Abstract

Clinicians consider polypharmacy, comorbidities, and other factors including the potential for drug-drug interactions (DDIs) when evaluating therapeutic options for specific clinical diagnoses. Contemporary treatment for coronavirus disease 2019 (COVID-19) includes direct-acting antivirals (DAAs). We sought to characterize patients' characteristics, comorbidities, and medications received during their hospitalization for COVID-19 and quantify potential DDIs that clinicians consider in selecting appropriate DAAs.Patients hospitalized with a primary diagnosis of COVID-19 between May 2020 and December 2022 from the PINC AI Healthcare Database were identified. Medications administered during the hospitalization with the potential to cause DDIs with nirmatrelvir/ritonavir, remdesivir, or molnupiravir (per the Emergency Use Authorization factsheet or package insert) were assessed. For DDIs with nirmatrelvir/ritonavir, medications are categorized as "Contraindicated," "Avoid Concomitant Use," or "Other DDIs" (includes recommendation for dose modification or clinical and laboratory monitoring). For remdesivir, coadministration with chloroquine phosphate and hydroxychloroquine sulfate was not recommended. For molnupiravir, no drugs are listed as having potential DDIs. In a subset of patients, a multivariable logistic regression model was used to examine the association between documented patient/hospital characteristics and the likelihood of being "Contraindicated" to receive nirmatrelvir/ritonavir.Of the 788,238 patients hospitalized for COVID-19 in 920 hospitals, 53% were ≥ 65 years old, and 31% had Charlson Comorbidity Index (CCI) ≥ 3. During the study period, about half of the patients received medications categorized as "Contraindicated" (11%) and/or "Avoid Concomitant Use" (41%) with nirmatrelvir/ritonavir. The frequency of administered drugs was higher in those aged ≥ 65 years (68%), CCI ≥ 3 (78%), with high-risk underlying conditions (55%). About 1% of patients received medications that were not recommended to be coadmistered with remdesivir. Among a subset of patients hospitalized for COVID-19 in 2022, those who were older, had higher CCI, high-risk underlying conditions, severe hepatic impairment, Medicare insurance, and hospitalized in larger hospitals were significantly more likely to be categorized as "Contraindicated" when considering nirmatrelvir/ritonavir as a therapeutic option to manage COVID-19.A significant proportion of patients hospitalized for COVID-19 receive medications for other conditions that have the potential to result in DDIs with DAAs; most predominantly with nirmatrelvir/ritonavir, a strong CYP3A enzyme inhibitor, fewer with remdesivir, and none with molnupiravir. Higher age and comorbidity burden were significantly associated with a higher likelihood of receiving medications that are "Contraindicated" with nirmatrelvir/ritonavir. In the evolving COVID-19 era, these findings provide insights into patients hospitalized for COVID-19, and the polypharmacy evaluations that clinicians may encounter when selecting among DAAs to manage COVID-19.

View details for DOI 10.1016/j.clinthera.2024.08.004

View details for PubMedID 39244489

View details for DOI 10.1182/blood-2023-181459

View details for Web of Science ID 001159740307053

View details for DOI 10.7759/cureus.9537

View details for Web of Science ID 000554830700009

View details for Web of Science ID 001053772002374

Abstract

Optimizing insulin therapy for patients with type 2 diabetes can be challenging given the need for frequent dose adjustments. Most patients receive suboptimal doses and do not achieve glycemic control.To examine whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control.In this randomized clinical trial conducted at 4 primary care clinics at an academic medical center from March 1, 2021, to December 31, 2022, 32 adults with type 2 diabetes requiring initiation or adjustment of once-daily basal insulin were followed up for 8 weeks. Statistical analysis was performed from January to February 2023.Participants were randomized in a 1:1 ratio to receive basal insulin management with a voice-based conversational AI application or standard of care.Primary outcomes were time to optimal insulin dose (number of days needed to achieve glycemic control), insulin adherence, and change in composite survey scores measuring diabetes-related emotional distress and attitudes toward health technology and medication adherence. Secondary outcomes were glycemic control and glycemic improvement. Analysis was performed on an intent-to-treat basis.The study population included 32 patients (mean [SD] age, 55.1 [12.7] years; 19 women [59.4%]). Participants in the voice-based conversational AI group more quickly achieved optimal insulin dosing compared with the standard of care group (median, 15 days [IQR, 6-27 days] vs >56 days [IQR, >29.5 to >56 days]; a significant difference in time-to-event curves; P = .006) and had better insulin adherence (mean [SD], 82.9% [20.6%] vs 50.2% [43.0%]; difference, 32.7% [95% CI, 8.0%-57.4%]; P = .01). Participants in the voice-based conversational AI group were also more likely than those in the standard of care group to achieve glycemic control (13 of 16 [81.3%; 95% CI, 53.7%-95.0%] vs 4 of 16 [25.0%; 95% CI, 8.3%-52.6%]; difference, 56.3% [95% CI, 21.4%-91.1%]; P = .005) and glycemic improvement, as measured by change in mean (SD) fasting blood glucose level (-45.9 [45.9] mg/dL [95% CI, -70.4 to -21.5 mg/dL] vs 23.0 [54.7] mg/dL [95% CI, -8.6 to 54.6 mg/dL]; difference, -68.9 mg/dL [95% CI, -107.1 to -30.7 mg/dL]; P = .001). There was a significant difference between the voice-based conversational AI group and the standard of care group in change in composite survey scores measuring diabetes-related emotional distress (-1.9 points vs 1.7 points; difference, -3.6 points [95% CI, -6.8 to -0.4 points]; P = .03).In this randomized clinical trial of a voice-based conversational AI application that provided autonomous basal insulin management for adults with type 2 diabetes, participants in the AI group had significantly improved time to optimal insulin dose, insulin adherence, glycemic control, and diabetes-related emotional distress compared with those in the standard of care group. These findings suggest that voice-based digital health solutions can be useful for medication titration.ClinicalTrials.gov Identifier: NCT05081011.

View details for DOI 10.1001/jamanetworkopen.2023.40232

View details for PubMedID 38039007

Abstract

Increasing use of EHRs has generated interest in the potential of computerized clinical decision support to improve treatment of sepsis. Electronic sepsis alerts have had mixed results due to poor test characteristics, the inability to detect sepsis in a timely fashion and the use of outside software limiting widespread adoption. We describe the development, evaluation and validation of an accurate and timely severe sepsis alert with the potential to impact sepsis management.To develop, evaluate, and validate an accurate and timely severe sepsis alert embedded in a commercial EHR.The sepsis alert was developed by identifying the most common severe sepsis criteria among a cohort of patients with ICD 9 codes indicating a diagnosis of sepsis. This alert requires criteria in three categories: indicators of a systemic inflammatory response, evidence of suspected infection from physician orders, and markers of organ dysfunction. Chart review was used to evaluate test performance and the ability to detect clinical time zero, the point in time when a patient develops severe sepsis.Two physicians reviewed 100 positive cases and 75 negative cases. Based on this review, sensitivity was 74.5%, specificity was 86.0%, the positive predictive value was 50.3%, and the negative predictive value was 94.7%. The most common source of end-organ dysfunction was MAP less than 70 mm/Hg (59%). The alert was triggered at clinical time zero in 41% of cases and within three hours in 53.6% of cases. 96% of alerts triggered before a manual nurse screen.We are the first to report the time between a sepsis alert and physician chart-review clinical time zero. Incorporating physician orders in the alert criteria improves specificity while maintaining sensitivity, which is important to reduce alert fatigue. By leveraging standard EHR functionality, this alert could be implemented by other healthcare systems.

View details for DOI 10.4338/ACI-2015-11-RA-0159

View details for PubMedID 27437061

View details for PubMedCentralID PMC4941860

Abstract

Patients hospitalized for COVID-19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non-COVID-19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID-19 ARDS.This was a retrospective study of consecutive adults admitted for COVID-19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS-III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward-first vs. ICU-direct), and 28- and 60-day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome.A total of 157 patients were included, 48% of whom were first admitted to the ward (n = 75). Ward-first patients had more comorbidities, including lung disease. Ward-first patients had lower 4C and similar SAPS-III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU-direct patients. More ward-first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward-first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis.Despite similar baseline risk scores, ward-first patients with COVID-19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU-direct patients. Ward-first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

View details for DOI 10.1002/emp2.13192

View details for PubMedID 38887225

View details for PubMedCentralID PMC11180691

View details for DOI 10.4236/ce.2022.134082

Abstract

Since the nationally televised cardiac arrest of American National Football League player Damar Hamlin in January 2023, commotio cordis has come to the forefront of public attention. Commotio cordis is defined as sudden cardiac arrest due to direct trauma to the precordium resulting in ventricular fibrillation or ventricular tachycardia. While the precise incidence of commotio cordis is not known due to a lack of standardized, mandated reporting, it is the third most common cause of sudden cardiac death in young athletes, with more than 75% of cases occurring during organized and recreational sporting events. Given that survival is closely tied to how quickly victims receive cardiopulmonary resuscitation and defibrillation, it is crucial to raise awareness of commotio cordis so that athletic trainers, coaches, team physicians, and emergency medical personnel can rapidly diagnose and treat this often-fatal condition. Broader distribution of automated external defibrillators in sporting facilities as well as increased presence of medical personnel during sporting events would also likely lead to higher survival rates.

View details for DOI 10.1007/s40279-023-01873-6

View details for Web of Science ID 001020188900002

View details for PubMedID 37382827

View details for PubMedCentralID PMC10356869

Abstract

The goal of this report was to find the frequency of synchronous airway lesions (SAL) identified during microdirect laryngoscopy and bronchoscopy (MDLB) that influenced treatment decisions beyond the information provided by drug induced sleep endoscopy (DISE) alone in children with obstructive sleep apnea (OSA) at a tertiary care pediatric hospital.This was a retrospective chart review of all pediatric patients who underwent drug induced sleep endoscopy in conjunction with direct laryngoscopy and bronchoscopy as part of a comprehensive airway evaluation for obstructive sleep apnea at a tertiary care pediatric hospital.Three hundred thirty-five patients with obstructive sleep apnea were evaluated with both sleep endoscopy and direct laryngoscopy with bronchoscopy. Five percent of patients had SAL identified on MDLB contributing to airway obstruction. Three patients (0.9%) who underwent MDLB for OSA required surgical correction of SAL that was identified.In a limited subset of patients, direct laryngoscopy with bronchoscopy provides additional positive findings to aid with treatment planning for obstructive sleep apnea.

View details for PubMedID 29859583

Abstract

Impostor syndrome is an internalized sense of incompetence and not belonging. We examined associations between impostor syndrome and holding leadership positions in medicine.A cross-sectional survey was distributed to US physicians from 6/2021-12/2021 through medical schools and professional organizations. Differences were tested with the chi-square test and t-test for categorical and continuous variables, respectively. Logistic regression was used to identify factors associated with holding leadership positions and experiencing impostor syndrome.2183 attending and retired physicians were included in the analytic cohort; 1471 (67.4%) were in leadership roles and 712 (32.6%) were not. After adjustment, male physicians were more likely than women to hold leadership positions (OR=1.4, 95% CI 1.16-1.69; p<0.001). Non-US citizens (permanent resident or visa holder) were less likely to hold leadership positions than US citizens (OR=0.3, 95% CI 0.16-0.55; p<0.001). Having a leadership position was associated with lower odds of impostor syndrome (OR=0.54, 95% CI 0.43-0.68; p<0.001). Female surgeons were more likely to report impostor syndrome compared to male surgeons (90.0% vs 67.7%; p<0.001), an association that persisted even when female surgeons held leadership roles. Similar trends were appreciated for female and male non-surgeons. Impostor syndrome rates did not differ by race/ethnicity, including among those underrepresented in medicine, even after adjustment for gender and leadership role.Female physicians were more likely to experience impostor syndrome than men, regardless of specialty or leadership role. While several identity-based gaps persist in leadership, impostor syndrome among racially minoritized groups may not be a significant contributor.

View details for DOI 10.1097/XCS.0000000000000788

View details for PubMedID 37350479

Abstract

SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis.RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms.RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.NCT05172024.

View details for DOI 10.1371/journal.pone.0286297

View details for PubMedID 37352211

View details for PubMedCentralID PMC10289397

Abstract

Aldosterone sensitivity is defined as an outcome variable for a given circulating level of aldosterone. In basic and translational studies, this has been measured in differential tissue responses, e.g. lower urine sodium and higher urine potassium, as an index of renal response; and in clinical studies has been measured in differential blood pressure. This concept of aldosterone sensitivity disrupts the conventional wisdom of the renin-angiotensin-aldosterone system and has the potential to uncover novel mechanisms of hypertension. We review basic and translational science studies that uncovered differential renal responses to aldosterone and connect this earlier work to more recent observational and randomized trials that have demonstrated differential blood pressure for a given level of aldosterone in healthy and hypertensive subjects. Black race and age are associated with higher aldosterone sensitivity and blood pressure. We also discuss gaps in the field and how future basic and clinical studies can inform mechanisms of differential sensitivity.

View details for DOI 10.1152/ajprenal.00415.2020

View details for PubMedID 33491565

Abstract

Mechanical circulatory support (MCS) has made rapid progress over the last 3 decades. This was driven by the need to develop acute and chronic circulatory support as well as by the limited organ availability for heart transplantation. The growth of MCS was also driven by the use of extracorporeal membrane oxygenation (ECMO) after the worldwide H1N1 influenza outbreak of 2009. The majority of mechanical pumps (ECMO and left ventricular assist devices) are currently based on continuous flow pump design. It is interesting to note that in the current era, we have reverted from the mammalian pulsatile heart back to the continuous flow pumps seen in our simple multicellular ancestors. This review will highlight key physiological concepts of the assisted circulation from its effects on cardiac dynamic to principles of cardiopulmonary fitness. We will also examine the physiological principles of the ECMO-assisted circulation, anticoagulation, and the haemocompatibility challenges that arise when the blood is exposed to a foreign mechanical circuit. Finally, we conclude with a perspective on smart design for future development of devices used for MCS.

View details for DOI 10.1016/j.cjca.2019.11.002

View details for PubMedID 32036862

Abstract

BACKGROUND: Time spent awaiting discharge after the acute need for hospitalization has resolved is an important potential contributor to hospital length of stay (LOS).OBJECTIVE: To measure the prevalence, impact, and context of patients who remain hospitalized for prolonged periods after completion of acute care needs.DESIGN, SETTING, AND PARTICIPANTS: We conducted a cross-sectional "point-in-time" survey at each of 15 academic US hospitals using a structured data collection tool with on-service acute care medicine attending physicians in fall 2022.MAIN OUTCOMES AND MEASURES: Primary outcomes were number and percentage of patients considered "medically ready for discharge" with emphasis on those who had experienced a "major barrier to discharge" (medically ready for discharge for ≥1 week). Estimated LOS attributable to major discharge barriers, contributory discharge needs, and associated hospital characteristics were measured.RESULTS: Of 1928 patients sampled, 35.0% (n=674) were medically ready for discharge including 9.8% (n=189) with major discharge barriers. Many patients with major discharge barriers (44.4%; 84/189) had spent a month or longer medically ready for discharge and commonly (84.1%; 159/189) required some form of skilled therapy or daily living support services for discharge. Higher proportions of patients experiencing major discharge barriers were found in public versus private, nonprofit hospitals (12.0% vs. 7.2%; p=.001) and county versus noncounty hospitals (14.5% vs. 8.8%; p=.002).CONCLUSIONS: Patients experience major discharge barriers in many US hospitals and spend prolonged time awaiting discharge, often for support needs that may be outside of clinician control.

View details for DOI 10.1002/jhm.13184

View details for PubMedID 37553979

Abstract

To estimate the prevalence of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) after infection with SARS-CoV-2 during pregnancy and to characterize associated risk factors.In a multicenter cohort study (NIH RECOVER [Researching COVID to Enhance Recovery]-Pregnancy Cohort), individuals who were pregnant during their first SARS-CoV-2 infection were enrolled across the United States from December 2021 to September 2023, either within 30 days of their infection or at differential time points thereafter. The primary outcome was PASC, defined as score of 12 or higher based on symptoms and severity as previously published by the NIH RECOVER-Adult Cohort, at the first study visit at least 6 months after the participant's first SARS-CoV-2 infection. Risk factors for PASC were evaluated, including sociodemographic characteristics, clinical characteristics before SARS-CoV-2 infection (baseline comorbidities, trimester of infection, vaccination status), and acute infection severity (classified by need for oxygen therapy). Multivariable logistic regression models were fitted to estimate associations between these characteristics and presence of PASC.Of the 1,502 participants, 61.1% had their first SARS-CoV-2 infection on or after December 1, 2021 (ie, during Omicron variant dominance); 51.4% were fully vaccinated before infection; and 182 (12.1%) were enrolled within 30 days of their acute infection. The prevalence of PASC was 9.3% (95% CI, 7.9-10.9%) measured at a median of 10.3 months (interquartile range 6.1-21.5) after first infection. The most common symptoms among individuals with PASC were postexertional malaise (77.7%), fatigue (76.3%), and gastrointestinal symptoms (61.2%). In a multivariable model, the proportion PASC positive with vs without history of obesity (14.9% vs 7.5%, adjusted odds ratio [aOR] 1.65, 95% CI, 1.12-2.43), depression or anxiety disorder (14.4% vs 6.1%, aOR 2.64, 95% CI, 1.79-3.88) before first infection, economic hardship (self-reported difficulty covering expenses) (12.5% vs 6.9%, aOR 1.57, 95% CI, 1.05-2.34), and treatment with oxygen during acute SARS-CoV-2 infection (18.1% vs 8.7%, aOR 1.86, 95% CI, 1.00-3.44) were associated with increased prevalence of PASC.The prevalence of PASC at a median time of 10.3 months after SARS-CoV-2 infection during pregnancy was 9.3% in the NIH RECOVER-Pregnancy Cohort. The predominant symptoms were postexertional malaise, fatigue, and gastrointestinal symptoms. Several socioeconomic and clinical characteristics were associated with PASC after infection during pregnancy.ClinicalTrials.gov, NCT05172024.

View details for DOI 10.1097/AOG.0000000000005670

View details for PubMedID 38991216

Abstract

The in vivo and in vitro effects of M-CSF on bronchoalveolar macrophages (BAM) activity against the intracellular fungal pathogen Histoplasma capsulatum (Hc) were studied. Three days after a single subcutaneous (s.c.) dose of M-CSF (2.5 mg/kg), enhanced ex vivo antifungal activity of BAM was measured. BAM from M-CSF-treated CD-1 mice significantly (P < 0.01) inhibited the intracellular multiplication of Hc yeast cells in 20 h assays compared to BAM from control mice. This effect was not observed at days 1, 7, 11 or 21 post-treatment. A dose of 5 mg/kg s.c., but not 1 mg/kg, induced similar antifungal activity in BAM by day 3. Peritoneal macrophages (PM) from M-CSF-treated mice did not have enhanced antifungal activity at days and doses tested. BAM could also be activated for antihistoplasmal activity by M-CSF in vitro. M-CSF at 10,000 U/ml for 24 h or 5000 U/ml for 48 h induced significant (P < 0.01) inhibition of intracellular multiplication of Hc. Interferon-gamma (IFN) plus lipopolysaccharide (LPS) activated BAM and PM in vitro to inhibit intracellular multiplication of Hc (P < 0.001); the antihistoplasmal activity was completely inhibited by NG-monomethyl L-arginine (N-MMA), indicating that an L-arginine-dependent nitric oxide-producing mechanism was operative. N-MMA could not inhibit the antihistoplasmal activity of BAM or PM activated by M-CSF in vitro. The mechanism by which M-CSF-activated macrophages inhibit intracellular multiplication of Hc remains to be determined.

View details for Web of Science ID A1995QN91500006

View details for PubMedID 7782153

Abstract

The increasing linguistic and cultural diversity in the United States underscores the necessity of enhancing healthcare professionals' cross-cultural communication skills. This study focuses on incorporating interpreter and limited-English proficiency (LEP) patient training into the medical and physician assistant student curriculum. This aims to improve equitable care provision, addressing the vulnerability of LEP patients to healthcare disparities, including errors and reduced access. Though training is recognized as crucial, opportunities in medical curricula remain limited.To bridge this gap, a novel initiative was introduced in a medical school, involving second-year students in clinical sessions with actual LEP patients and interpreters. These sessions featured interpreter input, patient interactions, and feedback from interpreters and clinical preceptors. A survey assessed the perspectives of students, preceptors, and interpreters.Outcomes revealed positive reception of interpreter and LEP patient integration. Students gained confidence in working with interpreters and valued interpreter feedback. Preceptors recognized the sessions' value in preparing students for future clinical interactions.This study underscores the importance of involving experienced interpreters in training students for real-world interactions with LEP patients. Early interpreter training enhances students' communication skills and ability to serve linguistically diverse populations. Further exploration could expand languages and interpretation modes and assess long-term effects on students' clinical performance. By effectively training future healthcare professionals to navigate language barriers and cultural diversity, this research contributes to equitable patient care in diverse communities.

View details for DOI 10.1186/s12909-024-05173-z

View details for PubMedID 38395858

View details for PubMedCentralID 9932446

Abstract

Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioration, but there is limited evidence for their effectiveness.To evaluate the effectiveness of an artificial intelligence deterioration model-enabled intervention to reduce the risk of escalations in care among hospitalized patients using a study design that facilitates stronger causal inference.This cohort study used a regression discontinuity design that controlled for confounding and was based on Epic Deterioration Index (EDI; Epic Systems Corporation) prediction model scores. Compared with other observational research, the regression discontinuity design facilitates causal analysis. Hospitalized adults were included from 4 general internal medicine units in 1 academic hospital from January 17, 2021, through November 16, 2022.An artificial intelligence deterioration model-enabled intervention, consisting of alerts based on an EDI score threshold with an associated collaborative workflow among nurses and physicians.The primary outcome was escalations in care, including rapid response team activation, transfer to the intensive care unit, or cardiopulmonary arrest during hospitalization.During the study, 9938 patients were admitted to 1 of the 4 units, with 963 patients (median [IQR] age, 76.1 [64.2-86.2] years; 498 males [52.3%]) included within the primary regression discontinuity analysis. The median (IQR) Elixhauser Comorbidity Index score in the primary analysis cohort was 10 (0-24). The intervention was associated with a -10.4-percentage point (95% CI, -20.1 to -0.8 percentage points; P = .03) absolute risk reduction in the primary outcome for patients at the EDI score threshold. There was no evidence of a discontinuity in measured confounders at the EDI score threshold.Using a regression discontinuity design, this cohort study found that the implementation of an artificial intelligence deterioration model-enabled intervention was associated with a significantly decreased risk of escalations in care among inpatients. These results provide evidence for the effectiveness of this intervention and support its further expansion and testing in other care settings.

View details for DOI 10.1001/jamainternmed.2024.0084

View details for PubMedID 38526472

View details for DOI 10.1186/s13054-023-04666-5

View details for PubMedID 37773187

View details for PubMedCentralID 8935253

Abstract

Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), none have yet been shown to be efficacious.We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults hospitalized with Covid-19 with evidence of lower respiratory tract involvement. Patients were randomly assigned to receive either remdesivir (200 mg loading dose on day 1, followed by 100 mg daily for up to 9 additional days) or placebo for up to 10 days. The primary outcome was the time to recovery, defined by either discharge from the hospital or hospitalization for infection-control purposes only.A total of 1063 patients underwent randomization. The data and safety monitoring board recommended early unblinding of the results on the basis of findings from an analysis that showed shortened time to recovery in the remdesivir group. Preliminary results from the 1059 patients (538 assigned to remdesivir and 521 to placebo) with data available after randomization indicated that those who received remdesivir had a median recovery time of 11 days (95% confidence interval [CI], 9 to 12), as compared with 15 days (95% CI, 13 to 19) in those who received placebo (rate ratio for recovery, 1.32; 95% CI, 1.12 to 1.55; P<0.001). The Kaplan-Meier estimates of mortality by 14 days were 7.1% with remdesivir and 11.9% with placebo (hazard ratio for death, 0.70; 95% CI, 0.47 to 1.04). Serious adverse events were reported for 114 of the 541 patients in the remdesivir group who underwent randomization (21.1%) and 141 of the 522 patients in the placebo group who underwent randomization (27.0%).Remdesivir was superior to placebo in shortening the time to recovery in adults hospitalized with Covid-19 and evidence of lower respiratory tract infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; ACCT-1 ClinicalTrials.gov number, NCT04280705.).

View details for DOI 10.1056/NEJMoa2007764

View details for PubMedID 32445440

View details for PubMedCentralID PMC7262788

Abstract

Diabetes impacts tens of millions of people in the United States of America and 9 % of the worldwide population. Given the public health implications and economic burden of diabetes, the needs of people with diabetes must be addressed through strategic and effective advocacy efforts. Diabetes advocacy aims to increase public awareness about diabetes, raise funds for research and care, influence policy impacting people with diabetes, and promote optimal individual outcomes. We present a framework for diabetes advocacy activities by individuals and at the community, national, and international levels and identify challenges and gaps in current diabetes advocacy. Various groups have organized successful diabetes advocacy campaigns toward these goals, and lessons for further advancing diabetes advocacy can be learned from other health-related populations. Finally, we discuss the role of healthcare providers and mental/behavioral health professionals in advocacy efforts that can benefit their patients and the broader population of people with diabetes.

View details for DOI 10.1007/s11892-015-0636-z

View details for Web of Science ID 000377953300003

View details for PubMedID 26194156

View details for PubMedCentralID PMC4581582

Abstract

This report describes a root cause analysis of incorrect provider assignments and a standardized workflow developed to improve the clarity and accuracy of provider assignments.A multidisciplinary working group involving housestaff was assembled. Key drivers were identified using value stream mapping and fishbone analysis. A report was developed to allow for the analysis of correct provider assignments. A standardized workflow was created and piloted with a single service line. Pre- and post-pilot surveys were administered to nursing staff and participating housestaff on the unit.Four key drivers were identified. A standardized workflow was created with an exclusive treatment team role in Epic held by a single provider at any given time, with a corresponding patient list column displaying provider information for each patient. Pre- and post-survey responses report decreased confusion, decreased provider identification errors, and increased user satisfaction among RNs and residents with sustained uptake over time.This work demonstrates structured root cause analysis, notably engaging housestaff, to develop a standardized workflow for an understudied and growing problem. The development of tools and strategies to address the widespread burdens resulting from clinical communication failures is needed.

View details for DOI 10.1093/jamiaopen/ooae057

View details for PubMedID 38974405

View details for PubMedCentralID PMC11226879

Abstract

Hypnotizability is a stable trait that moderates the benefit of hypnosis for treating pain, but limited availability of hypnotizability testing deters widespread use of hypnosis. Inexpensive genotyping of 4 single nucleotide polymorphisms in the catechol-o-methyltransferase (COMT) gene was performed using giant magnetoresistive biosensors to determine if hypnotizable individuals can be identified for targeted hypnosis referrals. For individuals with the proposed 'optimal' COMT diplotypes, 89.5% score highly on the Hypnotic Induction Profile (OR = 6.12, 95%CI = 1.26-28.75), which identified 40.5% of the treatable population. Mean hypnotizability scores of the optimal group were significantly higher than the total population (p = 0.015 effect size = 0.60), an effect that was present in females (p = 0.0015, effect size = 0.83), but not in males (p = 0.28). In an exploratory cohort, optimal individuals also reported significantly higher postoperative pain scores (p = 0.00030, effect size = 1.93), indicating a greater need for treatment.

View details for DOI 10.1016/j.jmoldx.2023.01.002

View details for PubMedID 36702396

View details for DOI 10.1007/s11606-024-08784-w

View details for PubMedID 38689120

View details for PubMedCentralID 10589311

Abstract

Immune checkpoint inhibitor (ICI) therapy has improved survivals with a favorable toxicity profile in a variety of cancer patients. We hypothesized that hospitalized cancer patients who have acute or chronic comorbidities may have suppressed immune systems and poor clinical outcomes to ICIs. The objective of this study was to explore clinical outcomes and predictive factors of hospitalized cancer patients who received ICI therapy at an NCI-designated Comprehensive Cancer Center.A retrospective review of electronic medical records was conducted for adult cancer patients who received an FDA-approved ICI during admission from 08/2016 to 01/2022. For each patient we extracted demographics, cancer histology, comorbidities, reasons for hospitalization, ICI administered, time from treatment to discharge, time from treatment to progression or death, and complete blood counts. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. The 95% confidence interval for survival was calculated using the exact binomial distribution. Statistical significance was defined as 2-sided p<0.05.Of 37 patients identified, 2 were excluded due to lack of complete blood counts on admission. Average hospital stay was 24.2 (95% CI 16.5, 31.9) days. Ten (27.0%) patients died during the same hospitalization as treatment. Of those who followed up, 22 (59.5%) died within 90 days of inpatient therapy. The median PFS was 0.86 (95% CI 0.43, 1.74) months and median OS was 1.55 (95% CI 0.76, 3.72) months. Patients with ≥3 comorbidities had poorer PFS (2.4 vs. 0.4 months; p=0.0029) and OS (5.5 vs. 0.6 months; p=0.0006). Pre-treatment absolute lymphocyte counts (ALC) <600 cells/µL were associated with poor PFS (0.33 vs. 1.35 months; p=0.0053) and poor OS (0.33 vs. 2.34 months; p=0.0236). Pre-treatment derived neutrophil to lymphocyte ratio (dNLR) <4 was associated with good median PFS (1.6 vs. 0.4 months; p=0.0157) and OS (2.8 vs. 0.9 months; p=0.0375).Administration of ICI therapy was associated with poor clinical outcomes and high rates of both inpatient mortality and 90-day mortality after inpatient ICI therapy. The presence of ≥3 comorbidities, ALC <600/μL, or dNLR >4 in hospitalized patients was associated with poor survival outcomes.

View details for DOI 10.3389/fonc.2022.980181

View details for PubMedID 36185315

View details for PubMedCentralID PMC9515784

Abstract

Right ventricular (RV) dysfunction is common among patients hospitalized with COVID-19; however, its epidemiology may depend on the echocardiographic parameters used to define it.To evaluate the prevalence of abnormalities in three common echocardiographic parameters of RV function among COVID-19 patients admitted to the intensive care unit, as well as the effect of RV dilatation on differential parameter abnormality and the association of RV dysfunction with 60-day mortality.Retrospective cohort study of COVID-19 ICU patients between March 4th,2020 to March 4th, 2021, who received a transthoracic echocardiogram within 48 hours before to at most 7 days after ICU admission. RV dysfunction and dilatation respectively defined by guideline thresholds for tricuspid annular plane systolic excursion (TAPSE), RV fractional area change (RVFAC), RV free wall longitudinal strain (RVFWS), and RV basal dimension or RV end-diastolic area. Association of RV dysfunction with 60-day mortality assessed through logistic regression adjusting for age, prior history of congestive heart failure, invasive ventilation at time of TTE and APACHE II score.116 patients were included, of which 69% had RV dysfunction by > 1 parameter and 36.3% of these had RV dilatation. The three most common patterns of RV dysfunction included: Presence of 3 abnormalities, the combination of abnormal RVFWS and TAPSE, and isolated TAPSE abnormality. Patients with RV dilatation had worse RVFAC (24% vs 36%, p = 0.001), worse RVFWS (16.3% vs 19.1%, p = 0.005), higher RVSP (45mmHg vs 31mmHg, p = 0.001) but similar TAPSE (13mm vs 13mm, p = 0.30) compared to those with normal RV size. After multivariable adjustment, 60-day mortality was significantly associated with RV dysfunction (OR 2.91, 95% CI 1.01 - 9.44), as was the presence of at least 2 parameter abnormalities.ICU patients with COVID-19 had significant heterogeneity in RV function abnormalities present with different patterns associated with RV dilatation. RV dysfunction by any parameter was associated with increased mortality. Therefore, a multiparameter evaluation may be critical in recognizing RV dysfunction in COVID-19.

View details for DOI 10.1513/AnnalsATS.202303-235OC

View details for PubMedID 37478340

View details for DOI 10.1001/jamanetworkopen.2024.33009

View details for PubMedID 39264634

Abstract

Policy Points Health care systems around the world rely on a range of methods to ensure the affordability of prescription drugs, including negotiating prices soon after drug approval and relying on formal clinical assessments that compare newly approved therapies with existing alternatives. The negotiation framework established under the Inflation Reduction Act is far more limited than other frameworks explored in this study. Adding elements from these frameworks could lead to more effective price negotiation in the United States.CONTEXT: In 2022, Congress passed the Inflation Reduction Act, which allowed Medicare, for the first time, to begin negotiating the prices for certain high-cost brand-name prescription drugs. Many other industrialized countries negotiate drug prices, and we sought to compare and contrast key features of the negotiation process across several health systems. We focused, in particular, on the criteria for selecting drugs for price negotiation, procedures for negotiation, factors that influence negotiated prices, and how prices are implemented.METHODS: We included four G7 countries in our analysis (Canada, France, Germany, and the United Kingdom [England]), two Benelux countries (Belgium and the Netherlands), and one Scandinavian country (Norway) with long-established frameworks for drug price negotiation. We also analyzed the Veterans Affairs Health System in the United States. For each system, we gathered relevant legislation, government publications, and guidelines to understand negotiation frameworks, and we reached out to key drug price negotiators in each system to conduct semistructured interviews. All interviews were recorded, transcribed, and coded, and data were analyzed based on an internal assessment tool that we developed.FINDINGS: All eight systems negotiate the prices of brand-name prescription drugs soon after approval and rely on formal clinical assessments that compare newly approved drugs with existing therapies. Systems in our study differed on characteristics such as whether the body performing clinical assessments is separate from the negotiating authority, how added health benefit is assessed, whether explicit willingness-to-pay thresholds are employed, and how specific approaches for priority disease areas are taken.CONCLUSIONS: High-income countries around the world adopt different approaches to conducting price negotiations on brand-name drugs but coalesce around a set of practices that will largely be absent from the current Medicare negotiation framework. US policymakers might consider adding some of these characteristics in the future to improve negotiation outcomes.

View details for DOI 10.1111/1468-0009.12714

View details for PubMedID 39289915

View details for DOI 10.1111/joim.13501

View details for PubMedID 35417053

View details for Web of Science ID 001275557403539

Abstract

Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown.To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources.Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024.Multi-institutional study from Stanford University, Beth Israel Deaconess Medical Center, and the University of Virginia involving physicians from across the United States.92 practicing attending physicians and residents with training in internal medicine, family medicine, or emergency medicine.Five expert-developed clinical case vignettes were presented with multiple open-ended management questions and scoring rubrics created through a Delphi process. Physicians were randomized to use either GPT-4 via ChatGPT Plus in addition to conventional resources (e.g., UpToDate, Google), or conventional resources alone.The primary outcome was difference in total score between groups on expert-developed scoring rubrics. Secondary outcomes included domain-specific scores and time spent per case.Physicians using the LLM scored higher compared to those using conventional resources (mean difference 6.5 %, 95% CI 2.7-10.2, p<0.001). Significant improvements were seen in management decisions (6.1%, 95% CI 2.5-9.7, p=0.001), diagnostic decisions (12.1%, 95% CI 3.1-21.0, p=0.009), and case-specific (6.2%, 95% CI 2.4-9.9, p=0.002) domains. GPT-4 users spent more time per case (mean difference 119.3 seconds, 95% CI 17.4-221.2, p=0.02). There was no significant difference between GPT-4-augmented physicians and GPT-4 alone (-0.9%, 95% CI -9.0 to 7.2, p=0.8).LLM assistance improved physician management reasoning compared to conventional resources, with particular gains in contextual and patient-specific decision-making. These findings indicate that LLMs can augment management decision-making in complex cases.ClinicalTrials.gov Identifier: NCT06208423 ; https://classic.clinicaltrials.gov/ct2/show/NCT06208423.Question: Does large language model (LLM) assistance improve physician performance on complex management reasoning tasks compared to conventional resources?Findings: In this randomized controlled trial of 92 physicians, participants using GPT-4 achieved higher scores on management reasoning compared to those using conventional resources (e.g., UpToDate).Meaning: LLM assistance enhances physician management reasoning performance in complex cases with no clear right answers.

View details for DOI 10.1101/2024.08.05.24311485

View details for PubMedID 39148822

View details for PubMedCentralID PMC11326321

View details for DOI 10.1097/MCG.0000000000001742

Abstract

We identified that Stanford Health Care had a significant number of patients who after discharge are found by the utilization review committee not to meet Center for Mediare and Medicaid Services (CMS) 2-midnight benchmark for inpatient status. Some of the charges incurred during the care of these patients are written-off and known as Medicare 1-day write-offs. This study which aims to evaluate the use of a Best Practice Alert (BPA) feature on the electronic medical record, EPIC, to ensure appropriate designation of a patient's hospitalization status as either inpatient or outpatient in accordance with Center for Medicare and Medicaid services (CMS) 2 midnight length of stay benchmark thereby reducing the number of associated write-offs.We incorporated a best practice alert (BPA) into the Epic Electronic Medical Record (EMR) that would prompt the discharging provider and the case manager to review the patients' inpatient designation prior to discharge and change the patient's designation to observation when deemed appropriate. Patients who met the inclusion criteria (Patients must have Medicare fee-for-service insurance, inpatient length of stay (LOS) less than 2 midnights, inpatient designation as hospitalization status at time of discharge, was hospitalized to an acute level of care and belonged to one of 37 listed hospital services at the time of signing of the discharge order) were randomized to have the BPA either silent or active over a three-month period from July 18, 2019, to October 18, 2019.A total of 88 patients were included in this study: 40 in the control arm and 48 in the intervention arm. In the intervention arm, 8 (8/48, 16.7%) had an inpatient status designation despite potentially meeting Medicare guidelines for an observation stay, comparing to 23 patients (23/40, 57.5%) patients in the control group (p = 0.001). The estimated number of write-offs in the control arm was 17 (73.9%, out of 23 inpatient patients) while in the intervention arm was 1 (12.5%, out of 8 inpatient patient) after accounting for patients who may have met inpatient criteria for other reasons based on case manager note review.This is the first time to our knowledge that a BPA has been used in this manner to reduce the number of Medicare 1-day write-offs.

View details for DOI 10.1186/s12913-024-10594-z

View details for PubMedID 38355492

View details for PubMedCentralID 6181108

Abstract

Whether patients with defecatory disorders (DDs) with favorable response to a footstool have distinctive anorectal pressure characteristics is unknown. We aimed to identify the clinical phenotype and anorectal pressure profile of patients with DDs who benefit from a footstool.This is a retrospective review of patients with high resolution anorectal manometry (HR-ARM) and balloon expulsion test (BET) from a tertiary referral center. BET was repeated with a 7-inch-high footstool in those who failed it after 120 s. Data were compared among groups with respect to BET results.Of the 667 patients with DDs, a total of 251 (38%) had failed BET. A footstool corrected BET in 41 (16%) of those with failed BET. Gender-specific differences were noted in anorectal pressures, among patients with and without normal BET, revealing gender-based nuances in pathophysiology of DDs. Comparing patients who passed BET with footstool with those who did not, the presence of optimal stool consistency, with reduced instances of loose stools and decreased reliance on laxatives were significant. Additionally, in women who benefited from a footstool, lower anal pressures at rest and simulated defecation were observed. Independent factors associated with a successful BET with a footstool in women included age <50, Bristol 3 or 4 stool consistency, lower anal resting pressure and higher rectoanal pressure gradient.Identification of distinctive clinical and anorectal phenotype of patients who benefited from a footstool could provide insight into the factors influencing the efficacy of footstool utilization and allow for an individualized treatment approach in patients with DDs.

View details for DOI 10.1111/nmo.14781

View details for PubMedID 38488172

Abstract

Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout.We conducted cross-sectional analyses of 2018 national Veterans Health Administration(VA) primary care personnel survey, administered as an online survey to all VA primary care personnel (n = 4257, response rate = 17.7%), using bivariate and multivariate logistic regressions. Our analytical sample included providers (medical doctors, nurse practitioners, physicians' assistants) and nurses (registered nurses, licensed practical nurses). The outcomes included two items measuring high burnout. Primary predictors included importance ratings of 10 population health management tools (eg. VA risk prediction algorithm, recent hospitalizations and emergency department visits, etc.).High ratings of 9 tools were associated with lower odds of high burnout, independent of covariates including VA tenure, team role, gender, ethnicity, staffing, and training. For example, clinicians who rated the risk prediction algorithm as important were less likely to report high burnout levels than those who did not use or did not know about the tool (OR 0.73; CI 0.61-0.87), and they were less likely to report frequent burnout (once per week or more) (OR 0.71; CI 0.60-0.84).Burned-out clinicians may not consider the EHR-based tools important and may not be using them to perform care management. Tools that create additional technological burden may need adaptation to become more accessible, more intuitive, and less burdensome to use. Finding ways to improve the use of tools that streamline the work of population health management and/or result in less workload due to patients with poorly managed chronic conditions may alleviate burnout. More research is needed to understand the causal directional of the association between burnout and ratings of population health management tools.

View details for DOI 10.1186/s12875-024-02410-8

View details for PubMedID 38750457

View details for PubMedCentralID PMC11094957

View details for DOI 10.3389/fdgth.2022.943768

Abstract

With 15 drugs currently approved for the treatment of metastatic renal cell carcinoma (mRCC) and even more combination regimens with immunotherapy on the horizon, there remains a distinct lack of molecular biomarkers for therapeutic efficacy. Our study reports on real-world clinical outcomes of mRCC patients from a tertiary academic medical center treated with empirically selected standard-of-care therapy. We utilized the Stanford Renal Cell Carcinoma Database (RCCD) to report on various outcome measures, including overall survival (OS) and the median number of lines of targeted therapies received from the time of metastatic diagnosis. We found that most metastatic patients did not survive long enough to attempt even half of the available targeted therapies. We also noted that patients who failed to receive a clinical benefit within the first two lines of therapy could still go on to experience clinical benefit in later lines of therapy. The term, "clinical benefit" was assigned to a line of therapy if a patient remained on drug treatment for three months or longer. Moreover, patients with clinical benefit in at least one line of therapy experienced significantly longer OS compared to those who did not have clinical benefit in at least one line of therapy. Developing biomarkers that identify patients who will receive clinical benefit in individual lines of therapy is one potential strategy for achieving rational drug sequencing in mRCC.

View details for DOI 10.3390/cancers11071000

View details for PubMedID 31319594

Abstract

Following the adoption of an acuity-adaptable unit model in an academic medical center, a