Publications

Facilitating Responsible Governance of Healthcare AI Tools

Many U.S. states have legislated to allow nurse practitioners (NPs) to independently prescribe drugs. Critics contend that these moves will adversely affect quality of care.

Compartmental infectious disease (ID) models are often used to evaluate non-pharmaceutical interventions (NPIs) and vaccines. Such models rarely separate within-household and community transmission, potentially introducing biases in situations where multiple transmission routes exist. We formulated an approach that incorporates household structure into ID models, extending the work of House and Keeling.

Extreme air pollution events, like those from wildfires, negatively affect health through physiological responses but may also be salient enough to induce behavioral changes in individuals protecting their own health. The net impacts of these complex tradeoffs are poorly characterized. By joining the near-universe of emergency department visits in California from 2006 to 2017 with spatially and temporally resolved estimates of ambient wildfire smoke, we find total visits respond nonlinearly to increasing wildfire smoke concentrations, but that response differs by cause of visit. Total visits increase at lower concentrations but then decline at higher concentrations, suggesting that populations shift their behaviors following salient smoke periods. Whereas respiratory-related visits steadily increase, visits for accidental injuries and non-respiratory symptoms like stomach pains decline at high smoke concentrations.

During the COVID-19 pandemic, courts have limited the federal government’s ability to impose vaccination mandates; some judges have also questioned whether states must grant religious exemptions to vaccination mandates. The Supreme Court’s June 2023 decision in Groff v DeJoy2 concerning Title VII of the Civil Rights Act of 1964 raises new questions about the ability of private employers—including health care organizations—to enforce vaccination requirements for employees who have religious objections.

Low- to moderate-intensity statins were associated with a greater reduction in LDL-C levels in older persons than younger persons and may be more appealing as initial treatment in older adults who are at increased risk for adverse events.

The authority of states and localities to require vaccination is a bedrock principle of public health law. Since 1905, when the US Supreme Court upheld compulsory smallpox inoculations, there has been sustained judicial consensus that the Constitution “does not import an absolute right to be…wholly freed from restraint.” Otherwise, “organized society could not exist with safety to its members.” Until recently, objections to mandatory vaccinations were confined to a small minority of US residents. However, civic values eroded during the COVID-19 pandemic, creating a groundswell of resistance. With state legislatures now sharply limiting public health authority and a bevy of legal challenges mounted vaccination mandates—an old and highly effective public health tool—face legal uncertainty that only a few years ago seemed inconceivable.

Under the current US kidney allocation system, older candidates receive a disproportionately small share of deceased donor kidneys despite a reserve of potentially usable kidneys that could shorten their wait times. To consider potential health gains from increasing access to kidneys for these candidates, we developed and calibrated a microsimulation model of the transplantation process and long-term outcomes for older deceased donor kidney transplant candidates.

Is government guiding the invisible hand at the top of the labor market? We use new administrative data to measure physicians' earnings and estimate the influence of healthcare policies on these earnings, physicians' labor supply, and allocation of talent. Combining the administrative registry of U.S. physicians with tax data, Medicare billing records, and survey responses, we find that physicians' annual earnings average $350,000 and comprise 8.6% of national healthcare spending. The age-earnings profile is steep; business income comprises one quarter of earnings and is systematically underreported in survey data. There are major differences in earnings across specialties, regions, and firm sizes, with an unusual geographic pattern compared with other workers. We show that health policy has a major impact on the margin: 25% of physician fee revenue driven by Medicare reimbursements accrues to physicians personally. Physicians earn 6% of public money spent on insurance expansions. We find that these policies in turn affect the type and quantity of medical care physicians supply in the short run; retirement timing in the medium run; and earnings affect specialty choice in the long run.

One-time CKD screening at age 55 years had an ICER of $86 300 per QALY gained by increasing costs from $249 800 to $259 000 and increasing QALYs from 12.61 to 12.72; this was accompanied by a decrease in the incidence of kidney failure requiring dialysis or kidney transplant of 0.29 percentage points and an increase in life expectancy from 17.29 to 17.45 years. Other options were also cost-effective. During ages 35 to 75 years, screening once prevented dialysis or transplant in 398 000 people and screening every 10 years until age 75 years cost less than $100 000 per QALY gained.

The Spring 2023 issue of Dædalus takes a transdisciplinary approach to understanding the dilemmas facing humanitarian health actors, and to finding room for innovation in humanitarian health delivery. Recognizing that shared compassion cannot be proscribed but must be felt, the issue also draws on the power of the arts, and features paintings, poetry, photography, fiction, and creative nonfiction by artists whose lives have been shaped by violent conflict and displacement.

Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.

ChatGPT has exploded into the national consciousness. The potential for large language models (LLMs) such as ChatGPT, Bard, and many others to support or replace humans in a range of areas is now clear—and medical decisions are no exception. This has sharpened a perennial medicolegal question: How can physicians incorporate promising new technologies into their practice without increasing liability risk?

In this JAMA Health Forum commentary, SHP's Michelle Mello and colleagues argue that the $1.7 trillion omnibus bill that Congress passed in December 2022 responds to several urgent public health needs, yet only narrowly addresses some of the critical determinants of pandemic preparedness.

Objective: To evaluate the cost effectiveness of California's statewide perinatal quality collaborative for reducing severe maternal morbidity (SMM) from hemorrhage.

Results: The collaborative was cost effective, exhibiting strong dominance when compared with the baseline or standard of care. In a theoretical cohort of 480,000 births, collaborative implementation added 182 QALYs (0.000379/birth) by averting 913 cases of SMM, 28 emergency hysterectomies, and one maternal mortality. Additionally, it saved $9 million ($17.78/birth) due to averted SMM costs. Although sensitivity analyses across parameter uncertainty ranges provided cases where the intervention was not cost saving, it remained cost effective throughout all analyses. Additionally, scenario-based sensitivity analysis found the intervention cost effective regardless of birth volume and implementation costs.

Abstract

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop a framework to generate simple classification rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We show that these classification rules present reasonable accuracy, sensitivity, and specificity (all ≥ 80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

The COVID-19 pandemic spurred a rapid expansion of wastewater-based infectious disease surveillance systems to monitor and anticipate disease trends in communities.The Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System in September 2020 to help coordinate and build upon those efforts. Produced at the request of CDC, this report reviews the usefulness of community-level wastewater surveillance during the pandemic and assesses its potential value for control and prevention of infectious diseases beyond COVID-19.

Objective: To develop a measure for fair inclusion in pivotal trials by assessing transparency and representation of enrolled women, older adults (aged 65 years and older), and racially and ethnically minoritized patients.

Federal courts in Texas are fast becoming known as the graveyards of U.S. health policies.1 Decisions concerning a range of statutes, from the Affordable Care Act (ACA) to the Emergency Medical Treatment and Labor Act, have chipped away at federal powers to protect the public’s health. The latest case in this series, Braidwood Management Inc. v. Becerra,2 targets the ACA’s use of U.S. Preventive Services Task Force (USPSTF) recommendations as a basis for mandating insurance coverage for preventive care. The Braidwood decision not only destabilizes efforts to ensure access to essential insurance benefits but also illustrates an emerging strategy among litigants with antiregulatory agendas: wielding heretofore sleepy doctrines of administrative and constitutional law to undercut health initiatives.