Race adjustments in clinical algorithms can help correct for racial disparities in data quality.

Despite ethical and historical arguments for removing race from clinical algorithms, the consequences of removal remain unclear. Here, we highlight a largely undiscussed consideration in this debate: varying data quality of input features across race groups. For example, family history of cancer is an essential predictor in cancer risk prediction algorithms but is less reliably documented for Black participants and may therefore be less predictive of cancer outcomes. Using data from the Southern Community Cohort Study, we assessed whether race adjustments could allow risk prediction models to capture varying data quality by race, focusing on colorectal cancer risk prediction. We analyzed 77,836 adults with no history of colorectal cancer at baseline. The predictive value of self-reported family history was greater for White participants than for Black participants. We compared two cancer risk prediction algorithms-a race-blind algorithm which included standard colorectal cancer risk factors but not race, and a race-adjusted algorithm which additionally included race. Relative to the race-blind algorithm, the race-adjusted algorithm improved predictive performance, as measured by goodness of fit in a likelihood ratio test (P-value: <0.001) and area under the receiving operating characteristic curve among Black participants (P-value: 0.006). Because the race-blind algorithm underpredicted risk for Black participants, the race-adjusted algorithm increased the fraction of Black participants among the predicted high-risk group, potentially increasing access to screening. More broadly, this study shows that race adjustments may be beneficial when the data quality of key predictors in clinical algorithms differs by race group.

Pooled testing efficiency increases with test frequency.

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around [Formula: see text] However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

Characteristics and determinants of high-risk unscheduled return visits to the emergency department.

BACKGROUND: High-risk unscheduled return visits (HRURVs), defined as return visits within 72 hours that require admission or die in the emergency department (ED) on representation, are a key quality metric in the ED. The objective of this study was to determine the incidence and describe the characteristics and predictors of HRURVs to the ED. METHODS: Case-control study, conducted between 1 November 2014 and 31 October 2015. Cases included all HRURVs over the age of 18 that presented to the ED. Controls were selected from patients who were discharged from the ED during the study period and did not return in the next 72 hours. Controls were matched to cases based on gender, age (±5 years) and date of presentation. RESULTS: Out of 38 886 ED visits during the study period, 271 are HRURVs, giving an incidence of HRURV of 0.70% (95% CI 0.62% to 0.78%). Our final analysis includes 270 HRURV cases and 270 controls, with an in-ED mortality rate of 0.7%, intensive care unit admission of 11.1% and need for surgical intervention of 22.2%. After adjusting for other factors, HRURV cases are more likely to be discharged with a diagnosis related to digestive system or infectious disease (OR 1.64, 95% CI 1.02 to 2.65 and OR 2.81, 95% CI 1.05 to 7.51, respectively). Furthermore, presentation to the ED during off-hours is a significant predictor of HRURV (OR 1.64, 95% CI 1.11 to 2.43) as is the presence of a handover during the patient visit (OR 1.68, 95% CI 1.02 to 2.75). CONCLUSION: HRURV is an important key quality outcome metric that reflects a subgroup of ED patients with specific characteristics and predictors. Efforts to reduce this HRURV rate should focus on interventions targeting patients discharged with digestive system, kidney and urinary tract and infectious diseases diagnosis as well as exploring the role of handover tools in reducing HRURVs.

Prioritizing Primary Care Patients for a Communication Intervention Using the "Surprise Question": a Prospective Cohort Study.

BACKGROUND: Communication about priorities and goals improves the value of care for patients with serious illnesses. Resource constraints necessitate targeting interventions to patients who need them most. OBJECTIVE: To evaluate the effectiveness of a clinician screening tool to identify patients for a communication intervention. DESIGN: Prospective cohort study. SETTING: Primary care clinics in Boston, MA. PARTICIPANTS: Primary care physicians (PCPs) and nurse care coordinators (RNCCs) identified patients at high risk of dying by answering the Surprise Question (SQ): "Would you be surprised if this patient died in the next 2 years?" MEASUREMENTS: Performance of the SQ for predicting mortality, measured by the area under receiver operating curve (AUC), sensitivity, specificity, and likelihood ratios. RESULTS: Sensitivity of PCP response to the SQ at 2 years was 79.4% and specificity 68.6%; for RNCCs, sensitivity was 52.6% and specificity 80.6%. In univariate regression, the odds of 2-year mortality for patients identified as high risk by PCPs were 8.4 times higher than those predicted to be at low risk (95% CI 5.7-12.4, AUC 0.74) and 4.6 for RNCCs (3.4-6.2, AUC 0.67). In multivariate analysis, both PCP and RNCC prediction of high risk of death remained associated with the odds of 2-year mortality. LIMITATIONS: This study was conducted in the context of a high-risk care management program, including an initial screening process and training, both of which affect the generalizability of the results. CONCLUSION: When used in combination with a high-risk algorithm, the 2-year version of the SQ captured the majority of patients who died, demonstrating better than expected performance as a screening tool for a serious illness communication intervention in a heterogeneous primary care population.

Short-term Outcomes for Medicare Beneficiaries After Low-acuity Visits to Emergency Departments and Clinics.

BACKGROUND: There is substantial interest in identifying low-acuity visits to emergency departments (EDs) that could be treated more appropriately in other settings. Systematic differences in illness severity between ED patients and comparable patients elsewhere could make such strategies unsafe, but little evidence exists to guide policy makers. OBJECTIVE: To compare illness severity between patients visiting EDs and outpatient clinics, by comparing short-term mortality and hospitalization, controlling for patient demographics, comorbidity, and visit acuity. RESEARCH DESIGN: Cross-sectional study of outcomes after medical encounters. SUBJECTS: Nationally representative 20% sample of Medicare fee-for-service beneficiaries discharged home from ED or clinic visit in 2011, and enrolled continuously for 1 year before the visit. MEASURES: All-cause mortality and hospitalization in the 8, 15, and 30 days after discharge home from ED or clinic visits. RESULTS: After risk-adjusting for patient demographic, comorbidity, disability, and dual-eligibility status, as well as visit acuity as measured by a commonly used algorithm, we found that ED patients were more likely to die (risk-adjusted odds ratio=2.75; 95% confidence interval, 2.56-2.96) or be hospitalized (odds ratio=1.97; 95% confidence interval, 1.95-2.00) after discharge than clinic patients. Differences in short-term outcomes were observed even when comparing patients with the same discharge diagnoses after risk adjustment. CONCLUSIONS: Patients presenting to EDs have worse risk-adjusted short-term outcomes than those presenting to outpatient clinics, even after controlling for acuity level of visit or discharge diagnosis. Existing measures of acuity using administrative data may not adequately capture severity of illness, making judgments of the appropriate setting for care difficult.

The Emergency Care of Patients With Cancer: Setting the Research Agenda.

To identify research priorities and appropriate resources and to establish the infrastructure required to address the emergency care of patients with cancer, the National Institutes of Health's National Cancer Institute and the Office of Emergency Care Research sponsored a one-day workshop, "Cancer and Emergency Medicine: Setting the Research Agenda," in March 2015 in Bethesda, MD. Participants included leading researchers and clinicians in the fields of oncology, emergency medicine, and palliative care, and representatives from the National Institutes of Health. Attendees were charged with identifying research opportunities and priorities to advance the understanding of the emergency care of cancer patients. Recommendations were made in 4 areas: the collection of epidemiologic data, care of the patient with febrile neutropenia, acute events such as dyspnea, and palliative care in the emergency department setting.

Burden of emergency conditions and emergency care usage: new estimates from 40 countries.

OBJECTIVE: To estimate the global and national burden of emergency conditions, and compare them to emergency care usage rates. METHODS: We coded all 291 Global Burden of Disease 2010 conditions into three categories to estimate emergency burden: conditions that, if not addressed within hours to days of onset, commonly lead to serious disability or death; conditions with common acute decompensations that lead to serious disability or death; and non-emergencies. Emergency care usage rates were obtained from a systematic literature review on emergency care facilities in low-income and middle-income countries (LMICs), supplemented by national health system reports. FINDINGS: All 15 leading causes of death and disability-adjusted life years (DALYs) globally were conditions with potential emergent manifestations. We identified 41 facility-based reports in 23 countries, 12 of which were in LMICs; data for 17 additional countries were obtained from national or regional reports on emergency usage. Burden of emergency conditions was the highest in low-income countries, with median DALYs of 47 728 per 100 000 population (IQR 45 253-50 085) in low-income, 25 186 (IQR 21 982-40 480) in middle-income and 15 691 (IQR 14 649-16 382) in high-income countries. Patterns were similar using deaths to measure burden and excluding acute decompensations from the definition of emergency conditions. Conversely, emergency usage rates were the lowest in low-income countries, with median 8 visits per 1000 population (IQR 6-10), 78 (IQR 25-197) in middle-income and 264 (IQR 177-341) in high-income countries. CONCLUSIONS: Despite higher burden of emergency conditions, emergency usage rates are substantially lower in LMICs, likely due to limited access to emergency care.

Emergency care in 59 low- and middle-income countries: a systematic review.

OBJECTIVE: To conduct a systematic review of emergency care in low- and middle-income countries (LMICs). METHODS: We searched PubMed, CINAHL and World Health Organization (WHO) databases for reports describing facility-based emergency care and obtained unpublished data from a network of clinicians and researchers. We screened articles for inclusion based on their titles and abstracts in English or French. We extracted data on patient outcomes and demographics as well as facility and provider characteristics. Analyses were restricted to reports published from 1990 onwards. FINDINGS: We identified 195 reports concerning 192 facilities in 59 countries. Most were academically-affiliated hospitals in urban areas. The median mortality within emergency departments was 1.8% (interquartile range, IQR: 0.2-5.1%). Mortality was relatively high in paediatric facilities (median: 4.8%; IQR: 2.3-8.4%) and in sub-Saharan Africa (median: 3.4%; IQR: 0.5-6.3%). The median number of patients was 30 000 per year (IQR: 10 296-60 000), most of whom were young (median age: 35 years; IQR: 6.9-41.0) and male (median: 55.7%; IQR: 50.0-59.2%). Most facilities were staffed either by physicians-in-training or by physicians whose level of training was unspecified. Very few of these providers had specialist training in emergency care. CONCLUSION: Available data on emergency care in LMICs indicate high patient loads and mortality, particularly in sub-Saharan Africa, where a substantial proportion of all deaths may occur in emergency departments. The combination of high volume and the urgency of treatment make emergency care an important area of focus for interventions aimed at reducing mortality in these settings.

Frequency of ED revisits and death among older adults after a fall.

INTRODUCTION: Falls among older adults (aged ≥65 years) are the leading cause of both injury deaths and emergency department (ED) visits for trauma. We examine the characteristics and prevalence of older adult ED fallers as well as the recurrent ED visit and mortality rate. METHODS: This was a retrospective analysis of a cohort of elderly fall patients who presented to the ED between 2005 and 2011 of 2 urban, level 1 trauma, teaching hospitals with approximately 80000 to 95000 annual visits. We examined the frequency of ED revisits and death at 3 days, 7 days, 30 days, and 1 year controlling for certain covariates. RESULTS: Our cohort included 21340 patients. The average age was 78.6 years. An increasing proportion of patients revisited the ED over the course of 1 year, ranging from 2% of patients at 3 days to 25% at 1 year. Death rates increased from 1.2% at 3 days to 15% at 1 year. A total of 10728 patients (50.2%) returned to the ED at some point during our 7-year study period, and 36% of patients had an ED revisit or death within 1 year. In multivariate logistic regression, male sex and comorbidities were associated with ED revisits and death. CONCLUSION: More than one-third of older adult ED fall patients had an ED revisit or died within 1 year. Falls are one of the geriatric syndromes that contribute to frequent ED revisits and death rates. Future research should determine whether falls increase the risk of such outcomes and how to prevent future fall and death.

Cause-specific risk of hospital admission related to extreme heat in older adults.

IMPORTANCE: Heat exposure is known to have a complex set of physiological effects on multiple organ systems, but current understanding of the health effects is mostly based on studies investigating a small number of prespecified health outcomes such as cardiovascular and respiratory diseases. OBJECTIVES: To identify possible causes of hospital admissions during extreme heat events and to estimate their risks using historical data. DESIGN, SETTING, AND POPULATION: Matched analysis of time series data describing daily hospital admissions of Medicare enrollees (23.7 million fee-for-service beneficiaries [aged ≥65 years] per year; 85% of all Medicare enrollees) for the period 1999 to 2010 in 1943 counties in the United States with at least 5 summers of near-complete (>95%) daily temperature data. EXPOSURES: Heat wave periods, defined as 2 or more consecutive days with temperatures exceeding the 99th percentile of county-specific daily temperatures, matched to non-heat wave periods by county and week. MAIN OUTCOMES AND MEASURES: Daily cause-specific hospitalization rates by principal discharge diagnosis codes, grouped into 283 disease categories using a validated approach. RESULTS: Risks of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke were statistically significantly higher on heat wave days relative to matched non-heat wave days, but risk of hospitalization for congestive heart failure was lower (P < .05). Relative risks for these disease groups were 1.18 (95% CI, 1.12-1.25) for fluid and electrolyte disorders, 1.14 (95% CI, 1.06-1.23) for renal failure, 1.10 (95% CI, 1.04-1.16) for urinary tract infections, 1.06 (95% CI, 1.00-1.11) for septicemia, and 2.54 (95% CI, 2.14-3.01) for heat stroke. Absolute risk differences were 0.34 (95% CI, 0.22-0.46) excess admissions per 100,000 individuals at risk for fluid and electrolyte disorders, 0.25 (95% CI, 0.12-0.39) for renal failure, 0.24 (95% CI, 0.09-0.39) for urinary tract infections, 0.21 (95% CI, 0.01-0.41) for septicemia, and 0.16 (95% CI, 0.10-0.22) for heat stroke. For fluid and electrolyte disorders and heat stroke, the risk of hospitalization increased during more intense and longer-lasting heat wave periods (P < .05). Risks were generally highest on the heat wave day but remained elevated for up to 5 subsequent days. CONCLUSIONS AND RELEVANCE: Among older adults, periods of extreme heat were associated with increased risk of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke. However, the absolute risk increase was small and of uncertain clinical importance.

Association between the Medicare hospice benefit and health care utilization and costs for patients with poor-prognosis cancer.

IMPORTANCE: More patients with cancer use hospice currently than ever before, but there are indications that care intensity outside of hospice is increasing, and length of hospice stay decreasing. Uncertainties regarding how hospice affects health care utilization and costs have hampered efforts to promote it. OBJECTIVE: To compare utilization and costs of health care for patients with poor-prognosis cancers enrolled in hospice vs similar patients without hospice care. DESIGN, SETTING, AND PARTICIPANTS: Matched cohort study of patients in hospice and nonhospice care using a nationally representative 20% sample of Medicare fee-for-service beneficiaries who died in 2011. Patients with poor-prognosis cancers (eg, brain, pancreatic, metastatic malignancies) enrolled in hospice before death were matched to similar patients who died without hospice care. EXPOSURES: Period between hospice enrollment and death for hospice beneficiaries, and the equivalent period of nonhospice care before death for matched nonhospice patients. MAIN OUTCOMES AND MEASURES: Health care utilization including hospitalizations and procedures, place of death, cost trajectories before and after hospice start, and cumulative costs, all during the last year of life. RESULTS: Among 86,851 patients with poor-prognosis cancers, median time from first poor-prognosis diagnosis to death was 13 months (interquartile range [IQR], 3-34), and 51,924 patients (60%) entered hospice before death. Matching yielded a cohort balanced on age, sex, region, time from poor-prognosis diagnosis to death, and baseline care utilization, with 18,165 patients in the hospice group and 18,165 in the nonhospice group. After matching, 11% of nonhospice and 1% of hospice beneficiaries who had cancer-directed therapy after exposure were excluded. Median hospice duration was 11 days. After exposure, nonhospice beneficiaries had significantly more hospitalizations (65% [95% CI, 64%-66%], vs hospice with 42% [95% CI, 42%-43%]; risk ratio, 1.5 [95% CI, 1.5-1.6]), intensive care (36% [95% CI, 35%-37%], vs hospice with 15% [95% CI, 14%-15%]; risk ratio, 2.4 [95% CI, 2.3-2.5]), and invasive procedures (51% [95% CI, 50%-52%], vs hospice with 27% [95% CI, 26%-27%]; risk ratio, 1.9 [95% CI, 1.9-2.0]), largely for acute conditions not directly related to cancer; and 74% (95% CI, 74%-75%) of nonhospice beneficiaries died in hospitals and nursing facilities compared with 14% (95% CI, 14%-15%) of hospice beneficiaries. Costs for hospice and nonhospice beneficiaries were not significantly different at baseline, but diverged after hospice start. Total costs over the last year of life were $71,517 (95% CI, $70,543-72,490) for nonhospice and $62,819 (95% CI, $62,082-63,557) for hospice, a statistically significant difference of $8697 (95% CI, $7560-$9835). CONCLUSIONS AND RELEVANCE: In this sample of Medicare fee-for-service beneficiaries with poor-prognosis cancer, those receiving hospice care vs not (control), had significantly lower rates of hospitalization, intensive care unit admission, and invasive procedures at the end of life, along with significantly lower total costs during the last year of life.

Receipt of Medications for Chronic Disease During the First 2 Years of the COVID-19 Pandemic Among Enrollees in Fee-for-Service Medicare.

Importance: During the first 2 years of the COVID-19 pandemic, inpatient and ambulatory care declined dramatically. Little is known about prescription drug receipt during this period, particularly for populations with chronic illness and with high risk of adverse COVID-19 outcomes and decreased access to care. Objective: To investigate whether receipt of medications was maintained during the first 2 years of the COVID-19 pandemic among older people with chronic diseases, particularly Asian, Black, and Hispanic populations and people with dementia, who faced pandemic-related care disruptions. Design, Setting, and Participants: This cohort study used a 100% sample of US Medicare fee-for-service administrative data from 2019 to 2021 for community-dwelling beneficiaries aged 65 years or older. Population-based prescription fill rates were compared for 2020 and 2021 vs 2019. Data were analyzed from July 2022 to March 2023. Exposure: The COVID-19 pandemic. Main Outcomes and Measures: Age- and sex-adjusted monthly prescription fill rates were calculated for 5 groups of medications commonly prescribed for chronic disease : angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors (statins), oral diabetes medications, asthma and chronic obstructive pulmonary disease medications, and antidepressants. Measurements were stratified by race and ethnicity group and dementia diagnosis. Secondary analyses measured changes in the proportion of prescriptions dispensed as a 90-day or greater supply. Results: Overall, the mean monthly cohort included 18 113 000 beneficiaries (mean [SD] age, 74.5 [7.4] years; 10 520 000 females [58.1%]; 587 000 Asian [3.2%], 1 069 000 Black [5.9%], 905 000 Hispanic [5.0%], and 14 929 000 White [82.4%]); 1 970 000 individuals (10.9%) were diagnosed with dementia. Across 5 drug classifications, mean fill rates increased by 2.07% (95% CI, 2.01% to 2.12%) in 2020 and decreased by 2.61% (95% CI, -2.67% to -2.56%) in 2021 compared with 2019. Fill rates decreased by less than the mean overall decrease for Black enrollees (-1.42%; 95% CI, -1.64% to -1.20%) and Asian enrollees (-1.05%; 95% CI, -1.36% to -0.77%) and people diagnosed with dementia (-0.38%; 95% CI, -0.54% to -0.23%). The proportion of fills dispensed as 90-day or greater supplies increased during the pandemic for all groups, with an increase per 100 fills of 3.98 fills (95% CI, 3.94 to 4.03 fills) overall. Conclusions and Relevance: This study found that, in contrast to in-person health services, receipt of medications for chronic conditions was relatively stable in the first 2 years of the COVID-19 pandemic overall, across racial and ethnic groups, and for community-dwelling patients with dementia. This finding of stability may hold lessons for other outpatient services during the next pandemic.

Implications of predicting race variables from medical images.

AI-predicted race variables pose risks and opportunities for studying health disparities.