BACKGROUND AND AIMS:Understanding of population-level outcomes for patients with Guillain-Barré syndrome (GBS) remains limited. We identified which GBS patients are most likely to experience worse outcomes using the largest and most current GBS cohort in the United States. METHODS:This retrospective cohort study used 2005-2020 fee-for-service Medicare claims to identify individuals newly diagnosed with GBS (N = 16 280). We used three person-level modified Poisson regressions to estimate hospital and intensive care unit (ICU) lengths of stay and GBS episode length as a function of sociodemographic characteristics, comorbid conditions, and year of diagnosis. We also documented hospital-acquired pressure ulcers and deep vein thromboses as quality indicators. RESULTS:Median hospital length of stay was 9 days [IQR: 6-18 days] and median GBS episode length was 26 days [IQR: 10-60 days]. Approximately 43% of patients spent time in the ICU, with most of those stays (57%) lasting ≤ 1 week. On average, stays and episodes were significantly longer for men, those with a disability, and those diagnosed with an impulse control disorder, other nervous system diagnoses, or certain cancers, but significantly shorter for Black individuals and those dually eligible for Medicare and Medicaid. Most patients avoided developing pressure ulcers (96%) or deep vein thromboses (91%). INTERPRETATION:The GBS disease course varies significantly among Medicare enrollees. We identified some factors associated with worse GBS outcomes and others suggesting structural barriers to care. Our findings can improve care delivery by helping clinicians identify high-risk patients, facilitate early interventions, and reduce morbidity and mortality.

Medicare began reimbursing Transitional Care Management (TCM) services in 2013 to cover the transitional care gap for Medicare beneficiaries after hospital discharge and reduce their readmission risk. While a minority of practices bill TCM services for their Medicare patients, practices that do bill for TCM are likely to participate in the Medicare Shared Savings Program (MSSP). However, little is known about the impacts associated with TCM among high-cost, high-need patient populations, especially in the context of the MSSP. To examine the association between billing TCM codes and changes in the likelihood of hospital-based care among dual-eligible beneficiaries, and whether MSSP participation among practices enhances patient-level effects. This retrospective cross-sectional cohort study used Medicare fee-for-service claims, MSSP provider files, and the Medicare Data on Provider Practice and Specialty files (2013–2017). Dual-eligible beneficiaries with 60-day post-discharge episodes (3,766,804) that are potentially eligible for TCM. Key explanatory variables are billed TCM codes within 30 days of discharge and practice MSSP participation status. Outcomes are the likelihood of an emergency visit or observation stay within 60 days after discharge, a 30-day readmission, and a 31–60-day readmission. Billing TCM codes is associated with significant reductions in the likelihood of an ED visit or a 30-day readmission, with relative reductions of 9.0

Hospitalized patients continue to experience preventable harm and safety threats. The purpose of this study was to evaluate the extent to which nurse judgments of credibility and concern (perceived importance) mediated the relationships between patient demographic characteristics and nurse intent to report a patient-reported safety event while adjusting for nurse and event characteristics. A cross-sectional, quantitative study using a factorial survey experiment was conducted. Hospital nurses working in United States practice settings (N = 240) participated in an online survey. Path analysis was used to test the study model. Our findings indicate that increased nurse concern regarding a patient-reported safety event increased the likelihood of reporting the event to organizational incident reporting systems. Nurse concern also mediated the relationship between patient socioeconomic status and race/ethnicity (Black vs. non-Hispanic White) and nurses’ intent to report. Other variables directly affecting intent to report were patient ethnicity (Hispanic White versus Non-Hispanic White), and event type (medication versus miscommunication). The degree of credibility judged by participants had no effect on intent to report. These results suggest key motivations for nurse reporting are (a) the degree of concern (perceived importance) of the event and (b) the type of event, with medication errors associated with both greater nurse concern and intent to report. While literature suggests that patient characteristics are directly and indirectly associated with intent to report, our study suggests credibility is not a mitigating factor in that relationship. Overall, our study suggests interventions focusing on nurse judgments of importance may be more effective than those focused on judgments of credibility.

Using 2012-2018 Medicare claims and health center data, we identified factors associated with variation in rates of hospital care among Medicare-Medicaid dual enrollees receiving primary care at health centers. In our sample (n = 5961 health center-years), we found no evidence that patient-centered medical home designation or other modifiable health center characteristics were associated with reductions in hospital care use, which depends more on health center patient mix. Thus, policymakers should target efforts to health centers serving the most disadvantaged and marginalized communities.

Observation stays in Medicare have grown over the last 15 years, yet limited research exists on how observation may impact outcomes for older adults. To examine the relationship of an observation stay with 30-day hospital returns, total acute care days post-discharge, mortality, and out-of-pocket costs, compared to an inpatient admission. Retrospective cohort study using instrumental variable analysis. A 20

Importance:Current policies to divert emergency department (ED) visits for less medically urgent conditions to more cost-effective settings rely on retrospective adjudication of discharge diagnoses. However, patients present to the ED with concerns, making it challenging for clinicians. Objective:To characterize ED visits based on the medical urgency of the presenting reasons for visit and to explore the concordance between discharge diagnoses and reasons for visit. Design, Setting, and Participants:In this retrospective, cross-sectional study, a nationwide sample of ED visits by adults (aged ≥18 years) in the US from the 2018 and 2019 calendar years' ED data of the National Hospital Ambulatory Medical Care Survey was used. An algorithm to probabilistically assign ED visits into medical urgency categories based on the presenting reason for visit was developed. A 3-step, look-back method was applied using an updated version of the New York University ED algorithm, and a map of all possible discharge diagnoses to the same reasons for visit was developed. Analyses were conducted in July and August 2023. Main Outcomes and Measures:The main outcome was probabilistic medical urgency classification of reasons for visits and discharge diagnoses and their concordance. Results:We analyzed 27 068 ED visits (mean age, 48.2% years [95% CI, 47.5%-48.9% years]) representing 190.7 million visits nationwide. Women (mean, 57.0% [95% CI, 55.9%-58.1%]) and patients with public health insurance coverage, including Medicare (mean, 24.9% [95% CI, 21.9%-28.0%]) and Medicaid (mean, 25.1% [95% CI, 21.0%-29.2%]), accounted for the largest share of ED visits, and a mean of 13.2% (95% CI, 11.4%-15.0%) of all visits resulted in a hospital admission. Overall, about 38.5% and 53.9% of all ED visits were classified with 100% and 75% probabilities, respectively, as injury related, emergency care needed, emergent but primary care treatable, nonemergent, or mental health or substance use disorders related based on discharge diagnosis compared with 0.4% and 12.4%, respectively, of all encounters based on patients' reason for visit. Among discharge diagnoses assigned with high certainty to only 1 urgency category using the New York University ED algorithm, between 38.0% (95% CI, 36.3%-39.6%) and 57.4% (95% CI, 56.0%-58.8%) aligned with the probabilistic categorical assignments of their corresponding reasons for visit. Conclusions and Relevance:In this cross-sectional study of 190.7 million ED visits among adults aged 18 years or older, a smaller percentage of reasons for visit could be prospectively categorized with high accuracy to a specific medical urgency category compared with all visits based on discharge diagnoses, and a limited concordance between reasons for visit and discharge diagnoses was found. Alternative methods are needed to identify the medical necessity of ED encounters more accurately.

Avni Gupta, PhD, MPH, BDS; Diana Silver, PhD, MPH; David J. Meyers, PhD, MPH; Sherry Glied, PhD; José A. Pagán, PhD

Background: COVID-19 accelerated federally qualified health centers’ use of telemental health. However, factors associated with telemental health service delivery remain unclear. We examined telemental health delivery by clinician type and mental health workforce composition across the U.S. to understand how staffing and other organizational characteristics are related to telemental health delivery at health centers. Methods: Using data from the 2021 Uniform Data System, we characterized the proportion of mental health care delivered via elemental (i.e., virtual visits) at health centers in the U.S. that received HRSA grant funding (n = 1,270) overall and by state and clinician type. Then, we conducted multivariate beta regression analyses to assess the proportion of mental health visits delivered via telemental health at health centers as a function of mental health workforce composition, while adjusting for health center size, patient mix, and state. Results: In 2021, health centers delivered 43% of their mental health visits via telemental health, with significant variation by state and clinician type. On average, the proportion of mental health visits delivered via telemental health was greater among psychiatrists (61%, P < .001) than psychologists (49%) and clinical social workers (45%). Factors significantly associated with the increased proportion of telemental health delivered by health centers included a higher supply of psychiatrists per patient, more grant dollars per patient, and a greater proportion of Asian patients served. Conclusions: Access to telemental health varies by state and across health centers based on mental health workforce composition. Future work is needed to examine funding and workforce strategies to increase telemental health service availability.

ObjectiveClaims data can be leveraged to study rare diseases such as Guillain-Barré Syndrome (GBS), a neurological autoimmune condition. It is difficult to accurately measure and distinguish true cases of disease with claims without a validated algorithm. Our objective was to identify the best-performing algorithm for identifying incident GBS cases in Medicare Fee-For-Service claims data using chart reviews as the gold standard.Study design and settingThis was a multi-center, single institution cohort study from 2015 to 2019 that used Medicare-linked Electronic Health Record (EHR) data. We identified 211 patients with a GBS diagnosis code in any position of an inpatient or outpatient claim in Medicare that also had a record of GBS in their electronic medical record. We reported the positive predictive value (PPV = number of true GBS cases/total number of GBS cases identified by the algorithm) for each algorithm tested. We also tested algorithms using several prevalence assumptions for false negative GBS cases and calculated a ranked sum for each algorithm's performance.ResultsWe found that 40 patients out of 211 had a true case of GBS. Algorithm 17, a GBS diagnosis in the primary position of an inpatient claim and a diagnostic procedure within 45 days of the inpatient admission date, had the highest PPV (PPV = 81.6%, 95% CI (69.3, 93.9). Across three prevalence assumptions, Algorithm 15, a GBS diagnosis in the primary position of an inpatient claim, was favored (PPV = 79.5%, 95% CI (67.6, 91.5).ConclusionsOur findings demonstrate that patients with incident GBS can be accurately identified in Medicare claims with a chart-validated algorithm. Using large-scale administrative data to study GBS offers significant advantages over case reports and patient repositories with self-reported data, and may be a potential strategy for the study of other rare diseases.

AimTo test the influences of patient, safety event and nurse characteristics on nurse judgements of credibility, importance and intent to report patients' safety concerns.DesignFactorial survey experiment.MethodsA total of 240 nurses were recruited and completed an online survey including demographic information and responses to eight factorial vignettes consisting of unique combinations of eight patient and event factors. Hierarchical multivariate analysis was used to test influences of vignette factors and nurse characteristics on nurse judgements.ResultsThe intraclass coefficients for nurse judgements suggest that the variation among nurses exceeded the influence of contextual vignette factors. Several significant sources of nurse variation were identified, including race/ethnicity, suggesting a complex relationship between nurses' characteristics and their potential biases, and the influence of personal and patient factors on nurses' judgements, including the decision to report safety concerns.ConclusionNurses are key players in the system to manage patient safety concerns. Variation among nurses and how they respond to scenarios of patient safety concerns highlight the need for nurse-level intervention.Implications for the Profession and Patient CareComplex factors influence nurses' judgement, interpretation and reporting of patients' safety concerns.ImpactUnderstanding nurse judgement regarding patient-expressed safety concerns is critical for designing processes and systems that promote reporting. Multiple event and patient characteristics (type of event and apparent harm, and patient gender, race/ethnicity, socioeconomic status, and communication approach) as well as participant characteristics (race/ethnicity, gender, years of experience and primary hospital area) impacted participants' judgements of credibility, degree of concern and intent to report. These findings will help guide patient safety nurse education and training.Reporting MethodSTROBE guidelines.Patient or Public ContributionMembers of the public, including patient advocates, were involved in content validation of the vignette scenarios, norming photographs used in the factorial survey and testing the survey functionality.

Using novel national data, we examined the association between 2020 federal COVID-related funding targeted to health centers (i.e., H8 funding) and health center workforce and operational capacity measures that may be important for preserving patient access to care and staff safety. We assigned health centers to quartiles based on federal funding distribution per patient and used adjusted linear probability models to estimate differences in workforce and operational capacity outcomes across quartiles from April 2020 to June 2022. We found a nearly 6-fold difference in 2020 H8 funding per patient when comparing health centers in the lowest versus highest quartiles. Despite this difference, health centers’ outcomes improved similarly across quartiles over time, with the lowest-funded health centers having the greatest staffing and service capacity challenges. Our findings suggest that COVID-related health center funding may have contributed to stabilization of health centers’ workforce and operations. Amid concerns about staff turnover, sustained investments targeted to supporting workforce retention at health centers can help to ensure ongoing delivery of critical services.

BackgroundPrimary care is essential for persons with Alzheimer's disease and related dementias (ADRD). Prior research suggests that the propensity to provide high-quality, continuous primary care varies by provider setting, but the settings used by Medicare-Medicaid dual-eligibles with ADRD have not been described at the population level. MethodsUsing 2012-2018 Medicare data, we identified dual-eligibles with ADRD. For each person-year, we identified primary care visits occurring in six settings. We calculated descriptive statistics for beneficiaries with a majority of visits in each setting, and conducted a k-means cluster analysis to determine utilization patterns, using the standardized count of primary care visits in each setting. ResultsEach year from 2012 to 2018, at least 45.6% of dual-eligibles with ADRD received a majority of their primary care in nursing facilities, while at least 25.2% did so in physician offices. Over time, the share relying on nursing facilities for primary care decreased by 5.2 percentage points, offset by growth in Federally Qualified Health Centers (FQHCs) and miscellaneous settings (2.3 percentage points each). Dual-eligibles relying on nursing facilities had more annual primary care visits (16.1) than those relying on other settings (range: 6.8-10.7 visits). Interpersonal care continuity was also higher in nursing facilities (97.0%) and physician offices (87.9%) than in FQHCs (54.2%), rural health clinics (RHCs, 46.6%), or hospital-based clinics (56.8%). Among dual-eligibles without care continuity, 82.7% were assigned to a cluster with few primary care visits. ConclusionsA trend toward care in different settings likely reflects improved access to patient-centered primary care. Low rates of interpersonal care continuity in FQHCs, RHCs, and physician offices may warrant concern, unless providers in these settings function as a care team. Nonetheless, every healthcare system encounter presents an opportunity to designate a primary care provider for dual-eligibles with ADRD who use little or no primary care.

Objective: To determine the extent to which counting observation stays changes hospital performance on 30-day readmission measures. Methods: This was a retrospective study of inpatient admissions and observation stays among fee-for-service Medicare enrollees in 2017. We generated 3 specifications of 30-day risk-standardized readmissions measures: the hospital-wide readmission (HWR) measure utilized by the Centers for Medicare and Medicaid Services, which captures inpatient readmissions within 30 days of inpatient discharge; an expanded HWR measure, which captures any unplanned hospitalization (inpatient admission or observation stay) within 30 days of inpatient discharge; an all-hospitalization readmission (AHR) measure, which captures any unplanned hospitalization following any hospital discharge (observation stays are included in both the numerator and denominator of the measure). Estimated excess readmissions for hospitals were compared across the 3 measures. High performers were defined as those with a lower-than-expected number of readmissions whereas low performers had higher-than-expected or excess readmissions. Multivariable logistic regression identified hospital characteristics associated with worse performance under the measures that included observation stays. Results: Our sample had 2586 hospitals with 5,749,779 hospitalizations. Observation stays ranged from 0% to 41.7% of total hospitalizations. Mean (SD) readmission rates were 16.6% (5.4) for the HWR, 18.5% (5.7) for the expanded HWR, and 17.9% (5.7) in the all-hospitalization readmission measure. Approximately 1 in 7 hospitals (14.9%) would switch from being classified as a high performer to a low performer or vice-versa if observation stays were fully included in the calculation of readmission rates. Safety-net hospitals and those with a higher propensity to use observation would perform significantly worse. Conclusions: Fully incorporating observation stays in readmission measures would substantially change performance in value-based programs for safety-net hospitals and hospitals with high rates of observation stays.

Introduction:Health center use may reduce hospital-based care among Medicare-Medicaid dual eligibles, but racial and ethnic disparities in this population have not been widely studied. We examined the extent of racial and ethnic disparities in hospital-based care among duals using health centers and the degree to which disparities occur within or between health centers. Methods:We used 2012-2018 Medicare claims and health center data to model emergency department (ED) visits, observation stays, hospitalizations, and 30-day unplanned returns as a function of race and ethnicity among dual eligibles using health centers. Results:In rural and urban counties, age-eligible Black individuals had more ED visits (7.9 [4.0, 11.7] and 13.7 [10.0, 17.4] per 100 person-years) and were more likely to experience an unplanned return (1.4 [0.4, 2.4] and 1 [0.4, 1.6] percentage points [pp]) than White individuals, but were less likely to be hospitalized (-3.3 [-3.9, -2.8] and -1.2 [-1.6, -0.9] pp). In urban counties, age-eligible Black individuals were 1.2 [0.9, 1.5] pp more likely than White individuals to have observation stays. Other racial and ethnic groups used the same or less hospital-based care than White individuals. Including state and health center fixed effects eliminated Black versus White disparities in all outcomes, except hospitalization. Results were similar among disability-eligible duals. Conclusion:Racial and ethnic disparities in hospital-based care among dual eligibles are less common within than between health centers. If health centers are to play a more central role in eliminating racial and ethnic health disparities, these differences across health centers must be understood and addressed.

ObjectiveTo evaluate whether Medicare's Hospital Readmissions Reduction Program (HRRP) is associated with increased observation stay use. Data Sources and Study SettingA nationally representative sample of fee-for-service Medicare claims, January 2009-September 2016. Study DesignUsing a difference-in-difference (DID) design, we modeled changes in observation stays as a proportion of total hospitalizations, separately comparing the initial (acute myocardial infarction, pneumonia, heart failure) and subsequent (chronic obstructive pulmonary disease) target conditions with a control group of nontarget conditions. Each model used 3 time periods: baseline (15 months before program announcement), an intervening period between announcement and implementation, and a 2-year post-implementation period, with specific dates defined by HRRP policies. Data Collection/Extraction MethodsWe derived a 20% random sample of all hospitalizations for beneficiaries continuously enrolled for 12 months before hospitalization (N = 7,162,189). Principal FindingsObservation stays increased similarly for the initial HRRP target and nontarget conditions in the intervening period (0.01% points per month [95% CI -0.01, 0.3]). Post-implementation, observation stays increased significantly more for target versus nontarget conditions, but the difference is quite small (0.02% points per month [95% CI 0.002, 0.04]). Results for the COPD analysis were statistically insignificant in both policy periods. ConclusionsThe increase in observation stays is likely due to other factors, including audit activity and clinical advances.

OBJECTIVE:To examine the relationship between federally qualified health center (FQHC) use and hospital-based care among individuals dually enrolled in Medicare and Medicaid. DATA SOURCES:Data were obtained from 2012 to 2018 Medicare claims. STUDY DESIGN:We modeled hospital-based care as a function of FQHC use, person-level factors, a Medicare prospective payment system (PPS) indicator, and ZIP code fixed effects. Outcomes included emergency department (ED) visits (overall and nonemergent), observation stays, hospitalizations (overall and for ambulatory care sensitive conditions), and 30-day unplanned returns. We stratified all models on the basis of eligibility and rurality. DATA EXTRACTION METHODS:Our sample included individuals dually enrolled in Medicare and Medicaid for at least two full consecutive years, residing in a primary care service area with an FQHC. We excluded individuals without primary care visits, who died, or had end-stage renal disease. PRINCIPAL FINDINGS:After the Medicare PPS was introduced, FQHC use in rural counties was associated with fewer ED and nonemergent ED visits per 100 person-years among both age-eligible (-14.8 [-17.5, -12.1]; -6.6 [-7.5, -5.6]) and disability-eligible duals (-11.3 [-14.4, -8.3]; -6 [-7.4, -4.6]) as well as a lower probability of observation stays (-0.8 pp age-eligible; -0.4 pp disability-eligible) and unplanned returns (-2.1 pp age-eligible; -1.9 pp disability-eligible). In urban counties, FQHC use was associated with more ED and nonemergent ED visits per 100 person-years (10.6 [8.4, 12.8]; 4.0 [2.6, 5.4]) among disability-eligible duals (a decrease of more than 60% compared with the pre-PPS period) and increases in the probability of hospitalization (1.1 pp age-eligible; 0.8 pp disability-eligible) and ACS hospitalization (0.5 pp age-eligible; 0.3 pp disability-eligible) (a decrease of roughly 50% compared with the pre-PPS period). CONCLUSIONS:FQHC use is associated with reductions in hospital-based care among dual enrollees after introduction of the Medicare PPS. Further research is needed to understand how FQHCs can tailor care to best serve this complex population.

Context: Although community health centers (CHCs) arose in the 1960s as part of a Democratic policy push committed to social justice, subsequent support has been shaped by paradoxical poli-tics wherein Republican and Democratic support for CHCs continually morphed in response to changes in the health policy landscape.Methods: Drawing on the CHC literature and empirical examples from firsthand accounts and reporting, this article explains CHCs' curious historical development from 1965 to the present.Findings: Both Republicans and Democrats have calibrated their support for CHCs in response to a broader set of political considerations, from antiwelfare policy commitments to aspirations of establishing a national health care plan.Conclusions: CHCs have proven to be a politically malleable policy tool within the broader context of American health care policy. The COVID-19 pandemic raised new questions about CHCs' sustainability and future, but CHCs will continue to play a critical role in providing health care access to underserved populations. They also will continue to be an attractive bipartisan pol-icy option within the larger framework of US health policy.

Federally qualified health centers (FQHCs) increasingly provide high-quality, cost-effective primary care to individuals dually enrolled in Medicare and Medicaid. However, not everyone can access an FQHC. We used 2012 to 2018 Medicare claims and federally collected FQHC data to examine communities where an FQHC first opened and determine which dual eligibles used it. Overall uptake was 10%, ranging from 6.6% among age-eligible urban residents to 14.8% among disability-eligible rural residents. Community-level uptake ranged from 0% to 76.4% (median = 5.5%; interquartile range = 2.8%-11.3%). Certain subpopulations of dual eligibles are significantly more likely to use FQHCs. Our findings should inform the targeting of future FQHC expansions.

Background Food insecurity has been identified as an important social determinant of health and is associated with many health issues prevalent in Medicaid members. Despite this, little research has been done around food insecurity within Medicaid populations. Objective Our objective was to estimate the prevalence of household food insecurity and identify factors associated with experiencing food insecurity in Iowa's Medicaid expansion population. Design We conducted a cross-sectional telephone survey between March and May of 2019. Participants Our sample was drawn from Medicaid members enrolled in Iowa's expansion program at least 14 months, stratified by Federal Poverty Level (FPL) category. Members who did not have valid contact information were excluded. We selected one individual per household to reduce the interrelatedness of responses. We sampled 6,000 individuals and had 1,349 respondents in the analytic sample. Main outcome measure Our main outcome was whether a respondent's household experienced food insecurity in the previous year, using the Hunger Vital Sign screening tool. Statistical analyses performed We weighted responses to account for the sampling design and differential nonresponse between strata. We estimated the prevalence of food insecurity and used logistic regression to model food insecurity as a function of demographic (age, FPL category, gender, employment, education, race, rurality, and Supplemental Nutrition Assistance Program [SNAP] participation) and health-related (self-rated health, self-rated oral health, health literacy) factors. Results The estimated prevalence of experiencing food insecurity was 51.3%. Race, gender, education, employment, health literacy, and self-rated health were all signifi-cantly associated with food insecurity. Conclusions Our findings show that food insecurity is prevalent in Iowa's Medicaid expansion population. Food insecurity should be more widely measured as a critical social determinant of health in Medicaid populations. Policymakers and clinicians should consider interventions that connect households experiencing food insecurity to food resources (eg, produce prescriptions and food pantry referrals) and policies that increase food access. Abbreviations Iowa Wellness Plan (IWP); Federal Poverty Level (FPL); Healthy Behavior Program (HBP); Supplemental Nutrition Assistance Program (SNAP) J Acad Nutr Diet. 2022;122(2):394-402.