Harm and Medication-Type Impact Agreement with Hypothetical Deprescribing Recommendations: a Vignette-Based Experiment with Older Adults Across Four Countries

How Should Clinicians Discuss Deprescribing with Caregivers of Older Adults Living with Dementia? A Qualitative Study

BACKGROUND

Preventive medications are potential targets for deprescribing in older adults with dementia as goals of care change from preventive to palliative. Yet, prescribers lack communication guidance to address deprescribing.

OBJECTIVE

Using bisphosphonates as a case example, we sought to characterize and compare communication preferences of prescribers and family/informal caregivers regarding deprescribing.

METHODS

We conducted 23 semi-structured interviews with prescribers (12) and caregivers (11) of older adults with Alzheimer's disease or related dementias (ADRD). Prescribers and caregivers were asked to provide their impressions of seven conversation starters for discussing deprescribing, focusing on a case example using bisphosphonates. These phrases focused on topics including life expectancy, treatment burden, adverse effects, and costs. We used a qualitative framework analysis to identify relevant themes as prescribers and caregivers discussed their general perceptions of the potential benefits and harms of bisphosphonates and experiences with deprescribing.

RESULTS

Among prescribers, there were ten physicians and two nurse practitioners; most (nine) female and white. Among caregivers, eight were female, seven were white, and five were Latino/a. For both prescribers and caregivers, preferred conversation starters initiated a risk versus benefit discussion, emphasizing medication adverse effects and patient-specific factors, such as functional status and indication for treatment. While prescribers emphasized discussing common medication adverse effects, caregivers noted the importance of knowing a medication's potential impact on ADRD. The least preferred conversation starter for deprescribing among both groups focused on the extra effort and cost of continuing bisphosphonates. Discordance between caregivers and prescribers were identified in several phrases; notably, caregivers disliked statements that introduced discussions of prognosis and life expectancy.

CONCLUSIONS

Deprescribing conversations may be best perceived by caregivers when introduced with a discussion of a medication's adverse effects and potential impact on cognition. In addition, deprescribing conversations should be tailored to patient-specific factors, including functional status, goals of care, and the role of their caregiver in medical decision-making. Avoiding discussions of medication cost, pill burden, and life expectancy may help reassure the caregiver that deprescribing is a form of medication optimization and not a withdrawal of care.

Effects of warning information at medication initiation on deprescribing intentions in older adults: A hypothetical vignette

OBJECTIVES

To explore to what degree providing patients warning information about the long-term risks of a medication would affect their subsequent desire to discontinue it.

METHODS

We conducted a vignette-based online experiment in which participants aged ≥ 65 years from the United States were asked to imagine starting and subsequently stopping omeprazole. Participants were randomized to one of four vignettes about starting omeprazole (potential long-term harms or no harm information; OTC vs. prescription). Participants reported interest in stopping omeprazole on a 6-point Likert scale. We calculated descriptive statistics and used logistic regression to compare participants with high (scores 4-6) versus low agreement (scores 1-3) with stopping.

RESULTS

Participants (n = 1245) had a median age of 70 years. After adjusting for demographic characteristics, older adults who received warning information when starting the medication were more likely to agree to stop omeprazole (OR 1.21, 95 % C.I. 1.02, 1.43). Willingness to stop omeprazole was higher among women (vs. men), among respondents with higher literacy, and among those who had never or previously used PPIs (vs current use).

CONCLUSION

Warning information about potential long-term risks when initiating a medication may increase the likelihood of subsequently stopping a medication when recommended by a PCP.

Investigating Older Adults' Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey

BACKGROUND

Given the public release of large language models, research is needed to explore whether older adults would be receptive to personalized medication advice given by artificial intelligence (AI) tools.

OBJECTIVE

This study aims to identify predictors of the likelihood of older adults stopping a medication and the influence of the source of the information.

METHODS

We conducted a web-based experimental survey in which US participants aged ≥65 years were asked to report their likelihood of stopping a medication based on the source of information using a 6-point Likert scale (scale anchors: 1=not at all likely; 6=extremely likely). In total, 3 medications were presented in a randomized order: aspirin (risk of bleeding), ranitidine (cancer-causing chemical), or simvastatin (lack of benefit with age). In total, 5 sources of information were presented: primary care provider (PCP), pharmacist, AI that connects with the electronic health record (EHR) and provides advice to the PCP ("EHR-PCP"), AI with EHR access that directly provides advice ("EHR-Direct"), and AI that asks questions to provide advice ("Questions-Direct") directly. We calculated descriptive statistics to identify participants who were extremely likely (score 6) to stop the medication and used logistic regression to identify demographic predictors of being likely (scores 4-6) as opposed to unlikely (scores 1-3) to stop a medication.

RESULTS

Older adults (n=1245) reported being extremely likely to stop a medication based on a PCP's recommendation (n=748, 60.1% [aspirin] to n=858, 68.9% [ranitidine]) compared to a pharmacist (n=227, 18.2% [simvastatin] to n=361, 29% [ranitidine]). They were infrequently extremely likely to stop a medication when recommended by AI (EHR-PCP: n=182, 14.6% [aspirin] to n=289, 23.2% [ranitidine]; EHR-Direct: n=118, 9.5% [simvastatin] to n=212, 17% [ranitidine]; Questions-Direct: n=121, 9.7% [aspirin] to n=204, 16.4% [ranitidine]). In adjusted analyses, characteristics that increased the likelihood of following an AI recommendation included being Black or African American as compared to White (Questions-Direct: odds ratio [OR] 1.28, 95% CI 1.06-1.54 to EHR-PCP: OR 1.42, 95% CI 1.17-1.73), having higher self-reported health (EHR-PCP: OR 1.09, 95% CI 1.01-1.18 to EHR-Direct: OR 1.13 95%, CI 1.05-1.23), having higher confidence in using an EHR (Questions-Direct: OR 1.36, 95% CI 1.16-1.58 to EHR-PCP: OR 1.55, 95% CI 1.33-1.80), and having higher confidence using apps (EHR-Direct: OR 1.38, 95% CI 1.18-1.62 to EHR-PCP: OR 1.49, 95% CI 1.27-1.74). Older adults with higher health literacy were less likely to stop a medication when recommended by AI (EHR-PCP: OR 0.81, 95% CI 0.75-0.88 to EHR-Direct: OR 0.85, 95% CI 0.78-0.92).

CONCLUSIONS

Older adults have reservations about following an AI recommendation to stop a medication. However, individuals who are Black or African American, have higher self-reported health, or have higher confidence in using an EHR or apps may be receptive to AI-based medication recommendations.

Effect of Messaging on Support for Breast Cancer Screening Cessation Among Older US Women: A Randomized Clinical Trial

Importance

Many older women are screened for breast cancer beyond guideline-recommended thresholds. Messaging holds promise to reduce overscreening.

Objective

To investigate the effect of a message on older women's support for and intentions of stopping breast cancer screening.

Design, Setting, and Participants

A 2-wave randomized clinical online survey trial using a nationally representative online panel was performed from May 12 to June 19, 2023. Women 65 years or older without breast cancer were eligible to participate.

Intervention

A pilot-tested breast cancer screening cessation message delivered to a hypothetical older woman with serious illnesses and functional impairment. The message was described as from 1 of 3 sources (clinician, news story, or family member). Participants were randomized into 4 groups: no message (group 1 [control]), a single message from a clinician at wave 1 and no message at wave 2 (group 2), a message from a news story (wave 1) and a clinician (wave 2) (group 3), and a message from a family member (wave 1) and a clinician (wave 2) (group 4).

Main Outcomes and Measures

Support for stopping screening in the hypothetical older woman (primary) and screening intentions for oneself (secondary) were assessed on 7-point scales, with higher values indicating stronger support for and intentions to stop screening. Means were compared using analysis of variance. The message effect on screening intentions among participants 75 years or older and those with life expectancy of less than 10 years were also explored.

Results

A total of 3051 women participated in wave 1 of the trial. The mean (SD) age was 72.8 (5.9) years; 272 (8.9%) were non-Hispanic Black and 2506 (82.1%) were non-Hispanic White. Of these women, 2796 (91.6%) completed wave 2. Group 2 had significantly higher support for screening cessation in the hypothetical patient at wave 2 (mean score, 3.14 [95% CI, 2.99-3.29]) compared with group 1 (mean score, 2.68 [95% CI, 2.54-2.82]; P < .001). The effect was even stronger in group 3 (mean score, 4.23 [95% CI, 4.09-4.38]) and group 4 (mean score, 4.12 [95% CI, 3.97-4.27]) compared with both groups 1 and 2 (all P < .001). Message effects on self-screening intentions followed a similar pattern, with larger effects among participants 75 years or older or with limited life expectancy.

Conclusions and Relevance

In this randomized clinical trial, a breast cancer screening cessation message significantly increased older women's support for and intentions of screening cessation. The strongest effects were observed when the message was delivered over time from multiple sources. Future work needs to engage potential message sources to examine the feasibility and acceptability of multilevel messaging strategies and their effect on screening behavior.

Trial Registration

ClinicalTrials.gov Identifier: NCT05821023.

Factors Important to Older Adults Who Disagree With a Deprescribing Recommendation

Importance

Little is known about why older adults decline deprescribing recommendations, primarily because interventional studies rarely capture the reasons.

Objective

To examine factors important to older adults who disagree with a deprescribing recommendation given by a primary care physician to a hypothetical patient experiencing polypharmacy.

Design, Setting, and Participants

This online, vignette-based survey study was conducted from December 1, 2020, to March 31, 2021, with participants 65 years or older in the United Kingdom, the US, Australia, and the Netherlands. The primary outcome of the main study was disagreement with a deprescribing recommendation. A content analysis was subsequently conducted of the free-text reasons provided by participants who strongly disagreed or disagreed with deprescribing. Data were analyzed from August 22, 2022, to February 12, 2023.

Main Outcomes and Measures

Attitudes, beliefs, fears, and recommended actions of older adults in response to deprescribing recommendations.

Results

Of the 899 participants included in the analysis, the mean (SD) age was 71.5 (4.9) years; 456 participants (50.7%) were men. Attitudes, beliefs, and fears reported by participants included doubts about deprescribing (361 [40.2%]), valuing medications (139 [15.5%]), and a preference to avoid change (132 [14.7%]). Valuing medications was reported more commonly among participants who strongly disagreed compared with those who disagreed with deprescribing (48 of 205 [23.4%] vs 91 of 694 [13.1%], respectively; P < .001) or had personal experience with the same medication class as the vignette compared with no experience (93 of 517 [18.0%] vs 46 of 318 [12.1%], respectively; P = .02). Participants shared that improved communication (225 [25.0%]), alternative strategies (138 [15.4%]), and consideration of medication preferences (137 [15.2%]) may increase their agreement with deprescribing. Participants who disagreed compared with those who strongly disagreed were more interested in additional communication (196 [28.2%] vs 29 [14.2%], respectively; P < .001), alternative strategies (117 [16.9%] vs 21 [10.2%], respectively; P = .02), or consideration of medication preferences (122 [17.6%] vs 15 [7.3%], respectively; P < .001).

Conclusions and Relevance

In this survey study, older adults who disagreed with a deprescribing recommendation were more interested in additional communication, alternative strategies, or consideration of medication preferences compared with those who strongly disagreed. These findings suggest that identifying the degree of disagreement with deprescribing could be used to tailor patient-centered communication about deprescribing in older adults.