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As artificial intelligence grows in informing and guiding clinical care, the need to develop strategic workforce and implementation planning is paramount. In this commentary, the authors lay out opportunities and ways in which to meet this challenge. [ABSTRACT FROM AUTHOR]

Background: The impact of multimorbidity (≥ 2 chronic diseases) on the well-being of older adults is substantial but variable. The burden of multimorbidity varies by the number and kinds of conditions, and timing of onset. The impact varies by age, race, ethnicity, socioeconomic status, and health indicators. Large scale longitudinal surveys linked to medical claims provide unique opportunities to characterize this variability. Methods: We analyzed Medicare-linked Health and Retirement Study data for respondents 65 and older with 3 or more years of fee-for-service coverage (n = 17,199; 2000–2016). We applied standardized claims algorithms for operationalizing 21 chronic diseases. We compared multimorbidity levels, demographics, and outcomes at baseline and over time and escalation to high multimorbidity levels (≥ 5 conditions). Results: At baseline, 51.2% had no multimorbidity, 36.5% had multimorbidity, and 12.4% had high multimorbidity. Loss of function, cognitive decline, and higher healthcare utilization were up to ten times more prevalent in the high multimorbidity group. Greater rates of high multimorbidity were seen among non-Hispanic Black and Hispanic groups, those with lower wealth, younger birth cohorts, and adults with obesity. Rates of transition to high multimorbidity varied greatly and was highest among Hispanic and respondents with lower education. Conclusions: The development and progression of multimorbidity in old age is influenced by many factors. Higher levels of multimorbidity are associated with sociodemographic characteristics, suggesting possible mitigation strategies. [ABSTRACT FROM AUTHOR]

Background: Patients with opioid use disorder (OUD) experience various forms of stigma at the individual, public, and structural levels that can affect how they access and engage with healthcare, particularly with medications for OUD treatment. Telehealth is a relatively new form of care delivery for OUD treatment. As reducing stigma surrounding OUD treatment is critical to address ongoing gaps in care, the aim of this study was to explore how telehealth impacts patient experiences of stigma. Methods: In this qualitative study, we interviewed patients with OUD at a single urban academic medical center consisting of multiple primary care and addiction clinics in Oregon, USA. Participants were eligible if they had (1) at least one virtual visit for OUD between March 2020 and December 2021, and (2) a prescription for buprenorphine not exclusively used for chronic pain. We conducted phone interviews between October and December 2022, then recorded, transcribed, dual-coded, and analyzed using reflexive thematic analysis. Results: The mean age of participants (n = 30) was 40.5 years (range 20–63); 14 were women, 15 were men, and two were transgender, non-binary, or gender-diverse. Participants were 77% white, and 33% had experienced homelessness in the prior six months. We identified four themes regarding how telehealth for OUD treatment shaped patient perceptions of and experiences with stigma at the individual (1), public (2–3), and structural levels (4): (1) Telehealth offers wanted space and improved control over treatment setting; (2) Public stigma and privacy concerns can impact both telehealth and in-person encounters, depending on clinical and personal circumstances; (3) The social distance of telehealth could mitigate or exacerbate perceptions of clinician stigma, depending on both patient and clinician expectations; (4) The increased flexibility of telehealth translated to perceptions of increased clinician trust and respect. Conclusions: The forms of stigma experienced by individuals with OUD are complex and multifaceted, as are the ways in which those experiences interact with telehealth-based care. The mixed results of this study support policies allowing for a more individualized, patient-centered approach to care delivery that allows patients a choice over how they receive OUD treatment services. [ABSTRACT FROM AUTHOR]

Background The rapidly growing field of multimorbidity research demonstrates that changes in multimorbidity in mid- and late-life have far reaching effects on important person-centered outcomes, such as health-related quality of life. However, there are few organizing frameworks and comparatively little work weighing the merits and limitations of various quantitative methods applied to the longitudinal study of multimorbidity. Methods We identify and discuss methods aligned to specific research objectives with the goals of (i) establishing a common language for assessing longitudinal changes in multimorbidity, (ii) illuminating gaps in our knowledge regarding multimorbidity progression and critical periods of change, and (iii) informing research to identify groups that experience different rates and divergent etiological pathways of disease progression linked to deterioration in important health-related outcomes. Results We review practical issues in the measurement of multimorbidity, longitudinal analysis of health-related data, operationalizing change over time, and discuss methods that align with 4 general typologies for research objectives in the longitudinal study of multimorbidity: (i) examine individual change in multimorbidity, (ii) identify subgroups that follow similar trajectories of multimorbidity progression, (iii) understand when, how, and why individuals or groups shift to more advanced stages of multimorbidity, and (iv) examine the coprogression of multimorbidity with key health domains. Conclusions This work encourages a systematic approach to the quantitative study of change in multimorbidity and provides a valuable resource for researchers working to measure and minimize the deleterious effects of multimorbidity on aging populations. [ABSTRACT FROM AUTHOR]

Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials. The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM. Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis. Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13]). In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD. [ABSTRACT FROM AUTHOR]

The US health care delivery system does not systematically engage or support family or friend care partners. Meanwhile, the uptake and familiarity of portals to personal health information are increasing among patients. Technology innovations, such as shared access to the portal, use separate identity credentials to differentiate between patients and care partners. Although not well-known, or commonly used, shared access allows patients to identify who they do and do not want to be involved in their care. However, the processes for patients to grant shared access to portals are often limited or so onerous that interested patients and care partners often circumvent the process entirely. As a result, the vast majority of care partners resort to accessing portals using a patient's identity credentials-a "do-it-yourself" solution in conflict with a health systems' legal responsibility to protect patient privacy and autonomy. The personal narratives in this viewpoint (shared by permission) elaborate on quantitative studies and provide first-person snapshots of challenges faced by patients and families as they attempt to gain or grant shared access during crucial moments in their lives. As digital modalities increase patient roles in health care interactions, so does the importance of making shared access work for all stakeholders involved-patients, clinicians, and care partners. Electronic health record vendors must recognize that both patients and care partners are important users of their products, and health care organizations must acknowledge and support the critical contributions of care partners as distinct from patients., (©Liz Salmi, Danielle Peereboom, David A Dorr, Leilani R Graham, Jennifer L Wolff, Catherine M DesRoches. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.06.2024.)

With widespread electronic health record (EHR) adoption and improvements in health information interoperability in the United States, troves of data are available for knowledge discovery. Several data sharing programs and tools have been developed to support research activities, including efforts funded by the National Institutes of Health (NIH), EHR vendors, and other public- and private-sector entities. We surveyed 65 leading research institutions (77% response rate) about their use of and value derived from ten programs/tools, including NIH's Accrual to Clinical Trials, Epic Corporation's Cosmos, and the Observational Health Data Sciences and Informatics consortium. Most institutions participated in multiple programs/tools but reported relatively low usage (even when they participated, they frequently indicated that fewer than one individual/month benefitted from the platform to support research activities). Our findings suggest that investments in research data sharing have not yet achieved desired results., (©2023 AMIA - All rights reserved.)