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Over the last decade, biomarker research has identified potential biomarkers for the diagnosis, prognosis, and management of traumatic brain injury (TBI). Several cerebrospinal fluid (CSF) and serum biomarkers have shown promise in predicting long-term outcome after severe TBI. Despite this increased focus on identifying biomarkers for outcome prognostication after a severe TBI, several challenges still exist in effectively modeling the significant heterogeneity observed in TBI-related pathology, as well as the biomarker-outcome relationships. Biomarker data collected over time are usually summarized into single-point estimates (e.g., average or peak biomarker levels), which are, in turn, used to examine the relationships between biomarker levels and outcomes. Further, many biomarker studies to date have focused on the prediction power of biomarkers without controlling for potential clinical and demographic confounders that have been previously shown to affect long-term outcome. In this article, we demonstrate the application of a practical approach to delineate and describe distinct subpopulations having similar longitudinal biomarker profiles and to model the relationships between these biomarker profiles and outcomes while taking into account potential confounding factors. As an example, we demonstrate a group-based modeling technique to identify temporal S100 calcium-binding protein B (S100b) profiles, measured from CSF over the first week post-injury, in a sample of adult subjects with TBI, and we use multivariate logistic regression to show that the prediction power of S100b biomarker profiles can be superior to the prediction power of single-point estimates.

We conducted a mediation analysis of the provider team's role in changes to chronic condition medication adherence among cancer survivors. We used a retrospective, longitudinal cohort design following Medicare beneficiaries from 18-months before through 24-months following cancer diagnosis. We included beneficiaries aged ≥66 years newly diagnosed with breast, colorectal, lung or prostate cancer and using medication for non-insulin anti-diabetics, statins, and/or anti-hypertensives and similar individuals without cancer from Surveillance, Epidemiology, and End Results-Medicare data, 2008-2014. Chronic condition medication adherence was defined as a proportion of days covered ≥ 80%. Provider team structure was measured using two factors capturing the number of providers seen and the historical amount of patient sharing among providers. Linear regressions relying on within-survivor variation were run separately for each cancer site, chronic condition, and follow-up period. The number of providers and patient sharing among providers increased after cancer diagnosis relative to the non-cancer control group. Changes in provider team complexity explained only small changes in medication adherence. Provider team effects were statistically insignificant in 13 of 17 analytic samples with significant changes in adherence. Statistically significant provider team effects were small in magnitude (<0.5 percentage points). Increased complexity in the provider team associated with cancer diagnosis did not lead to meaningful reductions in medication adherence. Interventions aimed at improving chronic condition medication adherence should be targeted based on the type of cancer and chronic condition and focus on other provider, systemic, or patient factors.

The biochemical cascades associated with cell death after traumatic brain injury (TBI) involve both pro-survival and pro-apoptotic proteins. We hypothesized that elevated cerebrospinal fluid (CSF) Bcl-2 and cytochrome C (CytoC) levels over time would reflect cellular injury response and predict long-term outcomes after TBI. Cerebrospinal fluid Bcl-2 and CytoC levels were measured for 6 days after injury for adults with severe TBI (N = 76 subjects; N = 277 samples). Group-based trajectory analysis was used to generate distinct temporal biomarker profiles that were compared with Glasgow Outcome Scale (GOS) and Disability Rating Scale (DRS) scores at 6 and 12 months after TBI. Subjects with persistently elevated temporal Bcl-2 and CytoC profiles compared with healthy controls had the worst outcomes at 6 and 12 months (P ≤ 0.027). Those with CytoC profiles near controls had better long-term outcomes, and those with declining CytoC levels over time had intermediate outcomes. Subjects with Bcl-2 profiles that remained near controls had better outcomes than those with consistently elevated Bcl-2 profiles. However, subjects with Bcl-2 values that started near controls and steadily rose over time had 100% good outcomes by 12 months after TBI. These results show the prognostic value of Bcl-2 and CytoC profiles and suggest a dynamic apoptotic and pro-survival response to TBI.

As an astrocytic protein specific to the central nervous system, S100b is a potentially useful marker in outcome prediction after traumatic brain injury (TBI). Some studies have questioned the validity of S100b, citing the extracerebral origins of the protein as reducing the specificity of the marker. This study evaluated S100b as a prognostic biomarker in adult subjects with severe TBI (sTBI) by comparing outcomes with S100b temporal profiles generated from both cerebrospinal fluid (CSF) (n=138 subjects) and serum (n=80 subjects) samples across a 6-day time course. Long-bone fracture, Injury Severity Score (ISS), and isolated head injury status were variables used to assess extracerebral sources of S100b in serum. After TBI, CSF and serum S100b levels were increased over healthy controls across the first 6 days post-TBI (p≤0.005 and p≤0.031). Though CSF and serum levels were highly correlated during early time points post-TBI, this association diminished over time. Bivariate analysis showed that subjects who had temporal CSF profiles with higher S100b concentrations had higher acute mortality (p<0.001) and worse Glasgow Outcome Scale (GOS; p=0.002) and Disability Rating Scale (DRS) scores (p=0.039) 6 months post-injury. Possibly as a result of extracerebral sources of S100b in serum, as represented by high ISS scores (p=0.032), temporal serum profiles were associated with acute mortality (p=0.015). High CSF S100b levels were observed in women (p=0.022) and older subjects (p=0.004). Multivariate logistic regression confirmed CSF S100b profiles in predicting GOS and DRS and showed mean and peak serum S100b as acute mortality predictors after sTBI.

Supplemental Digital Content is available in the text. Background:The Patient Protection and Affordable Care Act (PPACA) established new parameters for the individual and small group health insurance markets starting in 2014. We study these 2 reformed markets by comparing health risk and costs to the more mature large employer market.Study Data:For 2017, claims data for all enrollees in PPACA-compliant individual and small group market plans as well as claims data from a sample of large employer market enrollees.Variables and Methodology:Risk scores and total (unadjusted and risk-adjusted) per-member-per-month (PMPM) allowed charges. Differences across markets in enrollment duration, age, and geographic distribution are addressed. The analysis is descriptive.Results:Compared with large employer market enrollees, health risk was 3% lower among PPACA small group market enrollees and 20% higher among PPACA individual market enrollees. After adjusting for differences in health risk, enrollees in the PPACA individual market had 27% lower PMPM allowed charges than enrollees in the large employer market and enrollees in the PPACA small group market had 12% lower PMPM allowed charges than enrollees in the large employer market.Conclusions:On average, the PPACA individual market enrolls sicker individuals than the 2 group markets. But this does not translate to higher health costs; in fact, enrollees in the PPACA individual market accumulate lower allowed charges than enrollees in the large employer market. Lower-income enrollees particularly accumulate lower allowed charges. Narrower networks and increased enrollee cost-sharing among individual market plans, though they may reduce the value of coverage, likely significantly reduce allowed charges.

Insurers have the potential to reduce health care costs by negotiating lower prices with narrow provider networks. Although narrow networks may impose substantial and unexpected cost burden on enrollees who use out-of-network services. Some states have implemented policies on network adequacy to ensure plan networks include a minimal set of providers, or on arbitration requirements, whereby insurers and providers are required to enter mediation to arrive at a payment agreement. This dissertation sought to estimate the impact of any out-of-network service use on patient out-of-pocket (OOP) cost sharing, plan payments and total payments (sum of patient OOP cost sharing and plan payment) as observed in claims data in Aim 1. Aim 2 estimated the differential effect of out-of-network service use on follow-up evaluation and management (E&M) visits. Aim 3 examined whether state network adequacy or arbitration policy changes during the study period affected the probability of out-of-network service use, as well as payments among those who used any out-of-network services. The study focused on two samples: those with an acute myocardial infarction (AMI) or a total knee replacement (TKR). Enrollees who used any out-of-network services had higher patient OOP cost sharing, plan payments and total payments compared to enrollees who did not use out-of-network services. The differential effect of any out-of-network service use on follow-up E&M visits was not statistically significant. Relevant network adequacy and arbitration state policy changes during study period lowered the probability of using out-of-network services for preferred provider organization (PPO) or point of service (POS) plan enrollees. As a result of state policy changes, enrollees in the PPO/POS plans in the AMI sample experienced a reduction in patient OOP cost sharing, as did enrollees in consumer-driven health plan or high deductible health plan and PPO/POS in the TKR samples. Enrollees in the health maintenance organization or exclusive provider organization plans in the TKR sample observed an increase in plan payments and total payments. While state network adequacy and arbitration policy changes succeeded in reducing OOP cost burden, they increased plan payments and total payments for some cohorts.

[...]of lagging vaccinations and the more infectious Delta variant, COVID-19 cases, hospitalizations, and deaths are on the rise again. [...]our analysis of pre-pandemic private insurance claims for pneumonia hospitalizations with complications averaged $20,292 (though the cost for hospitalizations requiring a ventilator are much higher). Though this estimate may not be generalizable to the U.S. population, it is a more conservative estimate of the share of COVID-19 hospitalizations among vaccinated people. [...]we multiply the number of adults hospitalized with COVID-19 by 86% to get the number of unvaccinated adults hospitalized with COVID-19.

HEALTH CARE POLICY As part of the Inflation Reduction Act, the Senate recently passed a three-year extension (through 2025) of enhanced subsidies for people buying their own health coverage on the Affordable Care Act Marketplaces. If signed into law, the Inflation Reduction Act will prevent steep increases in Marketplace premium payments. The passage of the Inflation Reduction Act will extend temporary subsidies, preventing out-of-pocket premium payments from rising across the board next year for virtually all 13 million subsidized enrollees.

HEALTH CARE INDUSTRY \"The Medical Loss Ratio (MLR) provision of the Affordable Care Act (ACA) limits the amount of premium income that insurers can keep for administration, marketing, and profits. Expected rebate amounts vary by market segment, with the majority going to individual market enrollees, including ACA Marketplace enrollees. The average individual market loss ratio (without adjusting for quality improvement expenses or taxes) was 88%, meaning these insurers spent out an average of 88% of their premium income in the form of health claims in 2021.

After an initial decrease in visits, utilization has now surpassed pre-pandemic levels; In-person outpatient visits have exceeded t1he 6-months immediately preceding the pandemic (106% in September 2019-February 2020 vs. 110% in March-August 2021), but with an additional boost from telehealth visits, the total number of outpatient visits between March and August 2021 was 19% higher than the number of visits before the pandemic in March to August of 2019. [...]telehealth may not reduce spending if it leads to increased utilization or requires in-person visits in addition to the telehealth visit, even if telehealth is available at lower prices. Telehealth may further impact costs of health services if improved case management of complex conditions reduces utilization of high-cost services, such as emergency room visits.