OBJECTIVE: Insufficient sleep costs the U.S. economy over $411 billion per year. However, most studies investigating economic costs of sleep rely on one-time measures of sleep, which may be prone to recall bias and cannot capture variability in sleep. To address these gaps, we examined how sleep metrics captured from daily sleep diaries predicted medical expenditures.
METHODS: Participants were 391 World Trade Center responders enrolled in the World Trade Center Health Program (mean age = 54.97 years, 89% men). At baseline, participants completed 14 days of self-reported sleep and stress measures. Mean sleep, variability in sleep, and a novel measure of sleep reactivity (i.e., how much people\'s sleep changes in response to daily stress) were used to predict the subsequent year\'s medical expenditures, covarying for age, race/ethnicity, sex, medical diagnoses, and body mass index.
RESULTS: Mean sleep efficiency did not predict mental healthcare utilization. However, greater sleep efficiency reactivity to stress (b=$191.75, p=.027), sleep duration reactivity to stress (b=$206.33, p=.040), variability in sleep efficiency (b=$339.33, p=.002), variability in sleep duration (b=$260.87, p=.004), and quadratic mean sleep duration (b=$182.37, p=.001) all predicted greater mental healthcare expenditures. Together, these sleep variables explained 12% of the unique variance in mental healthcare expenditures. No sleep variables were significantly associated with physical healthcare expenditures.
CONCLUSIONS: People with more irregular sleep, more sleep reactivity, and either short or long sleep engage in more mental healthcare utilization. It may be important to address these individuals\' sleep problems to improve mental health and reduce healthcare costs.

BACKGROUND: Pulmonary hypertension due to interstitial lung disease (PH-ILD) is associated with high rates of respiratory failure and death. Healthcare resource utilization (HCRU) and cost data are needed to characterize PH-ILD disease burden.
METHODS: A retrospective cohort analysis of the Truven Health MarketScan® Commercial Claims and Encounters Database and Medicare Supplemental Database between June 2015 to June 2019 was conducted. Patients with ILD were identified and indexed based on their first claim with a PH diagnosis. Patients were required to be 18 years of age on the index date and continuously enrolled for 12-months pre- and post-index. Patients were excluded for having a PH diagnosis prior to ILD diagnosis or the presence of other non-ILD, PH-associated conditions. Treatment patterns, HCRU, and healthcare costs were compared between the 12 months pre- versus 12 months post-index date.
RESULTS: In total, 122 patients with PH-ILD were included (mean [SD] age, 63.7 [16.6] years; female, 64.8%). The same medication classes were most frequently used both pre- and post-index (corticosteroids: pre-index 43.4%, post-index 53.5%; calcium channel blockers: 25.4%, 36.9%; oxygen: 12.3%, 25.4%). All-cause hospitalizations increased 2-fold, with 29.5% of patients hospitalized pre-index vs. 59.0% post-index (P < 0.0001). Intensive care unit (ICU) utilization increased from 6.6 to 17.2% (P = 0.0433). Mean inpatient visits increased from 0.5 (SD, 0.9) to 1.1 (1.3) (P < 0.0001); length of stay (days) increased from 5.4 (5.9) to 7.5 (11.6) (P < 0.0001); bed days from 2.5 (6.6) to 8.0 (16.3) (P < 0.0001); ICU days from 3.8 (2.3) to 7.0 (13.2) (P = 0.0362); and outpatient visits from 24.5 (16.8) to 32.9 (21.8) (P < 0.0001). Mean (SD) total all-cause healthcare costs increased from $43,201 ($98,604) pre-index to $108,387 ($190,673) post-index (P < 0.0001); this was largely driven by hospitalizations (which increased from a mean [SD] of $13,133 [$28,752] to $63,218 [$75,639] [P < 0.0001]) and outpatient costs ($16,150 [$75,639] to $25,604 [$93,964] [P < 0.0001]).
CONCLUSIONS: PH-ILD contributes to a high HCRU and cost burden. Timely identification, management, and treatment are needed to mitigate the clinical and economic consequences of PH-ILD development and progression.

OBJECTIVE: To compare 12-month spinal fusion surgery rates in the setting of low back pain among digital musculoskeletal (MSK) program participants versus a comparison cohort who only received usual care.
METHODS: Retrospective cohort study with propensity score matched comparison cohort using commercial medical claims data representing over 100 million commercially insured lives.
METHODS: All study subjects experienced low back pain between January 2020 and December 2021. Digital MSK participants enrolled in the digital MSK low back program between January 2020 and December 2021. Non-participants had low back pain related physical therapy (PT) between January 2020 and December 2021. Digital MSK participants were matched to non-participants with similar demographics, comorbidities and baseline MSK-related medical care use. Spinal fusion surgery rates at 12 months post participation were compared.
RESULTS: Compared to non-participants, digital MSK participants had lower rates of spinal fusion surgery in the post-period (0.7% versus 1.6%; p < 0.001). Additionally, in the augmented inverse probability weighting (AIPW) model, digital MSK participants were found to have decreased odds of undergoing spinal fusion surgery (adjusted odds ratio: 0.64, 95% CI: 0.51-0.81).
CONCLUSIONS: This study provides evidence that participation in a digital MSK program is associated with a lower rate of spinal fusion surgery.

OBJECTIVE: To estimate the effect of reversible postpartum contraception use on the risk of recurrent pregnancy condition in the subsequent pregnancy and if this effect was mediated through lengthening the interpregnancy interval (IPI).
METHODS: We used data from the Maine Health Data Organization\'s Maine All Payer Claims dataset. Our study population was Maine women with a livebirth index pregnancy between 2007 and 2019 that was followed by a subsequent pregnancy starting within 60 months of index pregnancy delivery. We examined recurrence of three pregnancy conditions, separately, in groups that were not mutually exclusive: prenatal depression, hypertensive disorders of pregnancy (HDP), and gestational diabetes (GDM). Effective reversible postpartum contraception use was defined as any intrauterine device, implant, or moderately effective method (pills, patch, ring, injectable) initiated within 60 days of delivery. Short IPI was defined as ≤ 12 months. We used log-binomial regression models to estimate risk ratios and 95 % confidence intervals, adjusting for potential confounders.
RESULTS: Approximately 41 % (11,448/28,056) of women initiated reversible contraception within 60 days of delivery, the prevalence of short IPI was 26 %, and the risk of pregnancy condition recurrence ranged from 38 % for HDP to 55 % for prenatal depression. Reversible contraception initiation within 60 days of delivery was not associated with recurrence of the pregnancy condition in the subsequent pregnancy (aRR ranged from 0.97 to 1.00); however, it was associated with lower risk of short IPI (aRR ranged from 0.67 to 0.74).
CONCLUSIONS: Although initiation of postpartum reversible contraception within 60 days of delivery lengthens the IPI, our findings suggest that it does not reduce the risk of prenatal depression, HDP, or GDM recurrence. This indicates a missed opportunity for providing evidence-based healthcare and health interventions in the intrapartum period to reduce the risk of recurrence.

This retrospective cohort study identifies differences between rates of selected mental illnesses and sleep disorders according to eight gynecological problems. Analyses utilize medical claims data for adult employees of a large corporation during 2017-2021. Women with a gynecological problem (most notably pain, endometriosis, pelvic inflammation and bleeding) are significantly more likely to experience mental illness. Several gynecological problems are also significantly associated with sleep disorders. Women with a gynecological problem (vs. none) are 50% more likely to have a mental health problem and 44% more likely to have a sleep disorder after adjusting for age, marital status, dependent children and year. The largest differences between higher (%) mental illness and sleep disorders appear for hyperplasia (6% vs. 45%), cancer (11% vs. 68%), pelvic inflammation (46% vs. 79%) and pain (79% vs. 43%), respectively. On the other hand, the rate of having one or more gynecological problems ranges from 7.1% for women with no mental illness or sleep disorder to 20.6% for women with schizophrenia. Understanding the association between gynecological problems, mental illness and sleep disorders can help clinicians more effectively identify and treat patients.

In a retrospective, ecological analysis of US medical claims, visit rates explained more of the geographic variation in outpatient antibiotic prescribing rates than per-visit prescribing. Efforts to reduce antibiotic use may benefit from addressing the factors that drive higher rates of outpatient visits, in addition to continued focus on stewardship.

BACKGROUND: Group A Streptococcus (GAS) causes an estimated 5.2 million outpatient visits for pharyngitis annually in the United States, with incidence peaking in winter, but the annual spatiotemporal pattern of GAS pharyngitis across the United States is poorly characterized.
METHODS: We used outpatient claims data from individuals with private medical insurance between 2010 and 2018 to quantify GAS pharyngitis visit rates across U.S. census regions, subregions, and states. We evaluated seasonal and age-based patterns of geographic spread and the association between school start dates and the summertime upward inflection in GAS visits.
RESULTS: The South had the most visits per person (yearly average, 39.11 visits per 1000 people; 95% confidence interval, 36.21-42.01) and the West had the fewest (yearly average, 17.63 visits per 1000 people; 95% confidence interval, 16.76-18.49). Visits increased earliest in the South and in school-age children. Differences in visits between the South and other regions were most pronounced in the late summer through early winter. Visits peaked earliest in central southern states, in December to January, and latest on the coasts, in March. The onset of the rise in GAS pharyngitis visits correlated with, but preceded, average school start times.
CONCLUSIONS: The burden and timing of GAS pharyngitis varied across the continental United States, with the South experiencing the highest overall rates and earliest onset and peak in outpatient visits. Understanding the drivers of these regional differences in GAS pharyngitis will help in identifying and targeting prevention measures.

This study compares the rate of selected types of mental illnesses (stress, anxiety, depression) and sleep disorders (insomnia, sleep apnea) according to the status of eight male genital problems. Analyses utilize medical claims data for male employees aged 18 to 64 years of a large corporation, 2017 to 2021. Approximately 1,076 (7.3%) men per year have one or more genital problems. The most common being benign prostatic hyperplasia (BPH; 3.8%) and then erectile dysfunction (ED; 1.7%). For BPH patients, the rate experiencing stress, anxiety, depression, or a combination of these is 0.96%, 6.2%, 5.3%, and 5.1%, respectively. Corresponding rates for ED are 1.5%, 7.2%, 5.9%, and 7.5%. For BPH patients, the rate experiencing insomnia, sleep apnea, or both is 3.1%, 22.7%, and 2.0%, respectively. Corresponding rates for ED are 1.2%, 20.6%, and 2.2%. Male genital problems positively associate with having one or more mental illnesses (stress, anxiety, depression), except for hydrocele, with ED and penis disorder having the strongest associations. Male genital problems also positively associate with having insomnia and/or sleep apnea, except for infertility and orchitis, with BPH and ED having the strongest associations. The positive associations involving BPH and ED with mental illnesses are each more pronounced in the younger age group (18-49 vs. 50-64). Similar results are seen in the models involving sleep disorders. Thus, comorbid male genital problems, mental illnesses, and sleep disorders exist, with the strength of associations unique to the male genital problem and sometimes modified by age.

UNASSIGNED: Cardiovascular disease (CVD) and cancer share several risk factors. Although preclinical models show that various types of CVD can accelerate cancer progression, clinical studies have not determined the impact of atherosclerosis on cancer risk.
UNASSIGNED: The objective of this study was to determine whether CVD, especially atherosclerotic CVD, is independently associated with incident cancer.
UNASSIGNED: Using IBM MarketScan claims data from over 130 million individuals, 27 million cancer-free subjects with a minimum of 36 months of follow-up data were identified. Individuals were stratified by presence or absence of CVD, time-varying analysis with multivariable adjustment for cardiovascular risk factors was performed, and cumulative risk of cancer was calculated. Additional analyses were performed according to CVD type (atherosclerotic vs nonatherosclerotic) and cancer subtype.
UNASSIGNED: Among 27,195,088 individuals, those with CVD were 13% more likely to develop cancer than those without CVD (HR: 1.13; 95% CI: 1.12-1.13). Results were more pronounced for individuals with atherosclerotic CVD (aCVD), who had a higher risk of cancer than those without CVD (HR: 1.20; 95% CI: 1.19-1.21). aCVD also conferred a higher risk of cancer compared with those with nonatherosclerotic CVD (HR: 1.11; 95% CI: 1.11-1.12). Cancer subtype analyses showed specific associations of aCVD with several malignancies, including lung, bladder, liver, colon, and other hematologic cancers.
UNASSIGNED: Individuals with CVD have an increased risk of developing cancer compared with those without CVD. This association may be driven in part by the relationship of atherosclerosis with specific cancer subtypes, which persists after controlling for conventional risk factors.

UNASSIGNED: To develop and validate machine learning models for predicting COVID-19 related hospitalization as early as CDC contact tracing using integrated CDC contact tracing and South Carolina medical claims data.
UNASSIGNED: Using the dataset (n=82,073, 1/1/2018 - 3/1/2020), we identified 3,305 patients with COVID-19 and were captured by contact tracing. We developed and validated machine learning models (i.e., support vector machine, random forest, XGboost), followed by multi-level validations and pilot statewide implementation.
UNASSIGNED: Using 10-cross validation, random forest outperformed other models (F1=0.872 for general hospitalization and 0.763 for COVID-19 related hospitalization), followed by XGBoost (F1=0.845 and 0.682) and support vector machine (F1=0.845 and 0.644). We identified new self-reported symptoms from contact tracing (e.g., fatigue, congestion, headache, loss of taste) that are highly predictive of hospitalization.
UNASSIGNED: Our study demonstrated the feasibility of identifying individuals at risk of hospitalization at the time of contact tracing for early intervention and prevention.
UNASSIGNED: Our findings demonstrate existing promise for leveraging CDC contact tracing for establishing a cost-effective statewide surveillance and generalizability for nationwide adoption for enhancing pandemic preparedness in the US.