Publications

STUDY OBJECTIVES: To compare end-of-life predictions as measured by the physician-answered surprise question (SQ), "Would you be surprised if this patient died in the next 6 months?"), the Geriatric End-of-Life Screening Tool (GEST) artificial intelligence (AI) model, and a new collaborative GEST+SQ model for predicting 6-month mortality in older emergency department (ED) patients.

METHODS: This was a single-site prospective cohort study (Nov 2022 to June 2023) at a tertiary academic ED of patients aged 65 years and older. Answers to the SQ were collected within the electronic health record at ED disposition and GEST scores were calculated from available records using laboratory, vital signs, demographic and historical data. Six-month mortality was adjudicated via electronic health record and state records. SQ and GEST were compared using sensitivity and specificity. A new logistic regression model was developed combining SQ and GEST (GEST+SQ) and compared with GEST alone, using area under receiver-operating characteristic curves (ROC-AUC) for discrimination and expected calibration error for calibration. We modeled a sequential screening pathway where low- and high-risk patients received only GEST screening, whereas intermediate-risk patients received both GEST and SQ, reporting the proportion of patients for whom adding the SQ to GEST would change a theoretical referral to intervention.

RESULTS: From 9,256 eligible patients, 3,479 had SQ responses (37.6%), with 13.3% 6-month mortality. When matching GEST sensitivity to SQ (83.8%), GEST had greater specificity than the SQ (61.5% [56.7 to 67.1] vs. 50.8% [49.1 to 52.6]). At matching specificity (50.8%), GEST sensitivity (90.0% [87.0 to 92.7]) exceeded the SQ (83.8% [80.3 to 87.0]). GEST had an receiver-operating characteristic - area under the curve (ROC-AUC) of 0.79 (0.77 to 0.81), whereas the GEST+SQ model had ROC-AUC of 0.80 (0.78 to 0.82). The GEST+SQ model had significantly improved expected calibration error of 0.01 (0.01 to 0.02) for GEST+SQ vs. 0.042 (0.03 to 0.05) for GEST alone. In a sequential screening pathway, as few as 5% of patients required SQ screening following GEST risk scoring.

CONCLUSION: GEST modestly outperformed the SQ for predicting 6-month mortality. A GEST+SQ collaborative model did not improve discrimination (ROC-AUC) over GEST alone, but improved calibration. Sequential screening using GEST and then the SQ for intermediate-risk patients could decrease physician screening burden by 95% relative to manual, SQ-only screening. Collaborative approaches integrating automated tools with targeted physician input may enhance ED mortality risk assessment while reducing clinician effort.

BACKGROUND: Whether to continue breast cancer screening beyond age 74 is uncertain. Decision aids may improve understanding of health information and support informed screening decisions. The goal of this study was to develop a video-based decision aid for breast cancer screening among older women using patient-centered design.

METHODS: Following the Framework for Innovation, the research team first used formative focus groups to understand older women's perspectives on mammography. We developed a prototype video based on decision aid best practices and formative focus group findings. We then evaluated the content, clarity, and style of the decision aid in cognitive testing focus groups. We made iterative changes to the video in response to focus group feedback. Focus groups included women age ≥ 70 without a personal history of breast cancer from Connecticut-area community and clinical settings. We coded and analyzed transcripts using both abductive and deductive approaches.

RESULTS: We convened 6 formative focus groups and 7 cognitive testing groups with 31 participants (mean age 78 [range 70-93]); 39% Black, 58% White, and 3% Latina. In focus groups, participants perceived screening as largely beneficial and saw overdiagnosis as unfamiliar. Some participants valued quantitative information about risks and benefits of screening, while others relied on experience, perceptions of risk, and beliefs about the efficacy of mammography to make screening decisions. We incorporated these perspectives into the framing, language, and narrative arc of the decision aid. In cognitive testing focus groups, participants found the decision aid informative and engaging.

DISCUSSION: Using a patient-centered approach, we developed a video-based decision aid for breast cancer screening for older women. Our design, which drew on the perspectives of older women, was perceived as easy to understand and informative. We will assess the impact of the decision aid on decision quality, decisional conflict, and intention to screen in future work.

BACKGROUND: Risks related to long-term opioid therapy for chronic pain are high and may increase over time with aging. Deprescribing may be a beneficial intervention for older adults prescribed chronic opioids.

METHODS: Semi-structured interviews with hypothetical clinical cases of older adults prescribed opioids for chronic pain: (1) low-risk case: a patient prescribed low-dose opioids without concerns; (2) moderate-risk case: a patient with multimorbidity and concurrent benzodiazepine use prescribed moderate opioid doses; (3) high-risk case: a patient prescribed high-dose opioids with signs of an opioid use disorder (OUD). PCPs were asked, in an open-ended fashion, to discuss whether they would initiate a deprescribing conversation, how they would approach deprescribing, and how they would approach a patient who declined recommendations to deprescribe.

PARTICIPANTS AND SETTING: PCPs from a Massachusetts health system.

RESULTS: 18 PCPs participated (56% female, 78% academic). More than half of PCPs would initiate a deprescribing conversation across the three cases. PCPs' approach to deprescribing and mitigating risks differed based on clinical risk. In low and moderate-risk cases, PCPs emphasized a patient-directed taper plan and education on opioid risks. In the high-risk case, some PCPs were uncertain about initiating a deprescribing conversation due to concerns about the patient's mental health and the risk of illicit opioid use. Naloxone was infrequently recommended across the three cases, but in the high-risk case, approximately half of PCPs suggested medications for OUD.

CONCLUSIONS: PCPs reported that they would often initiate opioid deprescribing conversations with older adults, but were less confident in managing older adults with signs of OUD. PCPs require additional support to implement successful conversations on opioid deprescribing with older adults.

BACKGROUND: Hospitalized older adults are commonly discharged with changes to antihypertensive and glucose-lowering (cardiometabolic) medications. Though adverse drug events remain a leading cause of readmissions, there is little contemporary data on how medication discharge planning is communicated and how often medication errors occur post-discharge.

OBJECTIVE: To assess older adults' post-hospital medication use and ambulatory follow-up after receiving cardiometabolic medication changes during hospitalization.

DESIGN: Prospective cohort study from 11/2022 to 01/2024.

PARTICIPANTS: Adults aged 65 years or older from discharged home from an academic medical center with changes to pre-admission cardiometabolic medications.

MAIN MEASURES: Participants completed 7- and 90-day telephonic surveys on health status, medication use, and discharge planning. Self-report of medication use was compared to discharge summaries to identify medication errors (not initiating, not stopping, or taking incorrect dose). Multivariable regression models were used to identify characteristics associated with errors.

KEY RESULTS: The cohort included 151 participants (median [IQR] age 74 [70-78] years; 54% male; 17% Black, 82% White, 41% frail). Participants were admitted with a median (IQR) of 3 (2-4) cardiometabolic medications and discharged with a median (IQR) of 2 (1-4) medication changes. Of the 319 individual medications changed at discharge, 33% were further modified by 90 days. Participants reported comprehensive medication discharge planning for only 13% of medication changes. Though 93% of participants reported they understood the purpose of each of their medications at discharge, 39% had ≥ 1 medication errors at 7 days and 50% at 90 days. Use of ≥ 5 cardiometabolic medications was associated with higher rates of medication errors at 7 days (IRR 1.63; 95% CI 1.07-2.48) and 90 days (IRR 1.66; 95% CI 1.13-2.45).

CONCLUSIONS: Most hospitalized older adults discharged with cardiometabolic medication changes experienced medication errors or gaps in discharge planning. Steps to ensure all patients receive high-quality medication discharge planning are needed.

BACKGROUND: ED disposition decisions for older adults are complex and often uncertain, yet studies rarely capture emergency physicians' real-time perspectives.

OBJECTIVE: To assess patient outcomes based on emergency physician-perceived need for admission.

DESIGN: Single-site prospective cohort study conducted between July and November 2024.

SETTING: A Boston-area academic tertiary care ED.

PARTICIPANTS: Patients aged 65 and older dispositioned by attending physicians, excluding patients who were handed off, left without being seen, or eloped.

MEASUREMENTS: Physicians rated admission need using a 5-point Likert scale (2-4 considered marginal). Primary outcome was ED disposition stratified by rating. Secondary outcomes were hospital length-of-stay (LOS), 7-day ED return, and 30-day mortality.

RESULTS: Of the 489 patients (mean age 76.9 years [SD 7.5], 51.1% female), 55.8% were non-marginal admissions, 26.0% were non-marginal discharges, and 18.2% were marginal dispositions. Patients with marginal dispositions had longer workup times than non-marginal admissions or discharges (3.3 vs. 2.8 vs. 2.4 h, p < 0.05). Thirty-day mortality was greater for non-marginal admissions (8.8%) than non-marginal discharges (1.6%, p = 0.01), but not significantly different than marginal dispositions (3.4%). Marginal admissions had shorter median LOS (3.1 vs. 5 days, p < 0.01) and higher early discharge rates (27.8% vs. 13.2%, p = 0.01) than non-marginal admissions. Marginal discharges had fewer 7-day returns than non-marginal discharges (0% vs. 11.7%, p = 0.04). For marginal cases, physicians discussed admission benefits more than risks (70.1% vs. 43.3%, p < 0.01) for marginal cases.

LIMITATIONS: Single-site and need for admission were reported contemporaneous with disposition decision.

CONCLUSIONS: One in six older adult ED dispositions was identified as marginal. These patients are potential targets for shared decision-making and alternative care pathways.

BackgroundMessaging strategies hold promise to reduce breast cancer overscreening. However, it is not known whether they may have differential effects among medical maximizers who prefer to take action about their health versus medical minimizers who prefer to wait and see.MethodsIn a randomized controlled survey experiment that included 2 sequential surveys with 3,041 women aged 65+ y from a US population-based online panel, we randomized participants to 1) no messages, 2) single exposure to a screening cessation message, or 3) 2 exposures over time to the screening cessation message. We assessed support for stopping screening in a hypothetical patient and intention to stop screening oneself on 7-point scales, where higher values indicated stronger support and intentions to stop screening. We conducted stratified analyses by medical-maximizing preference and moderation analysis.ResultsOf the women, 40.7% (n = 1,238) were medical maximizers; they had lower support and intention for screening cessation in all groups compared with the medical minimizers. Two message exposures increased support for screening cessation among medical maximizers, with a mean score of 3.68 (95% confidence interval [CI] 3.51-3.85) compared with no message (mean score 2.20, 95% CI 2.00-2.39, P < 0.001). A similar pattern was seen for screening intention. Linear regression models showed no differential messaging effect by medical-maximizing preference.ConclusionsMedical maximizers, although less likely to support screening cessation, were nonetheless responsive to messaging strategies designed to reduce breast cancer overscreening.HighlightsIt is not known if a message on rationales for stopping breast cancer screening would have differential effects among medical maximizers who prefer to take action when it comes to their health versus medical minimizers who prefer to wait and see.In a 2-wave randomized controlled survey experiment with 3,041 older women, we found that medical maximizers, although less likely to support screening cessation compared with medical minimizers, were nonetheless responsive to the messaging intervention, and the magnitude of the intervention effect was similar between maximizers and minimizers.Medical maximizers reported higher levels of worry and annoyance after reading the message compared with the minimizers, but the absolute levels of worry and annoyance were low.Our findings suggest that messaging can be a useful tool for reducing overscreening even in a highly reluctant population.

Sankey diagram of agreement between dischareg summary, discharge instructions, and patient provided reasoning for chronic medication changes made during hospitalization.

INTRODUCTION: Women ≥70 years with low-risk breast cancer face nuanced therapy decisions. Using qualitative analysis, we aimed to determine how oncologists and patients integrate geriatric considerations into complex treatment conversations.

MATERIALS AND METHODS: We recruited women aged ≥70, newly diagnosed with clinical T1-2N0 hormone receptor-positive/HER2-negative disease between October 2020 and March 2023 from a large cancer center and audio-recorded and transcribed their consults with surgical, medical, and radiation oncologists. We identified geriatric issues included in conversational content and the dynamics of patient/oncologist communication. Data collection and analysis were simultaneously performed. We also assessed participant decision-making preferences, frailty, and life expectancy.

RESULTS: Of 48 eligible patients approached, 27 (56 %) participated with eight surgical oncologists, 17 with 11 medical oncologists, and four with three radiation oncologists (n = 48 consultations recorded). Fourteen patients (48 %) were ≥ 75 years, 23 were non-Hispanic White (76 %). Patients preferred to share (n = 15, 58 %) or make their own treatment decisions (n = 10, 39 %), rather than defer to the oncologist. Oncologists presented an explicit treatment choice in 16 conversations (35 %). Chronological age was discussed in 27 (56 %) conversations, comorbidities in 44 (92 %), and multimorbidity in two (4 %). Other geriatric considerations were discussed in the minority of conversations [physiologic age: 20 (42 %); function: 20 (42 %); quality-of-life: 5 (10 %); life expectancy: 5 (10 %); polypharmacy: 2 (4 %)].

DISCUSSION: Despite numerous treatment options, oncologists neither commonly offer older women with low-risk breast cancer explicit treatment choices, nor discuss geriatric issues besides comorbidity. Training oncologists in communication around geriatric issues may lead to more person-centered breast cancer care.