US Health Care Research Articles

American health system problems and potential solutions

Abstract. The United States healthcare system indicates a paradox. It becomes famous for advances while plagues for significant challenges. This paper will emphasize the situation of the American health system, focus on its complexity and find out the potential factors. The burden stands out as a prominent characteristic of the US healthcare system. Despite its wealth, the US spends a disproportionate amount of its GDP on healthcare, surpassing other nations significantly. This financial strain affects individuals, families, insurers, healthcare facilities, and government budgets. The system lacks universal coverage and operates as a mixed system, combining publicly financed programs like Medicare and Medicaid with privately financed market coverage. One of the main challenges is the absence of price controls, leading to inflated healthcare costs compared to other countries. The US relies on individual insurers to negotiate prices, increasing prescription medication and medical services expenses. This model incentivizes innovation but burdens American consumers with subsidizing healthcare costs globally. The complexity and much broader structural problems intertwine, involving dispersive payment systems, for-profit markets and ultimately expensive management costs. All these factors push the price of American health soring, even persistent increasing through decades. Thus, this paper will have potential solutions by price negotiation and regulation, improving price transparency and easing price-setting. In addition, this paper will also analyze the effects of stakeholders due to these solutions. Generally, solving the issues of the US healthcare system requires a nuanced understanding of its intricacies and a concerted effort to promote affordability, accessibility, and quality of care for all Americans.

A Different View of the Issue: Seeing Disability Through the Lens of Diversity and Inclusivity in Healthcare in the United States

ABSTRACT Advocacy for diversity, inclusion and equity within healthcare continues to be an issue of importance and attention nationally. However, definitions of diversity often do not include people with disability. This commentary describes barriers to healthcare utilization experienced by people with disabilities in the United States (U.S.) and presents a rationale to refocus disability through this lens of diversity, equity, and inclusion within the U.S. systems of care. Bringing light to the ongoing challenges and inequities faced by our patients with disability is an essential first step toward improved inclusivity, leading to improved welfare of persons with disability as a whole.

Abstract 4135712: Mortality and Cardiovascular Complications Associated with Weight Loss Drugs among Breast Cancer Females Under Cardiotoxic Therapies: A Real-World Populational Study in the United States

Background: Obesity is an adverse prognostic factor for breast cancer (BC). While liraglutide and semaglutide, derived from antidiabetic glucagon-like peptide-1 receptor agonists (GLP1RA), are established weight loss drugs known for their cardiovascular safety in the general obese population, their safety in BC patients undergoing cardiotoxic antineoplastic therapies remains less understood. Objective: To investigate the mortality and cardiovascular outcomes related to GLP1RA used for weight loss among the highly susceptible BC females. Methods: This retrospective cohort study was based on the TrinetX network, comprising real-time health records from over 60 US healthcare organizations. The study population included obese females (≥18 years old) who received at least three prescriptions of either exclusive GLP1RA (liraglutide or semaglutide) or non-GLP1RA weight loss drugs (phentermine, bupropion-naltrexone, orlistat) upon BC diagnosis between 01/01/2015 and 01/01/2022. The index date was the initiation of systemic anti-cancer treatment, including chemotherapy (anthracycline, taxane, or cyclophosphamide), and/or anti-HER2 agents (trastuzumab, pertuzumab, or lapatinib). We used 1:1 propensity score-matching (PSM) to balance demographics, BMI, comorbidities, concurrent medications for cardiovascular diseases and metabolic disorders, BC receptor status and prior treatment, and levels of serum cholesterol (LDL, HDL) and hemoglobin A1c. Cox regression models were applied to compute hazard ratios (HR) and 95% confidence intervals (CIs). Follow-up continued until 05/24/2024, or until adverse cardiovascular events or death occurred. Results: Among 380 PSM-balanced pairs, the GLP1RA group (mean age: 57.6±11) showed significantly lower risks of all-cause mortality (HR 0.593, 95% CI 0.457-0.77), acute heart failure (HR 0.496, 95% CI 0.286-0.859), angina pectoris (HR 0.566, 95% CI 0.343-0.936), and acute stroke (HR 0.661, 95% CI 0.46-0.951) than the non-GLP1RA group (mean age: 57.5±12). Otherwise, no significant difference was shown in acute myocardial infarction (HR 0.787, 95% CI 0.495-1.251), pulmonary hypertension (HR 0.777, 95% CI 0.55-1.099), or arrhythmias (HR 0.829, 95% CI 0.566-1.215). Conclusion: Compared to non-GLP1RA weight loss agents, GLP1RA offers better survival and cardiovascular protection for BC patients undergoing cardiotoxic therapies. Future studies are warranted to validate the safety of these weight loss drugs during the BC treatment continuum.

Cost-effectiveness of midomafetamine-assisted therapy (MDMA-AT) in chronic and treatment-resistant post-traumatic stress disorder of moderate or higher severity: A health-economic model.

To explore the cost-effectiveness of midomafetamine-assisted therapy (MDMA-AT) compared to placebo with therapy (PT) in US healthcare settings. A health state-transition model was used to analyze the cost-effectiveness of MDMA-AT for treating patients with chronic PTSD of moderate or higher severity. Both treatment arms consisted of 3 preparation (90-min), 3 interventional (8-h), and 9 integration (90-min) sessions, lasting ~4 months total. All sessions included psychotherapy, with interventional also including MDMA or placebo. After receiving treatment, patients were distributed across health states of No PTSD (not meeting PTSD diagnostic criteria), Non-Severe PTSD (treatment responders), Severe PTSD (treatment non-responders), and death. Each state had unique healthcare costs and utilities sourced from real-world data analysis and patient data from MDMA-AT clinical trials (including long-term follow-up). The base-case analysis considered the payer's perspective with a 5-year horizon, 3.5% annual cost and effect discounts, and an assumed MDMA medication price of $12,000 per session. Trial-derived utilities and US life tables mortality data were used to calculate quality-adjusted life years (QALY). The main outcome was an incremental cost-effectiveness ratio (ICER) with a $150,000 willingness-to-pay (WTP) threshold. The base-case ICER was $83,845 per QALY. Total direct costs were $64,745 in the MDMA-AT and $33,132 in the PT arms ($31,613 increment). The costs of intervention were $48,376 for MDMA-AT and $12,376 for PT. The highest MDMA medication cost to fit under the WTP threshold was $20,314 per session. Costs related to PTSD healthcare visits and other PTSD treatments were lower with MDMA-AT than PT (-$2,511 and -$1,877 increments, respectively). Utility benefits were higher in MDMA-AT than PT, with 3.691 and 3.314 QALYs generated over 5 years, respectively (0.377 QALY increment). These data suggest MDMA-AT may be a cost-effective treatment compared to PT for patients with chronic PTSD of moderate or higher severity.

Abstract 4128599: Facility-level Variation Underlying Low Inferior Vena Cava Filter Retrieval in the United States

Background: Inferior vena cava (IVC) filters are commonly implanted in patients with venous thromboembolism (VTE) who are unable to receive anticoagulation, to protect against clot migration to the heart. With prolonged implantation, IVC filters are associated with complications: device fracture, migration, penetration into adjacent organs and worsened VTE. Two Federal Drug Administration advisories and multi-society guidelines have emphasized the importance of timely retrieval but national retrieval rates remain low (<30%). Aims: To quantify hospital-level variation in IVC filter retrieval , describe time-based retrieval rates and examine factors associated with retrieval. Methods: IVC Filter implantation for all patients >= 18 years was identified in the 2016-2020 inpatient and outpatient 100% limited data set Medicare files using claims codes. Hospital information for the implanting facility was cross-linked from the American Hospital Association and Healthcare Cost Report Information System files, including identifying information, teaching status, census location, operating margin and % uncompensated care. IVC filter retrieval rates and time to retrieval from implantation was calculated. Bayesian hospital profiling methods were used to quantify 1-year retrieval rate for all U.S. facilities, adjusting for patient factors – demographics, diagnostic indications and comorbidities. Results: Among Medicare beneficiaries, there were 140,481 IVC Filter implantations across 2,850 facilities. Excluding patients who died within 90 days of implantation (25.7%), retrieval rates at 3 months, 1 year and anytime were 7.9%, 18.7% and 20.0% respectively. IVC Filter retrieval within 1 year varied significantly at the facility-level, from 0-100% . Focusing on facilities with at least 13 IVC filter implantations each year (top 25%ile volume), 1-year retrieval ranged from 0 to 74.5%. Higher 1-year retrieval was seen among higher implantation volume (12.4% bottom quartile, 20.5% top quartile), teaching (21.1% teaching vs. 16.9% nonteaching) and non-safety net (21.1% low uncompensated care, 15.0% high uncompensated care) hospitals. Retrieval rates did not vary significantly by hospital operating margin or rurality. Conclusion(s): There is low overall IVC filter retrieval in the United States with large underlying facility-level variation. Focused examination of high-performing facilities could yield insights on how to improve device retrieval nationally.

Abstract 4123530: Disparities in Hypertension Treatment Intensification among Adults in a Large United States Healthcare System

Background: There are racial/ethnic and socioeconomic status (SES) disparities in hypertension control, even in populations with regular care. It is unclear if clinical inertia by clinicians contributes to these disparities. Objectives: To quantify racial/ethnic and SES disparities in treatment intensification (TI) among adults with hypertension. Methods: We performed a retrospective cohort study using electronic health records from Johns Hopkins primary care practices from January 2018 to December 2022. We included non-Hispanic Black (Black) and non-Hispanic White (White) adults with at least 2 elevated blood pressure readings (>=140/90 mm Hg) in the 12 months prior to the index primary care visit and a diagnosis of essential hypertension. We excluded patients with diagnoses of end-stage renal disease, liver disease, dementia, and metastatic solid tumor. Patients could contribute multiple index visits. We measured SES using the national Area Deprivation Index, which comprises 17 neighborhood-level SES indicators, and dichotomized the population into high and low median SES groups. We defined TI as a change in antihypertensive class or dose increase within 14 days of the index visit. We balanced covariates reflecting clinical need at the index visit (age, sex, blood pressure readings, cardiometabolic comorbidities, body mass index) and the index visit’s calendar time across racial/ethnic and SES groups using inverse probability weighting. We estimated annual race/ethnic and SES specific TI rates and risk difference measures of disparity with 95% confidence intervals (CI) using a clustered bootstrap. Results: The cohort included 25,287 patients (11,800 Black, 13,487 White) with 79,898 eligible visits. Black patients were more often younger, female, and residing in low SES areas compared to White patients. In 2018, TI rates for Black patients (37%, 95% CI: 36-38%) were slightly lower than rates for White patients (39%, 95% CI: 38-40%). In 2022, the disparity persisted, with the Black patients’ TI rate lower by 3% (95% CI: -5%, -1%). Similarly, low SES patients had lower TI rates than high SES patients by 2% to 3% over the study period. Conclusion: Black patients and those from low SES consistently had modestly lower rates of TI compared to White patients and those from high SES. It will be important to identify the drivers and clinical implications of these treatment disparities.

INNV-38. 3 DAYS-ON-1 DAY-OFF FRACTIONATED USE PROTOCOL FOR IMPROVED COMPLIANCE AND PREVENTATIVE SKIN SAFETY FOR USE OF TUMOR TREATING FIELDS: PRACTICE IMPROVEMENT STRATEGY IN NEURO-ONCOLOGY

Abstract BACKGROUND Compassionate care delivery requires that providers understand patient values and adopt practices aimed to improve the quality of extended survival. Many brain tumor clinical trials measure survival outcomes based on therapeutic interventions, but often fail to anticipate patient noncompliance and the provider’s ability to communicate the plan. Tumor Treating Fields (TTFields) is an FDA-approved locoregional, noninvasive therapy worn on the scalp to treat glioblastoma (GBM). When worn, TTFields therapy disrupts cancer cell viability and delays tumor progression but is complicated by mild-moderate skin irritation and real-world inconvenience of the unclear recommendation to wear the device an average of “≥18 hours/day or 75% of the time”. We simplified the physician instructions to encourage patient compliance and skin safety on TTFields. METHODS Adults with GBM were provided an easy-to-follow flow chart and advised across multiple centers to follow the 3-days-on (72 hours) and 1-day-off (16–24 hours) TTFields therapy use schedule and given skin-specific wound prevention guidance (cleansing selenium-based shampoo and reparative skin-barrier moisturizing) during the ‘off day’. We evaluated the ease to explain the 3-on-1-off schedule, patient adherence, and the presence and severity of skin AEs during follow-up visits. REAL-WORLD PRACTICE OUTCOMES Seventy-six patients received TTFields therapy using the 3-on-1-off protocol between 2015 and 2021 at two US healthcare centers. The median age was 57 years (range 25–81). The mean time on TTFields therapy was 73 weeks. Skin AEs occurred in 5% of patients on the 3-on-1-off protocol, as compared to 16% and 52% reported on EF-11 (NCT00379470) and EF-14 (NCT00916409) GBM studies, respectively. Majority of AEs were mild, and no patients discontinued TTFields therapy or modified electrode placement due to skin AEs while on the 3-on-1-off protocol. CONCLUSION We report real-world data confirming a practice improvement for patient compliance using a novel 3-on-1-off protocol which minimizes skin AEs and treatment interruptions to improves patient outcomes. An ounce of prevention is worth a pound of cure.

Strengthening healthcare providers’ leadership capabilities, interprofessional collaboration, and systems thinking: a conceptualization of the Clinical Scholars program impact

BackgroundHealthcare provider leadership programs represent an intervention opportunity to support advancement of the national system of care and an evaluation of their program impacts is needed. Between 2016 and 2023, the Robert Wood Johnson Foundation (RWJF) funded Clinical Scholars (CS), a three-year equity-centered leadership training program for US healthcare providers. CS recruited participants (referred to as Fellows) in cohorts and engaged them as members of interprofessional teams to transform their careers and the health of their communities. The aim of this study was to evaluate Fellows’ perspectives on the success of CS, specifically the program elements and their importance for community well-being and sustainability.MethodsWe used the mixed methods group concept mapping (GCM) approach to evaluate Fellows’ perspectives on program success. First, we conducted the qualitative phases of brainstorming, sorting, and rating with Fellows. Secondly, we conducted the quantitative phases using multi-dimensional scaling and hierarchical cluster analysis and integrated the sorting and rating information from each Fellow to develop a series of concept maps. Finally, we conducted the interpretation phase to synthesize findings. Fellows (N = 177) across five cohorts were invited to participate in the study.ResultsFifty-seven Fellows (32%) completed one or more GCM phases. A conceptual map emerged, consisting of seven thematic clusters, which showed that program value could be attributed to the following elements: “Resources”, “Wicked Problem Impact Project (WPIP) Support”, “Curriculum”, “Thinking Bigger”, “Leadership Training”, “Networking”, and “Teamwork.” The pattern match showed that all seven clusters were highly rated by Fellows across the Community Well-being Impact and Sustainability domains.ConclusionStudy findings support the value of the RWJF-CS program strategy of long-term investment in the development of healthcare leaders with applied skills in interprofessional collaboration who will be prepared to continue addressing complex, multi-faceted challenges in the system of care.

Patient Health Record Protection Beyond the Health Insurance Portability and Accountability Act: Mixed Methods Study.

The security and privacy of health care information are crucial for maintaining the societal value of health care as a public good. However, governance over electronic health care data has proven inefficient, despite robust enforcement efforts. Both federal (HIPAA [Health Insurance Portability and Accountability Act]) and state regulations, along with the ombudsman rule, have not effectively reduced the frequency or impact of data breaches in the US health care system. While legal frameworks have bolstered data security, recent years have seen a concerning increase in breach incidents. This paper investigates common breach types and proposes best practices derived from the data as potential solutions. The primary aim of this study is to analyze health care and hospital breach data, comparing it against HIPAA compliance levels across states (spatial analysis) and the impact of the Omnibus Rule over time (temporal analysis). The goal is to establish guidelines for best practices in handling sensitive information within hospitals and clinical environments. The study used data from the Department of Health and Human Services on reported breaches, assessing the severity and impact of each breach type. We then analyzed secondary data to examine whether HIPAA's storage and retention rule amendments have influenced security and privacy incidents across all 50 states. Finally, we conducted a qualitative analysis of textual data from vulnerability and breach reports to identify actionable best practices for health care settings. Our findings indicate that hacking or IT incidents have the most significant impact on the number of individuals affected, highlighting this as a primary breach category. The overall difference-in-differences trend reveals no significant reduction in breach rates (P=.50), despite state-level regulations exceeding HIPAA requirements and the introduction of the ombudsman rule. This persistence in breach trends implies that even strengthened protections and additional guidelines have not effectively curbed the rising number of affected individuals. Through qualitative analysis, we identified 15 unique values and associated best practices from industry standards. Combining quantitative and qualitative insights, we propose the "SecureSphere framework" to enhance data security in health care institutions. This framework presents key security values structured in concentric circles: core values at the center and peripheral values around them. The core values include employee management, policy, procedures, and IT management. Peripheral values encompass the remaining security attributes that support these core elements. This structured approach provides a comprehensive security strategy for protecting patient health information and is designed to help health care organizations develop sustainable practices for data security.

Advanced Disease Detection and Personalized Medicine: Integrated Data Approaches for Enhanced Parkinson's Disease and Breast Cancer Detection and Treatment in the USA

This present study focuses on integrating data-driven approaches into personalized medicine for better detection and treatment of Parkinson's disease and breast cancer through the US healthcare system. The deeper integration of genomics, clinical records, and patient self-reported data with machine learning algorithms will enhance early disease detection and optimization of treatment pathways. The results show that, more precisely, Random Forest and XGBoost machine learning models hold great promise for considerably improving diagnostic precision and predictive power. This realization opens a door for precision medicine-tailored health services according to the peculiarities of individual patients, which would improve treatment outcomes and encourage preventive healthcare. In addition, this approach aligns with the latest US efforts in precision medicine and contributes to evidence-based transformation in healthcare practice.

Risk Factors for Suboptimal Treatment in Patients with Newly Diagnosed Multiple Myeloma across US Healthcare Systems

Risk Factors for Suboptimal Treatment in Patients with Newly Diagnosed Multiple Myeloma across US Healthcare Systems

Nurse practitioner oversight ratios and labor market outcomes

AbstractNurse practitioners are important to the US healthcare system; however, many states impose physician oversight ratios, which limit the number of NPs a physician may supervise. In this study, we evaluate the effect of eliminating physician oversight ratios on the supply of NPs by conducting case studies of three states—New York, Nevada, and Pennsylvania—using synthetic control and related approaches. Surprisingly, we find that eliminating oversight ratios had little effect on the labor supply of NPs. For New York, we also analyze the effects of eliminating oversight ratios on wages and hours worked and again find null results.

Association Between Medical Debt and Vaccine Uptake in the USA, 2021-2022.

Many individuals do not receive recommended vaccines, increasing infectious disease morbidity and mortality. It is unknown whether the financial practices of US healthcare institutions contribute to vaccine hesitancy. To determine whether medical debt is associated with low vaccine uptake. Cross-sectional analysis of the association between medical debt and vaccine receipt. 56,373 adult participants in the 2021-2022 National Health Interview Survey. Presence of medical debt at the time of survey administration. We used logistic regression models to assess whether medical debt was associated with recent vaccine receipt, adjusting for sociodemographic, health, and access-to-care variables. We performed a sensitivity analysis restricted to individuals with health insurance and conducted a falsification test of the hypothesis that current medical debt would not be associated with remote prior vaccination (i.e., > 1year prior, likely before debt acquisition). Individuals with medical debt were less likely than those without such debt to receive any recent vaccine (adjusted odds ratio [aOR] 0.83, 95% confidence interval [CI] 0.76-0.91), including influenza vaccination (aOR 0.83, 95% CI 0.75-0.91) or COVID-19 vaccination (aOR 0.79, 95% CI 0.69-0.91). Analyses limited to insured individuals had similar findings (aOR for any recent vaccination 0.79, 95% CI 0.72-0.88). In the falsification test, current medical debt was not associated with remote prior vaccination (aOR 1.04, 95% CI 0.93-1.16). Current medical debt is associated with lower likelihood of recent vaccine receipt in both insured and uninsured individuals. Policies that minimize medical debt may improve vaccine coverage.

Evaluating machine learning model bias and racial disparities in non-small cell lung cancer using SEER registry data.

Despite decades of pursuing health equity, racial and ethnic disparities persist in healthcare in America. For cancer specifically, one of the leading observed disparities is worse mortality among non-Hispanic Black patients compared to non-Hispanic White patients across the cancer care continuum. These real-world disparities are reflected in the data used to inform the decisions made to alleviate such inequities. Failing to account for inherently biased data underlying these observations could intensify racial cancer disparities and lead to misguided efforts that fail to appropriately address the real causes of health inequity. Estimate the racial/ethnic bias of machine learning models in predicting two-year survival and surgery treatment recommendation for non-small cell lung cancer (NSCLC) patients. A Cox survival model, and a LOGIT model as well as three other machine learning models for predicting surgery recommendation were trained using SEER data from NSCLC patients diagnosed from 2000-2018. Models were trained with a 70/30 train/test split (both including and excluding race/ethnicity) and evaluated using performance and fairness metrics. The effects of oversampling the training data were also evaluated. The survival models show disparate impact towards non-Hispanic Black patients regardless of whether race/ethnicity is used as a predictor. The models including race/ethnicity amplified the disparities observed in the data. The exclusion of race/ethnicity as a predictor in the survival and surgery recommendation models improved fairness metrics without degrading model performance. Stratified oversampling strategies reduced disparate impact while reducing the accuracy of the model. NSCLC disparities are complex and multifaceted. Yet, even when accounting for age and stage at diagnosis, non-Hispanic Black patients with NSCLC are less often recommended to have surgery than non-Hispanic White patients. Machine learning models amplified the racial/ethnic disparities across the cancer care continuum (which are reflected in the data used to make model decisions). Excluding race/ethnicity lowered the bias of the models but did not affect disparate impact. Developing analytical strategies to improve fairness would in turn improve the utility of machine learning approaches analyzing population-based cancer data.

Implementation of a collaborative practice agreement for depression and anxiety in the primary care setting

BackgroundThere is a lack of appropriate access to mental health care in the United States, particularly in the underserved community. Data show that individuals living below the poverty level are 2.5 times more likely to develop depression and similar trends have been reported for anxiety. However, socioeconomic status and these conditions are not mutually exclusive and occur throughout the general population. To expand patient access, a collaborative practice agreement (CPA) for major depressive disorder (MDD) and generalized anxiety disorder (GAD) was developed and implemented within a network of primary care clinics. ObjectivesThis study aimed to (1) describe the development of a pharmacist-led CPA for MDD and GAD within an outpatient primary care clinic and (2) describe the growth of the depression and anxiety CPA service after implementation. MethodsThis intervention was completed at a network of 7 primary care clinics associated with a large academic medical center in Columbus, Ohio. A CPA for MDD and GAD was created and implemented in November 2021. An electronic health record–generated report was used to identify patients for which a referral to pharmacy for MDD or GAD was placed between November 1, 2021, and March 1, 2023. A retrospective chart review was used to collect information to describe the growth of the service. Data were analyzed using descriptive statistics. ResultsA total of 308 patients were appropriately referred to the pharmacist-led service for MDD and GAD between November 1, 2021, and March 1, 2023. Of the patients who established care with the pharmacist, 35% (54 of 155) experienced improvement in symptoms and 29% (45 of 155) achieved remission. ConclusionThe implementation of a pharmacist-led CPA for MDD and GAD in a primary care setting improved patient access to pharmacotherapy management for depression and anxiety.

Strong Primary Health Care in the United States - Closer Than We Might Think.

Strong Primary Health Care in the United States - Closer Than We Might Think.

Specialization of Physician Associates and Nurse Practitioners as Reflected in Workforce Projections.

Introduction The utilization of physician associates (PAs) and nurse practitioners (NPs) within the United States healthcare system has increased substantially since their inception in the 1960s. While many PAs and NPs are educated and work within specialty areas in their clinical practice, the federal government does not identify PAs and NPs by specialty in its workforce projections. Methods We obtained data from publicly available sources as well as professional organizations.Employment status, specialty, and location information for NPs and PAs were drawn from association census surveys. Results Outpatient or ambulatory care employment sites employ46.6% of NPs and 55.3% of PAs, whilealmost a quarter of each group(22.1% and 23.9%, respectively) workin general and surgical hospitals.About 9% of providers who are PAs and NPs are employed in Federally Qualified Health Centers, many of which are in health professional shortage areas (HPSAs). The number of PAs and NPs working in HPSAs hassignificantly increased from 72,000 PAs and NPs in2011 to 110,000 in 2023.There has been no growth of physicians in HPSAs during this same time. The Health Resources and Services Administration (HRSA) does not identify NPs and PAs by their specialty practice areaso the extent to which they providecare in specialty areas is unknown based on HRSA data. Conclusion It is essential to providedetailed information inclusive of PAs andNPs as well asphysicians in planning for healthcare workforce needs. The accurate projection of potential healthcare provider shortages requires knowledge of each type of provider along with their role and specialization to determine gaps in healthcare service delivery.

Learning From Ervin's Care: Ethics, Health Care Finance, and Human Connection.

A 70-year-old man with complex multimorbidity and intellectual disability was my patient for the last 5 years of his life. He taught me important lessons about the challenges of practicing medicine as a primary care physician. He embodied all the complexities of multimorbidity, the ways in which clinical decision making can be fraught with uncertainties and tradeoffs. He raised difficult ethical questions for his care team, questions about how to respect the dignity of patients who lack decisional capacity and who do not have surrogate decision makers. The gaps in his care revealed shortcomings of the US health care system, but his care in his final years also showed some of the bright spots in coordinated, team-based care. Most importantly, caring for this patient taught me about the rewards of the human connections that primary care physicians establish with their patients.

Sleep Hygiene for the Prevention of Hospital Delirium in Neurocritical Care Patients

Background Delirium is a state of altered level of consciousness often leading to confusion, inattention, and changes to levels of cognition. Delirium increases average length of stay in the hospital and costs the US health care system approximately $148 billion each year in associated medical costs. Sleep hygiene is an important factor in delirium prevention for all hospitalized patients. Objectives This quality improvement project was designed to increase implementation of an evidence-based sleep hygiene bundle in the neurocritical care population in order to decrease rates of hospital-acquired delirium. Methods This project followed the Plan, Do, Study, Act (PDSA) framework to facilitate a continuous quality improvement intervention at a mid-Atlantic academic medical center in the neurocritical care population. The continuous quality improvement included the incorporation of “sleep” as a topic into the daily rounding checklist, thus optimizing the ability to improve adherence to a multicomponent sleep hygiene bundle. The intervention includes the preintervention-postintervention occurrences of delirium and use of the daily rounding checklist. Results Nursing adherence to documentation of delirium assessments was high at approximately 99%. Following the intervention, there was a 41% decrease in the number of patients who screened positive for hospital-acquired delirium. Discussion The improvement in cases of hospital-acquired delirium may be attributed to the project intervention. Recommendations for future interventions include analysis of training on sleep plans, focus on nursing education regarding delirium assessment tools, or a measure of staff and/or patient satisfaction related to the intervention.

Multicenter validation of an RNA-based assay to predict anti-PD-1 disease control in patients with recurrent or metastatic head and neck squamous cell carcinoma: the PREDAPT study.

Despite advances in cancer care and detection, >65% of patients with squamous cell cancer of the head and neck (HNSCC) will develop recurrent and/or metastatic disease. The prognosis for these patients is poor with a 5-year overall survival of 39%. Recent treatment advances in immunotherapy, including immune checkpoint inhibitors like pembrolizumab and nivolumab, have resulted in clinical benefit in a subset of patients. There is a critical clinical need to identify patients who benefit from these antiprogrammed cell death protein 1 (anti-PD-1) immune checkpoint inhibitors. Here, we report findings from a multicenter observational study, PREDicting immunotherapy efficacy from Analysis of Pre-treatment Tumor biopsies (PREDAPT), conducted across 17 US healthcare systems. PREDAPT aimed to validate OncoPrism-HNSCC, a clinical biomarker assay predictive of disease control in patients with recurrent or metastatic HNSCC treated with anti-PD-1 immune checkpoint inhibitors as a single agent (monotherapy) and in combination with chemotherapy (chemo-immunotherapy). The test used RNA-sequencing data and machine learning models to score each patient and place them into groups of low, medium, or high. The OncoPrism-HNSCC prediction significantly correlated with disease control in both the monotherapy cohort (n=62, p=0.004) and the chemo-immunotherapy cohort (n=50, p=0.01). OncoPrism-HNSCC also significantly predicted progression-free survival in both cohorts (p=0.015 and p=0.037, respectively). OncoPrism-HNSCC had more than threefold higher specificity than programmed death-ligand 1 combined positive score and nearly fourfold higher sensitivity than tumor mutational burden for predicting disease control. Here, we demonstrate the clinical validity of the OncoPrism-HNSCC assay in identifying patients with disease control in response to anti-PD-1 immune checkpoint inhibitors. NCT04510129.