Journal of General Internal Medicine最新文献

{"title":"Central Nervous System-Active Medication Use in Older Adults With and Without Dementia-A Retrospective Cohort Study.","authors":"Nafisseh S Warner, Holly K Van Houten, Ericka E Tung, Brandon P Verdoorn, David O Warner, Michelle M Mielke, Molly M Jeffery","doi":"10.1007/s11606-025-09454-1","DOIUrl":"https://doi.org/10.1007/s11606-025-09454-1","url":null,"abstract":"<p><strong>Importance: </strong>Central nervous system (CNS)-active medication use is common in older adults; however, there are limited data on utilization trends over time, differences in utilization amongst those with and without dementia, and modification of utilization surrounding dementia diagnosis.</p><p><strong>Objective: </strong>To evaluate CNS-active medication trends in US older adults with and without dementia over 13 years, including evaluation of changes in utilization before and after dementia diagnosis.</p><p><strong>Design: </strong>Retrospective observational cohort study using de-identified administrative claims data.</p><p><strong>Participants: </strong>Older adult (age ≥ 65 years) commercial and Medicare Advantage enrollees with continuous medical and pharmacy coverage for at least one calendar year from 2010 through 2022.</p><p><strong>Main measures: </strong>(1) Annual probability of receiving CNS-active medications; (2) changes in medication use with dementia diagnosis.</p><p><strong>Key results: </strong>In total, 6,062,601 enrollees were included; 682,833 (11.3%) with dementia and 5,379,768 (88.7%) without. CNS-active medication use was highest in those with dementia throughout the study time period. Opioid utilization in those with and without dementia was 36.1% and 29.6% in 2010, decreasing to 24.3% and 22.2%, respectively, in 2022. Antidepressant use increased over time (i.e., 45.2 to 52.0% dementia; 15.8 to 24.6% without). Antipsychotic use in those with dementia was 18.1% in 2010, decreased to 15.9% in 2016, and increased back to 18.0% in 2022. A total of 444,587 enrollees experienced incident dementia diagnosis. There were immediate increases in antipsychotic (0.9% [0.5, 1.4] absolute increase, p < 0.001) and antidepressant (4.0% [3.3, 4.6] absolute increase, p < 0.001) use in the month following diagnosis. Increased use of these medications peaked 3-5 years after diagnosis. Dementia diagnosis was associated with decreased slopes of opioid (- 0.2% [- 0.3, - 0.1], p < 0.001) and benzodiazepine (- 0.07% [- 0.11, - 0.03], p < 0.001) use.</p><p><strong>Conclusions: </strong>CNS-active medication use is higher in older adults with dementia when compared to those without dementia. Incident dementia diagnosis is accompanied by marked increases in the use of antidepressants and antipsychotics.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of the Nudge Theory-Based Multifaceted Intervention on Reducing Inappropriate Proton Pump Inhibitors Use for Prophylaxis in Hospitalized Patients: A Non-Randomized Controlled Study.","authors":"Chun-Xing Li, Shuo Liang, Yin-Shi Xu, Si-Meng Gu, Chun-Xia Man, Xin-Ying Mao, Jia-Yi Li, Yu-Qiao Wang, Li-Chaoyue Sun, Yue Qiao, Gui-Bin Yang, Qing Xie, Ling-Yan Gao, Ju-Qi Zhang, Yue Wang, Hua Liu, Zhao Ren","doi":"10.1007/s11606-025-09460-3","DOIUrl":"https://doi.org/10.1007/s11606-025-09460-3","url":null,"abstract":"<p><strong>Background: </strong>Inappropriate use of proton pump inhibitors (PPIs) for prophylaxis among hospitalized patients continues to be a significant issue. Previous interventions have often been ineffective and lack evaluation of their longer-term impacts.</p><p><strong>Aim: </strong>This study aims to assess the clinical and economic effects of a nudge theory-based multifaceted intervention on reducing inappropriate PPI prophylaxis in hospitalized patients.</p><p><strong>Methods: </strong>This non-randomized controlled study was carried out in a teaching hospital's wards from January 2021 to June 2023, with a 12-month pre-intervention period, a 12-month intervention period (including the first and second stages of intervention), and a post-intervention period with 6-month follow-up. The intervention, based on nudge theory, was implemented among 114 doctors across 10 wards, sequentially involved peer comparison, information provision, and face-to-face feedback. The outcomes were assessed by randomly selecting cases of adult patients who received at least one PPI treatment during hospitalization, and the statistical analysis included univariate analysis, and multivariate and subgroup analyses.</p><p><strong>Results: </strong>The study included 1782 patients, with a median age of 61 years. During and after intervention, the rate of appropriate PPI use significantly increased by 2.83- to 5.47-fold, rising from 23.82% (147/617) to 46.96% (139/296) after the first stage, to 63.13% (202/320) after the second stage, and remained at 53.01% (291/549) later on. The rate of PPI injections decreased from 92.54 to 74.13-84.12%, the median defined daily doses from 16 to 7-12, and PPI-related expenditures from 484.80 to 156.00-262.99 CNY per-patient. The cost associated with inappropriate PPI use dropped from 161.60 to 0-45.58 CNY per-patient. Subgroup analyses supported these findings.</p><p><strong>Conclusion: </strong>A nudge theory-based multifaceted intervention led to increased appropriate PPI use, decreased PPI injections, and cost savings, with benefits lasting at least 6 months post-intervention.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expanding Patient-Centered Medical Home Teams in Primary Care: Qualitative Evaluation of Implementation Experiences from a Multi-site Pilot Within the VA Healthcare System.","authors":"Neetu Chawla, Michael McGowan, Eleni Skaperdas, Idamay Curtis, Alaina Mori, Susan Stockdale, Danielle Rose","doi":"10.1007/s11606-025-09438-1","DOIUrl":"https://doi.org/10.1007/s11606-025-09438-1","url":null,"abstract":"<p><strong>Background: </strong>More than a decade ago, the Veterans Health Administration (VA) implemented the Patient-Centered Medical Home (PCMH) model in primary care (PC) to improve healthcare access, care coordination, and patient outcomes. In 2021, VA's Office of Primary Care piloted three new PCMH models that aimed to improve provider efficiency and patient healthcare access by adding new team roles and increasing panel sizes.</p><p><strong>Objective: </strong>To describe frontline staff experiences and lessons learned during implementation of expanded PCMH team models.</p><p><strong>Design: </strong>Qualitative, semi-structured interviews of 25 frontline staff at 6 VA sites participating in the PCMH Modernization pilot conducted between March and August 2022.</p><p><strong>Participants: </strong>Interview participants included physicians, nurses, physical therapists, high-risk care managers, and other staff.</p><p><strong>Approach: </strong>We used a rapid analysis approach that included creating and validating interview summaries, developing a matrix of interview domains to identify common themes, and iterative discussion among the research team to build consensus and interpret findings.</p><p><strong>Key results: </strong>We found that when the basic PCMH structure and processes (e.g., staffing, huddling, pre-visit planning) were not in place, it was challenging to integrate new team members and to increase panel sizes. Role clarity challenges were also introduced by adding certain roles to PCMH teams. The physical therapist and high-risk care manager roles were seen as positive additions to PCMH models. Lastly, matching panel size expansion with staffing capacity was crucial to optimizing team efficiency while increasing patient healthcare access.</p><p><strong>Conclusions: </strong>Healthcare administrators considering expanding PCMH team models may need to thoroughly assess and address site readiness (e.g., adherence to foundational PCMH model, staffing, and practices) prior to implementation. Role clarity challenges should also be anticipated when adding new team roles. Physical therapists and high-risk care managers could be important contributions to existing PCMH models for offloading provider workload and improving population health management.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"More on Food as Medicine: Critical Need for Effective Interventions.","authors":"D Michael Elnicki, Lenny Lopez, Joseph Conigliaro","doi":"10.1007/s11606-025-09469-8","DOIUrl":"https://doi.org/10.1007/s11606-025-09469-8","url":null,"abstract":"","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143649173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing and Applying the BE-FAIR Equity Framework to a Population Health Predictive Model: A Retrospective Observational Cohort Study.","authors":"Reshma Gupta, Mayu Sasaki, Sandra L Taylor, Sili Fan, Jeffrey S Hoch, Yi Zhang, Matthew Crase, Dan Tancredi, Jason Y Adams, Hendry Ton","doi":"10.1007/s11606-025-09462-1","DOIUrl":"https://doi.org/10.1007/s11606-025-09462-1","url":null,"abstract":"<p><strong>Background: </strong>Population health programs rely on healthcare predictive models to allocate resources, yet models can perpetuate biases that exacerbate health disparities among marginalized communities.</p><p><strong>Objective: </strong>We developed the Bias-reduction and Equity Framework for Assessing, Implementing, and Redesigning (BE-FAIR) healthcare predictive models, an applied framework tested within a large health system using a population health predictive model, aiming to minimize bias and enhance equity.</p><p><strong>Design: </strong>Retrospective cohort study conducted at an academic medical center. Data collected from September 30, 2020, to October 1, 2022, were analyzed to assess bias resulting from model use.</p><p><strong>Participants: </strong>Primary care or payer-attributed patients at the medical center identified through electronic health records and claims data. Participants were stratified by race-ethnicity, gender, and social vulnerability defined by the Healthy Places Index (HPI).</p><p><strong>Intervention: </strong>BE-FAIR implementation involved steps such as an anti-racism lens application, de-siloed team structure, historical intervention review, disaggregated data analysis, and calibration evaluation.</p><p><strong>Main measures: </strong>The primary outcome was the calibration and discrimination of the model across different demographic groups, measured by logistic regression and area under the receiver operating characteristic curve (AUROC).</p><p><strong>Results: </strong>The study population consisted of 114,311 individuals with a mean age of 43.4 years (SD 24.0 years), 55.4% female, and 59.5% white/Caucasian. Calibration differed by race-ethnicity and HPI with significantly lower predicted probabilities of hospitalization for African Americans (0.129±0.051, p=0.016), Hispanics (0.133±0.047, p=0.004), AAPI (0.120±0.051, p=0.018), and multi-race (0.245±0.087, p=0.005) relative to white/Caucasians and for individuals in low HPI areas (0 - 25%, 0.178±0.042, p<0.001; 25 - 50%, 0.129±0.044, p=0.003). AUROC values varied among demographic groups.</p><p><strong>Conclusions: </strong>The BE-FAIR framework offers a practical approach to address bias in healthcare predictive models, guiding model development, and implementation. By identifying and mitigating biases, BE-FAIR enhances the fairness and equity of healthcare delivery, particularly for minoritized groups, paving the way for more inclusive and effective population health strategies.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of EHR-Integrated Secure Messaging Use with Clinician Workload and Attention Switching.","authors":"Daphne Lew, Laura R Baratta, Linlin Xia, Elise Eiden, Christine A Sinsky, Thomas Kannampallil, Sunny S Lou","doi":"10.1007/s11606-025-09466-x","DOIUrl":"https://doi.org/10.1007/s11606-025-09466-x","url":null,"abstract":"<p><strong>Background: </strong>Secure messaging use for clinician-to-clinician communication has grown rapidly in recent years.</p><p><strong>Objective: </strong>To examine the association between secure messaging use, electronic health record (EHR) time, and frequency of attention switching among clinicians primarily working in an inpatient setting.</p><p><strong>Design: </strong>Retrospective cohort study.</p><p><strong>Participants: </strong>Attending physicians, trainee physicians, and advanced practice providers who worked in an inpatient setting during a 3-month period (February-April, 2023) from 14 hospitals within a large midwestern health system.</p><p><strong>Main measures: </strong>Secure messaging use (i.e., Epic Secure Chat) was measured as the total number of messages sent or received between clinicians, aggregated at the clinician-day level. The primary outcomes were EHR time (a measure for workload) and the frequency of patient switching (a measure for cognitive burden) within the EHR. Linear mixed-effect models were used to examine the association between daily secure messaging volume and the primary outcomes, adjusting for age, gender, patient load, and correlations within clinicians and clinical service assignments.</p><p><strong>Key results: </strong>A total of 3996 clinicians (2174 [54%] female, median age 38 years [IQR 33, 48]) with 103,285 clinical work days, > 145 million audit log actions, and ~ 4.5 million secure messages were included. Median secure messaging volume was 9 (IQR 0, 51) messages per day, median EHR time was 250.5 min (IQR 140.3, 377.4) per day, and median number of patient switches was 79 (IQR 35, 147) per day. An increase in secure messaging volume from the 25th to 75th percentile was associated with a 25.5 min (95% CI 24.8, 26.2, p < 0.001) increase in EHR time and 18.1 (95% CI 17.6,18.6, p < 0.001) additional patient switches.</p><p><strong>Conclusions: </strong>Secure messaging use was associated with increased EHR time and frequency of attention switching. The results suggest that secure messaging use is associated with clinician work behaviors, potentially contributing to increased workload and cognitive burden.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical Students' Observations of High-Value Care in Clinical Training: Progress Rather than Perfection.","authors":"Richard M Wardrop, Abigail M Papé","doi":"10.1007/s11606-025-09468-9","DOIUrl":"https://doi.org/10.1007/s11606-025-09468-9","url":null,"abstract":"","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mrs. Helena's Big Heart.","authors":"Mariana Sousa de Pina Silva, Marcin Chwistek","doi":"10.1007/s11606-025-09447-0","DOIUrl":"https://doi.org/10.1007/s11606-025-09447-0","url":null,"abstract":"","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of COVID-19 on Trends in Physician Payments from Traditional Medicare from 2017-2021.","authors":"Xenia Mendez, Ulrike Muench, Corinne P Lewis, Taressa K Fraze","doi":"10.1007/s11606-024-08927-z","DOIUrl":"https://doi.org/10.1007/s11606-024-08927-z","url":null,"abstract":"","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143605165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The 2024 National Academies of Sciences, Engineering, and Medicine Long COVID Definition: What Clinicians Need to Know.","authors":"Lily Chu, Karyn Bishof, Abigail A Dumes, E Wesley Ely, Paule V Joseph, Andrea B Troxel","doi":"10.1007/s11606-025-09415-8","DOIUrl":"https://doi.org/10.1007/s11606-025-09415-8","url":null,"abstract":"<p><p>Millions of Americans affected by Long COVID (LC) report difficulty accessing care and support. One barrier is obtaining a diagnosis. In response, US federal agencies commissioned a National Academies of Sciences, Engineering, and Medicine (NASEM) committee to re-examine the existing federal definitions for LC. The Committee concluded that LC is \"an infection-associated chronic condition (IACC) occurring after SARS-CoV-2 infection that is present for at least 3 months as a continuous, relapsing and remitting, or progressive disease state that can present as singular or multiple symptoms and/or diagnosable conditions.\" The full report was released in June 2024. We briefly highlight features and aspects of the definition that may help clinicians identify those who remain undiagnosed and improve care for all LC patients.</p>","PeriodicalId":15860,"journal":{"name":"Journal of General Internal Medicine","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143597212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}