Mild Cognitive Impairment: Data-Driven Prediction, Risk Factors, and Workup.

Over 78 million people will suffer from dementia by 2030, emphasizing the need for early identification of patients with mild cognitive impairment (MCI) at risk, and personalized clinical evaluation steps to diagnose potentially reversible causes. Here, we leverage real-world electronic health records in the observational medical outcomes partnership (OMOP) data model to develop machine learning models to predict MCI up to a year in advance of recorded diagnosis. Our experimental results with logistic regression, random forest, and xgboost models trained and evaluated on more than 531K patient visits show random forest model can predict MCI onset with ROC-AUC of 68.2±0.7. We identify the clinical factors mentioned in clinician notes that are most predictive of MCI. Using similar association mining techniques, we develop a data-driven list of clinical procedures commonly ordered in the workup of MCI cases, that could be used as a basis for guidelines and clinical order set templates.

Evaluating implementation strategies to support documentation of veterans' care preferences.

OBJECTIVE: To evaluate the effectiveness of feedback reports and feedback reports + external facilitation on completion of life-sustaining treatment (LST) note the template and durable medical orders. This quality improvement program supported the national roll-out of the Veterans Health Administration (VA) LST Decisions Initiative (LSTDI), which aims to ensure that seriously-ill veterans have care goals and LST decisions elicited and documented. DATA SOURCES: Primary data from national databases for VA nursing homes (called Community Living Centers [CLCs]) from 2018 to 2020. STUDY DESIGN: In one project, we distributed monthly feedback reports summarizing LST template completion rates to 12 sites as the sole implementation strategy. In the second involving five sites, we distributed similar feedback reports and provided robust external facilitation, which included coaching, education, and learning collaboratives. For each project, principal component analyses matched intervention to comparison sites, and interrupted time series/segmented regression analyses evaluated the differences in LSTDI template completion rates between intervention and comparison sites. DATA COLLECTION METHODS: Data were extracted from national databases in addition to interviews and surveys in a mixed-methods process evaluation. PRINCIPAL FINDINGS: LSTDI template completion rose from 0% to about 80% throughout the study period in both projects' intervention and comparison CLCs. There were small but statistically significant differences for feedback reports alone (comparison sites performed better, coefficient estimate 3.48, standard error 0.99 for the difference between groups in change in trend) and feedback reports + external facilitation (intervention sites performed better, coefficient estimate -2.38, standard error 0.72). CONCLUSIONS: Feedback reports + external facilitation was associated with a small but statistically significant improvement in outcomes compared with comparison sites. The large increases in completion rates are likely due to the well-planned national roll-out of the LSTDI. This finding suggests that when dissemination and support for widespread implementation are present and system-mandated, significant enhancements in the adoption of evidence-based practices may require more intensive support.

Improving Medical and Nurse Practitioner Student Confidence and Clinical Skill in Advance Care Plan Development: A Multidisciplinary Mentorship Model.

BACKGROUND: Advance care planning (ACP) is an integral aspect of patient-centered care, however medical (MD) and Adult-Gerontology Acute Care Nurse Practitioner (AGACNP) students receive minimal education on how to facilitate ACP discussions and ultimately feel uncomfortable having these discussions with patients.1-4 The aim of this project was to increase MD and AGACNP students' perceived ability and confidence in leading ACP conversations through an ACP educational program called the Letter Project Pilot (LPP). METHODS: The LPP consisted of faculty-supervised interactions in the inpatient setting during which students were able to lead ACP discussions with patients by guiding them through an advance directive worksheet that was structured in the format of a letter. Student participants were recruited from the MD and AGACNP programs associated with the academic medical center. Patients were recruited from inpatient medicine and geriatrics units at the academic medical center. At the end of the 3-month pilot, a voluntary, anonymous REDCap survey was used to evaluate 2 primary outcomes of interest:1) the association of the LPP pilot on perceived ACP skills, and 2) the perceived impact of the LPP pilot on ACP in future practice. RESULTS: Students perceived that their experiences positively enhanced their current ACP skills and their ability to have ACP conversations in their future practice. CONCLUSION: The results support that the LPP is a scalable, cost-effective project that increases students' perceived ability and confidence in leading ACP conversations.

Women in Academic Medicine: Measuring Stereotype Threat Among Junior Faculty.

BACKGROUND: Gender stereotypes in science impede supportive environments for women. Research suggests that women's perceptions of these environments are influenced by stereotype threat (ST): anxiety faced in situations where one may be evaluated using negative stereotypes. This study developed and tested ST metrics for first time use with junior faculty in academic medicine. METHODS: Under a 2012 National Institutes of Health Pathfinder Award, Stanford School of Medicine's Office of Diversity and Leadership, working with experienced clinicians, social scientists, and epidemiologists, developed and administered ST measures to a representative group of junior faculty. RESULTS: 174 School of Medicine junior faculty were recruited (62% women, 38% men; 75% assistant professors, 25% instructors; 50% white, 40% Asian, 10% underrepresented minority). Women reported greater susceptibility to ST than did men across all items including ST vulnerability (p < 0.001); rejection sensitivity (p = 0.001); gender identification (p < 0.001); perceptions of relative potential (p = 0.048); and, sense of belonging (p = 0.049). Results of career-related consequences of ST were more nuanced. Compared with men, women reported lower beliefs in advancement (p = 0.021); however, they had similar career interest and identification, felt just as connected to colleagues, and were equally likely to pursue careers outside academia (all p > 0.42). CONCLUSIONS: Innovative ST metrics can provide a more complete picture of academic medical center environments. While junior women faculty are susceptible to ST, they may not yet experience all of its consequences in their early careers. As such, ST metrics offer a tool for evaluating institutional initiatives to increase supportive environments for women in academic medicine.