Provision of Hospital Price Information After Increases in Financial Penalties for Failure to Comply With a US Federal Hospital Price Transparency Rule.

Importance: Price transparency regulations aim to help patients make informed decisions about medical care, but enforcing these rules is a policy challenge. There may be an association between financial penalties and hospital compliance for enforcing price transparency regulations. Objective: To evaluate the association between financial penalties and acute care hospital compliance with the 2021 Centers for Medicare & Medicaid Services (CMS) Price Transparency Rule. Design, Setting, and Participants: This cohort study uses an instrumental variable design to evaluate the responses of 4377 acute care hospitals in the US operating in 2021 and 2022 to changes in financial penalties in the context of a federal rule requiring hospitals to disclose privately negotiated prices. Exposure: Changes in noncompliance penalties between 2021 and 2022 based on a nonlinear function of bed counts. Main Outcomes and Measures: Whether hospitals publicly posted a machine-readable file with private, payer-specific negotiated prices at the service-code level. Negative controls were used to address confounding. Results: The final sample included 4377 hospitals. Compliance increased from 70.4% (n = 3082) in 2021 to 87.7% (n = 3841) in 2022, with 90.2% of hospitals (n = 3948) reporting prices in at least 1 year. Noncompliance penalties increased from $109 500/y in 2021 to a mean (SD) of $510 976 ($534 149)/y in 2022. Penalties in 2022 were substantial, averaging 0.49% of total hospital revenue, 0.53% of total hospital costs, and 1.3% of total employee wages. Compliance increases were significantly positively correlated with penalty increases: a $500 000 increase in penalty was associated with a 2.9-percentage point (95% CI, 1.7-4.2 percentage points; P < .001) increase in compliance. Results were robust to controlling for observable hospital characteristics. No associations were found for preperiod (2021) compliance or ranges of bed counts where penalties do not vary. Conclusions and Relevance: In this cohort study of 4377 hospitals, compliance with the CMS Price Transparency Rule was associated with increased financial penalties. These findings are relevant for the enforcement of other regulations designed to promote transparency in health care.

US Hospital Characteristics Associated With Price Transparency Regulation Compliance.

This cross-sectional study examines associations between characteristics of US hospitals and their compliance with Centers for Medicare & Medicaid Services regulations for transparency of insurance-negotiated prices.

Turnover in Zero-Premium Status Among Health Insurance Marketplace Plans Available to Low-Income Enrollees.

Importance: Recent subsidy enhancements in Affordable Care Act (ACA) Marketplaces made many low-income enrolles (below 150% of the federal poverty level [FPL]) eligible for 2 free silver-tier plans. eligible for 2 free silver-tier plans. However, an unintended consequence of this structure is that the identity of which silver plans are free will often "turn over" between years, requiring that enrollees actively initiate premium payment (or lose coverage). The prevalence of this free-plan turnover is not known. Objective: To measure the prevalence of free-plan turnover in ACA Marketplaces and to estimate how many enrollees below 150% of FPL are likely to be affected. Design Setting and Participants: This observational cross-sectional study used data on plan offerings and premiums in 33 state ACA Marketplaces using HealthCare.gov in 2021 and 2022, along with estimates of county-level enrollee characteristics and plan selection patterns. The enrollment-weighted share of county markets affected by free-plan turnover was quantified, along with the association of turnover with enrollee and market characteristics. Estimates of the number of affected low-income enrollees were calculated using the data plus statistics reported in past research. Data were analyzed from November 21, 2021, to February 28, 2022. Results: This study found that turnover of zero-premium plans was quite common, with 93% of HealthCare.gov counties (weighted by enrollment) experiencing at least 1 zero-premium plan in 2021 turning over to nonfree in 2022; 84% of counties experienced turnover of all $0 silver plans from 2021 to 2022. This turnover affected an estimated 1.36 million people with incomes below 150% of FPL. Turnover was more common in counties with a higher share of non-White enrollees, in Medicaid nonexpansion states, in counties with more carriers, and in counties with changes in the number of offered plans. Conclusions and Relevance: The findings of this cross-sectional study suggest that owing to the prevalence of zero-premium plan turnover, many low-income ACA enrollees faced elevated risk of disenrollment at the start of 2022. Outreach to affected enrollees and other actions to encourage coverage retention and midyear reenrollment could help mitigate coverage losses.

Characterizing the Reaction of Doctors to COVID-19 on Twitter.

With the recent surges of new COVID-19 variants, clear public health messaging on social media has become more vital than ever. One important source of public health information are messages and reactions expressed by medical professionals. However, the content of messages promogulated by these experts are not fully understood. In this study, we demonstrate how unique Twitter data can be used to explore doctors' reactions to the early months of the COVID-19 pandemic. We examine 265,412 English-language tweets about COVID-19 from doctors and a comparable subset of tweets from non-doctors using two-sample t-tests with a Bonferroni-corrected significance threshold. We elucidate how discussion differed over time and in comparison to non-doctors. Tweets spiked surrounding major events and in locations with rising case numbers. Discussion from doctors initially focused on the origin of the virus in Wuhan, later switching to calls to "stay home." Doctors tweeted more often about public health and healthcare workers, whereas non-doctors were more likely to tweet about political topics, including China and the Trump administration. The differences in how doctors and non-doctors engage about COVID-19 can provide insight into the similarities and differences in communication between medical experts and the public. For example, in future surges, experts could tailor their health messaging around topics of interest to the general public to increase engagement. Alternatively, topics that differ across groups may warrant educational messages to better align expert and public perspectives. By identifying both areas of shared purpose and differences in prioritized topics, future public health communications may benefit from analyses that compare the social media messages promulgated by various groups.

Live-dead assay on unlabeled cells using phase imaging with computational specificity.

Existing approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.

Do physician incentives increase patient medication adherence?

OBJECTIVE: To test the effectiveness of physician incentives for increasing patient medication adherence in three drug classes: diabetes medication, antihypertensives, and statins. DATA SOURCES: Pharmacy and medical claims from a large Medicare Advantage Prescription Drug Plan from January 2011 to December 2012. STUDY DESIGN: We conducted a randomized experiment (911 primary care practices and 8,935 nonadherent patients) to test the effect of paying physicians for increasing patient medication adherence in three drug classes: diabetes medication, antihypertensives, and statins. We measured patients' medication adherence for 18 (6) months before (after) the intervention. DATA COLLECTION/EXTRACTION METHODS: We obtained data directly from the health insurer. PRINCIPAL FINDINGS: We found no evidence that physician incentives increased adherence in any drug class. Our results rule out increases in the proportion of days covered by medication larger than 4.2 percentage points. CONCLUSIONS: Physician incentives of $50 per patient per drug class are not effective for increasing patient medication adherence among the drug classes and primary care practices studied. Such incentives may be more likely to improve measures under physicians' direct control rather than those that predominantly reflect patient behaviors. Additional research is warranted to disentangle whether physician effort is not responsive to these types of incentives, or medication adherence is not responsive to physician effort. Our results suggest that significant changes in the incentive amount or program design may be necessary to produce responses from physicians or patients.

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences.

Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

PROMIS Computer Adaptive Tests Compared With Time to Brake in Patients With Complex Lower Extremity Trauma.

OBJECTIVES: To compare the PROMIS Physical Function and Pain Interference Computer Adaptive Tests (PROMIS PF CAT and PROMIS PI CAT) with time to brake (TTB) in patients with complex lower extremity traumas for evaluating whether patients can safely return to driving. DESIGN: Prospective. SETTING: Level-1 trauma center. PATIENTS: Sixty-three patients with lower extremity injuries to the pelvis, acetabulum, hip, femur, knee, tibia/fibula, ankle, and foot within 15 weeks of treatment. INTERVENTION: The TTB of patients with complex lower extremity trauma were tested at various time points postoperatively on a computerized driving simulator. Patients concurrently completed PROMIS PF CAT and PROMIS PI CAT. MAIN OUTCOME MEASURE: Correlations between TTB, PROMIS PF CAT, and PROMIS PI CAT. RESULTS: The mean TTB for the healthy control group was 0.61 seconds. There was a statistically significant correlation between time since treatment and TTB (B = -0.008 s/d; P = 0.041) for right-sided lower extremity injuries below the knee (tibia/fibula, ankle, foot). TTB for right-sided injuries below the knee also significantly correlated with PROMIS PI CAT (B = 0.022; P = 0.029). The PROMIS PI CAT value was 43 when the healthy control group TTB was equal to 0.61 seconds. CONCLUSIONS: This study suggests that the PROMIS PI CAT can be used as an adjunct to the TTB in assessing whether a patient can safely return to driving.