The influence of social determinants of health on epilepsy treatment delays in an Arizona Medicaid population.

OBJECTIVE: The purpose of this study was to better understand the role of social determinants of health (SDoH) in both treatment delays and treatment gaps for individuals with epilepsy (IWE) enrolled in Arizona's Medicaid program using predictive models at the population and individual levels. METHODS: In this retrospective cohort study, two statistical regression models were developed using Arizona Medicaid medical and pharmacy claims records from 2015-2019 and selected census tract-level SDoH data. Three treatment outcomes were defined: timely treatment (treated within thirty days); delayed treatment (treated after thirty days); and untreated. For the first model, least squares regression was used to regress the epilepsy treatment delays on selected SDoH factors at the population-level. For the second model, multinomial logistic regression was used to estimate associations between epilepsy treatment delays and individual-level sociodemographic factors. RESULTS: Of the 5965 IWE identified with a new epilepsy diagnosis during the study period, 43.1% were treated with a mean delay of 180 days. Among the treated population, 42% received timely treatment. A treatment gap of at least 40.6% and potentially up to 56.9% was calculated. Individuals with epilepsy diagnosed in an inpatient setting or in emergency departments were more likely to be treated and receive timely treatment than those diagnosed in an office or clinic setting. Individuals with epilepsy diagnosed in "other" settings were more likely to go untreated or receive delayed treatment than a patient diagnosed in an office or clinic. Compared to IWE aged 31-50 years, IWE aged 0-30 years were more likely to receive timely treatment, IWE aged 51-64 years were more likely to receive delayed treatment, and IWE aged 65 years or older were more likely to go untreated. Widowed IWE were more likely to go untreated relative to single patients. Individuals with epilepsy experiencing homelessness were also more likely to go untreated. Unemployed IWE were more likely to go untreated or receive delayed treatment. Native American IWE were more likely to go untreated compared to White patients. CONCLUSIONS: Treatment gaps and treatment delays are experienced by IWE in the Arizona Medicaid population. The SDoH factors predicted to impact treatment delays include care setting, age, race, marital status, homelessness, and employment.

Variability in asthma quality and costs in children with different Medicaid insurance plans in Maricopa County.

OBJECTIVE: To describe the variation in asthma quality and costs among children with different Medicaid insurance plans. METHODS: We used 2013 data from the Center for Health Information and Research, which houses a database that includes individuals who have Medicaid insurance in Arizona. We analyzed children ages 2-17 years-old who lived in Maricopa County, Arizona. Asthma medication ratio (AMR, a measure of appropriate asthma medication use), outpatient follow-up within 2 weeks after asthma-related hospitalization (a measure of continuity of care), asthma-related hospitalizations, and all emergency department (ED) visits were the primary quality metrics. Direct costs were reported in 2013 $US dollars. We used one-way analysis of variance to compare the health plans for AMR and per member cost (total, ER, and hospital), and the chi-squared test for the outpatient follow-up measure. We used coefficient of variation to identify variation of each measure across all individuals in the study. RESULTS: In 2013, 90,652 children in Maricopa County were identified as having asthma. The average patient-weighted AMR for children with persistent asthma was 0.35, well short of the goal of ≥0.70, and only 36% of hospitalized asthma patients had outpatient follow-up within 2 weeks of hospitalization. AMR, total costs, and ED costs varied significantly (p <.0001) when comparing health plans while hospital costs and outpatient follow-up showed no significant variation. CONCLUSIONS: Targeting appropriate medication use for asthma may help reduce variation, improve outcomes, and increase healthcare value for children with asthma and Medicaid insurance in the US.

Registered Nurses: The Curious Case of a Persistent Shortage.

PURPOSE: To better understand the apparent persistent shortage of registered nurses (RNs), including both aggregate trends and cyclical responses. DESIGN: We examine the employment of RNs over variations in economic activity, employing national aggregate and unique micro-population data on nurses in Arizona. METHODS: These data, including our unique, ongoing survey of nurses in Arizona, enable a systematic examination of the cyclical demand for hospital care and institutional responses to that demand in the nursing market by employing multivariate regressions. FINDINGS: Demand for hospital nursing care increases rapidly during the early years of recessions, moderating as the economy improves. Hospitals initially employ more temporary nurses, then reduce temporary hires by shifting employed RNs from part time to full time while also adding RNs not previously employed in hospitals. The substitution of regularly employed RNs for temporary nurses reflects the need to reduce staffing costs to offset increases in uncompensated care. CONCLUSIONS: The increased supply of nurses came from delayed retirements, higher relative hospital wages (inducing nurses in other sectors to return to hospitals), and added-worker effects. Additional nursing hours were drawn from a pool of RNs who were not employed in health care. CLINICAL RELEVANCE: These results strongly suggest that correctly aligned incentives could reduce RN shortages without waiting for another recession.

Patient Flow and Reutilization of Crisis Services Within 30 Days in a Comprehensive Crisis System.

OBJECTIVE: Crisis services are undergoing an unprecedented expansion in the United States, but research is lacking on crisis system design. This study describes how individuals flow through a well-established crisis system and examines factors associated with reutilization of such services. METHODS: This cross-sectional study used Medicaid claims to construct episodes describing the flow of individuals through mobile crisis, specialized crisis facility, emergency department, and inpatient services. Claims data were merged with electronic health record (EHR) data for the subset of individuals receiving care at a crisis response center. A generalized estimating equation was used to calculate adjusted odds ratios for demographic, clinical, and operational factors associated with reutilization of services within 30 days of an episode's end point. RESULTS: Of 41,026 episodes, most (57.4%) began with mobile crisis services or a specialized crisis facility rather than the emergency department. Of the subset (N=9,202 episodes) with merged EHR data, most episodes (63.3%) were not followed by reutilization. Factors associated with increased odds of 30-day reutilization included Black race, homelessness, stimulant use, psychosis, and episodes beginning with mobile crisis services or ending with inpatient care. Decreased odds were associated with depression, trauma, and involuntary legal status. Most (59.3%) episodes beginning with an involuntary legal status ended with a voluntary status. CONCLUSIONS: Crisis systems can serve a large proportion of individuals experiencing psychiatric emergencies and divert them from more restrictive and costly levels of care. Understanding demographic, clinical, and operational factors associated with 30-day reutilization may aid in the design and implementation of crisis systems.

Epidemiology of Pediatric Traumatic Brain Injury and Hypothalamic-Pituitary Disorders in Arizona.

Traumatic brain injury (TBI) in children can result in long-lasting social, cognitive, and neurological impairments. In adults, TBI can lead to endocrinopathies (endocrine system disorders), but this is infrequently reported in children. Untreated endocrinopathies can elevate risks of subsequent health issues, such that early detection in pediatric TBI survivors can initiate clinical interventions. To understand the risk of endocrinopathies following pediatric TBI, we identified patients who had experienced a TBI and subsequently developed a new-onset hypothalamic regulated endocrinopathy (n = 498). We hypothesized that pediatric patients who were diagnosed with a TBI were at higher risk of being diagnosed with a central endocrinopathy than those without a prior diagnosis of TBI. In our epidemiological assessment, we identified pediatric patients enrolled in the Arizona Health Care Cost Containment System (AHCCCS) from 2008 to 2014 who were diagnosed with one of 330 TBI International Classification of Diseases (ICD)-9 codes and subsequently diagnosed with one of 14 central endocrinopathy ICD-9 codes. Additionally, the ICD-9 code data from over 600,000 Arizona pediatric patients afforded an estimate of the incidence, prevalence, relative risk, odds ratio, and number needed to harm, regarding the development of a central endocrinopathy after sustaining a TBI in Arizona Medicaid pediatric patients. Children with a TBI diagnosis had 3.22 times the risk of a subsequent central endocrine diagnosis compared with the general population (±0.28). Pediatric AHCCCS patients with a central endocrine diagnosis had 3.2-fold higher odds of a history of a TBI diagnosis than those without an endocrine diagnosis (±0.29). Furthermore, the number of patients with a TBI diagnosis for one patient to receive a diagnosis of a central endocrine diagnosis was 151.2 (±6.12). Female subjects were more likely to present with a central endocrine diagnosis after a TBI diagnosis compared to male subjects (64.1 vs. 35.9%). These results are the first state-wide epidemiological study conducted to determine the risk of developing a hypothalamic-pituitary disorder after a TBI in the pediatric population. Our results contribute to a body of knowledge demonstrating a TBI etiology for idiopathic endocrine disorders, and thus advise physicians with regard to TBI follow-up care that includes preventive screening for endocrine disorders.

Are low income patients receiving the benefits of electronic health records? A statewide survey.

There are concerns that physicians serving low-income, Medicaid patients, in the United States are less likely to adopt electronic health records and, if so, that Medicaid patients will be denied the benefits from electronic health record use. This study seeks to determine whether physicians treating Medicaid patients were less likely to have adopted electronic health records. Physician surveys completed during physicians' license renewal process in Arizona were merged with the physician licensing data and Medicaid administrative claims data. Survey responses were received from 50.7 percent (6,780 out of 13,380) of all physicians practicing in Arizona. Physician survey responses were used to identify whether the physician used electronic health records and the degree to which the physician exchanged electronic health records with other health-care providers. Medicaid claims data were used to identify which physicians provided health care to Medicaid beneficiaries. The primary outcome of interest was whether Medicaid providers were more or less likely to have adopted electronic health records. Logistic regression analysis was used to estimate average marginal effects. In multivariate analysis, physicians with 20 or more Medicaid patients during the survey cycle were 4.1 percent more likely to use an electronic health record and 5.2 percent more likely to be able to transmit electronic health records to at least one health-care provider outside of their practice. These effects increase in magnitude when the analysis is restricted to solo practice physicians This is the first study to find a pro-Medicaid gap in electronic health record adoption suggesting that the low income patients served by Arizona's Health Care Cost Containment System are not at a disadvantage with regard to electronic health record access and that Arizona's model of promoting electronic health record adoption merits further study.