Journal of the American Medical Directors Association最新文献

{"title":"Non-pharmacological Interventions to Promote Sleep in Nursing Home Residents","authors":"","doi":"10.1016/j.jamda.2025.105655","DOIUrl":"10.1016/j.jamda.2025.105655","url":null,"abstract":"","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 6","pages":"Article 105655"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144253703","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":"Palliative Care for a Resident with Chronic Wound","authors":"","doi":"10.1016/j.jamda.2025.105649","DOIUrl":"10.1016/j.jamda.2025.105649","url":null,"abstract":"","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 6","pages":"Article 105649"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254559","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":"Relationship Between Nursing Home Quality Rating and Pain in Dementia","authors":"","doi":"10.1016/j.jamda.2025.105678","DOIUrl":"10.1016/j.jamda.2025.105678","url":null,"abstract":"","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 6","pages":"Article 105678"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254738","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":"Improving Patient Care: A Transformative Outcomes Based Model","authors":"","doi":"10.1016/j.jamda.2025.105660","DOIUrl":"10.1016/j.jamda.2025.105660","url":null,"abstract":"","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 6","pages":"Article 105660"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254743","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":"Physician Health Counseling for Older Adults with Obesity in the United States, 2015-2019: An Analysis of Repeated Cross-Sectional Data","authors":"Joseph A. Ladapo MD, PhD ,&nbsp;Christopher R. D'Adamo PhD ,&nbsp;Stephen Anton PhD ,&nbsp;Amy J. Sheer MD, MPH ,&nbsp;Carla VandeWeerd PhD ,&nbsp;Kevin R. Vincent MD, PhD ,&nbsp;Soma Wali MD ,&nbsp;Heather K. Vincent PhD ,&nbsp;Todd M. Manini PhD","doi":"10.1016/j.jamda.2025.105628","DOIUrl":"10.1016/j.jamda.2025.105628","url":null,"abstract":"<div><h3>Objectives</h3><div>Obesity affects one-third of American adults aged ≥65 years. Despite the increasing uptake of prescription weight loss medications, physician provision of diet and exercise weight loss counseling and referrals benefits patients and improves health outcomes. To increase awareness about possible underuse of physician weight loss counseling and referrals, we used nationally representative data to examine their rates in older adults with obesity.</div></div><div><h3>Design</h3><div>Retrospective cross-sectional analysis of publicly available data from National Ambulatory Medical Care Survey from January 1, 2015, through December 31, 2019.</div></div><div><h3>Setting and Participants</h3><div>Adults aged ≥65 years with obesity, as defined by a body mass index (BMI) of 30 or higher.</div></div><div><h3>Methods</h3><div>Primary outcomes were prevalence of obesity diagnosis and type of physician behavioral counseling provided to older patients. Data were analyzed using Poisson regression.</div></div><div><h3>Results</h3><div>Between 2015 and 2019, American adults aged ≥65 years made approximately 301 million physician office visits annually, and height and weight data were available for BMI estimation in 65.2% of visits. Among these visits, 35.3% were for patients with BMI ≥30 and 29.4% had a diagnosis of obesity during the visit. The prevalence of health counseling for obesity was low and ranged from 7.9% for weight reduction counseling to 18.7% for diet counseling. In adjusted analyses, patients aged ≥75 years were less likely to receive weight reduction counseling than patients aged 65-74 years. Women were less likely to receive weight reduction counseling than men. Having a diagnosis of obesity and seeing a primary care physician were both associated with increased likelihood of receiving weight reduction, diet, and exercise counseling. Antiobesity medication was prescribed in &lt;1% of visits.</div></div><div><h3>Conclusions and Implications</h3><div>Despite a high prevalence of obesity among older adults in the United States, physicians underdiagnose these patients and often do not provide them with obesity-related health counseling. Substantial opportunities exist to improve the care of older adults with obesity who face an increased risk of obesity-related chronic disease and physical disability.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105628"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086452","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":"Screening/Diagnosing Sarcopenia with Machine Learning–Powered Risk Assessment: The SARCO X Study","authors":"Murat Kara MD ,&nbsp;Yasin Ceran PhD ,&nbsp;Pelin Analay MD ,&nbsp;Mahmud Fazıl Aksakal MD ,&nbsp;Mahmut Esad Durmuş MD ,&nbsp;Tülay Tiftik MD ,&nbsp;Beyzanur Çıtır MD ,&nbsp;Fatıma Edibe Şener MD ,&nbsp;Mehmet Emin Yılmaz MD ,&nbsp;Evrim Coşkun MD ,&nbsp;Zeliha Ünlü MD ,&nbsp;Pelin Yıldırım MD ,&nbsp;Eda Gürçay MD ,&nbsp;Orhan Güvener MD ,&nbsp;Hacer Doğan Varan MD ,&nbsp;Eda Çeker MD ,&nbsp;Esra Çataltepe MD ,&nbsp;Fatih Güngör MD ,&nbsp;Özden Özyemişci Taskiran MD ,&nbsp;Duygu Keler Külcü MD ,&nbsp;Levent Özçakar MD","doi":"10.1016/j.jamda.2025.105683","DOIUrl":"10.1016/j.jamda.2025.105683","url":null,"abstract":"<div><h3>Objectives</h3><div>Sarcopenia imposes significant morbidity and economic burden on health care systems, underscoring the critical need for early/effective screening and diagnosis. This study aimed to develop a machine learning (ML)-based algorithm to facilitate the screening/diagnosis of sarcopenia.</div></div><div><h3>Design</h3><div>A cross-sectional case-control study.</div></div><div><h3>Setting and Participants</h3><div>This multicenter study enrolled subjects aged ≥45 years.</div></div><div><h3>Methods</h3><div>Demographic data such as age, weight, height, education/exercise status, smoking, and comorbid diseases were obtained. Sarcopenia was diagnosed using the basic and ML-based algorithms, which incorporate low quadriceps muscle mass/thickness, combined with prolonged chair stand test (CST) duration and/or reduced hand grip strength (HGS).</div></div><div><h3>Results</h3><div>Of 5649 participants (1379 males, 24.4%), 1097 of them (19.4%) were sarcopenic. Using the ML-based model, significantly associated factors with sarcopenia were age, weight, height, education level, exercise status, and presence of hypertension and diabetes mellitus. Of the various ML models, the Gradient Boosting Classifier (GBC) demonstrated the highest performance in predicting sarcopenia in the holdout test data. For the ML-augmented algorithm, the recall value was 0.979; the precision value was 0.926, and the accuracy value was 0.980 for making the diagnosis of sarcopenia. When compared with the basic sarcopenia algorithm, the ML-augmented algorithm further decreased the need for HGS and ultrasound by 38.1% and 49.5%, respectively, demonstrating its effectiveness in optimizing sarcopenia diagnosis while minimizing testing required for medical device(s).</div></div><div><h3>Conclusions and Implications</h3><div>The ML-based algorithm significantly reduces the need for testing/imaging in the diagnosis of sarcopenia. It facilitates the identification of sarcopenia particularly in the primary and secondary care settings and decreases the number of individuals who should be referred for further evaluation.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105683"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094177","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":"Feasibility of Novel Opioid Assessment Tool for Rehabilitation Patients in a Skilled Nursing Facility","authors":"Nisha Mathur MD ,&nbsp;Hollis D. Day MD, MS, MHPE ,&nbsp;Rossana Lau-Ng MD, MBA, CMD","doi":"10.1016/j.jamda.2025.105679","DOIUrl":"10.1016/j.jamda.2025.105679","url":null,"abstract":"<div><h3>Objectives</h3><div>A uniform standardized assessment of opioid treatment does not exist to guide management decisions for patients in skilled nursing facilities (SNFs). The purpose of this study is to determine if (1) a novel opioid assessment tool can be feasibly used to support clinician decision-making in opioid management for patients in rehabilitation, and (2) if this tool can address the existing gaps in care to pain management in SNFs.</div></div><div><h3>Design</h3><div>This qualitative study thematically analyzed anonymous interview responses from SNF providers.</div></div><div><h3>Setting and Participants</h3><div>SNF providers and nursing staff from SNFs in 1 hospital system participated in structured interviews.</div></div><div><h3>Methods</h3><div>The Pain Assessment and Documentation Tool, validated to evaluate opioid therapy and its impact on function over time in the outpatient setting, was modified to assess opioid treatment in SNFs. SNF providers were invited to participate in anonymous interviews regarding the tool's use and feasibility. Interview transcripts were analyzed using NVivo data analysis software to generate themes to determine the most significant takeaways.</div></div><div><h3>Results</h3><div>Twenty providers were interviewed and found that the tool was feasible for use in SNFs to improve clinical decision-making. Assessing patient's activities of daily living and opioid misuse risk were the most positively regarded metrics of the tool. The tool was found to provide standardization and specificity for management decisions, address the current gap in standardization and communication between providers, and improve existing variability in treatment of patients with substance use disorder and cognitive impairment. The barriers to implementation include that the tool is too redundant and can contribute to worsening staff burden.</div></div><div><h3>Conclusions and Implications</h3><div>This study found that this novel tool of opioid management is feasible in SNFs, and that it standardizes opioid management, improves provider communication, and reduces variability in treating patients with substance use disorder.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105679"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094074","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":"Which Enhanced Influenza Vaccine Has the Greatest Immunogenicity in Long-Term Care Residents: The Adjuvanted or the High-Dose Formulation?","authors":"Elise M. Didion PhD ,&nbsp;Joseph D. Kass BA ,&nbsp;Dennis J. Wilk BA ,&nbsp;Emily Buss MA ,&nbsp;Sarah-Michelle Frischmann PhD ,&nbsp;Sabina Rubeck MPH ,&nbsp;Richard Banks BA ,&nbsp;Brigid M. Wilson PhD ,&nbsp;Stefan Gravenstein MD, MPH ,&nbsp;David H. Canaday MD","doi":"10.1016/j.jamda.2025.105625","DOIUrl":"10.1016/j.jamda.2025.105625","url":null,"abstract":"<div><h3>Objectives</h3><div>This study compares enhanced influenza vaccines recommended for older adults, adjuvanted flu vaccine (aTIV, FLUAD) vs high-dose flu vaccine (HD-IIV3, FLUZONE HD) to determine if they met noninferiority standards for older long-term care facility (LTCF) residents.</div></div><div><h3>Design</h3><div>A phase 4, randomized, active-controlled, noninferiority trial on influenza vaccine immunogenicity conducted over 2 influenza seasons (2018-2019 and 2019-2020) (NCT03694808).</div></div><div><h3>Setting and Participants</h3><div>Residents of LTCFs aged ≥65 years.</div></div><div><h3>Methods</h3><div>Participants were randomized 1:1 to receive either aTIV or HD-IIV3 using computer-generated randomization. Only laboratory personnel were blinded. Hemagglutination inhibition (HAI) and neuraminidase inhibition (NI) assays measured antibody responses at baseline and 28 days postvaccination. The primary outcome compared the geometric mean titers (GMTs) at day 28. Secondary outcomes included seroconversion rates and NI titers.</div></div><div><h3>Results</h3><div>We randomized 387 LTCF residents to receive either aTIV (n = 194) or HD-IIV3 (n = 193) over 2 flu seasons. We observed noninferior HAI levels at postvaccination day 28 to A/H1N1 and A/H3N2 for aTIV and HD-IIV3 (GMT ratio, 1.03; 95% CI, 0.76-1.4; and GMT ratio, 1.04; 95% CI, 0.73-1.48, respectively), meeting noninferiority criteria with 95% CI upper bounds &lt;1.5. However, noninferiority criteria were not met for influenza B HAI levels (GMT ratio, 1.21; 95% CI, 0.91-1.61). Also, noninferiority criteria for HAI seroconversion were not met for any of the 3 strains. Applying the same noninferiority criteria to NI, both day 28 titer and seroconversion in aTIV were noninferior to HD-IIV3 for A/H1N1 and A/H3N2 strains.</div></div><div><h3>Conclusions and Implications</h3><div>Overall the anti-hemagglutinin and anti-neuraminidase titers demonstrate similarities between the vaccines and support them both being in the enhanced flu vaccine category preferentially recommended by the Centers for Disease Control and Prevention for people aged ≥65 years.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105625"},"PeriodicalIF":4.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078833","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 an Artificial Intelligence and Machine Learning Enhanced Electronic Health Record System on Quality Measures in Nursing Homes: A Difference-in-Differences Analysis","authors":"Meredith A. Barrett PhD ,&nbsp;Angier Allen MA ,&nbsp;Vy T. Vuong MPS ,&nbsp;Daniel Zhu MSc ,&nbsp;Allison J. Rainey MSN ,&nbsp;Will M. McConnell PhD, JD ,&nbsp;Abel N. Kho MD ,&nbsp;Annette Salisbury BS ,&nbsp;Dustin D. French PhD","doi":"10.1016/j.jamda.2025.105680","DOIUrl":"10.1016/j.jamda.2025.105680","url":null,"abstract":"<div><h3>Objectives</h3><div>This study evaluated the impact of an electronic health record (EHR) system enhanced with artificial intelligence and machine learning (EHR+AI) on quality measures in nursing homes in the United States.</div></div><div><h3>Design</h3><div>A difference-in-differences (DiD) design was used to estimate the effect of the EHR+AI intervention on quality measures among nursing homes with and without the AI intervention. The intervention included a feature that analyzed 150 daily clinical data elements per patient, alerting staff to changes in conditions, acuity, fall risk, and medication monitoring.</div></div><div><h3>Setting and Participants</h3><div>The analysis included 218 nursing homes, with 94 using EHR+AI and 124 using EHR only. Baseline differences in organizational characteristics, acuity index, neighborhood affluence, and racial or ethnic composition were evaluated.</div></div><div><h3>Methods</h3><div>Eighteen quality measures from the Centers for Medicare and Medicaid Services (CMS) were analyzed over 6 quarters before and 5 quarters after EHR+AI implementation. A DiD approach with linear mixed effects models was used, adjusting for significantly different baseline characteristics.</div></div><div><h3>Results</h3><div>Statistically greater improvements were observed in 16 of 18 quality measures (89%) in EHR+AI sites, with 11 measures (61%) also meeting the parallel trends assumption. Notably, EHR+AI sites demonstrated larger improvements in functional status, including greater reductions in major falls (−9%, 95% CI –17, −1; <em>P</em> = .034) and residents needing help with daily activities (−22%, 95% CI –29, −15; <em>P</em> &lt; .001), and a 5% larger increase in residents who made improvements in function (95% CI 2, 7; <em>P</em> = .001). Higher decline in depressive symptoms and the use of antipsychotic, antianxiety, or hypnotic medications were also noted. These results were observed among sites with higher patient acuity and neighborhood diversity.</div></div><div><h3>Conclusions and Implications</h3><div>These findings suggest that an EHR enhanced with AI can improve the quality and efficiency of care in nursing homes through real-time monitoring and response of resident assessment protocol triggers for clinical modification, but further research is needed.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105680"},"PeriodicalIF":4.2,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094077","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":"Lifting Federal Visitation Restriction and COVID-19 Infections in Nursing Homes","authors":"John R. Bowblis PhD ,&nbsp;Shuang Li PhD ,&nbsp;Yong-Fang Kuo PhD ,&nbsp;Jennifer Heston-Mullins PhD, LISW ,&nbsp;James S. Goodwin MD ,&nbsp;Huiwen Xu PhD","doi":"10.1016/j.jamda.2025.105682","DOIUrl":"10.1016/j.jamda.2025.105682","url":null,"abstract":"<div><h3>Objectives</h3><div>Early in the COVID-19 pandemic, the Centers for Medicare and Medicaid Services (CMS) recommended restricting visitors from entering nursing homes as a precaution. The restriction was lifted on September 17, 2020. This study examines whether COVID-19 infection rates among residents increased after the lifting of the federal restriction, providing indirect evidence on the impact of introducing visitation restrictions.</div></div><div><h3>Design</h3><div>We used a difference-in-differences event-study framework to compare changes in nursing home COVID-19 infection rates in the 4 weeks before (August 23, 2020–September 13, 2020) vs. 8 weeks after (October 4, 2020–November 22, 2020) the lifting of the federal visitation restriction.</div></div><div><h3>Setting and Participants</h3><div>The study cohort included 4823 nursing homes in the 19 treatment states that never had state-level visitation bans and 1654 nursing homes in the 8 control states that implemented state bans but lifted their bans by August 2020. The control group theoretically had the ability to allow visitation before the lifting of the federal restriction.</div></div><div><h3>Methods</h3><div>Our primary outcomes were weekly nursing home COVID-19 infection rates among residents and community-adjusted resident infection rates. The policy change was the lifting of federal visitation restriction on September 17, 2020. All analyses control for other facility characteristics that may impact COVID-19 spread in nursing homes.</div></div><div><h3>Results</h3><div>Nursing home infection rates closely mirrored the trend in community COVID-19 infections. Our regression analyses found no statistically significant increase in nursing home infection rates (ß = 2.4; 95% CI, −6.4 to 11.2) or the community-adjusted infection rates (ß = −5.2; 95% CI, −10.9 to 0.5) associated with the lifting of the federal restriction.</div></div><div><h3>Conclusions and Implications</h3><div>Lifting the federal visitation restriction had a negligible impact on nursing home infection rates. Policymakers and nursing home administrators should only consider implementing visitation restrictions under extreme circumstances.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"26 7","pages":"Article 105682"},"PeriodicalIF":4.2,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094175","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}