Ambulatory Care Fragmentation and Total Health Care Costs.

BACKGROUND: The magnitude of the relationship between ambulatory care fragmentation and subsequent total health care costs is unclear. OBJECTIVE: To determine the association between ambulatory care fragmentation and total health care costs. RESEARCH DESIGN: Longitudinal analysis of 15 years of data (2004-2018) from the national Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, linked to Medicare fee-for-service claims. SUBJECTS: A total of 13,680 Medicare beneficiaries who are 65 years and older. MEASURES: We measured ambulatory care fragmentation in each calendar year, defining high fragmentation as a reversed Bice-Boxerman Index ≥0.85 and low as <0.85. We used generalized linear models to determine the association between ambulatory care fragmentation in 1 year and total Medicare expenditures (costs) in the following year, adjusting for baseline demographic and clinical characteristics, a time-varying comorbidity index, and accounting for geographic variation in reimbursement and inflation. RESULTS: The average participant was 70.9 years old; approximately half (53%) were women. One-fourth (26%) of participants had high fragmentation in the first year of observation. Those participants had a median of 9 visits to 6 providers, with the most frequently seen provider accounting for 29% of visits. By contrast, participants with low fragmentation had a median of 8 visits to 3 providers, with the most frequently seen provider accounting for 50% of visits. High fragmentation was associated with $1085 more in total adjusted costs per person per year (95% CI $713 to $1457) than low fragmentation. CONCLUSIONS: Highly fragmented ambulatory care in 1 year is independently associated with higher total costs the following year.

Association between Gaps in Care Coordination and Emergency Department Visits Among Children without Chronic Conditions or Special Needs.

OBJECTIVE: Prior studies and have shown that gaps in care coordination (CC) increase the risk of emergency department (ED) visits among children with special healthcare needs. This study aims to determine if gaps in CC are associated with an increased risk of ED visits among children without special needs (non-CSHCN). STUDY DESIGN: We conducted a cross-sectional study using the National Survey of Children's Health (2018-2019), representing children up to age 17. A "gap" in CC occurs if the adult proxy reported dissatisfaction with communication between providers or difficulty getting the help needed to coordinate care for the child. Using logistic regression models adjusting for age and sex, we measured the association between a gap in CC and 1 or more ED visits during the past 12 months overall and stratified by any special needs. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were calculated. RESULTS: Between 2018 and 2019, 15% of respondents reported a gap in CC and 19.4% of children had at least one ED visit. Among non-CSHCN, these rates were 11% and 17%. In this population, a gap in CC was independently associated with an increased odds of ED use (AOR: 2.14; 95% CI 1.82, 2.52). CONCLUSIONS FOR PRACTICE: Self-reported gaps in ambulatory CC were associated with increased odds of ED visits even among non-CSHCN children with minor illnesses, suggesting that providers need to be aware of potential pitfalls in CC for all children, and ensure that pertinent information is available where needed.

Comparison of two frailty definitions in women with systemic lupus erythematosus.

OBJECTIVES: Frailty is a risk factor for adverse health in systemic lupus erythematosus (SLE). The Fried phenotype (FP) and the Systemic Lupus International Collaborating Clinics Frailty Index (SLICC-FI) are common frailty metrics reflecting distinct approaches to frailty assessment. We aimed to 1) compare frailty prevalence according to both metrics in women with SLE and describe differences between frail and non-frail participants using each method and 2) evaluate for cross-sectional associations between each metric and self-report disability. METHODS: Women aged 18-70 years with SLE were enrolled. FP and SLICC-FI were measured, and agreement calculated using a kappa statistic. Physician-reported disease activity and damage, Patient Reported Outcome Measurement Information System (PROMIS) computerized adaptive tests, and Valued Life Activities (VLA) self-report disability were assessed. Differences between frail and non-frail participants were evaluated cross-sectionally, and the association of frailty with disability was determined for both metrics. RESULTS: Of 67 participants, 17.9% (FP) and 26.9% (SLICC-FI) were frail according to each metric (kappa = 0.41, p< 0.01). Compared with non-frail women, frail women had greater disease damage, worse PROMIS scores, and greater disability (all p< 0.01 for FP and SLICC-FI). After age adjustment, frailty remained associated with a greater odds of disability (FP: odds ratio [OR] 4.7, 95% confidence interval [CI] 1.2-18.8; SLICC-FI: OR 4.6, 95% CI 1.3-15.8). CONCLUSION: Frailty is present in 17.9-26.9% of women with SLE. These metrics identified a similar, but non-identical group of women as frail. Further studies are needed to explore which metric is most informative in this population.

Ambulatory Care Fragmentation, Emergency Department Visits, and Race: a Nationwide Cohort Study in the U.S.

BACKGROUND: It is unclear whether highly fragmented ambulatory care (i.e., care spread across multiple providers without a dominant provider) increases the risk of an emergency department (ED) visit. Whether any such association varies with race is unknown. OBJECTIVE: We sought to determine whether highly fragmented ambulatory care increases the risk of an ED visit, overall and by race. DESIGN AND PARTICIPANTS: We analyzed data for 14,361 participants ≥ 65 years old from the nationwide prospective REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study, linked to Medicare claims (2003-2016). MAIN MEASURES: We defined high fragmentation as a reversed Bice-Boxerman Index ≥ 0.85 (≥ 75th percentile). We used Poisson models to determine the association between fragmentation (as a time-varying exposure) and ED visits, overall and stratified by race, adjusting for demographics, medical conditions, medications, health behaviors, psychosocial variables, and physiologic variables. KEY RESULTS: The average participant was 70.5 years old; 53% were female, and 33% were Black individuals. Participants with high fragmentation had a median of 9 visits to 6 providers, with 29% of visits by the most frequently seen provider; participants with low fragmentation had a median of 7 visits to 3 providers, with 50% of visits by the most frequently seen provider. Overall, high fragmentation was associated with more ED visits than low fragmentation (adjusted risk ratio [aRR] 1.31, 95% confidence interval [CI] 1.29, 1.34). The magnitude of this association was larger among Black (aRR 1.48, 95% CI 1.44, 1.53) than White participants (aRR 1.23, 95% CI 1.20, 1.25). CONCLUSIONS: Highly fragmented ambulatory care was an independent predictor of ED visits, especially among Black individuals.

Healthcare disparities: patients' perspectives on barriers to joint replacement.

OBJECTIVE: Racial and ethnic disparities in arthroplasty utilization are evident, but the reasons are not known. We aimed to identify concerns that may contribute to barriers to arthroplasty from the patient's perspective. METHODS: We identified patients' concerns about arthroplasty by performing a mixed methods study. Themes identified during semi-structured interviews with Black and Hispanic patients with advanced symptomatic hip or knee arthritis were used to develop a questionnaire to quantify and prioritize their concerns. Multiple linear and logistic regression analyses were conducted to determine the association between race/ethnicity and the importance of each theme. Models were adjusted for sex, insurance, education, HOOS, JR/KOOS, JR, and discussion of joint replacement with a doctor. RESULTS: Interviews with eight participants reached saturation and provided five themes used to develop a survey answered by 738 (24%) participants; 75.5% White, 10.3% Black, 8.7% Hispanic, 3.9% Asian/Other. Responses were significantly different between groups (p < 0.05). Themes identified were "Trust in the surgeon" "Recovery", "Cost/Insurance", "Surgical outcome", and "Personal suitability/timing". Compared to Whites, Blacks were two-fold, Hispanics four-fold more likely to rate "Trust in the surgeon" as very/extremely important. Blacks were almost three times and Hispanics over six times more likely to rate "Recovery" as very/extremely important. CONCLUSION: We identified factors of importance to patients that may contribute to barriers to arthroplasty, with marked differences between Blacks, Hispanics, and Whites.

Health Status, Persistent Symptoms, and Effort Intolerance One Year After Acute COVID-19 Infection.

BACKGROUND: The long-term prevalence and risk factors for post-acute COVID-19 sequelae (PASC) are not well described and may have important implications for unvaccinated populations and policy makers. OBJECTIVE: To assess health status, persistent symptoms, and effort tolerance approximately 1 year after COVID-19 infection DESIGN: Retrospective observational cohort study using surveys and clinical data PARTICIPANTS: Survey respondents who were survivors of acute COVID-19 infection requiring Emergency Department presentation or hospitalization between March 3 and May 15, 2020. MAIN MEASURE(S): Self-reported health status, persistent symptoms, and effort tolerance KEY RESULTS: The 530 respondents (median time between hospital presentation and survey 332 days [IQR 325-344]) had mean age 59.2±16.3 years, 44.5% were female and 70.8% were non-White. Of these, 41.5% reported worse health compared to a year prior, 44.2% reported persistent symptoms, 36.2% reported limitations in lifting/carrying groceries, 35.5% reported limitations climbing one flight of stairs, 38.1% reported limitations bending/kneeling/stooping, and 22.1% reported limitations walking one block. Even those without high-risk comorbid conditions and those seen only in the Emergency Department (but not hospitalized) experienced significant deterioration in health, persistent symptoms, and limitations in effort tolerance. Women (adjusted relative risk ratio [aRRR] 1.26, 95% CI 1.01-1.56), those requiring mechanical ventilation (aRRR 1.48, 1.02-2.14), and people with HIV (aRRR 1.75, 1.14-2.69) were significantly more likely to report persistent symptoms. Age and other risk factors for more severe COVID-19 illness were not associated with increased risk of PASC. CONCLUSIONS: PASC may be extraordinarily common 1 year after COVID-19, and these symptoms are sufficiently severe to impact the daily exercise tolerance of patients. PASC symptoms are broadly distributed, are not limited to one specific patient group, and appear to be unrelated to age. These data have implications for vaccine hesitant individuals, policy makers, and physicians managing the emerging longer-term yet unknown impact of the COVID-19 pandemic.

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load on Risk of Intubation and Mortality Among Hospitalized Patients With Coronavirus Disease 2019.

BACKGROUND: Patients hospitalized with coronavirus disease 2019 (COVID-19) frequently require mechanical ventilation and have high mortality rates. However, the impact of viral burden on these outcomes is unknown. METHODS: We conducted a retrospective cohort study of patients hospitalized with COVID-19 from 30 March 2020 to 30 April 2020 at 2 hospitals in New York City. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load was assessed using cycle threshold (Ct) values from a reverse transcription-polymerase chain reaction assay applied to nasopharyngeal swab samples. We compared characteristics and outcomes of patients with high, medium, and low admission viral loads and assessed whether viral load was independently associated with intubation and in-hospital mortality. RESULTS: We evaluated 678 patients with COVID-19. Higher viral load was associated with increased age, comorbidities, smoking status, and recent chemotherapy. In-hospital mortality was 35.0% (Ct <25; n = 220), 17.6% (Ct 25-30; n = 216), and 6.2% (Ct >30; n = 242) with high, medium, and low viral loads, respectively (P < .001). The risk of intubation was also higher in patients with a high viral load (29.1%) compared with those with a medium (20.8%) or low viral load (14.9%; P < .001). High viral load was independently associated with mortality (adjusted odds ratio [aOR], 6.05; 95% confidence interval [CI], 2.92-12.52) and intubation (aOR, 2.73; 95% CI, 1.68-4.44). CONCLUSIONS: Admission SARS-CoV-2 viral load among hospitalized patients with COVID-19 independently correlates with the risk of intubation and in-hospital mortality. Providing this information to clinicians could potentially be used to guide patient care.

Ambulatory Care Fragmentation and Subsequent Hospitalization: Evidence From the REGARDS Study.

BACKGROUND: Previous studies have suggested that highly fragmented ambulatory care increases the risk of subsequent hospitalization, but those studies used claims only and were not able to adjust for many clinical potential confounders. OBJECTIVE: The objective of this study was to determine the association between fragmented ambulatory care and subsequent hospitalization, adjusting for demographics, medical conditions, medications, health behaviors, psychosocial variables, and physiological variables. DESIGN: Longitudinal analysis of data (2003-2016) from the nationwide REasons for Geographic And Racial Differences in Stroke (REGARDS) study, linked to Medicare fee-for-service claims. SUBJECTS: A total of 12,693 Medicare beneficiaries 65 years and older from the REGARDS study who had at least 4 ambulatory visits in the first year of observation and did not have a hospitalization in the prior year. MEASURES: We defined high fragmentation as a reversed Bice-Boxerman score above the 75th percentile. We used Cox proportional hazards models to determine the association between fragmentation as a time-varying exposure and incident hospitalization in the 3 months following each exposure period. RESULTS: The mean age was 70.4 years; 54% were women, and 33% were African American. During the first year of observation, participants with high fragmentation had a median of 8 ambulatory visits with 6 providers, whereas participants with low fragmentation had a median of 7 visits with 3 providers. Over 11.8 years of follow-up, 6947 participants (55%) had a hospitalization. High fragmentation was associated with an increased hazard of hospitalization (adjusted hazard ratio=1.18; 95% confidence interval: 1.12, 1.24). CONCLUSION: Highly fragmented ambulatory care is an independent risk factor for hospitalization.

Healthcare Fragmentation and Incident Acute Coronary Heart Disease Events: a Cohort Study.

BACKGROUND: Highly fragmented ambulatory care (i.e., care spread across many providers without a dominant provider) has been associated with excess tests, procedures, emergency department visits, and hospitalizations. Whether fragmented care is associated with worse health outcomes, or whether any association varies with health status, is unclear. OBJECTIVE: To determine whether fragmented care is associated with the risk of incident coronary heart disease (CHD) events, overall and stratified by self-rated general health. DESIGN AND PARTICIPANTS: We conducted a secondary analysis of the nationwide prospective Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study (2003-2016). We included participants who were ≥ 65 years old, had linked Medicare fee-for-service claims, and had no history of CHD (N = 10,556). MAIN MEASURES: We measured fragmentation with the reversed Bice-Boxerman Index. We used Cox proportional hazards models to determine the association between fragmentation as a time-varying exposure and adjudicated incident CHD events in the 3 months following each exposure period. KEY RESULTS: The mean age was 70 years; 57% were women, and 34% were African-American. Over 11.8 years of follow-up, 569 participants had CHD events. Overall, the adjusted hazard ratio (HR) for the association between high fragmentation and incident CHD events was 1.14 (95% confidence interval (CI) 0.92, 1.39). Among those with very good or good self-rated health, high fragmentation was associated with an increased hazard of CHD events (adjusted HR 1.35; 95% CI 1.06, 1.73; p = 0.01). Among those with fair or poor self-rated health, high fragmentation was associated with a trend toward a decreased hazard of CHD events (adjusted HR 0.54; 95% CI 0.29, 1.01; p = 0.052). There was no association among those with excellent self-rated health. CONCLUSION: High fragmentation was associated with an increased independent risk of incident CHD events among those with very good or good self-rated health.

Thirty-Day Post-Discharge Outcomes Following COVID-19 Infection.

BACKGROUND: The clinical course of COVID-19 includes multiple disease phases. Data describing post-hospital discharge outcomes may provide insight into disease course. Studies describing post-hospitalization outcomes of adults following COVID-19 infection are limited to electronic medical record review, which may underestimate the incidence of outcomes. OBJECTIVE: To determine 30-day post-hospitalization outcomes following COVID-19 infection. DESIGN: Retrospective cohort study SETTING: Quaternary referral hospital and community hospital in New York City. PARTICIPANTS: COVID-19 infected patients discharged alive from the emergency department (ED) or hospital between March 3 and May 15, 2020. MEASUREMENT: Outcomes included return to an ED, re-hospitalization, and mortality within 30 days of hospital discharge. RESULTS: Thirty-day follow-up data were successfully collected on 94.6% of eligible patients. Among 1344 patients, 16.5% returned to an ED, 9.8% were re-hospitalized, and 2.4% died. Among patients who returned to the ED, 50.0% (108/216) went to a different hospital from the hospital of the index presentation, and 61.1% (132/216) of those who returned were re-hospitalized. In Cox models adjusted for variables selected using the lasso method, age (HR 1.01 per year [95% CI 1.00-1.02]), diabetes (1.54 [1.06-2.23]), and the need for inpatient dialysis (3.78 [2.23-6.43]) during the index presentation were independently associated with a higher re-hospitalization rate. Older age (HR 1.08 [1.05-1.11]) and Asian race (2.89 [1.27-6.61]) were significantly associated with mortality. CONCLUSIONS: Among patients discharged alive following their index presentation for COVID-19, risk for returning to a hospital within 30 days of discharge was substantial. These patients merit close post-discharge follow-up to optimize outcomes.

A predictive model of clinical deterioration among hospitalized COVID-19 patients by harnessing hospital course trajectories.

From early March through mid-May 2020, the COVID-19 pandemic overwhelmed hospitals in New York City. In anticipation of ventilator shortages and limited ICU bed capacity, hospital operations prioritized the development of prognostic tools to predict clinical deterioration. However, early experience from frontline physicians observed that some patients developed unanticipated deterioration after having relatively stable periods, attesting to the uncertainty of clinical trajectories among hospitalized patients with COVID-19. Prediction tools that incorporate clinical variables at one time-point, usually on hospital presentation, are suboptimal for patients with dynamic changes and evolving clinical trajectories. Therefore, our study team developed a machine-learning algorithm to predict clinical deterioration among hospitalized COVID-19 patients by extracting clinically meaningful features from complex longitudinal laboratory and vital sign values during the early period of hospitalization with an emphasis on informative missing-ness. To incorporate the evolution of the disease and clinical practice over the course of the pandemic, we utilized a time-dependent cross-validation strategy for model development. Finally, we validated our prediction model on an external validation cohort of COVID-19 patients served in a demographically distinct population from the training cohort. The main finding of our study is the identification of risk profiles of early, late and no clinical deterioration during the course of hospitalization. While risk prediction models that include simple predictors at ED presentation and clinical judgement are able to identify any deterioration vs. no deterioration, our methodology is able to isolate a particular risk group that remain stable initially but deteriorate at a later stage of the course of hospitalization. We demonstrate the superior predictive performance with the utilization of laboratory and vital sign data during the early period of hospitalization compared to the utilization of data at presentation alone. Our results will allow efficient hospital resource allocation and will motivate research in understanding the late deterioration risk group.

Differences in ambulatory care fragmentation by race.

BACKGROUND: More fragmented ambulatory care (i.e., care spread across many providers without a dominant provider) has been associated with more subsequent healthcare utilization (such as more tests, procedures, emergency department visits, and hospitalizations) than less fragmented ambulatory care. It is not known if race and socioeconomic status are associated with fragmented ambulatory care. METHODS: We conducted a longitudinal analysis of data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, using the REGARDS baseline visit plus the first year of follow-up. We included participants ≥65 years old, who had linked fee-for-service Medicare claims, and ≥ 4 ambulatory visits in the first year of follow-up. We used Tobit regression to determine the associations between race, annual household income, and educational attainment at baseline and fragmentation score in the subsequent year (as measured with the reversed Bice-Boxerman Index). Covariates included other demographic characteristics, medical conditions, medication use, health behaviors, and psychosocial variables. Additional analyses categorized visits by the type of provider (primary care vs. specialist). RESULTS: The study participants (N = 6799) had an average age of 73.0 years, 53% were female, and 30% were black. Nearly half had low annual household income (<$35,000) and 41% had a high school education or less. Overall, participants had a median of 10 ambulatory visits to 4 providers in the 12 months following their baseline study visit. Participants in the highest quintile of fragmentation scores had a median of 11 visits to 7 providers. Black race was associated with an absolute adjusted 3% lower fragmentation score compared to white race (95% confidence interval (2% lower to 4% lower; p < 0.001). This difference was explained by blacks seeing fewer specialists than whites. Income and education were not independent predictors of fragmentation scores. CONCLUSIONS: Among Medicare beneficiaries, blacks had less fragmented ambulatory care than whites, due to lower utilization of specialty care. Future research is needed to determine the effect of fragmented care on health outcomes for blacks and whites.

The impact of a faculty development program, the Leadership in Academic Medicine Program (LAMP), on self-efficacy, academic promotion and institutional retention.

BACKGROUND: Academic medical centers invest considerably in faculty development efforts to support the career success and promotion of their faculty, and to minimize faculty attrition. This study evaluated the impact of a faculty development program called the Leadership in Academic Medicine Program (LAMP) on participants' (1) self-ratings of efficacy, (2) promotion in academic rank, and (3) institutional retention. METHOD: Participants from the 2013-2020 LAMP cohorts were surveyed pre and post program to assess their level of agreement with statements that spanned domains of self-awareness, self-efficacy, satisfaction with work and work environment. Pre and post responses were compared using McNemar's tests. Changes in scores across gender were compared using Wilcoxon Rank Sum/Mann-Whitney tests. LAMP participants were matched to nonparticipant controls by gender, rank, department, and time of hire to compare promotions in academic rank and departures from the organization. Kaplan Meier curves and Cox proportional hazards models were used to examine differences. RESULTS: There were significant improvements in almost all self-ratings on program surveys (p < 0.05). Greatest improvements were seen in "understand the promotions process" (36% vs. 94%), "comfortable negotiating" (35% vs. 74%), and "time management" (55% vs. 92%). There were no statistically significant differences in improvements by gender, however women faculty rated themselves lower on all pre-program items compared to men. There was significant difference found in time-to-next promotion (p = 0.003) between LAMP participants and controls. Kaplan-Meier analysis demonstrated that LAMP faculty achieved next promotion more often and faster than controls. Cox-proportional-hazards analyses found that LAMP faculty were 61% more likely to be promoted than controls (hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.16-2.23, p-value = 0.004). There was significant difference found in time-to-departure (p < 0.0001) with LAMP faculty retained more often and for longer periods. LAMP faculty were 77% less likely to leave compared to controls (HR 0.23, 95% CI 0.16-0.34, p < 0.0001). CONCLUSIONS: LAMP is an effective faculty development program as measured subjectively by participant self-ratings and objectively through comparative improvements in academic promotions and institutional retention.

Association Between Patients' Self-Reported Gaps in Care Coordination and Preventable Adverse Outcomes: a Cross-Sectional Survey.

BACKGROUND: Whether patients' reports of gaps in care coordination reflect clinically significant problems is unclear. OBJECTIVE: To determine any association between patient-reported gaps in care coordination and patient-reported preventable adverse outcomes. DESIGN AND PARTICIPANTS: We administered a cross-sectional survey on experiences with healthcare to participants in the national Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who were ≥ 65 years old. Of the 15,817 participants in REGARDS at the time of our survey (August 2017-November 2018), 11,138 completed the survey. We restricted the sample to participants who reported ≥ 2 ambulatory visits and ≥ 2 ambulatory providers in the past year (N = 7568). MAIN MEASURES: We considered 7 gaps in ambulatory care coordination, elicited with previously validated questions. We considered 4 outcomes: (1) a test that was repeated because the doctor did not have the result of the first test, (2) a drug-drug interaction that occurred due to multiple prescribers, (3) an emergency department visit that could have been prevented by better communication among providers, and (4) a hospital admission that could have been prevented by better communication among providers. We used logistic regression to determine the association between ≥ 1 gap in care coordination and ≥ 1 preventable outcome, adjusting for potential confounders. KEY RESULTS: The average age of the sample was 77.0 years; 55% were female, and 34% were African-American. More than one-third of participants (38.1%) reported ≥ 1 gap in care coordination and nearly one-tenth (9.8%) reported ≥ 1 preventable outcome. Having ≥ 1 gap in care coordination was associated with an increased odds of ≥ 1 preventable outcome (adjusted odds ratio 1.55; 95% confidence interval 1.33, 1.81). CONCLUSIONS: Participants' reports of gaps in care coordination were associated with an increased odds of preventable adverse outcomes. Future interventions should leverage patients' observations to detect and resolve gaps in care coordination.

Internal medicine residents identify gaps in medical education on outpatient referrals.

BACKGROUND: Relevant clinical information is often missing when a patient sees a specialist after being referred by another physician in the ambulatory setting. This can result in missed or delayed diagnoses, delayed treatment, unnecessary testing, and drug interactions. Residents' attitudes toward providing clinical information at the time of referral and their perspectives toward training on referral skills are not clear. We sought to assess internal medicine residents' attitudes toward and experiences with outpatient referrals. METHODS: We conducted a cross-sectional survey in October-December 2018 of all internal medicine interns and residents affiliated with a large, urban internal medicine residency program in New York, NY. We used a novel survey instrument that included 13 questions about attitudes toward and experiences with outpatient referrals. We used descriptive statistics to characterize the results. RESULTS: Overall, 122 of 132 residents participated (92% response rate). Respondents were approximately equally distributed across post-graduate years 1-3. Although 83% of residents reported that it is "always" important to provide the clinical reason for a referral, only 11% stated that they "always" provide a sufficient amount of clinical information for the consulting provider when making a referral. Only 9% of residents "strongly agree" that residency provides sufficient training in knowing when to refer patients, and only 8% "strongly agree" that residency provides sufficient training in what information to provide the consulting physician. CONCLUSIONS: These results suggest a substantial discrepancy between the amount of information residents believe they should provide at the time of a referral and the amount they actually provide. Many residents report not receiving adequate training during residency on when to refer patients and what clinical information to provide at the time of referral. Improvements to medical education regarding outpatient referrals are urgently needed.

Hurricane Sandy (New Jersey): Mortality Rates in the Following Month and Quarter.

OBJECTIVES: To describe changes in mortality after Hurricane Sandy made landfall in New Jersey on October 29, 2012. METHODS: We used electronic death records to describe changes in all-cause and cause-specific mortality overall, in persons aged 76 years or older, and by 3 Sandy impact levels for the month and quarter following Hurricane Sandy compared with the same periods in earlier years adjusted for trends. RESULTS: All-cause mortality increased 6% (95% confidence interval [CI] = 2%, 11%) for the month, 5%, 8%, and 12% by increasing Sandy impact level; and 7% (95% CI = 5%, 10%) for the quarter, 5%, 8%, and 15% by increasing Sandy impact level. In elderly persons, all-cause mortality rates increased 10% (95% CI = 5%, 15%) and 13% (95% CI = 10%, 16%) in the month and quarter, respectively. Deaths that were cardiovascular disease-related increased by 6% in both periods, noninfectious respiratory disease-related by 24% in the quarter, infection-related by 20% in the quarter, and unintentional injury-related by 23% in the month. CONCLUSIONS: Mortality increased, heterogeneous by cause, for both periods after Hurricane Sandy, particularly in communities more severely affected and in the elderly, who may benefit from supportive services.

A Novel Approach for Mixed-Methods Research Using Large Language Models: A Report Using Patients' Perspectives on Barriers to Arthroplasty.

OBJECTIVE: Mixed-methods research is valuable in health care to gain insights into patient perceptions. However, analyzing textual data from interviews can be time-consuming and require multiple analysts for investigator triangulation. This study aims to explore a novel approach to investigator triangulation in mixed-methods research by employing a large language model (LLM) for analyzing data from patient interviews. METHODS: This study compared the thematic analysis and survey generation performed by human investigators and ChatGPT-4, which uses GPT-4 as its backbone model, using data from an existing study that explored patient perceptions of barriers to arthroplasty. The human- and ChatGPT-4-generated themes and surveys were compared and evaluated based on their representation of salient themes from a predetermined topic guide. RESULTS: ChatGPT-4 generated analogous dominant themes and a comprehensive corresponding survey as the human investigators but in significantly less time. The survey questions generated by ChatGPT-4 were less precise than those developed by human investigators. The mixed-methods flowchart proposes integrating LLMs and human investigators as a supplementary tool for the preliminary thematic analysis of qualitative data and survey generation. CONCLUSION: By utilizing a combination of LLMs and human investigators through investigator triangulation, researchers may be able to conduct more efficient mixed-methods research to better understand patient perspectives. Ethical and qualitative implications of using LLMs should be considered.