Published research on the human health implications of climate change between 2012 and 2021: cross sectional study

Objective

To better understand the state of research on the effects of climate change on human health, including exposures, health conditions, populations, areas of the world studied, funding sources, and publication characteristics, with a focus on topics that are relevant for populations at risk.

Design

Cross sectional study.

Data sources

The National Institute of Environmental Health Sciences climate change and human health literature portal, a curated bibliographical database of global peer reviewed research and grey literature was searched. The database combines searches of multiple search engines including PubMed, Web of Science, and Google Scholar, and includes added-value expert tagging of climate change exposures and health impacts.

Eligibility criteria

Inclusion criteria were peer reviewed, original research articles that investigated the health effects of climate change and were published in English from 2012 to 2021. After identification, a 10% random sample was selected to manually perform a detailed characterisation of research topics and publication information.

Results

10 325 original research articles were published between 2012 and 2021, and the number of articles increased by 23% annually. In a random sample of 1014 articles, several gaps were found in research topics that are particularly relevant to populations at risk, such as those in the global south (134 countries established through the United Nations Office for South-South Cooperation) (n=444; 43.8%), adults aged 65 years or older (n=195; 19.2%), and on topics related to human conflict and migration (n=25; 2.5%) and food and water quality and security (n=148; 14.6%). Additionally, fewer first authors were from the global south (n=349; 34.4%), which may partly explain why research focusing on these countries is disproportionally less.

Conclusions

Although the body of research on the health effects of climate change has grown substantially over the past decade, including those with a focus on the global south, a disproportionate focus continues to be on countries in the global north and less at risk populations. Governments are the largest source of funding for such research, and governments, particularly in the global north, need to re-orient their climate and health research funding to support researchers in the global south and to be more inclusive of issues that are relevant to the global south.

Association of Psychiatric Diagnoses and Medicaid Coverage with Length of Stay Among Inpatients Discharged to Skilled Nursing Facilities

BACKGROUND

Inpatients with psychiatric diagnoses often require higher levels of care in skilled nursing facilities (SNFs) and are more likely to be covered by Medicaid, which reimburses SNFs at significantly lower rates than Medicare and commercial payors.

OBJECTIVE

To characterize factors affecting length of stay in inpatients discharged to SNFs.

DESIGN

A retrospective cross-sectional study design using 2016-2018 data from National Inpatient Sample.

PARTICIPANTS

Inpatients aged ≥ 40 who were discharged to SNFs.

EXPOSURES

Primary discharge diagnosis (medical, psychiatric, or substance use) and primary payor.

MAIN OUTCOMES AND MEASURES

Length of stay, categorized non-exclusively as >3 days, >7 days, or > 14 days.

RESULTS

Among 9,821,155 inpatient discharges to SNFs between 2016 and 2018, 95.7% had medical primary discharge diagnoses, 3.3% psychiatric diagnoses, and 1.0% substance use diagnoses; Medicare was the most common primary payor (83.3%), followed by private insurance (7.9%), Medicaid (6.6%), and others (2.2%). Median length of stay for all patients was 5.0 days (interquartile range [IQR], 3.0-8.0), 5.0 (IQR, 3.0-8.0) for those with medical diagnoses, 8.0 (IQR, 4.0-15.0) for psychiatric diagnoses, and 5.0 (IQR, 3.0-8.0) for substance use diagnoses. After multivariable adjustment, compared to patients with medical diagnoses, patients with psychiatric diagnoses were more likely to have hospital stays > 3, > 7, and > 14 days, respectively (p < 0.001). Compared to Medicare patients, Medicaid patients were more likely to have hospital stays > 3, > 7, and > 14 days, respectively (p < 0.001). Compared to patients with medical diagnoses, those with psychiatric diagnoses were also more likely to have lengths of stay 1 times, 1.5 times, and 2 times greater than the national geometric mean length of stay for that diagnosis-related group (p < 0.001).

CONCLUSIONS

Patients discharged to SNFs after inpatient hospitalization for psychiatric diagnoses and with Medicaid coverage were more likely to have longer lengths of stay than patients with medical diagnoses and those with Medicare coverage, respectively.

Physical activity, patient-reported symptoms, and clinical events: Insights into postprocedural recovery from personal digital devices

Background

Personal digital devices may offer insights into patient recovery and an approach for remote monitoring after procedures.

Objective

To examine associations between activity measured using personal digital devices, patient-reported outcome measures (PROMs), and clinical events among patients after catheter ablation for atrial fibrillation (AF) or bariatric surgery.

Methods

We aggregated personal digital device, PROM, and electronic health record data in a study conducted at 2 health systems. We used Fitbit devices for step count assessments, KardiaMobile for cardiac rhythm assessments, and PROMs for pain and palpitations over 5 weeks.

Results

Among 59 patients, 30 underwent AF ablation and 29 bariatric surgery. Thirty-six patients (63%) reported pain. There was no difference in median [interquartile range] daily steps between patients with and those without pain (4419 [3286–7041] vs 3498 [2609–5888]; P = .23). Among AF ablation patients, 21 (70%) reported palpitations. Median daily steps were lower among those with palpitations than among those without (4668 [3021–6116] vs 8040 [6853–10,394]; P = .03). When accounting for within-subject correlation, recordings of AF were associated with a significant mean decrease in median daily steps (–351; 95% confidence interval –524 to –177; P <.01). Patients who received a new antiarrhythmic drug prescription had AF recorded in a median of 5 [5–5] of 5 total weeks, whereas patients who did not receive a new antiarrhythmic recorded AF in a median of 1 [0–3] week (P = .02).

Conclusion

Personal digital device and PROM data can provide insight into postprocedural recovery outside of usual clinical settings and may inform follow-up and clinical decision-making. (ClinicalTrials.gov Identifier: NCT03436082)

Myopericarditis with Significant Left Ventricular Dysfunction Following COVID-19 Vaccination: A Case Report

Patient: Male, 46-year-old

Final Diagnosis: Myopericarditis

Symptoms: Chest discomfort

Medication:—

Clinical Procedure: —

Specialty: Cardiology

Feasibility of Using Real-world Data to Emulate Postapproval Confirmatory Clinical Trials of Therapeutic Agents Granted US Food and Drug Administration Accelerated Approval

This cross-sectional study examines the feasibility of using real-world data, such as billing, claims, and electronic health records, to emulate US Food and Drug Administration–required confirmatory clinical trials for the 50 new therapeutic agents that received accelerated approval between 2009 and 2018.

Prostaglandin Coverage and Costs to Medicare and Medicare Beneficiaries, 2009-2017

BACKGROUND

Prostaglandin analogs are the most effective treatment for glaucoma, a common condition among older adults. Despite the availability of generic drugs, the costs associated with these prescription drugs are rising.

OBJECTIVE

To characterize Medicare prescription drug plan (PDP) formulary coverage and beneficiary out-of-pocket cost for prostaglandin analogs from 2009 to 2017 and Medicare spending on prostaglandin analogs from 2013 to 2017.

METHODS

This study was a retrospective analysis. We used 2009, 2013, and 2017 Medicare PDP formulary, beneficiary cost, and pricing files to determine beneficiary first-prescription out-of-pocket costs and plan coverage (unrestricted, restricted, or not covered) of branded latanoprost 0.005%, travoprost 0.004%, bimatoprost 0.03% and 0.01%, and tafluprost 0.0015% and of generic latanoprost 0.005% and generic bimatoprost 0.03%. We also used Medicare Part D spending data to determine aggregate spend in 2013 and 2017.

RESULTS

In 2009, 92% of plans covered branded latanoprost, 83% covered branded bimatoprost; and 49% covered branded travoprost, whereas in 2017, 6% of plans covered branded latanoprost; 95% covered branded bimatoprost; and 96% covered branded travoprost. Although generic latanoprost was universally covered, generic bimatoprost was only covered by 35% of plans in 2017. Median out-of-pocket cost of branded prostaglandins without generic equivalents was $35 (IQR = $29-$40) in 2009, $45 (IQR = $42-$101) in 2013, and $90 (IQR = $45-$159) in 2017. Median out-of-pocket cost of all available generic prostaglandins was $10 (IQR = $5-$33) in 2013 and $10 (IQR = $4-$15) in 2017. In 2013, Medicare spent $733 million on prostaglandin analogs; in 2017, this increased to $1.09 billion, with $943 million (86%) spent on branded prostaglandins and $148 million (14%) spent on generics.

CONCLUSIONS

Medicare PDP coverage of branded prostaglandins remained stable from 2009 to 2017. While median beneficiary out-of-pocket costs associated with generic prostaglandins remained stable, those associated with branded prostaglandins increased nearly 3-fold.

DISCLOSURES

Research reported in this publication was supported by National Heart, Lung and Blood Institute of the National Institutes of Health under Award Number T35HL007649. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute or the National Institutes of Health. Shah has received research support through Mayo Clinic from the U.S. Food and Drug Administration (FDA) to establish Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation (CERSI) program (U01FD005938); the Centers of Medicare and Medicaid Innovation under the Transforming Clinical Practice Initiative (TCPI); the Agency for Healthcare Research and Quality (U19HS024075, R01HS025164, R01HS025402, R03HS025517); and the National Heart, Lung and Blood Institute of the National Institutes of Health (NIH) (R56HL130496, R01HL131535), National Science Foundation, and the Patient Centered Outcomes Research Institute to develop a clinical data research network. Ross has received research support through Yale University from Johnson & Johnson to develop methods of clinical trial data sharing; Medtronic and the FDA to develop methods for postmarket surveillance of medical devices (U01FD004585); the FDA to establish Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation program (U01FD005938); the Blue Cross Blue Shield Association to better understand medical technology evaluation; the Centers of Medicare & Medicaid Services to develop and maintain performance measures that are used for public reporting (HHSM-500-2013-13018I); the Agency for Healthcare Research and Quality (R01HS022882); the National Heart, Lung and Blood Institute of the NIH (R01HS025164); and the Laura and John Arnold Foundation to establish the Good Pharma Scorecard at Bioethics International and the Collaboration on Research Integrity and Transparency at Yale. The other authors have nothing to disclose.

Feasibility of Using Real-World Data to Replicate Clinical Trial Evidence

IMPORTANCE

Although randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear.

OBJECTIVE

To identify the number of clinical trials published in high-impact journals in 2017 that could be feasibly replicated using observational data from insurance claims and/or electronic health records (EHRs).

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional analysis, PubMed was searched to identify all US-based clinical trials, regardless of randomization, published between January 1, 2017, and December 31, 2017, in the top 7 highest-impact general medical journals of 2017. Trials were excluded if they did not involve human participants, did not use end points that represented clinical outcomes among patients, were not characterized as clinical trials, and had no recruitment sites in the United States.

MAIN OUTCOMES AND MEASURES

The primary outcomes were the number and percentage of trials for which the intervention, indication, trial inclusion and exclusion criteria, and primary end points could be ascertained from insurance claims and/or EHR data.

RESULTS

Of the 220 US-based trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion and exclusion criteria, and primary end points could be routinely ascertained from insurance claims and/or EHR data. Of the 220 trials, 86 (39.1%) had an intervention that could be ascertained from insurance claims and/or EHR data. Among the 86 trials, 62 (72.1%) had an indication that could be ascertained. Forty-five (72.6%) of 62 trials had at least 80% of inclusion and exclusion criteria data that could be ascertained. Of these 45 studies, 33 (73.3%) had at least 1 primary end point that could be ascertained.

CONCLUSIONS AND RELEVANCE

This study found that only 15% of the US-based clinical trials published in high-impact journals in 2017 could be feasibly replicated through analysis of administrative claims or EHR data. This finding suggests the potential for real-world evidence to complement clinical trials, both by examining the concordance between randomized experiments and observational studies and by comparing the generalizability of the trial population with the real-world population of interest.