Disparities in sleep-wake patterns by labor force status: Population-based findings.

Sleep disturbances have been associated with unemployment, but variation in sleep-wake patterns by labor force status has rarely been examined. With a population-based sample, we investigated differences in sleep-wake patterns by labor force status (employed, unemployed, and not-in-the-labor-force) and potential disparities by sociodemographic variables. The analysis included 130,602 adults aged 25-60 y, who participated in the American Time Use Survey between 2003 and 2019. Individual sleep-wake pattern was extracted from time use logs in a strict 24-h period (04:00 h-03:59 h). Functional nonparametric regression models based on dimensionality reduction and neighborhood matching were applied to model the relationship between sleep-wake patterns and labor force status. Specifically, we predicted changes in intra-person sleep-wake patterns under hypothetical changes of labor force status from employed to unemployed or not-in-the-labor-force. We then studied moderations of this association by gender, race/ethnicity and educational attainment. In comparison to the employed state, unemployed and not-in-the-labor-force states were predicted to have later wake-times, later bedtimes, and higher tendency for taking midday naps. Changes in labor force status led to more apparent shifts in wake-times than in bedtimes. Additionally, sleep schedules of Hispanics and those with higher education level were more vulnerable to the change of labor force status from employed to unemployed.

Designing and validating a low-cost real time locating system to continuously assess patient wait times.

OBJECTIVE: Outpatient clinics lack infrastructure to easily measure and understand patient wait times. Our objective was to design a low-cost, portable passive real time locating system within an outpatient clinic setting to measure patient wait times and patient-provider interactions. MATERIALS AND METHODS: Direct observation was used to determine workflow in an outpatient glaucoma clinic at the University of Michigan. We used off-the shelf, antenna-integrated ultra-high frequency (UHF) RFID readers (ThingMagic, Astra-Ex, Woburn, MA) and UHF re-useable passive RFID tags (Zebra Impinj Monza 4QT, Seattle, WA). We designed a custom RFID management application in the Java programming language that was equipped with 'live' device administration to collect time and location data from patients and providers. These hardware choices enabled low cost system installation. Hidden Markov Modeling (HMM) was used to smooth patient and provider location data. Location data were validated against direct observations and EHR evaluation. RESULTS: The HMM smoothed RFID system data accurately predicted patient location 80.6% of the time and provider location 79.1% of the time, compared to direct observation locations, an improvement over the raw RFID location data (65.0% and 77.9% accurate, respectively). Patient process time was on average 42.8 min (SD = 27.5) and wait time was 47.9 min (SD = 33.1). The installation and recurring capital costs of the system are approximately 10% of available commercially-supplied patient/provider tracking systems. DISCUSSION: Passive RFID time study systems can enable real-time localization of people in clinic, facilitating continuous capture of patient wait times and patient-provider interactions. The system must be tailored to the clinic to accurately reflect patient and provider movement. CONCLUSIONS: Capturing wait time data continuously and passively can empower continuous clinical quality improvement initiatives to enhance the patient experience.

Gender Disparities in Alcohol Use Disorder Treatment Among Privately Insured Patients with Alcohol-Associated Cirrhosis.

BACKGROUND: The burden of alcohol-associated cirrhosis (AC) is high, and though alcohol cessation improves mortality, many patients fail to engage in alcohol use disorder (AUD) treatment and continue drinking. Our aim was to determine rates, predictors, and outcomes of AUD treatment utilization in AC patients with private insurance. METHODS: We collected data from persons with AC (diagnosed by ICD-9/ICD-10 codes), aged 18 to 64 years, enrolled in the Truven MarketScan Commercial Claims and Encounters database (2009 to 2016). We determined rates and predictors of substance abuse treatment visits as well as rates of alcohol relapse prevention medication prescriptions, weighted to the national employer-sponsored insured population. Effects of AUD treatment utilization on decompensation rates were calculated using proportional hazards regression with propensity score adjustment. RESULTS: A total of 66,053 AC patients were identified, 32% were female, and mean age at diagnosis was 54.5 years. About 72% had insurance coverage for substance abuse treatment. Overall, AUD treatment utilization rates were low, with only 10% receiving a face-to-face mental health or substance abuse visit and only 0.8% receiving a Food and Drug Administration (FDA)-approved relapse prevention medication within 1 year of index diagnosis. Women were less likely to receive a face-to-face visit (hazard ratio [HR] 0.84, p < 0.001) or an FDA-approved relapse prevention medication (0.89, p = 0.05) than men. AC patients who had a clinic visit for AUD treatment or used FDA-approved relapse medication showed decreased risk of decompensation at 1 year (HR 0.85, p < 0.001 for either). CONCLUSIONS: AUD treatment utilization is associated with lower decompensation rates among privately insured patients with AC. Women were less likely to utilize AUD treatment visits. Efforts to reduce gender-specific barriers to treatment are urgently needed to improve outcomes.

The high burden of alcoholic cirrhosis in privately insured persons in the United States.

Alcoholic cirrhosis (AC) is a major cause of liver-related morbidity and mortality in the United States. Rising rates of alcohol use disorders in the United States will likely result in more alcoholic liver disease. Our aim was to determine the prevalence, health care use, and costs of AC among privately insured persons in the United States. We collected data from persons aged 18-64 with AC (identified by codes from the International Classification of Diseases, Ninth and Tenth Revisions) enrolled in the Truven MarketScan Commercial Claims and Encounters database (2009-2015). We determined yearly prevalence, weighted to the national employer-sponsored, privately insured population. Using competing risk analysis, we estimated event rates for portal hypertensive complications and estimated the association between AC and costs as well as admissions and readmissions. In 2015, 294,215 people had cirrhosis and 105,871 (36%) had AC. Mean age at AC diagnosis was 53.5 years, and 32% were women. Over the 7 years queried, estimated national cirrhosis prevalence rose from 0.19% to 0.27% (P < 0.001) and for AC from 0.07% to 0.10% (P < 0.001). Compared to non-AC, AC enrollees were significantly more likely to have portal hypertensive complications at diagnosis and higher yearly cirrhosis and alcohol-related admissions (25 excess cirrhosis admissions and 6.3 excess alcohol-related admissions per 100 enrollees) as well as all-cause readmissions. Per-person costs in the first year after diagnosis nearly doubled for AC versus non-AC persons (US$ 44,835 versus 23,319). CONCLUSION: In a nationally representative cohort of privately insured persons, AC enrollees were disproportionately sicker at presentation, were admitted and readmitted more often, and incurred nearly double the per-person health care costs compared to those with non-AC. (Hepatology 2018).