Hina Faisal MD, Faisal N. Masud MD, Kim Junhyoung PhD, Kenneth Podell PhD, Jiaqiong Xu PhD, Christina Boncyk MD, MPH, George E. Taffet MD, Malaz A. Boustani MD, MPH
{"title":"Virtual reality-based cognitive exercise games in geriatric surgical patients: A pilot trial","authors":"Hina Faisal MD, Faisal N. Masud MD, Kim Junhyoung PhD, Kenneth Podell PhD, Jiaqiong Xu PhD, Christina Boncyk MD, MPH, George E. Taffet MD, Malaz A. Boustani MD, MPH","doi":"10.1111/jgs.19181","DOIUrl":"10.1111/jgs.19181","url":null,"abstract":"","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"293-296"},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142243","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}
Antoinette B. Coe PharmD, PhD, Tingting Zhang MD, PhD, Andrew R. Zullo PharmD, PhD, Lauren B. Gerlach DO, MS, Lori A. Daiello PharmD, ScM, Hiren Varma MS, Derrick Lo ScM, Richa Joshi MS, Julie P. W. Bynum MD, MPH, Theresa I. Shireman PhD
Background
Antipsychotic and other psychotropic medication use is prevalent among community-dwelling older adults with dementia despite the potential for adverse effects. Two Centers for Medicare & Medicaid Services (CMS) initiatives, the National Partnership to Improve Dementia Care (“the Partnership”) and the Five Star Quality Rating System for antipsychotic use reporting, have been successful in reducing antipsychotic use in nursing home residents. We assessed if these initiatives had a spillover effect in antipsychotic and other psychotropic medication use among community dwellers with dementia due to potential overlap in prescribers across settings.
Methods
Among community-dwelling older adults with dementia, we examined psychotropic medication class use (i.e., antipsychotics, antidepressants, anxiolytics, anticonvulsants/mood stabilizers, antidementia) in 2010–2017 Medicare fee-for-service claims using interrupted time series analyses across three periods (“Pre-Partnership”: July 1, 2010 to March 31, 2012; “Post-Partnership”: April 1, 2012 to January 31, 2015; “Five Star Quality Rating”: February 1, 2015 to December 31, 2017).
Results
We included 1,289,401 community dwellers with dementia contributing 26,609,697 person-months. The mean age was 80 years, most were female (70%), approximately 80% were non-Hispanic Whites, 10% were non-Hispanic Blacks, and 5% were Hispanic ethnicity. Antipsychotic use was declining pre-Partnership (β = −0.06, 95% CI: −0.08, −0.05) and post-Partnership (β = −0.02, 95% CI: −0.02, −0.01). Post-Five Star Quality Rating, antipsychotic use remained stable with a nearly flat slope (β = −0.01, 95% CI: −0.01, 0.00). Anticonvulsant and antidepressant use increased and anxiolytic and antidementia medication use decreased among community-dwelling older adults with dementia.
Conclusions
These two CMS policies on antipsychotic use for nursing home residents were not associated with a spillover effect to community-dwelling older adults with dementia. Strategies to monitor the appropriateness of psychotropic medication use may be warranted for community-dwellers with dementia.
{"title":"Association of nursing home antipsychotic reduction policies with antipsychotic use in community dwellers with dementia","authors":"Antoinette B. Coe PharmD, PhD, Tingting Zhang MD, PhD, Andrew R. Zullo PharmD, PhD, Lauren B. Gerlach DO, MS, Lori A. Daiello PharmD, ScM, Hiren Varma MS, Derrick Lo ScM, Richa Joshi MS, Julie P. W. Bynum MD, MPH, Theresa I. Shireman PhD","doi":"10.1111/jgs.19184","DOIUrl":"10.1111/jgs.19184","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Antipsychotic and other psychotropic medication use is prevalent among community-dwelling older adults with dementia despite the potential for adverse effects. Two Centers for Medicare & Medicaid Services (CMS) initiatives, the National Partnership to Improve Dementia Care (“the Partnership”) and the Five Star Quality Rating System for antipsychotic use reporting, have been successful in reducing antipsychotic use in nursing home residents. We assessed if these initiatives had a spillover effect in antipsychotic and other psychotropic medication use among community dwellers with dementia due to potential overlap in prescribers across settings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Among community-dwelling older adults with dementia, we examined psychotropic medication class use (i.e., antipsychotics, antidepressants, anxiolytics, anticonvulsants/mood stabilizers, antidementia) in 2010–2017 Medicare fee-for-service claims using interrupted time series analyses across three periods (“Pre-Partnership”: July 1, 2010 to March 31, 2012; “Post-Partnership”: April 1, 2012 to January 31, 2015; “Five Star Quality Rating”: February 1, 2015 to December 31, 2017).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We included 1,289,401 community dwellers with dementia contributing 26,609,697 person-months. The mean age was 80 years, most were female (70%), approximately 80% were non-Hispanic Whites, 10% were non-Hispanic Blacks, and 5% were Hispanic ethnicity. Antipsychotic use was declining pre-Partnership (<i>β</i> = −0.06, 95% CI: −0.08, −0.05) and post-Partnership (<i>β</i> = −0.02, 95% CI: −0.02, −0.01). Post-Five Star Quality Rating, antipsychotic use remained stable with a nearly flat slope (<i>β</i> = −0.01, 95% CI: −0.01, 0.00). Anticonvulsant and antidepressant use increased and anxiolytic and antidementia medication use decreased among community-dwelling older adults with dementia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These two CMS policies on antipsychotic use for nursing home residents were not associated with a spillover effect to community-dwelling older adults with dementia. Strategies to monitor the appropriateness of psychotropic medication use may be warranted for community-dwellers with dementia.</p>\u0000 </section>\u0000 </div>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"214-222"},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11734101/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Assessing the effectiveness of a health system intervention when randomized controlled trials (RCTs) are infeasible has long been a challenge for clinicians, health economists, and health service researchers alike. Difference-in-differences (DID) is a quasi-experimental study design that can be particularly appealing in addressing this challenge using observational data. Other nonexperimental study designs, such as regression adjustment or propensity score matching, attempt to examine the impact of an intervention by only accounting for the observed differences between groups. In contrast, an appropriately designed DID study aims to exploit randomness in intervention timing to identify the causal effects of the intervention. The number of published papers applying DID designs in the medical field has been increasing in recent years.<span><sup>1, 2</sup></span> Following this trend, the <i>Journal of the American Geriatrics Society</i> (JAGS) published 18 studies, mostly since 2018 (original data from the authors), that apply DID designs to examine a wide range of health system interventions that pertain to geriatrics care (Figure 1).</p><p>DID designs assess the effect of an intervention (e.g., health policy or program) applied to one or more groups (treated) by comparing their outcomes relative to a group that has never or not yet received the intervention (control) in terms of two differences.<span><sup>3, 4</sup></span> The first set of differences compares outcomes before and after the timing of the intervention for the treated and control groups, respectively. This process removes the observed and unobserved group-specific factors that do not change over time. Subtracting these differences (i.e., the second difference or difference-in-differences) removes the time-varying trends that are common to both groups. Together, DID identifies the causal effect of the intervention assuming that the treated would have experienced the same trend as the control group in the absence of the intervention (parallel trends).</p><p>In the recent issue of JAGS, a study by Burke and colleagues<span><sup>5</sup></span> used a DID design to evaluate changes in patient care outcomes following the Age-Friendly health systems recognition in the Veterans Health Administration. The authors incorporated recent advances in DID with staggered treatment timing developed by Sun and Abraham,<span><sup>6</sup></span> which is appropriate as the receipt of recognition across the medical sites happened at different times. This approach addresses potential biases in traditional DID estimation—often referred to as two-way fixed effects—when treatment effects are not constant over time and differ by late versus early treated sites.<span><sup>6-8</sup></span> Given the absence of an RCT in this setting, one of the notable strengths of this study stems from using observational data to measure the effect of recognition for implementing evidence-based care transformations (4Ms: wh
{"title":"Applying difference-in-differences design in quality improvement and health systems research","authors":"Yucheng Hou PhD, MPP, Abdelaziz Alsharawy PhD","doi":"10.1111/jgs.19180","DOIUrl":"10.1111/jgs.19180","url":null,"abstract":"<p>Assessing the effectiveness of a health system intervention when randomized controlled trials (RCTs) are infeasible has long been a challenge for clinicians, health economists, and health service researchers alike. Difference-in-differences (DID) is a quasi-experimental study design that can be particularly appealing in addressing this challenge using observational data. Other nonexperimental study designs, such as regression adjustment or propensity score matching, attempt to examine the impact of an intervention by only accounting for the observed differences between groups. In contrast, an appropriately designed DID study aims to exploit randomness in intervention timing to identify the causal effects of the intervention. The number of published papers applying DID designs in the medical field has been increasing in recent years.<span><sup>1, 2</sup></span> Following this trend, the <i>Journal of the American Geriatrics Society</i> (JAGS) published 18 studies, mostly since 2018 (original data from the authors), that apply DID designs to examine a wide range of health system interventions that pertain to geriatrics care (Figure 1).</p><p>DID designs assess the effect of an intervention (e.g., health policy or program) applied to one or more groups (treated) by comparing their outcomes relative to a group that has never or not yet received the intervention (control) in terms of two differences.<span><sup>3, 4</sup></span> The first set of differences compares outcomes before and after the timing of the intervention for the treated and control groups, respectively. This process removes the observed and unobserved group-specific factors that do not change over time. Subtracting these differences (i.e., the second difference or difference-in-differences) removes the time-varying trends that are common to both groups. Together, DID identifies the causal effect of the intervention assuming that the treated would have experienced the same trend as the control group in the absence of the intervention (parallel trends).</p><p>In the recent issue of JAGS, a study by Burke and colleagues<span><sup>5</sup></span> used a DID design to evaluate changes in patient care outcomes following the Age-Friendly health systems recognition in the Veterans Health Administration. The authors incorporated recent advances in DID with staggered treatment timing developed by Sun and Abraham,<span><sup>6</sup></span> which is appropriate as the receipt of recognition across the medical sites happened at different times. This approach addresses potential biases in traditional DID estimation—often referred to as two-way fixed effects—when treatment effects are not constant over time and differ by late versus early treated sites.<span><sup>6-8</sup></span> Given the absence of an RCT in this setting, one of the notable strengths of this study stems from using observational data to measure the effect of recognition for implementing evidence-based care transformations (4Ms: wh","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"8-11"},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.19180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jean-François Huon PharmD, PhD, Chiranjeev Sanyal PhD, Camille L. Gagnon PharmD, MSc, Justin P. Turner PhD, Ninh B. Khuong MSc, Émilie Bortolussi-Courval RN, PhD Student, Todd C. Lee MD, MPH, James L. Silvius MD, Steven G. Morgan PhD, Emily G. McDonald MD, MSc
Background
Potentially inappropriate medications (PIMs) are medications whereby the harms may outweigh the benefits for a given individual. Although overprescribed to older adults, their direct costs on the healthcare system are poorly described.
Methods
This was a cross-sectional study of the cost of PIMs for Canadians aged 65 and older, using adapted criteria from the American Geriatrics Society. We examined prescription claims information from the National Prescription Drug Utilization Information System in 2021 and compared these with 2013. The overall levels of inflation-adjusted total annual expenditure on PIMs, average cost per quarterly exposure, and average quarterly exposures to PIMs were calculated in CAD$.
Results
Exposure to most categories of PIMs decreased, aside from gabapentinoids, proton pump inhibitors, and antipsychotics, all of which increased. Canadians spent $1 billion on PIMs in 2021, a 33.6% reduction compared with 2013 ($1.5 billion). In 2021, the largest annual expenditures were on proton pump inhibitors ($211 million) and gabapentinoids ($126 million). The quarterly amount spent on PIMs per person exposed decreased from $95 to $57. In terms of mean cost per person, opioids and antipsychotics were highest ($138 and $118 per exposure). Some cost savings may have occurred secondary to an observed decline of 16.4% in the quarterly rate of exposure to PIMs (from 7301 per 10,000 in 2013 to 6106 per 10,000 in 2021).
Conclusions
While expenditures on PIMs have declined in Canada, the overall cost remains high. Prescribing of some seriously harmful classes of PIMs has increased and so directed, scalable interventions are needed.
{"title":"The cost of potentially inappropriate medications for older adults in Canada: A comparative cross-sectional study","authors":"Jean-François Huon PharmD, PhD, Chiranjeev Sanyal PhD, Camille L. Gagnon PharmD, MSc, Justin P. Turner PhD, Ninh B. Khuong MSc, Émilie Bortolussi-Courval RN, PhD Student, Todd C. Lee MD, MPH, James L. Silvius MD, Steven G. Morgan PhD, Emily G. McDonald MD, MSc","doi":"10.1111/jgs.19164","DOIUrl":"10.1111/jgs.19164","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Potentially inappropriate medications (PIMs) are medications whereby the harms may outweigh the benefits for a given individual. Although overprescribed to older adults, their direct costs on the healthcare system are poorly described.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This was a cross-sectional study of the cost of PIMs for Canadians aged 65 and older, using adapted criteria from the American Geriatrics Society. We examined prescription claims information from the National Prescription Drug Utilization Information System in 2021 and compared these with 2013. The overall levels of inflation-adjusted total annual expenditure on PIMs, average cost per quarterly exposure, and average quarterly exposures to PIMs were calculated in CAD$.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Exposure to most categories of PIMs decreased, aside from gabapentinoids, proton pump inhibitors, and antipsychotics, all of which increased. Canadians spent $1 billion on PIMs in 2021, a 33.6% reduction compared with 2013 ($1.5 billion). In 2021, the largest annual expenditures were on proton pump inhibitors ($211 million) and gabapentinoids ($126 million). The quarterly amount spent on PIMs per person exposed decreased from $95 to $57. In terms of mean cost per person, opioids and antipsychotics were highest ($138 and $118 per exposure). Some cost savings may have occurred secondary to an observed decline of 16.4% in the quarterly rate of exposure to PIMs (from 7301 per 10,000 in 2013 to 6106 per 10,000 in 2021).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>While expenditures on PIMs have declined in Canada, the overall cost remains high. Prescribing of some seriously harmful classes of PIMs has increased and so directed, scalable interventions are needed.</p>\u0000 </section>\u0000 </div>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"72 11","pages":"3530-3540"},"PeriodicalIF":4.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.19164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Todd C. Lee MD, MPH, FIDSA, Émilie Bortolussi-Courval RN, Lisa M. McCarthy PharmD, MSc, Emily G. McDonald MD, MSc
<p>A recent systematic review and meta-analysis of inpatient studies<span><sup>1</sup></span> found that medication reviews coupled with deprescribing interventions were associated with a small but significant reduction in rehospitalizations. The authors reported a hazard ratio (HR) of 0.92 (95% CI 0.85 to 0.99) derived from 19 randomized controlled trials (RCTs) and observational studies with outcomes measured between 1 and 12 months. That analysis provided much needed evidence in support of inpatient deprescribing initiatives. However, there are two key points for discussion. First, some important RCT data were not included by the search and selection strategy. Second, the inclusion of non-randomized data may increase bias. To increase the strength of the findings, we performed a sensitivity analysis restricted to RCTs and incorporated additional data.</p><p>The MedSafer Study<span><sup>2</sup></span> was an 11 center cluster RCT of deprescribing decision support paired with medication reconciliation versus medication reconciliation alone. The primary outcome was adverse drug events within 30 days post-discharge and a key secondary outcome was hospital readmission. A total of 5698 participants were enrolled with 4989 surviving to hospital discharge who were followed for readmission within 30-days.</p><p>Although the search strategy by Carollo et al. captured this study, it was subsequently excluded (reason not specified). We reanalyzed the 30-day hospital readmission data from the MedSafer Study using a time-to-event approach. Patient survival time was censored at 30 days, readmission to hospital, or death (whichever occurred first). Patients who were readmitted on the day of discharge were excluded (<i>n</i> = 14). In keeping with the trial's statistical analysis plan, we used a mixed-effects exponential proportional hazards regression model with adjustment for age, biological sex, the presence of moderate or severe frailty, residing in a nursing home at the time of admission, the number of potentially inappropriate medications at baseline, and the temporal period. Cluster was included as a random effect.</p><p>Carollo et al.<span><sup>1</sup></span> analyzed 10,136 RCT patients including duplicated control patients. Our updated analysis contained 14,201 unique patients including 4975 from McDonald et al. and 695 from Franchi et al.<span><sup>6</sup></span> (Figure 1). Though the effect size was more modest, deprescribing remained statistically associated with a reduced hazard of readmission at 1–3 months (HR 0.84; 95% CI 0.73 to 0.97). When all durations of follow-up were included, the probability that readmission was reduced remained high, but this was no longer statistically significant (HR 0.94; 95%CI 0.87 to 1.01).</p><p>A meta-analysis restricted to RCTs and adding 5670 unique patients of additional data added substantial credibility to the finding of a reduction in the hazard of short-term readmission from inpatient deprescribing interv
{"title":"Deprescribing is associated with reduced readmission to hospital: An updated meta-analysis of randomized controlled trials","authors":"Todd C. Lee MD, MPH, FIDSA, Émilie Bortolussi-Courval RN, Lisa M. McCarthy PharmD, MSc, Emily G. McDonald MD, MSc","doi":"10.1111/jgs.19166","DOIUrl":"10.1111/jgs.19166","url":null,"abstract":"<p>A recent systematic review and meta-analysis of inpatient studies<span><sup>1</sup></span> found that medication reviews coupled with deprescribing interventions were associated with a small but significant reduction in rehospitalizations. The authors reported a hazard ratio (HR) of 0.92 (95% CI 0.85 to 0.99) derived from 19 randomized controlled trials (RCTs) and observational studies with outcomes measured between 1 and 12 months. That analysis provided much needed evidence in support of inpatient deprescribing initiatives. However, there are two key points for discussion. First, some important RCT data were not included by the search and selection strategy. Second, the inclusion of non-randomized data may increase bias. To increase the strength of the findings, we performed a sensitivity analysis restricted to RCTs and incorporated additional data.</p><p>The MedSafer Study<span><sup>2</sup></span> was an 11 center cluster RCT of deprescribing decision support paired with medication reconciliation versus medication reconciliation alone. The primary outcome was adverse drug events within 30 days post-discharge and a key secondary outcome was hospital readmission. A total of 5698 participants were enrolled with 4989 surviving to hospital discharge who were followed for readmission within 30-days.</p><p>Although the search strategy by Carollo et al. captured this study, it was subsequently excluded (reason not specified). We reanalyzed the 30-day hospital readmission data from the MedSafer Study using a time-to-event approach. Patient survival time was censored at 30 days, readmission to hospital, or death (whichever occurred first). Patients who were readmitted on the day of discharge were excluded (<i>n</i> = 14). In keeping with the trial's statistical analysis plan, we used a mixed-effects exponential proportional hazards regression model with adjustment for age, biological sex, the presence of moderate or severe frailty, residing in a nursing home at the time of admission, the number of potentially inappropriate medications at baseline, and the temporal period. Cluster was included as a random effect.</p><p>Carollo et al.<span><sup>1</sup></span> analyzed 10,136 RCT patients including duplicated control patients. Our updated analysis contained 14,201 unique patients including 4975 from McDonald et al. and 695 from Franchi et al.<span><sup>6</sup></span> (Figure 1). Though the effect size was more modest, deprescribing remained statistically associated with a reduced hazard of readmission at 1–3 months (HR 0.84; 95% CI 0.73 to 0.97). When all durations of follow-up were included, the probability that readmission was reduced remained high, but this was no longer statistically significant (HR 0.94; 95%CI 0.87 to 1.01).</p><p>A meta-analysis restricted to RCTs and adding 5670 unique patients of additional data added substantial credibility to the finding of a reduction in the hazard of short-term readmission from inpatient deprescribing interv","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"302-305"},"PeriodicalIF":4.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.19166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>We would like to thank Lee and colleagues for their interest in our study.<span><sup>1</sup></span> In their Letter,<span><sup>2</sup></span> they raised two key points for discussion: (1) the lack of inclusion of some RCT data in the systematic review and the following meta-analysis; (2) the inclusion of data coming from nonrandomized studies. Accordingly, they conducted a sensitivity analysis on rehospitalization rates restricted to RCTs only, incorporating additional data from two RCTs.<span><sup>3, 4</sup></span></p><p>Concerning the first point, we did not include the MedSafer Study<span><sup>3</sup></span> in the meta-analysis because it did not meet our selection criteria. Specifically, we restricted inclusion criteria to older patients hospitalized in geriatric or internal medicine wards, while excluding those studies that evaluated specifically deprescribing in other specialized settings (e.g., cardiology wards, benzodiazepines deprescribing in psychiatric wards as well as general practice settings). In the Supplementary Material of the abovementioned Canadian study, it was reported that the study was carried out in medical units and, as such, we assumed that also wards other than geriatrics and internal medicine were included. Studies excluded for similar reasons are shown in Table 1. On the other hand, we did not include the study by Franchi et al.<span><sup>4</sup></span> as it did not explicitly report the number of events (e.g., rehospitalization), while Lee and colleagues included this study only based on estimates employing a Kaplan–Meier tails method.</p><p>The second raised issue is the inclusion of nonrandomized data in the meta-analysis. While Lee and colleagues indicated that we also included observational studies, we included only experimental and quasi-experimental studies,<span><sup>5</sup></span> in agreement with previously published meta-analyses.<span><sup>6</sup></span> We did not include observational prospective cohort studies.</p><p>We agree that meta-analyses of RCTs only may yield more robust results; however, we also decided to include quasi-experimental studies in our meta-analysis, as our risk of bias assessments of selected RCTs highlighted limitations concerning randomization and patient allocation. For instance, in the study conducted by Wehling et al.<span><sup>7</sup></span> the authors noted that the main reason for heterogeneity between control and intervention groups was related to randomization restrictions due to limited availability of beds in the included wards. Furthermore, we included only six quasi-experimental studies, which overall had a low weight in our meta-analysis.</p><p>Based on the considerations above, we further extended the sensitivity analysis conducted by Lee and colleagues by including quasi-experimental studies and reporting each study-specific estimate as a hazard ratio (HR), carefully re-evaluating reported estimates from the studies by Nielsen et al., Gallagher et al., and
{"title":"Reply to: Deprescribing is associated with reduced readmission to hospital: An updated meta-analysis of randomized controlled trials","authors":"Andrea Fontana MSc, Massimo Carollo MD, Salvatore Crisafulli MSc, Gianluca Trifirò PhD","doi":"10.1111/jgs.19169","DOIUrl":"10.1111/jgs.19169","url":null,"abstract":"<p>We would like to thank Lee and colleagues for their interest in our study.<span><sup>1</sup></span> In their Letter,<span><sup>2</sup></span> they raised two key points for discussion: (1) the lack of inclusion of some RCT data in the systematic review and the following meta-analysis; (2) the inclusion of data coming from nonrandomized studies. Accordingly, they conducted a sensitivity analysis on rehospitalization rates restricted to RCTs only, incorporating additional data from two RCTs.<span><sup>3, 4</sup></span></p><p>Concerning the first point, we did not include the MedSafer Study<span><sup>3</sup></span> in the meta-analysis because it did not meet our selection criteria. Specifically, we restricted inclusion criteria to older patients hospitalized in geriatric or internal medicine wards, while excluding those studies that evaluated specifically deprescribing in other specialized settings (e.g., cardiology wards, benzodiazepines deprescribing in psychiatric wards as well as general practice settings). In the Supplementary Material of the abovementioned Canadian study, it was reported that the study was carried out in medical units and, as such, we assumed that also wards other than geriatrics and internal medicine were included. Studies excluded for similar reasons are shown in Table 1. On the other hand, we did not include the study by Franchi et al.<span><sup>4</sup></span> as it did not explicitly report the number of events (e.g., rehospitalization), while Lee and colleagues included this study only based on estimates employing a Kaplan–Meier tails method.</p><p>The second raised issue is the inclusion of nonrandomized data in the meta-analysis. While Lee and colleagues indicated that we also included observational studies, we included only experimental and quasi-experimental studies,<span><sup>5</sup></span> in agreement with previously published meta-analyses.<span><sup>6</sup></span> We did not include observational prospective cohort studies.</p><p>We agree that meta-analyses of RCTs only may yield more robust results; however, we also decided to include quasi-experimental studies in our meta-analysis, as our risk of bias assessments of selected RCTs highlighted limitations concerning randomization and patient allocation. For instance, in the study conducted by Wehling et al.<span><sup>7</sup></span> the authors noted that the main reason for heterogeneity between control and intervention groups was related to randomization restrictions due to limited availability of beds in the included wards. Furthermore, we included only six quasi-experimental studies, which overall had a low weight in our meta-analysis.</p><p>Based on the considerations above, we further extended the sensitivity analysis conducted by Lee and colleagues by including quasi-experimental studies and reporting each study-specific estimate as a hazard ratio (HR), carefully re-evaluating reported estimates from the studies by Nielsen et al., Gallagher et al., and ","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"306-311"},"PeriodicalIF":4.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.19169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Medical director presence and time in U.S. nursing homes, 2017–2023","authors":"Eric L. Goldwein MPH, Richard J. Mollot JD, Mary Ellen Dellefield PhD, RN, Michael R. Wasserman MD, CMD, Charlene A. Harrington PhD, RN","doi":"10.1111/jgs.19161","DOIUrl":"10.1111/jgs.19161","url":null,"abstract":"<p>See related editorial by Zwahlen and Luxenberg in this issue.</p>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"73 1","pages":"29-38"},"PeriodicalIF":4.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121451","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":"Cover","authors":"Kathleen T. Unroe MD, MHA, MS, Debra Saliba MD, MPH, AGSF, Susan E. Hickman PhD, Sheryl Zimmerman PhD, Cari Levy MD, PhD, Jerry Gurwitz MD","doi":"10.1111/jgs.17869","DOIUrl":"https://doi.org/10.1111/jgs.17869","url":null,"abstract":"<p><b>Cover caption</b>: Key elements for successful nursing home clinical trials. See the related article by Unroe et al., pages 2951–2956.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"72 9","pages":"C1"},"PeriodicalIF":4.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jgs.17869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142123134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anand S. Iyer MD, MSPH, Rachel D. Wells PhD, MSN, RN, Avery C. Bechthold PhD, BSN, RN, Margaret Armstrong MSN, MEd, RN, Ronan O'Beirne EdD, Jun Y. Byun PhD, MSN, Jazmine Coffee-Dunning MA, Ed, J. Nicholas Odom PhD, RN, Russell G. Buhr MD, PhD, Angela O. Suen MD, Ashwin A. Kotwal MD, MS, Leah J. Witt MD, Cynthia J. Brown MD, MSPH, Mark T. Dransfield MD, Marie A. Bakitas DNSc, NP-C
<div> <section> <h3> Background</h3> <p>Identifying priority challenges of older adults with chronic obstructive pulmonary disease (COPD) is critical to designing interventions aimed at improving their well-being and independence.</p> </section> <section> <h3> Objective</h3> <p>To prioritize challenges of older adults with COPD and those who care for them to guide refinement of a telephonic nurse coach intervention for patients with COPD and their family caregivers (EPIC: <span>E</span>mpowering <span>P</span>eople to <span>I</span>ndependence in <span>C</span>OPD).</p> </section> <section> <h3> Design</h3> <p>Multiphase study guided by Baltes Theory of Successful Aging and the 5Ms Framework: <i>Phase 1</i>: Nominal group technique (NGT), a structured process of prioritizing responses to a question through group consensus. <i>Phase 2</i>: Rapid qualitative analysis. <i>Phase 3</i>: Intervention mapping and refinement.</p> </section> <section> <h3> Setting</h3> <p>Ambulatory, virtual.</p> </section> <section> <h3> Participants</h3> <p>Older adults with COPD, family caregivers, clinic staff (nurses, respiratory therapists), clinicians (physicians, nurse practitioners), and health system leaders.</p> </section> <section> <h3> Results</h3> <p>NGT sessions were conducted by constituency group with 37 participants (<i>n</i> = 7 patients, <i>n</i> = 6 family caregivers, <i>n</i> = 8 clinic staff, <i>n</i> = 9 clinicians, <i>n</i> = 7 health system leaders) (<i>Phase 1</i>). Participants generated 92 statements across five themes (<i>Phase 2</i>): (1) “Barriers to care”, (2) “Family caregiver needs”, (3) “Functional status and mobility issues”, (4) “Illness understanding”, and (5) “COPD care complexities”. Supplemental oxygen challenges emerged as a critical problem, and prioritized challenges differed by group. Patients and clinic staff prioritized “Functional status and mobility issues”, family caregivers prioritized “Family caregiver needs”, and clinicians and health system leaders prioritized “COPD care complexities”. Intervention mapping (<i>Phase 3</i>) guided EPIC refinement focused on meeting patient priorities of independence and mobility but accounting for all priorities.</p> </section> <section> <h3> Conclusions</h3> <p>Diverse constituency groups identified priority challenges for older adults with COPD. Functional status and mobility issues, particularly related to supplemental oxygen, e
{"title":"Identifying priority challenges of older adults with COPD: A multiphase intervention refinement study","authors":"Anand S. Iyer MD, MSPH, Rachel D. Wells PhD, MSN, RN, Avery C. Bechthold PhD, BSN, RN, Margaret Armstrong MSN, MEd, RN, Ronan O'Beirne EdD, Jun Y. Byun PhD, MSN, Jazmine Coffee-Dunning MA, Ed, J. Nicholas Odom PhD, RN, Russell G. Buhr MD, PhD, Angela O. Suen MD, Ashwin A. Kotwal MD, MS, Leah J. Witt MD, Cynthia J. Brown MD, MSPH, Mark T. Dransfield MD, Marie A. Bakitas DNSc, NP-C","doi":"10.1111/jgs.19158","DOIUrl":"10.1111/jgs.19158","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Identifying priority challenges of older adults with chronic obstructive pulmonary disease (COPD) is critical to designing interventions aimed at improving their well-being and independence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To prioritize challenges of older adults with COPD and those who care for them to guide refinement of a telephonic nurse coach intervention for patients with COPD and their family caregivers (EPIC: <span>E</span>mpowering <span>P</span>eople to <span>I</span>ndependence in <span>C</span>OPD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Multiphase study guided by Baltes Theory of Successful Aging and the 5Ms Framework: <i>Phase 1</i>: Nominal group technique (NGT), a structured process of prioritizing responses to a question through group consensus. <i>Phase 2</i>: Rapid qualitative analysis. <i>Phase 3</i>: Intervention mapping and refinement.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>Ambulatory, virtual.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants</h3>\u0000 \u0000 <p>Older adults with COPD, family caregivers, clinic staff (nurses, respiratory therapists), clinicians (physicians, nurse practitioners), and health system leaders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>NGT sessions were conducted by constituency group with 37 participants (<i>n</i> = 7 patients, <i>n</i> = 6 family caregivers, <i>n</i> = 8 clinic staff, <i>n</i> = 9 clinicians, <i>n</i> = 7 health system leaders) (<i>Phase 1</i>). Participants generated 92 statements across five themes (<i>Phase 2</i>): (1) “Barriers to care”, (2) “Family caregiver needs”, (3) “Functional status and mobility issues”, (4) “Illness understanding”, and (5) “COPD care complexities”. Supplemental oxygen challenges emerged as a critical problem, and prioritized challenges differed by group. Patients and clinic staff prioritized “Functional status and mobility issues”, family caregivers prioritized “Family caregiver needs”, and clinicians and health system leaders prioritized “COPD care complexities”. Intervention mapping (<i>Phase 3</i>) guided EPIC refinement focused on meeting patient priorities of independence and mobility but accounting for all priorities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Diverse constituency groups identified priority challenges for older adults with COPD. Functional status and mobility issues, particularly related to supplemental oxygen, e","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"72 11","pages":"3346-3359"},"PeriodicalIF":4.3,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142116613","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}
Sydney M. Dy MD, Daniel L. Scerpella MPH, Valecia Hanna MS, Kathryn A. Walker PharmD, Danetta H. Sloan PhD, Chase Mulholland Green MPH, Valerie Cotter PhD, Jennifer L. Wolff PhD, Erin Rand Giovannetti PhD, Maura McGuire MD, Naaz Hussain MD, Kelly M. Smith PhD, Martha Abshire Saylor PhD
Background
Primary care can be an important setting for communication and advance care planning (ACP), including for those with dementia and their families. The study objective was to explore experiences with a pragmatic trial of a communication and ACP intervention, SHARING Choices, in primary care for older adults with and without dementia.
Methods
We conducted qualitative interviews using tailored semi-structured guides with three groups: ACP facilitators who conducted the intervention; clinicians, managers, and administrators from sites randomized to the intervention; and patients and families who met with ACP facilitators. We used thematic analysis to identify and synthesize emergent themes based on key Consolidated Framework for Implementation Research concepts and Proctor's Implementation Outcomes, triangulating the three groups' perspectives.
Results
We identified five key themes. For acceptability, perceptions of the intervention were mostly positive, although some components were not generally implemented. For adoption, respondents perceived that ACP facilitators mainly focused on conducting ACP, although facilitators often did not implement the ADRD and family engagement aspects with the ACP. For relational connections, ACP facilitator—practice and clinician communication and engagement were key to how the intervention was implemented. For adaptability, ACP facilitators and health systems adapted how the ACP facilitation component was implemented to local preferences and over time, given the pragmatic nature of the trial. And, for sustainability, ACP facilitators and clinicians/managers/facilitators were positive that the intervention should be continued but noted barriers to its sustainability. Patients and families generally did not recall the intervention.
Conclusions
ACP facilitators and clinicians, managers, and administrators had positive perceptions of the ACP facilitator component of the intervention in this pragmatic trial with adaptation to local preferences. However, engaging those with dementia and families was more challenging in the implementation of this intervention.
{"title":"Qualitative evaluation of the SHARING Choices trial of primary care advance care planning for adults with and without dementia","authors":"Sydney M. Dy MD, Daniel L. Scerpella MPH, Valecia Hanna MS, Kathryn A. Walker PharmD, Danetta H. Sloan PhD, Chase Mulholland Green MPH, Valerie Cotter PhD, Jennifer L. Wolff PhD, Erin Rand Giovannetti PhD, Maura McGuire MD, Naaz Hussain MD, Kelly M. Smith PhD, Martha Abshire Saylor PhD","doi":"10.1111/jgs.19154","DOIUrl":"10.1111/jgs.19154","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Primary care can be an important setting for communication and advance care planning (ACP), including for those with dementia and their families. The study objective was to explore experiences with a pragmatic trial of a communication and ACP intervention, SHARING Choices, in primary care for older adults with and without dementia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method<b>s</b></h3>\u0000 \u0000 <p>We conducted qualitative interviews using tailored semi-structured guides with three groups: ACP facilitators who conducted the intervention; clinicians, managers, and administrators from sites randomized to the intervention; and patients and families who met with ACP facilitators. We used thematic analysis to identify and synthesize emergent themes based on key Consolidated Framework for Implementation Research concepts and Proctor's Implementation Outcomes, triangulating the three groups' perspectives.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified five key themes. For <i>acceptability</i>, perceptions of the intervention were mostly positive, although some components were not generally implemented. For <i>adoption</i>, respondents perceived that ACP facilitators mainly focused on conducting ACP, although facilitators often did not implement the ADRD and family engagement aspects with the ACP. For <i>relational connections</i>, ACP facilitator—practice and clinician communication and engagement were key to how the intervention was implemented. For <i>adaptability</i>, ACP facilitators and health systems adapted how the ACP facilitation component was implemented to local preferences and over time, given the pragmatic nature of the trial. And, for <i>sustainability</i>, ACP facilitators and clinicians/managers/facilitators were positive that the intervention should be continued but noted barriers to its sustainability. Patients and families generally did not recall the intervention.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>ACP facilitators and clinicians, managers, and administrators had positive perceptions of the ACP facilitator component of the intervention in this pragmatic trial with adaptation to local preferences. However, engaging those with dementia and families was more challenging in the implementation of this intervention.</p>\u0000 </section>\u0000 </div>","PeriodicalId":17240,"journal":{"name":"Journal of the American Geriatrics Society","volume":"72 11","pages":"3413-3426"},"PeriodicalIF":4.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142116618","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}
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