; adjusted coefficient: 0.21 days; 95% CI: 0.21 to 0.22; p 0.001); and incurred higher charges ($47,651 vs. $40,173, respectively; adjusted difference = $9,006; 95% CI: $8,596 to $9,416; p 0.001).Frail patients with HF had significantly poorer outcomes than nonfrail patients after accounting for comorbidities. Clinicians should screen for frailty to identify high-risk patients who could benefit from targeted intervention. Policymakers should perform risk adjustments for frailty for more equitable quality measurement and financial incentive allocation.

Hospitalizations for ambulatory care–sensitive conditions indicate barriers to care outside of inpatient settings. We found that Medicaid expansions under the Affordable Care Act were associated wi...

BACKGROUND: Ambulatory care-sensitive condition (ACSC) hospitalizations are used to evaluate physicians’ performance in Medicare value-based payment programs. However, these measures may disadvantage physicians caring for vulnerable populations because they omit social, cognitive, and functional factors that may be important determinants of hospitalization. OBJECTIVE: To determine whether social, cognitive, and functional risk factors are associated with ACSC hospitalization rates and whether adjusting for them changes outpatient safety-net providers’ performance. DESIGN: Using data from the Medicare Current Beneficiary Survey, we conducted patient-level multivariable regression to estimate the association (as incidence rate ratios (IRRs)) between patient-reported social, cognitive, and functional risk factors and ACSC hospitalizations. We compared outpatient safety-net and non-safety-net providers’ performance after adjusting for clinical comorbidities alone and after additional adjustment for social, cognitive, and functional factors captured in survey data. SETTING: Safety-net and non-safety-net clinics. PARTICIPANTS: Community-dwelling Medicare beneficiaries contributing 38,616 person-years from 2006 to 2013. MEASUREMENTS: Acute and chronic ACSC hospitalizations. RESULTS: After adjusting for clinical comorbidities, Alzheimer’s/dementia (IRR 1.30, 95% CI 1.02–1.65), difficulty with 3–6 activities of daily living (ADLs) (IRR 1.43, 95% CI 1.05–1.94), difficulty with 1–2 instrumental ADLs (IADLs, IRR 1.54, 95% CI 1.26–1.90), and 3–6 IADLs (IRR 1.90, 95% CI 1.49–2.43) were associated with acute ACSC hospitalization. Low income (IRR 1.28, 95% CI 1.03–1.58), lack of educational attainment (IRR 1.33, 95% CI 1.04–1.69), being unmarried (IRR 1.18, 95% CI 1.01–1.36), difficulty with 1–2 IADLs (IRR 1.30, 95% CI 1.05–1.60), and 3–6 IADLs (IRR 1.44, 95% CI 1.16–1.80) were associated with chronic ACSC hospitalization. Adding these factors to standard Medicare risk adjustment eliminated outpatient safety-net providers’ performance gap (p

Objective To estimate the cost of infections associated with multidrug-resistant organisms (MDROs) during inpatient hospitalization in the United States. Data sources/study setting 2014 National Inpatient Sample. Study design Multivariable regression models assessed the incremental effect of MDROs on the cost of hospitalization and hospital length of stay among patients with bacterial infections. Data collection/extraction methods We retrospectively identified 6 385 258 inpatient stays for patients with bacterial infection. Principal findings The national incidence rate of inpatient stays with bacterial infection is 20.1 percent. At least 10.8 percent of such stays-and as many as 16.9 percent if we account for undercoded infections-show evidence of one or more MDROs. MRSA, C. difficile, infection with another MDRO, and the presence of more than one MDRO are associated with $1718 (95% CI, $1609-$1826), $4617 (95% CI, $4407-$4827), $2302 (95% CI, $2044-$2560), and $3570 (95% CI, $3019-$4122) in additional costs per stay, respectively. The national cost of infections associated with MDROs is at least $2.39 billion (95% CI, $2.25-$2.52 billion) and as high as $3.38 billion (95% CI, $3.13-$3.62 billion) if we account for undercoded infections. Conclusions Infections associated with MDROs result in a substantial cost burden to the US health care system.

The aim of the study was to estimate hospitalization cost, and factors associated with hospitalization costs and length of stay (LOS) of patients treated for head and neck cancer in the United States.Data on 71,440 weighted hospital admissions from the 2014 National Inpatient Sample with a diagnosis of head and neck cancer were examined. Multivariable linear regression models estimated factors associated with hospitalization costs, and negative binomial regression models were used to identify factors associated with hospital LOS. Factor variables included characteristics of the patient, clinical, and hospital characteristics.The average hospitalization cost was US $18,371 and the average LOS was 6.6 days. LOS was significantly associated with admissions involving bacterial infection, major operating procedures, chemo procedure, and radiation procedure as well as admissions at medium or small bed size hospitals, and rural hospitals. Admissions among black patients, elective admissions, admissions involving bacterial infection, major operating procedures, chemo procedure, radiation procedure, and advance comorbidities were associated with increased hospitalization costs. In contrast, admissions at urban nonteaching or rural had increased hospitalization costs.Admissions that involve higher number of comorbidities, metastasis, bacterial infection, radiation, and chemo procedures had longer hospital stay and higher cost whereas admissions are rural hospitals had shorter hospital stay and lower cost. Understanding these factors associated with increased LOS and hospitalization cost will help efforts to decrease health care cost and improve quality of care.

IMPORTANCE: Integration of physician practices into health systems composed of hospitals and multispecialty practices is increasing in the era of value-based payment. It is unknown how clinicians who affiliate with such health systems perform under the new mandatory Centers for Medicare & Medicaid Services Merit-based Incentive Payment System (MIPS) relative to their peers. OBJECTIVE: To assess the relationship between the health system affiliations of clinicians and their performance scores and value-based reimbursement under the 2019 MIPS. DESIGN, SETTING, AND PARTICIPANTS: Publicly reported data on 636 552 clinicians working at outpatient clinics across the US were used to assess the association of the affiliation status of clinicians within the 609 health systems with their 2019 final MIPS performance score and value-based reimbursement (both based on clinician performance in 2017), adjusting for clinician, patient, and practice area characteristics. EXPOSURES: Health system affiliation vs no affiliation. MAIN OUTCOMES AND MEASURES: The primary outcome was final MIPS performance score (range, 0-100; higher scores intended to represent better performance). The secondary outcome was MIPS payment adjustment, including negative (penalty) payment adjustment, positive payment adjustment, and bonus payment adjustment. RESULTS: The final sample included 636 552 clinicians (41% female, 83% physicians, 50% in primary care, 17% in rural areas), including 48.6% who were affiliated with a health system. Compared with unaffiliated clinicians, system-affiliated clinicians were significantly more likely to be female (46% vs 37%), primary care physicians (36% vs 30%), and classified as safety net clinicians (12% vs 10%) and significantly less likely to be specialists (44% vs 55%) (P

Background: Risk models in the private insurance setting may systematically underpredict in the socially disadvantaged. In this study, we sought to determine whether US minority Medicare beneficiaries had disproportionately low costs compared with their clinical outcomes and whether adding social determinants of health (SDOH) into risk prediction models improves prediction accuracy. Methods and Results: Retrospective observational cohort study of 2016 to 2017 Medicare Current Beneficiary Survey data (n=3614) linked to Medicare fee-for-service claims. Logistic and linear regressions were used to determine the relationship between race/ethnicity and annual costs of care, all-cause hospitalization, cardiovascular hospitalization, and death. We calculated the observed-to-expected (O:E) ratios for all outcomes under 4 risk models: (1) age+sex, (2) model 1+clinical comorbidity adjustment, (3) model 2+SDOH, and (4) SDOH alone. Our sample was 44% male and 11% black or Hispanic. Among minorities, adverse clinical outcomes were inversely related to cost. After multivariable adjustment, blacks/Hispanics had higher rates of cardiovascular hospitalization (incidence rate ratio, 1.78; P =0.012) but similar annual costs ($−336, P =0.77) compared with whites. Among whites, models 1 to 4 all showed similar O:E ratios, suggesting high accuracy in risk prediction using current models. Among minorities, adjustment for age, sex, and comorbidities underpredicted all-cause hospitalization by 20% (O:E, 1.20) and cardiovascular hospitalization by 70% (O:E, 1.70) and overpredicted death by 21% (O:E, 0.79); adding SDOH brought O:E near 1 for all outcomes. Among both groups, the SDOH risk model alone performed with equal or superior accuracy to the model based on clinical comorbidities. Conclusions: A paradoxical relationship was observed between clinical outcomes and costs among racial and ethnic minorities. Because of systematic differences in access to care, cost may not be an appropriate surrogate for predicting clinical risk among vulnerable populations. Adjustment for SDOH improves the accuracy of risk models among racial and ethnic minorities and could guide use of prevention strategies.

Background and objective Healthcare-associated infections (HAIs) are common and often preventable complications of care, with reduction emphasized in national policy. The Centers for Medicare and Medicaid Services introduced an HAI-focused Hospital Acquired Condition Reduction Program in 2015 to penalize poor-performing hospitals. Standardized infection ratios (SIRs) are used for comparisons between healthcare organizations, though they are not adjusted for socioeconomic risks known to impact infection. The objectives of this study were to assess the relationship between hospital-area deprivation with reported SIRs and reimbursement penalties. Methods This was a cohort study using 2018 Hospital Compare, as well as area deprivation data and other hospital characteristics. Multivariable regression models were used to evaluate associations between hospital-area deprivation and SIR reporting as well as payment reduction, adjusting for case mix index and hospital ownership. Results Of the 2102 unique hospitals in our study, 12.8% reported at least one worse than national benchmark SIR and 23.7% had a payment reduction. After adjustment, there was a 17% increased risk of reporting worse than benchmarked SIRs with quartile increases in deprivation (95% confidence interval: 5%-30%, P = .004). Despite this, there were no significant relationships between reimbursement penalties and ADI (risk ratio: 1.00, 95% confidence interval: 0.997-1.005, P = .567). Conclusions This study documented a significant relationship between hospital-area deprivation and the risk of reporting worse than national benchmark SIRs. Though this did not appear to translate to Hospital Acquired Condition Reduction Program penalties in this dataset, it reinforces problems with the current use of SIRs for interhospital comparisons.

Background Medicare uses the Centers for Medicare & Medicaid Services Hierarchical Condition Category (CMS-HCC) model to predict patients' annualized Medicare costs in value-based payment programs. The CMS-HCC model does not include measures of frailty, and prior research shows that it systematically underpredicts costs for frail Medicare beneficiaries. Objective To determine whether a claims-based frailty index can improve Medicare cost prediction. Design Retrospective cohort study. Setting Medicare Current Beneficiary Survey linked to Medicare claims, 2006 to 2013. Participants 16 535 community-dwelling, fee-for-service beneficiaries representing 26 705 patient-years. Measurements Patient frailty status was classified using a validated claims-based frailty index. The association between the frailty index and annualized Medicare costs was examined, and regression methods were used to compare observed Medicare costs versus predictions based on the standard CMS-HCC model with and without the frailty index. Results Mean costs were $5724 for the 8910 patients classified as robust (46.4% of patient-years), $12 462 for the 8405 prefrail patients (41.6%), $26 239 for the 2215 mildly frail patients (9.6%), and $44 586 for the 593 patients classified as moderately to severely frail (2.5%). The frailty index addition to the CMS-HCC model predicted on average an additional $2712, $7915, and $16 449 in costs for prefrail, mildly frail, and moderately to severely frail patients, respectively, beyond the CMS-HCC model alone. On average, the model with the frailty index addition resulted in more accurate predictions of costs for patients at all 4 levels of frailty. However, observed costs remained more widely distributed than predictions from the enhanced model at all levels of frailty. Limitation The claims-based index is a proxy for frailty and is likely less accurate than an in-person examination. Conclusion The CMS-HCC model with the frailty index addition is an improvement over current Medicare cost prediction. Primary funding source None.

OBJECTIVE: To identify patient social risk factors associated with Continuity of Care (COC) index. DATA SOURCES/STUDY SETTING: Medicare Current Beneficiary Survey (MCBS), the Dartmouth Institute, and Area Resource File for 2006‐2013. STUDY DESIGN: We use regression methods to assess the effect of patient social risk factors on COC after adjusting for medical complexity. In secondary analyses, we assess the effect of social risk factors on annual utilization of physicians and specialists for evaluation and management (E&M). DATA COLLECTION/EXTRACTION METHODS: We retrospectively identified 59 499 patient years for Medicare beneficiaries with one year of enrollment and three or more E&M visits. PRINCIPAL FINDINGS: After adjustment for medical complexity, individual‐level social risk factors such as lack of education, low income, and living alone are all associated with better patient COC (P

Objective To document erosion in the New York University Emergency Department (ED) visit algorithm's capability to classify ED visits and to provide a “patch” to the algorithm. Data Sources The Nationwide Emergency Department Sample. Study Design We used bivariate models to assess whether the percentage of visits unclassifiable by the algorithm increased due to annual changes to ICD-9 diagnosis codes. We updated the algorithm with ICD-9 and ICD-10 codes added since 2001. Principal Findings The percentage of unclassifiable visits increased from 11.2 percent in 2006 to 15.5 percent in 2012 (p

People living in rural areas have worse health outcomes than their urban counterparts do. Understanding what factors account for this could inform policy interventions for reducing rural-urban disparities in health. We examined a nationally representative survey of Medicare beneficiaries with one or more complex chronic conditions, which represented 61 percent of rural and 57 percent of urban Medicare beneficiaries. We found that rural residence was associated with a 40 percent higher preventable hospitalization rate and a 23 percent higher mortality rate, compared to urban residence. Having one or more specialist visits during the previous year was associated with a 15.9 percent lower preventable hospitalization rate and a 16.6 percent lower mortality rate for people with chronic conditions, after we controlled for having one or more primary care provider visits. Access to specialists accounted for 55 percent and 40 percent of the rural-urban difference in preventable hospitalizations and mortality, respectively. Medicare should consider interventions for rural beneficiaries who lack access to specialist care to reduce rural-urban disparities in health outcomes.

OBJECTIVES Medicare value-based payment programs evaluate physicians' performance on their patients' annual Medicare costs and clinical outcomes. However, little is known about how geriatricians, who disproportionately provide care for medically complex older adults, perform on these measures. DESIGN A retrospective study using multivariable regression methods to estimate the association of geriatric risk factors with annualized Medicare costs and preventable hospitalization rates and to compare geriatricians' performance on these outcomes to other primary care physicians (PCPs) under standard Medicare risk adjustment and after adding additional adjustment for geriatric risk factors. SETTING Eight years (2006-2013) of cohort data from the Medicare Current Beneficiary Survey. PARTICIPANTS Medicare beneficiaries, aged 65 years and older, with primary care services contributing 27 027 person-years of data. MEASUREMENTS Outcomes were costs and preventable hospitalization rates; geriatric risk factors were patient frailty, long-term institutionalization, dementia, and depression. RESULTS Geriatricians were more likely to care for patients with frailty (22.8% vs 14.1%), long-term institutionalization (12.0% vs 4.7%), dementia (21.6% vs 10.2%), and depression (23.6% vs 17.4%) than other PCPs (P

This study assesses the association between US clinicians’ caseload of minority patients and their 2019 Medicare Merit-based Incentive Payment System performance score.

In order to assess consistency across quality measures for Untied States hospitals, this paper uses patient responses to the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey for three years (2009-2011) from 1,333 acute-care hospitals in fourteen states to analyze patterns in hospital-reported patient experience-of-care scores by diagnosis-specific process and outcome measures for acute myocardial infarction, heart failure, and pneumonia. We also evaluate how scores have changed over the three-year period. We find significant differences in patient experience-of-care scores for 195 out of 230 relationships between HCAHPS patient experience-of-care scores and 23 diagnosis-specific process and outcomes measures. We find nearly no significant differences in changes in scores from 2009-2011 (8 out of 230) when comparing the same experience-of-care and diagnosis-specific quality measures. For the majority of measures, high scores on the quality metrics were associated with high patient experience-of-care scores.

Our objective was to describe and evaluate an innovative approach to combining worksite wellness and ergonomics, with an emphasis on retention and absenteeism during the intervention. The study enrolled 280 employee participants in a 3-year cluster randomized, controlled trial conducted at The University of Iowa, 5 local businesses, and 1 regional business. Our results showed a 90% retention rate with lower estimated absenteeism (although not statistically significant) in the intervention group compared with the control group. This type of highly interactive and integrated short intervention has the capacity to result in high levels of participation with the potential to reduce absenteeism.

Objectives Only one in three head and neck cancer (HNC) patients present with early-stage disease. We aimed to quantify associations between state Medicaid expansions and changes in insurance coverage rates and stage at diagnosis of HNC. Methods Using a quasi-experimental difference-in-differences (DID) approach and data from 26,330 cases included in the Surveillance, Epidemiology, and End Results program (2011–2015), we retrospectively examined changes in insurance coverage and stage at diagnosis of adult HNC in states that expanded Medicaid (EXP) versus those that did not (NEXP). Results There was a significant increase in Medicaid coverage in EXP (+1.6 percentage point (PP) versus) vs. NEXP (-1.8 PP) states (3.36 PP, 95% CI = 1.32, 5.41; p = 0.001), and this increase was mostly among residents of low income and education counties. We also observed a reduction in uninsured rates among HNC patients in low income counties (−4.17 PP, 95% CI = −6.84, −1.51; p = 0.002). Overall, early stage diagnosis rates were 28.3% (EXP) vs. 26.7% (NEXP), with significant increases in early stage diagnosis post-Medicaid expansion among young adults, 18–34 years (17.2 PP, 95% CI – 1.34 to 33.1, p = 0.034), females (7.54 PP, 95% CI = 2.00 to 13.10, p = 0.008), unmarried patients (3.83 PP, 95% CI = 0.30–7.35, p = 0.033), and patients with lip cancer (13.5 PP, 95% CI = 2.67–24.3, p = 0.015). Conclusions Medicaid expansion is associated with improved insurance coverage rates for HNC patients, particularly those with low income, and increases in early stage diagnoses for young adults and women.

Objective: Access to care is an important issue for head and neck cancer (HNC) patients as HNC is one of the most expensive cancers, particularly for late stage disease. While some data show increased insurance coverage with Medicaid expansion, evidence is limited for impacts on socioeconomic disparities in insurance or on stage at diagnoses. This study aimed to quantify the impact of state Medicaid expansion status on insurance status and stage at diagnosis in HNC patients. Methods: Using a quasi-experimental design, the 2011-2015 Surveillance, Epidemiology, and End Results database was queried for adults with HNC in the United States. Changes in insurance coverage and stage at diagnosis after 2014 in states that expanded Medicaid (EXP) were compared to changes in states that did not expand Medicaid (NEXP). Difference-in-differences analyses were used to assess changes in the percentage of Medicaid coverage, uninsured, and early stage diagnoses in EXP relative to NEXP states. Results: A total of 26,330 HNC cases were identified. In difference-in-difference analyses, we observed an increase in Medicaid insurance in expansion relative to non-expansion states (3.36 percentage points (PP), 95% CI = 1.32, 5.41, p=.001), especially for residents of low income and education counties. We also observed a reduction in uninsured status among HNC patients in low income counties (-4.17 PP, 95% CI = -6.84, -1.51; p=.002). Additionally, we found significant increases among young adults age 18-34 years (17.2 PP, 95% CI – 1.34, 33.10, p=0.034), females (7.54 PP, 95% CI = 2.00, 13.10, p=0.008), unmarried patients (3.83 PP, 95% CI = 0.30, 7.35, p=0.033), and patients with cancer of the lip (13.5 PP, 95% CI = 2.67, 24.30, p=0.015). There was some evidence for greater expansion-associated increases in early stage diagnoses for non-Hispanic blacks (8.53 PP) and other races (20.4 PP) relative to white HNC patients (p=.025). Conclusions: Medicaid expansion is associated with improved insurance coverage for HNC patients, particularly those with low income, and increased early stage diagnoses for young adults and for racial/ethnic minorities. Thus, Medicaid expansion may improve access to care for patients with HNC. Our findings are particularly relevant at a time when there is debate in the United States about healthcare financing, Medicaid, and the Affordable Care Act. Citation Format: Nosayaba Osazuwa-Peters, Justin M Barnes, Eric Adjei Boakye, Matthew E Gaubatz, Kenton J Johnston, Neelima Panth, Rosh KV Sethi, Uchechukwu Megwalu, Mark A Varvares. Effect of state Medicaid expansion status on insurance coverage and stage at diagnosis in head and neck cancer patients [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A121.

Importance Medicare is moving toward value-based payment. The Merit-Based Incentive Payment System (MIPS) program judges outpatient clinicians’ performance on a measure of annual Medicare spending. However, this measure may disadvantage outpatient clinicians who care for vulnerable populations because the algorithm omits meaningful determinants of cost. Objectives To determine whether factors not included in Medicare risk adjustment, including patient neuropsychological and functional status, as well as local area health resources and economic conditions, are associated with Medicare total annual cost of care (TACC), and evaluate whether accounting for these factors is associated with improved TACC performance by outpatient safety-net clinicians. Design, Setting, and Participants In this retrospective observational study, we used the Medicare Current Beneficiary Survey (MCBS) to examine patient-reported neuropsychological and functional status and the Area Health Resources File to obtain information on local area characteristics. Included were Medicare beneficiaries with annual physician or clinic visits to outpatient safety-net (federally qualified health centers and rural health clinics) and non–safety-net clinics, contributing 76 927 person-years of data to the MCBS from 2006 through 2013. We used patient-level multivariable regression models to estimate the association between each factor and annual Medicare spending, and compared outpatient safety-net performance under current risk adjustment and after adding additional adjustment for these factors. Main Outcomes and Measures Medicare TACC, measured as the total annual reimbursed amount per patient for Medicare Part A and Part B services, in all categories. Results Our study included 111 414 unique identifiable physicians, and the final weighted sample included 213 904 324 patient-years (unweighted, 76 927 patient-years) from 30 058 unique patients, of whom 17 478 (58.1%) were women. The mean (SD) patient age was 71.84 (12.48) years. The mean TACC was $9117. Those with higher than mean TACC included beneficiaries with depression ($14 436), dementia ($18 311), and difficulty with 3 or more activities of daily living (ADLs, $19 113) or instrumental ADLs ($17 443). After adjusting for comorbidities, depression and dementia were still associated with $2740 (95% CI, $2200-$2739) and $2922 (95% CI, $2399-$3445) higher TACC, respectively. Difficulty with 3 or more ADLs ($3121 higher; 95% CI, $2633-$3609) or instrumental ADLs ($895 higher; 95% CI, $452-$1337) was also associated with higher TACC. Adding these neuropsychological and functional factors, as well as local residence area factors, to risk adjustment calculations reduced outpatient safety-net clinicians’ underperformance on Medicare TACC relative to non-safety–net clinicians by 52% (from 0.098 to 0.047 difference in the observed to expected ratio). Conclusions and Relevance Neuropsychological and functional impairment are common in Medicare beneficiaries and are associated with increased annual Medicare spending. Failure to account for these factors may inappropriately penalize outpatient clinicians who care for these vulnerable groups, such as safety-net clinicians, for factors that are arguably beyond their control.

This paper uses patient responses to the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey for three years (2009-2011) from 1,333 acute-care hospitals in fourteen states to analyze patterns in 10 hospital-reported patient experience-of-care scores by 29 characteristics classified as: patient characteristics, payer source, patient severity, hospital characteristics, hospital operations, and market characteristics. We also evaluate how scores have changed over the three-year period. We find significant differences in patient experience-of-care scores by hospital characteristics for 250 out of 290 HCAHPS-hospital characteristic combinations measured. We find fewer significant differences in changes in scores from 2009-2011 (135 out of 290), with hospitals categorized as high scoring also reporting consistently greater improvement. We conclude that patient experience-of-care scores vary by hospital characteristics, although improvements in scores show less variety by hospital categorization.

Objective To examine the effects of physician division of labor and patient continuity of care (COC) on the care quality and outcomes of older adults with complex chronic conditions. Data Sources/Study Setting Seven years (2006–2012) of panel data from the Medicare Current Beneficiary Survey (MCBS). Study Design Regression models were used to estimate the effect of the specialty-type of physicians involved in annual patient evaluation and management, as well as patient COC, on simultaneous care processes and following year outcomes. Data Collection/Extraction Methods Multiyear cohorts of Medicare beneficiaries with diabetes and/or heart failure were retrospectively identified to create a panel of 15,389 person-year observations. Principal Findings Involvement of both primary care physicians and disease-relevant specialists is associated with better compliance with process-of-care guidelines, but patients seeing disease-relevant specialists also receive more repeat cardiac imaging (p

To quantify the direct and indirect costs of employee depression, anxiety, and emotional disorders at one large employer in 2004 using administrative data sources.Health care claims, personnel, disability, and productivity data were merged at the individual employee level. Direct medical costs were attributed to disease status using Episode Treatment Groups, and indirect costs were attributed using regression models and relative weights.Depression, anxiety, and emotional disorders were the fifth costliest of all disease categories. The average cost per case was $1646, with 53% coming from indirect costs and 47% from direct costs.The cost burden of depression, anxiety, and emotional disorders is among the greatest of any disease conditions in the workforce. It is worth considering methods for quantifying direct and indirect costs that use administrative data sources given their utility.

OBJECTIVE To evaluate the impact of a pilot workplace health partner intervention delivered by a predictive health institute to university and academic medical center employees on per-member, per-month health care expenditures. METHODS We analyzed the health care claims of participants versus nonparticipants, with a 12-month baseline and 24-month intervention period. Total per-member, per-month expenditures were analyzed using two-part regression models that controlled for sex, age, health benefit plan type, medical member months, and active employment months. RESULTS Our regression results found no statistical differences in total expenditures at baseline and intervention. Further sensitivity analyses controlling for high cost outliers, comorbidities, and propensity to be in the intervention group confirmed these findings. CONCLUSIONS We find no difference in health care expenditures attributable to the health partner intervention. The intervention does not seem to have raised expenditures in the short term.