State and Government Administrative Databases: Medicare, National Inpatient Sample (NIS), and State Inpatient Databases (SID) Programs.

The availability of large state and federally run administrative health-care databases provides potentially comprehensive population-wide information that can dramatically impact both medical and health-policy decision-making. Specific opportunities and important limitations exist with all administrative databases based on what information is collected and how reliably specific data elements are reported. Access to patient identifiable-level information can be critical for certain long-term outcome studies but can be difficult (although not impossible) due to patient privacy protections, while more easily available de-identified information can provide important insights that may be more than sufficient for some short-term operative or in-hospital outcome questions. The first section of this paper by Sarah K. Meier and Benjamin D. Pollock discusses Medicare and the different data files available to health-care researchers. They describe what is and is not generally available from even the most granular Medicare Standard Analytic Files, and provide an analysis of the strengths and weaknesses of Medicare administrative data as well as the resulting best and inappropriate uses of these data. In the second section, the Nationwide Inpatient Sample and complementary State Inpatient Database programs are reviewed by Steven M. Kurtz and Edmund Lau, with insights into the origins of these programs, the data elements that are recorded relating to the operative procedure and hospital stay, and examples of the types of studies that optimally utilize these data sources. They also detail the limitations of these databases and identify studies that they are not well-suited for, especially those involving linkage or longitudinal studies over time. Both sections provide useful guidance on the best uses and pitfalls related to these important large representative national administrative data sources.

Mental Health and Chemical Dependency Services at US Cancer Centers.

BACKGROUND: It is standard of care and an accreditation requirement to screen for and address distress and psychosocial needs in patients with cancer. This study assessed the availability of mental health (MH) and chemical dependency (CD) services at US cancer centers. METHODS: The 2017-2018 American Hospital Association (AHA) survey, Area Health Resource File, and Centers for Medicare & Medicaid Services Hospital Compare databases were used to assess availability of services and associations with hospital-level and health services area (HSA)-level characteristics. RESULTS: Of 1,144 cancer centers surveyed, 85.4% offered MH services and 45.5% offered CD services; only 44.1% provided both. Factors associated with increased adjusted odds of offering MH services were teaching status (odds ratio [OR], 1.76; 95% CI, 1.18-2.62), being a member of a hospital system (OR, 2.00; 95% CI, 1.31-3.07), and having more beds (OR, 1.04 per 10-bed increase; 95% CI, 1.02-1.05). Higher population estimate (OR, 0.98; 95% CI, 0.97-0.99), higher percentage uninsured (OR, 0.90; 95% CI, 0.86-0.95), and higher Mental Health Professional Shortage Area level in the HSA (OR, 0.99; 95% CI, 0.98-1.00) were associated with decreased odds of offering MH services. Government-run (OR, 2.85; 95% CI, 1.30-6.22) and nonprofit centers (OR, 3.48; 95% CI, 1.78-6.79) showed increased odds of offering CD services compared with for-profit centers. Those that were members of hospital systems (OR, 1.61; 95% CI, 1.14-2.29) and had more beds (OR, 1.02; 95% CI, 1.01-1.03) also showed increased odds of offering these services. A higher percentage of uninsured patients in the HSA (OR, 0.92; 95% CI, 0.88-0.97) was associated with decreased odds of offering CD services. CONCLUSIONS: Patients' ability to pay, membership in a hospital system, and organization size may be drivers of decisions to co-locate services within cancer centers. Larger organizations may be better able to financially support offering these services despite poor reimbursement rates. Innovations in specialty payment models highlight opportunities to drive transformation in delivering MH and CD services for high-need patients with cancer.

Impact of Patient Stage and Disease Characteristics on the proposed Radiation Oncology Alternative Payment Model (RO-APM).

PURPOSE: The proposed Radiation Oncology Alternative Payment Model (RO-APM) released on July 10, 2019, represents a dramatic shift from fee-for-service (FFS) reimbursement in radiation therapy (RT). This study compares historical revenue at Mayo Clinic to the RO-APM and quantifies the effect that disease characteristics may have on reimbursement. METHODS AND MATERIALS: FFS Medicare reimbursements were determined for patients undergoing RT at Mayo Clinic from 2015 to 2016. Disease categories and payment episodes were defined as per the RO-APM. Average RT episode reimbursements were reported for each disease site, except for lymphoma and metastases, and stratified by stage and disease subcategory. Comparisons with RO-APM reimbursements were made via descriptive statistics. RESULTS: A total of 2098 patients were identified, of whom 1866 (89%) were categorized per the RO-APM; 840 (45%) of those were aged >65 years. Breast (33%), head and neck (HN) (14%), and prostate (11%) cancer were most common. RO-APM base rate reimbursements and sensitivity analysis range were lower than historical reimbursement for bladder (-40%), cervical (-34%), lung (-28%), uterine (-26%), colorectal (-24%), upper gastrointestinal (-24%), HN (-23%), pancreatic (-20%), prostate (-16%), central nervous system (-13%), and anal (-10%) and higher for liver (+24%) and breast (+36%). Historical reimbursement varied with stage (stage III vs stage I) for breast (+57%, P < .01), uterine (+53%, P = .01), lung (+50%, P < .01), HN (+24%, P = .01), and prostate (+13%, P = .01). Overall, for patients older than 65 years of age, the RO-APM resulted in a -9% reduction in total RT reimbursement compared with historical FFS (-2%, -15%, and -27% for high, mid, and low adjusted RO-APM rates). CONCLUSIONS: Our findings indicate that the RO-APM will result in significant reductions in reimbursement at our center, particularly for cancers more common in underserved populations. Practices that care for socioeconomically disadvantaged populations may face significant reductions in revenue, which could further reduce access for this vulnerable population.

Patient attribution: why the method matters.

OBJECTIVES: To assess the impact of 5 commonly used patient attribution methods on measured healthcare cost, quality, and utilization metrics within an integrated healthcare delivery system. STUDY DESIGN: Cross-sectional analysis of administrative data of all patients attributed (by any of 5 methods) and/or paneled to a primary care provider (PCP) at Mayo Clinic Rochester (MCR) in 2011. METHODS: We retrospectively applied 5 attribution methods to MCR administrative data from January 1, 2010, to December 31, 2011. MCR is an integrated healthcare delivery system serving primary care and referral populations. The referral practice is geographically colocated but otherwise distinct from 6 primary care practice sites that include pediatric, internal medicine, and family medicine groups. Patients attributed by each method were compared on their concordance with PCP empanelment, quality measures, healthcare utilization, and total costs of care. RESULTS: The 5 methods attributed between 61,813 (42%) and 106,152 (72%) of paneled patients to a PCP at MCR, although not necessarily to the paneled PCP. There was marked variation in care utilization and total costs of care, but not quality measures, among patients attributed by the different methods and between those paneled versus not paneled. Patients with more primary care visits were more likely to be attributed by all methods. CONCLUSIONS: Reliable identification of the physician-patient relationship is necessary for accurate evaluation of healthcare processes, efficiencies, and outcomes. Optimization and standardization of attribution methods are therefore essential as health systems, payers, and policy makers seek to evaluate and improve the value of delivered care.

Risk Factors Associated With Health Care Utilization and Costs of Patients Undergoing Lower Extremity Joint Replacement.

BACKGROUND: The Comprehensive Care for Joint Replacement program implemented by the Centers for Medicare and Medicaid Services did not incorporate risk adjustment for lower extremity joint replacement (LEJR). Lack of adjustment places hospitals at financial risk and creates incentives for adverse patient selection. OBJECTIVE: To identify patient-level risk factors associated with health care utilization and costs of patients undergoing LEJR. METHODS: A comprehensive search of research databases from January 1, 1990, through January 31, 2016, was conducted. The databases included Ovid MEDLINE In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and SCOPUS and is reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The search identified 2020 studies. Eligible studies focused on primary unilateral and bilateral LEJR. Independent reviewers determined study eligibility and extracted utilization and cost data. RESULTS: Seventy-nine of 330 studies (24%) were included and were abstracted for analysis. Comorbidities, age, disease severity, and obesity were associated with increased costs. Increased number of comorbidities and age, presence of specific comorbidities, lower socioeconomic status, and female sex had evidence of increased length of stay. We found no significant association between indication for surgery and the likelihood of readmission. CONCLUSION: Developing a risk adjustment model for LEJR that incorporates clinical variables may serve to reduce the likelihood of adverse patient selection and enhance appropriate reimbursement aligned with procedural complexity.

Health Care Service Use Among Elderly Seasonal Migrators.

Elderly seasonal migrators share time between homes in different states, presenting challenges for care coordination and patient attribution methods. Medicare has prioritized alternative payment models, putting health care providers at risk for quality and value of services delivered to their attributed patients, regardless of the location of care. Little research is available to guide providers and payers on the service use of seasonal migrators. The authors use claims data on fee-for-service (FFS) Medicare beneficiaries' locations throughout the year to (1) identify seasonal migrators and (2) describe the care they receive in each seasonal home, focusing on primary care and emergency department (ED) visits and the relationships between the two. In all, 5.5% of the Medicare aged FFS population were identified as seasonal migrators, with 4.1% following the traditional snowbird pattern of migration, spending warm months in the north and cold months in the south. Migrators had higher rates of ED visits and primary care treatable (PCT) ED visits than the nonmigratory groups, controlling for location, age, race, sex, Medicaid status, season, and comorbidities. They also had more visits with specialist physicians, more days with outpatient services, and more days seeing a physician in any setting. Having local primary care strongly reduced rates of both PCT ED visits and total ED visits for all migration categories, with the greatest reduction seen in PCT ED visits by migrators (local primary care was associated with a 58% reduction in PCT ED visits by snowbirds and a 65% reduction in PCT ED visits by other migrators).

Redefining and Contextualizing the Hospital Volume-Outcome Relationship for Robot-Assisted Radical Prostatectomy: Implications for Centralization of Care.

PURPOSE: Robot-assisted radical prostatectomy has undergone rapid dissemination driven in part by market forces to become the most frequently used surgical approach in the management of prostate cancer. Accordingly, a critical analysis of its volume-outcome relationship has important health policy implications. Therefore, we evaluated the association of hospital robot-assisted radical prostatectomy volume with perioperative outcomes, and examined the distribution of hospital procedure volume to contextualize the volume-outcome relationship. MATERIALS AND METHODS: We identified 140,671 men who underwent robot-assisted radical prostatectomy from 2009 to 2011 in NIS (Nationwide Inpatient Sample). The associations of hospital volume with perioperative outcomes and total hospital costs were evaluated using multivariable logistic regression and generalized linear models. RESULTS: In 2011, 70% of hospitals averaged 1 robot-assisted radical prostatectomy per week or less, accounting for 28% of surgeries. Compared to patients treated at the lowest quartile hospitals, those treated at the highest quartile hospitals had significantly lower rates of intraoperative complications (0.6% vs 1.4%), postoperative complications (4.8% vs 13.9%), perioperative blood transfusion (1.5% vs 4.0%), prolonged hospitalization (4.3% vs 13.8%) and mean total hospital costs ($12,647 vs $15,394, all ptrend <0.001). When modeled as a nonlinear continuous variable, increasing hospital volume was independently associated with improved rates of each perioperative end point up to approximately 100 robot-assisted radical prostatectomies per year, beyond which there appeared to be marginal improvement. CONCLUSIONS: Increasing hospital robot-assisted radical prostatectomy volume was associated with improved perioperative outcomes up to approximately 100 surgeries per year, beyond which there appeared to be marginal improvement. A substantial proportion of these procedures is performed at low volume hospitals.

What fraction of Medicaid enrollees have private insurance coverage at the time of enrollment? Estimates from administrative data.

We use administrative data from Wisconsin to determine the fraction of new Medicaid enrollees who have private health insurance at the time of enrollment in the program. Through the linkage of several administrative data sources not previously used for research, we are able to observe coverage status directly for a large fraction of enrollees and indirectly for the remainder. We provide strict bounds for the percentages in each status and find that the percentage of new enrollees with private insurance coverage at the time of enrollment lies between 16 percent and 29 percent, and the percentage that dropped private coverage in favor of public insurance lies between 4 percent and 18 percent. Our point estimates indicate that, among all new enrollees, 21 percent had private health insurance at the time of enrollment and that 10 percent dropped this coverage. Our results show substantially lower rates than previous studies of crowd-out following public health insurance expansions and significant rates of dual coverage, whereby new enrollees into public insurance retain their previously held private insurance coverage.

The influence of different stimulation conditions on the assessment of antigen-induced CD154 expression on CD4+ T cells.

Recently, new methods have been introduced describing assessment of antigen-specific CD4+ T-cell immunity according to the induction of CD154 (CD40L) on CD4+ T cells during short-term activation. In our study, we have evaluated the influence of different stimulation conditions on the flow cytometric analysis of CD154 expression after antigenic in vitro activation. We used different cell preparation methods, antigen sources, and time periods of in vitro stimulation and analyzed their impact on intra and extracellular detection of antigen-induced CD154 expression on CD4+ T cells. We could demonstrate that analysis of CD4+ T-cell immunity according to CD154 expression displayed low intra-assay variability and was robust with respect to its induction in the course of a variety of stimulation conditions. For a basic quantitative evaluation of antigen-specific CD4+ T cells, surface CD154 analysis could be employed, enabling the fast analysis of live antigen-specific CD4+ T cells. Intracellular analysis of CD154 in combination with cytokines such as IL-2 and IFNgamma allowed quantitative and qualitative assessment of antigen-specific CD4+ T cells. The cytometric analysis of antigen-specific CD4+ T-cell immunity according to CD154 expression is characterized by robustness, high sensitivity, and low intra-assay variability.