Background: The recently published Climate Vulnerability Index (CVI) gives us a comprehensive overview of the counties that are most vulnerable to the effects of climate change. Understanding the health care delivery characteristics in these vulnerable communities may help to anticipate and mitigate the negative impacts of climate change. In this setting, we sought to assess hospital characteristics in the most climate-vulnerable counties in the United States. Methods: We conducted a cross-sectional study using county-level data from the CVI [2017-2019] to stratify counties into quintiles of climate vulnerability. These data were linked with hospital characteristics from the American Hospital Association survey [2016] and population characteristics from the American Community Survey [2021]. We analyzed the hospital and demographic characteristics of the most climate vulnerable counties. Results: Hospitals in the most climate-vulnerable counties are significantly more likely to be located in rural areas (34% vs. 24%, P<0.001), smaller in bed size (mean 135 vs. 167 beds, P<0.001), more often classified as rural referral centers (7.2% vs. 4.0%, P<0.001) or sole community providers (11% vs. 6.9%, P<0.001), and more likely to be private equity-owned (6.2% vs. 3.8%, P<0.001). They employ fewer full-time personnel, including physicians (mean 110 vs. 336, P<0.001) and nurses (mean 187 vs. 267, P<0.001), and have reduced diagnostic capabilities, with lower availability of magnetic resonance imaging (75% vs. 79%, P=0.008) and advanced computed tomography scanners (52% vs. 64%, P<0.001). The populations in these counties have a higher proportion of non-Hispanic Black residents (24% vs. 10%, P<0.001), lower education levels (18% vs. 28% with bachelor's degree, P<0.001), a higher percentage of individuals with disabilities (18% vs. 14%, P<0.001), and significantly higher poverty rates (20% vs. 14%, P<0.001) compared to national averages. Conclusions: Our results indicate that hospitals in the most climate-vulnerable counties in the United States are smaller and less well-resourced, with fewer beds, intensive care units, and clinical staff. Targeted investments are needed to strengthen their infrastructure and capacity, ensuring they can effectively respond to climate-related emergencies and support health equity in the face of climate change.

OBJECTIVE:This study aimed to evaluate the location-specific and time-sensitive trajectories of pressure injuries (PrIs) stages using real-world electronic health record (EHR) datasets. APPROACH:Using a dataset of 29,475 patients with records of PrIs documented from 2015 to 2023, we developed four PrI patient sub-cohorts with common PrI locations, including coccyx, buttocks, sacrum and heel. We estimated transition intensities between three PrI states: stage 1, stage 2, and a severe stage in each group. Stages and transition paths were derived from domain knowledge provided by clinical experts and The National PrI Advisory Panel (NPIAP) guidelines. RESULTS:The trajectory analysis suggested that stage 2 serves as a "gateway state" in all four locations, meaning that once a PrI reaches stage 2, the likelihood of transiting to severe stages increases significantly. The commonly used Braden Scale and its sub-components are more likely to be associated with transitions from stage 2 to severe stages, suggesting that manual risk assessment tools are suboptimal for predicting early-stage PrI transitions. Further, we observed race-dependent variations across injury location groups. INNOVATION:To our knowledge, this is the first study to introduce multi-state trajectory analysis in PrI research. Our model can investigate PrI status in a dynamic manner, which fills an important gap in the field. CONCLUSION:Our findings underscore the lack of time-sensitive information in existing PrI risk assessment tools, revealing a critical gap in their ability to capture the dynamic nature of PrI progression. Clinical decision support using time sensitive data is needed for delivering personalized, timely, and effective PrI prevention.

Objective: Natural disasters may worsen cancer outcomes through treatment delays, screening interruptions, or fragmented health care delivery. We investigated whether climate-related natural disasters were associated with changes in county-level prostate-specific antigen (PSA) screening. Methods: We modeled county-level screening estimates from the Behavioral Risk Factor Surveillance System (BRFSS) from 2004 to 2012 using Census-derived demographic weights. The Federal Emergency Management Agency (FEMA)'s Disaster Declarations Summaries database was used to include counties that experienced a single climate-related natural disaster. The year of disaster was considered the index date, with 2-year pre- and post-disaster periods used to model counterfactual screening prevalence with vs without a natural disaster. Primary outcome was county-level PSA screening prevalence. We applied log-linear regression to estimate prevalence ratios for the association between natural disaster and two-year county-level PSA screening. Results: In 37 states, 365 counties experienced a single natural disaster, including a total population of 7,584,059 men aged 40-79. Compared to baseline county-level screening prevalence, PSA screening in the 2-year post-disaster period was 8% lower (rate ratio [RR]:0.92, 95% CI: 0.90-0.94, P <0.001]). Conclusions: We observed significantly lower county-level PSA screening prevalence following a climate-related natural disaster. These results underscore the potential impacts of climate-related natural disasters on cancer screening services.

Diagnostic errors (DEs) are a major threat to hospital patient safety. Identifying admission-based predictors associated with harmful DEs may help improve diagnostic safety in high-risk populations. To assess the association between admission-based predictors derived from structured electronic health record (EHR) data with harmful DEs in high-risk patients receiving general medical care in the hospital. Retrospective multivariable analysis of a weighted sample of cases with and without harmful DE from a previously adjudicated cohort. A weighted sample of 4750 high-risk cases (ICU transfers, 90-day deaths, or complex clinical events) of patients admitted to general medicine teams at a tertiary academic medical center between 2019 and 2021. Estimated prevalence of harmful DE using inverse probability weighting. Adjusted weighted odds ratios (wORs) for six a priori admission-based predictors using multivariable logistic regression in the weighted sample and across subgroups. Among 569 sampled cases, 83 harmful DEs were identified, corresponding to a weighted prevalence of 9.1

Background Androgen receptor pathway inhibitors (ARPIs) improve the survival of men with various states of advanced prostate cancer, but complications, including bone fractures, have been associated with treatment. Although rates of SREs are reported in ARPI registration trials, real-world data describing SRE rates during treatment with ARPIs is lacking. Methods We conducted a global pharmacovigilance study using VigiBase, the World Health Organization’s international database of adverse drug reaction reports. All reports involving abiraterone, enzalutamide, apalutamide, or darolutamide in adult men from 2011 to September 2024 were included. Fractures were defined using standardized MedDRA terms, and disproportionality analyses quantified reporting odds ratios (RORs) with 95% confidence intervals and Bayesian shrinkage estimates (EB05). Two prespecified sensitivity analyses were performed, redefining the reference group as men on androgen deprivation therapy (ADT) alone and stratifying results by age groups. Results Among 282,143 VigiBase reports involving ARPIs, 1,140 (0.4%) included fractures. In primary analysis, ARPI therapy demonstrated a pharmacovigilance signal for increased SRE reporting (ROR 1.87, 95% CI 1.77–1.98; EB05 1.77). Signals were consistent for abiraterone, enzalutamide, and apalutamide, but not for darolutamide. Using ADT as reference, ARPIs remained associated with higher reporting of fractures (ROR 1.43, 95% CI 1.29–1.58; EB05 1.08). Age-stratified analyses demonstrated signals across all categories, with numerically larger disproportionality estimates among older men. Conclusions In this global pharmacovigilance analysis, ARPIs were consistently associated with increased reporting of fractures, including when compared with ADT alone. This highlights the potentially additive skeletal toxicity of treatment intensification, and underscore the importance of bone health monitoring and preventive strategies, particularly among older patients.

Either I’ve been missing something or nothing has been going on. —Karen Elizabeth Gordon

Objectives. To evaluate trends in racial and ethnic representation in the All of Us (AoU) Research Program from 2017 to 2023 and assess regional disparities relative to US Census benchmarks. Methods. Using the AoU data repository, we compared yearly and cumulative racial/ethnic representation with 2020 US Census data. Odds ratios (ORs) were calculated to quantify underrepresentation by group, year, region, and sex at birth. Results. Non-Hispanic White individuals accounted for the largest percentage of the 619 830 participants (56.3%), followed by non-Hispanic Blacks (15.9%), Hispanics (14.9%), Asians (3.5%), and individuals in the multiracial/other category (9.4%). Asians and Hispanics were consistently underrepresented. Regional disparities were notable: Asian representation was lowest in the West (OR = 0.48; 95% confidence interval [CI] = 0.47, 0.49), and Hispanic underrepresentation was most pronounced in the South (OR = 0.54; 95% CI = 0.53, 0.55). Conclusions. Persistent underrepresentation of Asian and Hispanic participants highlights ongoing gaps as AoU recruitment continues. Continued efforts toward equitable participation will be important for achieving the scientific and ethical goals of precision medicine.

BACKGROUND Social determinants of health (SDoH) in pediatric pulmonary hypertension (PH) outcomes are inadequately characterized. OBJECTIVES The authors examined associations between SDoH and pediatric PH outcomes. METHODS This retrospective cohort study utilizes the Pediatric Health Information System (47 children's hospitals). All pediatric PH patients with encounters from January 1, 2016, to December 31, 2022, were identified using International Classification of Diseases-10 codes. Demographics, therapeutics, and outcomes were compared according to SDoH including Child Opportunity Index (COI 3.0), race/ethnicity, insurance status, urbanicity, and home-to-hospital distance. Associations between SDoH and mortality were modeled, with each SDoH analyzed separately with clinical variables. RESULTS Of 24,321 pediatric PH patients, 1,702 (7.0%) died. The median age at first admission was 1 year (IQR: 0, 5) with PH groups of pulmonary arterial hypertension (n = 11,296, 46.4%), left heart disease (n = 2,332, 9.6%), lung disease (9,165, 37.7%), thromboembolic (n =180, 0.7%), and other (n = 1,348, 5.5%). No difference in the therapy use was observed by COI. Unadjusted mortality differed by COI quintile, with the highest proportion of deaths in very low (8.5%) vs very high (6.1%, P < 0.001). Mortality was higher for patients with public insurance, Black/African American race and those living further from hospital. In multivariable models adjusting for baseline unmodifiable factors and condition severity/therapy use, patients from the very high COI quintile had significantly lower odds of mortality vs very low quintile (adjusted OR: 0.78; 95% CI: 0.67-0.90; P < 0.001). CONCLUSIONS In this study of pediatric PH outcomes by SDoH at U.S. children's hospitals, lower COI, Black/African American race, public insurance, and greater home-to-hospital distance were associated with higher mortality. (JACC Adv. 2026;5:102773) (c) 2026 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

BACKGROUND:Social determinants of health (SDoH) in pediatric pulmonary hypertension (PH) outcomes are inadequately characterized. OBJECTIVES:The authors examined associations between SDoH and pediatric PH outcomes. METHODS:This retrospective cohort study utilizes the Pediatric Health Information System (47 children's hospitals). All pediatric PH patients with encounters from January 1, 2016, to December 31, 2022, were identified using International Classification of Diseases-10 codes. Demographics, therapeutics, and outcomes were compared according to SDoH including Child Opportunity Index (COI 3.0), race/ethnicity, insurance status, urbanicity, and home-to-hospital distance. Associations between SDoH and mortality were modeled, with each SDoH analyzed separately with clinical variables. RESULTS:Of 24,321 pediatric PH patients, 1,702 (7.0%) died. The median age at first admission was 1 year (IQR: 0, 5) with PH groups of pulmonary arterial hypertension (n = 11,296, 46.4%), left heart disease (n = 2,332, 9.6%), lung disease (9,165, 37.7%), thromboembolic (n = 180, 0.7%), and other (n = 1,348, 5.5%). No difference in the therapy use was observed by COI. Unadjusted mortality differed by COI quintile, with the highest proportion of deaths in very low (8.5%) vs very high (6.1%, P < 0.001). Mortality was higher for patients with public insurance, Black/African American race and those living further from hospital. In multivariable models adjusting for baseline unmodifiable factors and condition severity/therapy use, patients from the very high COI quintile had significantly lower odds of mortality vs very low quintile (adjusted OR: 0.78; 95% CI: 0.67-0.90; P < 0.001). CONCLUSIONS:In this study of pediatric PH outcomes by SDoH at U.S. children's hospitals, lower COI, Black/African American race, public insurance, and greater home-to-hospital distance were associated with higher mortality.

Despite low-level evidence, acutely ill patients are often continuously monitored. This creates high false alarm rates and alarm fatigue with unclear clinical effectiveness. We compare metrics, including alarm burden, area under the receiver operator characteristic curve (auROC), sensitivity, and specificity for threshold, score (i.e., National Early Warning Score [NEWS]), and machine learning (ML) alarms.We retrospectively annotated continuous biometric data for acutely ill patients receiving hospital care at home for clinical utility (change in clinical management) or a safety composite using the electronic health record. Threshold alarms for heart rate (HR), respiratory rate (RR), and fall were set pragmatically by clinical teams; the score alarm was the NEWS, and the ML alarm was an unsupervised ML algorithm that detected anomalies in HR, RR, and activity. Our primary outcome was alarm burden (alarms/patient-hour). Secondary outcomes included alarm performance.We studied 526 patients of median age 71 (interquartile range [IQR]: 25), 60.3% female, 45.1% White. Compared with threshold alarms (0.132 alarms/patient-hour), alarm burden was lower with score and ML alarms (0.005 score alarms/patient-hour; 0.032 ML alarms/patient-hour; p < 0.001 for both, compared with threshold). The positive predictive value for identifying clinical utility was 0.073 for threshold, 0.247 for score, and 0.181 for ML. The auROC for identifying the safety composite was 0.557 for threshold, 0.578 for score, and 0.656 for ML.Score and ML alarms decreased alarm burden with higher overall performance in recognizing clinically important events. Our findings suggest that the use of score or ML alarms holds promise in reducing alarm fatigue while improving recognition of clinically important events, although all alarms require improvement.

OBJECTIVE:The use of post-extubation respiratory support in single-ventricle neonates undergoing the Norwood procedure is poorly described. We investigated the patterns of respiratory support following extubation as well as factors associated with prolonged exposure to post-extubation noninvasive respiratory support (NRS), defined as greater than or equal to 72 hours, in neonates recovering from the Norwood procedure. DESIGN:Two-center retrospective cohort study. SETTING:North American pediatric cardiac ICUs. PATIENTS:Neonates (< 1 mo at the time of surgery) undergoing a Norwood procedure between January 1, 2019, and December 31, 2023. MEASUREMENTS AND MAIN RESULTS:The study included 127 neonates of whom 60 (47%) experienced the primary outcome of prolonged NRS. In multivariable analysis, the presence of an airway anomaly (adjusted odds ratio [aOR] 3.6; 95% CI, 1.4-8.9; p = 0.006), an unplanned surgical or catheter-based reintervention (aOR 3.2; 95% CI, 1.3-7.5; p = 0.010), and longer postoperative mechanical ventilation (aOR 1.1; 95% CI, 1.0-1.2; p = 0.018) were independently associated with prolonged NRS. Patients with prolonged NRS had lower weight-for-age z score at cardiac ICU (CICU) discharge (-2.11 vs. -1.14; p = 0.004), longer CICU length of stay (25.1 vs. 11.1 d; p < 0.001), and longer postoperative sedative exposure (59.8 vs. 16.8 d; p < 0.001). CONCLUSIONS:Prolonged NRS is common in neonates following the Norwood procedure. Patients receiving prolonged NRS experience worse clinical outcomes.

Background Factors associated with cancer survivors' preventive health behaviors are understudied. We hypothesized that socioeconomic and health-care access factors may be associated with adherence to recommended cancer screenings.Methods We conducted a cross-sectional analysis using the 2020 Behavioral Risk Factor Surveillance System. Cancer survivors eligible for United States Preventive Services Task Force-recommended breast, cervical, prostate, and colorectal screenings were included. Multivariable logistic regression models were used to identify socioeconomic factors significantly associated with screening adherence.Results Overall, 64 958 (weighted national estimate = 29 066 143) cancer survivors were included. Adherence rates varied across cancer types: 80.9% for breast, 88.9% for cervical, 54.1% for prostate, and 84.7% for colorectal cancer. Key predictors of low adherence included lower income (breast: adjusted odds ratio [aOR] = 0.56, 95% confidence interval [CI] = 0.43 to 0.74; cervical: aOR = 0.38, 95% CI = 0.24 to 0.59; prostate: aOR = 0.36, 95% CI = 0.24 to 0.52; colorectal: aOR = 0.74, 95% CI = 0.57 to 0.96), lack of health-care coverage for colorectal cancer (aOR = 0.51, 95% CI = 0.36 to 0.73), time since last checkup between 1 and 2 years prior for breast (aOR = 0.58, 95% CI = 0.45 to 0.75), prostate (aOR = 0.66, 95% CI = 0.47 to 0.91), and colorectal (aOR = 0.69, 95% CI = 0.56 to 0.86) cancer, and no health-care provider for breast (aOR = 0.68, 95% CI = 0.47 to 0.98), prostate (aOR = 0.45, 95% CI = 0.31 to 0.65), and colorectal (aOR = 0.51, 95% CI = 0.40 to 0.66) cancer.Conclusion Cancer survivors' adherence to screening is associated with factors including lack of health-care coverage, lower income, time since the last exam, and having a personal provider. Targeted interventions accounting for such factors may help mitigate these disparities.

Objectives The purpose of this study was to examine the impact of a contact-free continuous monitoring system on clinical outcomes including unplanned intensive care unit (ICU) transfer (primary), length of stay (LOS), code blue, and mortality. A secondary aim was to evaluate the return on investment associated with implementing the contact-free continuous monitoring program during the COVID public health emergency. Methods An interrupted time series evaluation was conducted to examine the association between the use of contact-free continuous monitoring and clinical outcomes. A cost-benefit analysis was planned to evaluate the return on investment. Results Use of contact-free continuous monitoring was not significantly associated with unplanned ICU transfers, deaths, ICU LOS, and or rapid response team calls. However, there were significant increases in code blue events (P = 0.02) and mean hospital LOS (P = 0.01) in the postimplementation period when compared with the preimplementation period. Due to the lack of improvement, costs were calculated but a cost-benefit analysis was not conducted. Conclusions Contact-free continuous monitoring bed use during the COVID-19 public health emergency was not associated with improvements in clinical outcomes, although there was substantial confounding. Future studies should include large randomized controlled trials to control for factors not under direct experimental control including unit staffing, staff turnover, and differences in the patient population related to surges in the COVID-19 pandemic.

Importance:Asthma affects an estimated 7.7% of the US population and 262 million people worldwide. Symptom monitoring has demonstrated benefits but has not achieved widespread use. Objective:To assess the effect of a scalable asthma symptom monitoring intervention on asthma outcomes. Design, Setting, and Participants:This randomized clinical trial was conducted between July 2020 and March 2023 at 7 primary care clinics affiliated with an academic medical center (Brigham and Women's Hospital in Boston, Massachusetts). Candidate patients with a diagnosis of asthma over a 20-month recruitment period (July 2020 to March 2022) were identified and categorized into tiers of varying disease activity based on electronic health record data. Eligible patients were adults (aged ≥18 years) and had a primary care practitioner in 1 of the 7 participating clinics. Intervention:Intervention group patients were asked to use a mobile health app to complete weekly symptom questionnaires; track notes, peak flows, and triggers; and view educational information. Patients who reported worsening or severe symptoms were offered clinical callback requests. App data were available in the electronic health record. Usual care group patients received general asthma guidance. Main Outcomes and Measures:The primary outcome was the mean change in Mini Asthma Quality of Life Questionnaire (MiniAQLQ) score for the intended 12-month study period. A change of 0.5 on a scale of 1 to 7 was considered a minimally important change. The secondary outcome was the mean number of asthma-related health care utilization events (urgent care visits, emergency department visits, or hospitalizations). Mean differences for all outcomes between groups were compared using robust linear regression models (generalized estimating equations) with treatment group as the only covariate. Results:Baseline questionnaires were completed by 413 patients (mean [SD] age, 52.2 [15.4] years; 321 women [77.7%]). Of these, 366 patients completed final questionnaires and were included in the primary analysis. MiniAQLQ scores increased 0.34 (95% CI, 0.19-0.49) in the intervention group and 0.11 (95% CI, -0.11 to 0.33) in the usual care group from baseline to final questionnaire completion (adjusted difference-in-difference, 0.23 [95% CI, 0.06-0.40]; P = .01); although the difference was statistically significant, it did not reach the threshold for a minimally important change. Intervention subgroups showed positive differences in MiniAQLQ scores relative to the usual care group, with noteworthy increases among individuals aged 18 to 44 years (adjusted difference-in-difference, 0.40 [95% CI, 0.13-0.66]), those with low baseline patient activation (adjusted difference-in-difference, 0.77 [95% CI, 0.30-1.24]), those with a low baseline MiniAQLQ score (adjusted difference-in-difference, 0.33 [95% CI, 0.07-0.59]), and those with uncontrolled asthma at baseline (adjusted difference-in-difference, 0.30 [95% CI, 0.05-0.54]). The intervention group had a mean of 0.59 (95% CI, 0.42-0.77) nonroutine asthma-related utilization events compared with 0.76 (95% CI, 0.55-0.96) in the usual care group (adjusted effect size, -0.16 [95% CI, -0.42 to 0.17]; P = .23). Conclusions and Relevance:In this randomized clinical trial of a scalable symptom monitoring intervention, the increase in asthma-related quality of life did not reach the threshold for a minimally important change. Exploratory analyses suggest possible benefits for patients with low levels of activation. Trial Registration:ClinicalTrials.gov Identifier: NCT04401332.

BACKGROUND:Seriously ill older surgical patients with preoperative palliative care needs, such as those with pain, depression, functional dependence, and care partner needs, may benefit from palliative care, but their prevalence, characteristics, and outcomes have not been described. STUDY DESIGN:We used data from the Health and Retirement Survey linked to Medicare claims and included older adults (age 66 years or older) with and without serious illness who underwent major elective surgery between 2007 and 2019. Exposures included serious illness and pain, depression, functional dependence, and care partner needs before operation. Outcomes were 1-year healthcare usage and cost (ie total hospital days, hospital readmission, emergency department visits, and Medicare cost). RESULTS:Among 2,499 older adults undergoing major elective surgery, 63% were seriously ill, and 79% reported pain, depression, functional dependence, or care partner needs. Seriously ill older adults with preoperative palliative care needs experienced a higher rate of total hospital days (incidence rate ratio [IRR] 2.0, 95% CI 1.5 to 2.6), hospital readmission (IRR 2.0, 95% CI 1.6 to 2.4) and emergency department visits (IRR 1.9, 95% CI 1.6 to 2.3). Adjusted 1-year healthcare cost was significantly higher among seriously ill older adults with these palliative care needs compared with those without serious illness (mean [SE] cost $38,187 [2,291] vs $20,129 [1,742]). CONCLUSIONS:Seriously ill older adults undergoing major elective surgery had a high prevalence of palliative care needs, which were associated with increased healthcare usage and cost. These findings highlight the imperative to identify and intervene in older surgical patients who may benefit from palliative care.

OBJECTIVE:To assess the postoperative performance of patients who have undergone the Ewing amputation (EA) on physical function tests and patient-reported outcome measures compared to their own preoperative state, as well as to normative data from non-EA transtibial amputees (TTAs) and able-bodied community adults (ABAs).` DESIGN: Intervention cohort study with a follow-up of approximately 1 year. SETTING:Tertiary/quaternary care academic medical center. PARTICIPANTS:N=22 patients aged 18-65 years who were candidates for elective transtibial amputation after failed attempts at limb salvage. INTERVENTIONS:The EA is a novel approach to transtibial amputation incorporating the construction of agonist-antagonist myoneural interfaces. MAIN OUTCOME MEASURES:Performance-based physical function tests and patient-reported outcome measures. RESULTS:A total of 22 patients with 26 EAs were studied. Over half of the studied EA patients were biological men (13, 59%), and the mean age of the intervention population was 40.6±12.9 years. All EA patients progressed to prosthetic fitting, with a mean time of 65±25 days. Functional testing was performed at a mean interval of 112±69 days prior to and 347±141 days after amputation. EA patients demonstrated statistically significant (P<.01) improvements on all functional outcome measures and patient-reported outcome measures with the exception of functional reach (P=.1222) when compared to themselves prior to amputation. EA patients demonstrated statistically significantly better performance on the 10-meter walk test, timed Up and Go, 6-minute walk test, and functional reach test than normative data from the TTA population (P<.05), and equivalent performance to ABA patients on the 10-meter walk test and timed Up and Go (P>.5). CONCLUSIONS:Patient performance on functional outcome measures improved after undergoing the EA and associated rehabilitation interventions. Additionally, EAs performed better on several physical function outcome measures postoperatively when compared to TTAs and were equivalent to ABAs on several of the same measures.

This study aimed to examine user actions within a clinical decision support (CDS) alert addressing hypertension (HTN) in chronic kidney disease (CKD).A pragmatic randomized controlled trial of a CDS alert for primary care patients with CKD and uncontrolled blood pressure included prechecked default orders for medication initiation or titration, basic metabolic panel (BMP), and nephrology electronic consult (e-consult). We examined each type of action and calculated percentages of placed and signed orders for subgroups of firings.There were firings for medication initiation (813) and medication titration (430), and every firing also included orders for nephrology e-consult (1,243) and BMP (1,243). High rates of override (59.6%) and deferral (14.6%) were observed, and CDS-recommended orders were only signed about one-third of the time from within the alert. The percentage of orders that were signed after being placed within the alert was higher for medication initiation than for medication titration (33 vs. 12.0% for angiotensin-converting enzyme inhibitors [ACEi] and 38.8 vs. 14% for angiotensin II receptor blockers [ARBs]). Findings suggest that users are hesitant to commit to immediate action within the alert.Evaluating user interaction within alerts reveals nuances in physician preferences and workflow that should inform CDS alert design. This study is registered with the Clinicaltrials.gov Trial Registration (identifier: NCT03679247).

Importance:The US health care sector accounts for about 8.5% of national greenhouse gas (GHG) emissions. Reliable estimates of emissions associated with health care-related travel are essential for informing policy changes. Objective:To generate a comprehensive national estimate of carbon emissions due to patient health care-related travel in the US. Design, Setting, and Participants:This cross-sectional study used data from the 2022 National Household Travel Survey (NHTS), conducted from January 2022 to January 2023. Participants were selected using an address-based sample from the US Postal Service Delivery Sequence File. Participating households reported all trips taken within 24 hours by all household members aged 5 years or older. Approximate emissions per mile were obtained from typical vehicle emissions data provided by US government institutions. Data were analyzed between March 11 and May 29, 2024. Main Outcomes and Measures:Estimated annual CO2 equivalent (CO2e) emissions from patient health care-related travel per year, per patient, per trip, and per mile. A survey-weighted λ regression analysis was used to identify factors associated with higher CO2e emissions per trip. An alternative scenario analysis estimated reductions if 30% or 50% of private vehicle users switched to electric vehicles. Results:The sample included 16 997 participants with a weighted total of 3 506 325 536 US health care trips. Of these trips, 52.0% were reported by female travelers, 80.1% were made in urban areas, and 19.9% were made in rural areas. These trips accounted for 84 057 963 340 miles, resulting in weighted annual estimated emissions of 35.7 megatons (Mt) (95% CI, 27.5-43.9 Mt) CO2e. Each mile traveled generated an estimated 424 g (95% CI, 418-428 g) CO2e. Emissions per trip were higher (exponentiated coefficient [exp(β)], 2.19; 95% CI, 1.51-2.86; P < .001) for rural patients compared with urban patients. However, 69.3% of emissions were attributable to urban patients and 30.7% to rural patients. Patients with annual median household incomes of $50 000 to $99 999 generated higher trip emissions (exp[β], 1.92; 95% CI, 1.09-2.76; P = .003) compared with those with incomes of $25 000 or less. A 30% shift to electric vehicles was estimated to reduce health care-related carbon emissions to 27.6 Mt (95% CI, 20.7-34.6 Mt) CO2e, and a 50% shift was estimated to lower emissions to 22.3 Mt (95% CI, 16.0-28.6 Mt) CO2e. Conclusions and Relevance:This cross-sectional study estimated that annual patient health care-related travel in the US generated 35.7 Mt CO2e, which accounts for a small but important proportion of total health care-related emissions in the US. These findings are essential for informing health care policy decisions and suggest that strategies such as telehealth and the adoption of electric vehicles may contribute to a small but significant reduction in health care-related GHG emissions.

Colorectal surgeons have been early adopters of MIS. The objective of this study was to evaluate whether use of minimally invasive surgery (MIS) for colorectal cancers (CRC) has had an impact on use of MIS for hepatic, pancreatic, biliary, and gastric cancer (HPB/gastric) at the hospital level. We hypothesized that there is cross-specialty, hospital-level impact between colorectal and HPB/gastric surgeons in their use of MIS. Using the 2010–2019 National Cancer Database, we identified patients with histologically confirmed cancers who underwent curative-intent surgery. The hospital-level use of MIS for CRC and HPB/gastric cancers was standardized by adjusting hospital and patient covariates. Using these adjusted MIS rates as covariates, the yearly-level odds of receiving MIS for HPB/gastric cancers were estimated using logistic regression models. 87,241 and 134,019 patients (median age 65 years) with HPB/gastric cancers and CRC, respectively, were included. The proportion of hospitals performing more than 50