Care partners and consumer health information technology: A framework to guide systems-level initiatives in support of digital health equity.

Introduction: Consumer-oriented health information technologies (CHIT) such as the patient portal have a growing role in care delivery redesign initiatives such as the Learning Health System. Care partners commonly navigate CHIT demands alongside persons with complex health and social needs, but their role is not well specified. Methods: We assemble evidence and concepts from the literature describing interpersonal communication, relational coordination theory, and systems-thinking to develop an integrative framework describing the care partner's role in applied CHIT innovations. Our framework describes pathways through which systematic engagement of the care partner affects longitudinal work processes and multi-level outcomes relevant to Learning Health Systems. Results: Our framework is grounded in relational coordination, an emerging theory for understanding the dynamics of coordinating work that emphasizes role-based relationships and communication, and the Systems Engineering Initiative for Patient Safety (SEIPS) model. Cross-cutting work systems geared toward explicit and purposeful support of the care partner role through CHIT may advance work processes by promoting frequent, timely, accurate, problem-solving communication, reinforced by shared goals, shared knowledge, and mutual respect between patients, care partners, and care team. We further contend that systematic engagement of the care partner in longitudinal work processes exerts beneficial effects on care delivery experiences and efficiencies at both individual and organizational levels. We discuss the utility of our framework through the lens of an illustrative case study involving patient portal-mediated pre-visit agenda setting. Conclusions: Our framework can be used to guide applied embedded CHIT interventions that support the care partner role and bring value to Learning Health Systems through advancing digital health equity, improving user experiences, and driving efficiencies through improved coordination within complex work systems.

Emergency department visits and hospital readmissions after a deprescribing intervention among hospitalized older adults.

BACKGROUND: Deprescribing is the planned/supervised method of dose reduction or cessation of medications that might be harmful, or no longer be beneficial. Though benefits of deprescribing are debatable in improving clinical outcomes, it has been associated with decreased number of potentially inappropriate medications, which may potentially reduce the risk of adverse events among hospitalized older adults. With unclear evidence for deprescribing in this population, this study aimed to examine time-to-first unplanned healthcare utilization, which included 90-day emergency department (ED) visits or hospital readmission and associated predictors, during a deprescribing intervention. METHODS: A secondary data analysis of a clinical trial (Shed-MEDS NCT02979353) was performed. Cox regression was used to compare the time-to-first 90-day ED visit/readmission/death from hospital discharge for the intervention and control groups. Additionally, we performed exploratory analysis of predictors (comorbidities, functional health status, drug burden index (DBI), hospital length of stay, health literacy, food insecurity, and financial burden) associated with the time-to-first 90-day ED visit/readmission/death. RESULTS: The hazard of first 90-day ED visits/readmissions/death was 15% lower in the intervention versus the control group (95% CI: 0.61-1.19, p = 0.352, respectively); however, this difference was not statistically significant. For every additional number of comorbidities (Hazard ratio (HR): 1.12, 95% CI: 1.04-1.21) and each additional day of hospital length of stay (HR: 1.04, 95% CI: 1.01-1.07) were significantly associated with a higher hazard of 90-day ED visit/readmission/death in the intervention group; whereas for each unit of increase in pre-hospital DBI score (HR: 1.08 and HR 1.16, respectively) was significantly associated with a higher hazard of 90-day ED visit/readmission/death in the control group. CONCLUSIONS: The intervention and control groups had comparable time-to-first 90-day ED visit/readmission/death during a deprescribing intervention. This finding suggests that deprescribing did not result in a higher risk of ED visit/readmission/death during the 90-day period following hospital discharge.

Pharmacist-led telehealth deprescribing for people living with dementia and polypharmacy in primary care: A pilot study.

BACKGROUND: People living with dementia (PLWD) have complex medication regimens, exposing them to increased risk of harm. Pragmatic deprescribing strategies that align with patient-care partner goals are needed. METHODS: A pilot study of a pharmacist-led intervention to optimize medications with patient-care partner priorities, ran May 2021-2022 at two health systems. PLWD with ≥7 medications in primary care and a care partner were enrolled. After an introductory mailing, dyads were randomized to a pharmacist telehealth intervention immediately (intervention) or delayed by 3 months (control). Feasibility outcomes were enrollment, intervention completion, pharmacist time, and primary care provider (PCP) acceptance of recommendations. To refine pragmatic data collection protocols, we assessed the Medication Regimen Complexity Index (MRCI; primary efficacy outcome) and the Family Caregiver Medication Administration Hassles Scale (FCMAHS). RESULTS: 69 dyads enrolled; 27 of 34 (79%) randomized to intervention and 28 of 35 (80%) randomized to control completed the intervention. Most visits (93%) took more than 20 min and required multiple follow-up interactions (62%). PCPs responded to 82% of the pharmacists' first messages and agreed with 98% of recommendations. At 3 months, 22 (81%) patients in the intervention and 14 (50%) in the control had ≥1 medication discontinued; 21 (78%) and 12 (43%), respectively, had ≥1 new medication added. The mean number of medications decreased by 0.6 (3.4) in the intervention and 0.2 (1.7) in the control, reflecting a non-clinically meaningful 1.0 (±12.4) point reduction in the MRCI among intervention patients and a 1.2 (±12.9) point increase among control. FCMAHS scores decreased by 3.3 (±18.8) points in the intervention and 2.5 (±14.4) points in the control. CONCLUSION: Though complex, pharmacist-led telehealth deprescribing is feasible and may reduce medication burden in PLWD. To align with patient-care partner goals, pharmacists recommended deprescribing and prescribing. If scalable, such interventions may optimize goal-concordant care for PLWD.

Evaluating the Safety of an Educational Deprescribing Intervention: Lessons from the Optimize Trial.

BACKGROUND: Patients, family members, and clinicians express concerns about potential adverse drug withdrawal events (ADWEs) following medication discontinuation or fears of upsetting a stable medical equilibrium as key barriers to deprescribing. Currently, there are limited methods to pragmatically assess the safety of deprescribing and ascertain ADWEs. We report the methods and results of safety monitoring for the OPTIMIZE trial of deprescribing education for patients, family members, and clinicians. METHODS: This was a pragmatic cluster randomized trial with multivariable Poisson regression comparing outcome rates between study arms. We conducted clinical record review and adjudication of sampled records to assess potential causal relationships between medication discontinuation and outcomes. This study included adults aged 65+ with dementia or mild cognitive impairment, one or more additional chronic conditions, and prescribed 5+ chronic medications. The intervention included an educational brochure on deprescribing that was mailed to patients prior to primary care visits, a clinician notification about individual brochure mailings, and an educational tip sheets was provided monthly to primary care clinicians. The outcomes of the safety monitoring were rates of hospitalizations and mortality during the 4 months following brochure mailings and results of record review and adjudication. The adjudication process was conducted throughout the trial and included classifications: likely, possibly, and unlikely. RESULTS: There was a total of 3012 (1433 intervention and 1579 control) participants. There were 420 total hospitalizations involving 269 (18.8%) people in the intervention versus 517 total hospitalizations involving 317 (20.1%) people in the control groups. Adjusted risk ratios comparing intervention to control groups were 0.92 [95% confidence interval (CI) 0.72, 1.16] for hospitalization and 1.19 (95% CI 0.67, 2.11) for mortality. Both groups had zero deaths "likely" attributed to a medication change prior to the event. A total of 3 out of 30 (10%) intervention group hospitalizations and 7 out of 35 (20%) control group hospitalizations were considered "likely" due to a medication change. CONCLUSIONS: Population-based deprescribing education is safe in the older adult population with cognitive impairment in our study. Pragmatic methods for safety monitoring are needed to further inform deprescribing interventions. TRIAL REGISTRATION: NCT03984396. Registered on 13 June 2019.

Ethical Aspects of Physician Decision-Making for Deprescribing Among Older Adults With Dementia.

Importance: Physicians endorse deprescribing of risky or unnecessary medications for older adults (aged ≥65 years) with dementia, but there is a lack of information on what influences decisions to deprescribe in this population. Objective: To understand how physicians make decisions to deprescribe for older adults with moderate dementia and ethical and pragmatic concerns influencing those decisions. Design, Setting, and Participants: A cross-sectional national mailed survey study of a random sample of 3000 primary care physicians from the American Medical Association Physician Masterfile who care for older adults was conducted from January 15 to December 31, 2021. Main Outcomes and Measures: The study randomized participants to consider 2 clinical scenarios in which a physician may decide to deprescribe a medication for older adults with moderate dementia: 1 in which the medication could cause an adverse drug event if continued and the other in which there is no evidence of benefit. Participants ranked 9 factors related to possible ethical and pragmatic concerns through best-worst scaling methods (from greatest barrier to smallest barrier to deprescribing). Conditional logit regression quantified the relative importance for each factor as a barrier to deprescribing. Results: A total of 890 physicians (35.0%) returned surveys; 511 (57.4%) were male, and the mean (SD) years since graduation was 26.0 (11.7). Most physicians had a primary specialty in family practice (50.4% [449 of 890]) and internal medicine (43.5% [387 of 890]). A total of 689 surveys were sufficiently complete to analyze. In both clinical scenarios, the 2 greatest barriers to deprescribing were (1) the patient or family reporting symptomatic benefit from the medication (beneficence and autonomy) and (2) the medication having been prescribed by another physician (autonomy and nonmaleficence). The least influential factor was ease of paying for the medication (justice). Conclusions and Relevance: Findings from this national survey study of primary care physicians suggests that understanding ethical aspects of physician decision-making can inform clinician education about medication management and deprescribing decisions for older adults with moderate dementia.

Barriers and facilitators to deprescribing before surgery: A qualitative study of providers and older adults.

INTRODUCTION: Deprescribing, the collaborative process between providers and patients to streamline medication regimen, may reduce the risk of adverse events following surgery among older adults with multimorbidity. However, barriers and facilitators to deprescribing for surgery has not been explored. METHODS: We conducted a qualitative study of Primary Care Providers (PCP) and patients aged 65 and older who were scheduled for surgery. We used the Theoretical Domains Framework, which informed the interview guide and analysis. RESULTS: A total of 16 participants (n=8 providers, n=8 patients) were included. Themes were regarding: 1) attitudes towards deprescribing before surgery, 2) perceived benefits of deprescribing before surgery, 3) patient-provider relationship and shared decision-making, 4) hope for surgery, 5) barriers to deprescribing before surgery, and 6) preferences for deprescribing follow-up. CONCLUSION: Our study findings regarding provider- and patient-related barriers and facilitators for deprescribing and desired processes before surgery may inform future deprescribing intervention targets before surgery.

Use of the patient portal among older adults with diagnosed dementia and their care partners.

INTRODUCTION: Care partners are at the forefront of dementia care, yet little is known about patient portal use in the context of dementia diagnosis. METHODS: We conducted an observational cohort study of date/time-stamped patient portal use for a 5-year period (October 3, 2017-October 2, 2022) at an academic health system. The cohort consisted of 3170 patients ages 65+ with diagnosed dementia with 2+ visits within 24 months. Message authorship was determined by manual review of 970 threads involving 3065 messages for 279 patients. RESULTS: Most (71.20%) older adults with diagnosed dementia were registered portal users but far fewer (10.41%) had a registered care partner with shared access. Care partners authored most (612/970, 63.09%) message threads, overwhelmingly using patient identity credentials (271/279, 97.13%). DISCUSSION: The patient portal is used by persons with dementia and their care partners. Organizational efforts that facilitate shared access may benefit the support of persons with dementia and their care partners. Highlights Patient portal registration and use has been increasing among persons with diagnosed dementia. Two thirds of secure messages from portal accounts of patients with diagnosed dementia were identified as being authored by care partners, primarily using patient login credentials. Care partners who accessed the patient portal using their own identity credentials through shared access demonstrate similar levels of activity to patients without dementia. Organizational initiatives should recognize and support the needs of persons with dementia and their care partners by encouraging awareness, registration, and use of proper identity credentials, including shared, or proxy, portal access.

Catalyzing dementia care through the learning health system and consumer health information technology.

To advance care for persons with Alzheimer's disease and related dementias (ADRD), real-world health system effectiveness research must actively engage those affected to understand what works, for whom, in what setting, and for how long-an agenda central to learning health system (LHS) principles. This perspective discusses how emerging payment models, quality improvement initiatives, and population health strategies present opportunities to embed best practice principles of ADRD care within the LHS. We discuss how stakeholder engagement in an ADRD LHS when embedding, adapting, and refining prototypes can ensure that products are viable when implemented. Finally, we highlight the promise of consumer-oriented health information technologies in supporting persons living with ADRD and their care partners and delivering embedded ADRD interventions at scale. We aim to stimulate progress toward sustainable infrastructure paired with person- and family-facing innovations that catalyze broader transformation of ADRD care.

Willingness of older people living with dementia and mild cognitive impairment and their caregivers to have medications deprescribed.

BACKGROUND: people living with cognitive impairment commonly take multiple medications including potentially inappropriate medications (PIMs), which puts them at risk of medication related harms. AIMS: to explore willingness to have a medication deprescribed of older people living with cognitive impairment (dementia or mild cognitive impairment) and multiple chronic conditions and assess the relationship between willingness, patient characteristics and belief about medications. METHODS: cross-sectional study using results from the revised Patients' Attitudes Towards Deprescribing questionnaire (rPATDcog) collected as baseline data in the OPTIMIZE study, a pragmatic, cluster-randomised trial educating patients and clinicians about deprescribing. Eligible participants were 65+, diagnosed with dementia or mild cognitive impairment, and prescribed at least five-long-term medications. RESULTS: the questionnaire was mailed to 1,409 intervention patients and 553 (39%) were returned and included in analysis. Participants had a mean age of 80.1 (SD 7.4) and 52.4% were female. About 78.5% (431/549) of participants said that they would be willing to have one of their medications stopped if their doctor said it was possible. Willingness to deprescribe was negatively associated with getting stressed when changes are made and with previously having a bad experience with stopping a medication (P < 0.001 for both). CONCLUSION: most older people living with cognitive impairment are willing to deprescribe. Addressing previous bad experiences with stopping a medication and stress when changes are made to medications may be key points to discuss during deprescribing conversations.

Intervention design in cognitively impaired populations-Lessons learned from the OPTIMIZE deprescribing pragmatic trial.

BACKGROUND: Polypharmacy is common in older adults with cognitive impairment and multiple chronic conditions, increasing risks of adverse drug events, hospitalization, and death. Deprescribing, the process of reducing or stopping potentially inappropriate medications, may improve outcomes. The OPTIMIZE pragmatic trial examined whether educating and activating patients, family members and clinicians about deprescribing reduces number of chronic medications and potentially inappropriate medications. Acceptability and challenges of intervention delivery in cognitively impaired older adults are not well understood. METHODS: We explored mechanisms of intervention implementation through post hoc qualitative interviews and surveys with stakeholder groups of 15 patients, 7 caregivers, and 28 clinicians. We assessed the context in which the intervention was delivered, its implementation, and mechanisms of impact. RESULTS: Acceptance of the intervention was affected by contextual factors including cognition, prior knowledge of deprescribing, communication, and time constraints. All stakeholder groups endorsed the acceptability, importance, and delivery of the intervention. Positive mechanisms of impact included patients scheduling specific appointments to discuss deprescribing and providers being prompted to consider deprescribing. Recollection of intervention materials was inconsistent but most likely shortly after intervention delivery. Short visit times remained the largest provider barrier to deprescribing. CONCLUSIONS: Our work identifies key learnings in intervention delivery that can guide future scaling of deprescribing interventions in this population. We highlight the critical roles of timing and repetition in intervention delivery to cognitively impaired populations and the barrier posed by short consultation times. The acceptability of the intervention to patients and family members highlights the potential to incorporate deprescribing education into routine clinical practice and expand proven interventions to other vulnerable populations.

An Automated Strategy to Calculate Medication Regimen Complexity.

Understanding medication regimen complexity is important to understand what patients may benefit from pharmacist interventions. Medication Regimen Complexity Index (MRCI), a 65-item tool to quantify the complexity by incorporating the count, dosage form, frequency, and additional administration instructions of prescription medicines, provides a more nuanced way of assessing complexity. The goal of this study was to construct and validate a computational strategy to automate the calculation of MRCI. The performance of our strategy was evaluated by comparing our calculated MRCI values with gold-standard values, using correlation coefficients and population distributions. The results revealed satisfactory performance to calculate the sub-score of MRCI that includes dosage form and frequency (76 to 80% match with gold standard), and fair performance for sub-score related to additional direction (52% match with gold standard). Our automated strategy shows potential to help reduce the effort for manually calculating MRCI and highlights areas for future development efforts.

Association between willingness to deprescribe and health outcome priorities among U.S. older adults: Results of a national survey.

BACKGROUND: It is not known whether older adults' willingness to deprescribe is associated with their health outcome priorities related to medications. METHODS: A cross-sectional survey was conducted from March-April 2020 using a nationally representative online panel. The survey presented two vignettes: (1) a preventive medicine; and (2) a symptom-relief medicine. Participants were asked whether they would be willing to stop each medicine if their doctor recommended it, and to rate their level of agreement with two health outcome priorities statements: "I am willing to accept the risk of future side effects … to feel better now," and "I would prefer to take fewer medicines, even if … I may not live as long or may have bothersome symptoms sometimes." Ordinal logistic regression was used to examine associations between willingness to stop each medicine, baseline characteristics and health outcome priorities. RESULTS: Of 1193 panel members ≥65 years invited to participate, 835 (70%) completed the survey. Mean (SD) age was 73 years; 496 (59%) had taken a statin and 124 (15%) a prescription sedative-hypnotic. 507 (61%) were willing to stop preventive medicines; 276 (33%) were maybe willing. 419 (50%) were willing to stop symptom-relief medicines; 380 (46%) were maybe willing. Prioritizing fewer medicines was associated with higher odds of being willing to stop symptom-relief medicines (aOR 1.43 [95% CI 1.02-2.00]) and preventive medicines (aOR 1.52 [95% CI 1.05-2.18]). Prioritizing now over future was associated with lower odds of being willing to stop symptom-relief medicines (aOR 0.62 [95% CI 0.39-1.00]). Current/prior use of statins was associated with lower willingness to stop preventive medicines (aOR 0.66 [95% CI 0.48-0.91]). CONCLUSIONS: Older adults' health outcome priorities related to medication use are associated with their willingness to consider deprescribing. Future research should determine how best to elicit patients' health outcome priorities to facilitate goal-concordant decisions about medication use.

Prevalence of co-occurring serious illness diagnoses and association with health care utilization at the end of life.

INTRODUCTION: End-of-life care differs by serious illness diagnosis. Cancer and dementia are serious illnesses that have been associated with less intensive end-of-life health care use. It is not known how health care utilization varies in the presence of >1 serious illness. METHODS: We used the Rochester Epidemiology Project to identify persons living in a midwestern area who died on July 1, 2017-June 30, 2018 at age ≥65 years, and were seriously ill. We examined the number of emergency department (ED), hospital, and intensive care unit (ICU) stays in the last 6 months and the last 30 days of life. We used Poisson regression to determine the incidence rate ratio for ED, hospital, and ICU stay in the last 6 months and 30 days of life by number of serious illness diagnoses. For cancer and dementia, we examined the effect of an additional serious illness. RESULTS: We included a population of 1372 adults who were, on average, 84 years, 52% female, and 96% white. Approximately 41% had multiple serious illnesses. Compared to older adults with 1 serious illness diagnosis, rates of hospitalization, and ICU stay for adults with 2 or ≥3 serious illness diagnoses were at least 1.5 times higher in the last 6 months and the last 30 days of life. Rates of ED visits were significantly higher for older adults with 2 or ≥3 serious illness diagnoses in the last 6 months of life, but only higher for those with ≥3 versus 1 serious illness diagnosis in the last 30 days of life. For both cancer and dementia, rates of ED visits, hospitalization and ICU stay were lower for the condition alone than when an additional serious illness diagnosis was present. CONCLUSION: Having multiple serious illnesses increases the risk of health care utilization at the end of life.

Complexities of care: Common components of models of care in geriatrics.

As people age, they are more likely to have an increasing number of medical diagnoses and medications, as well as healthcare providers who care for those conditions. Health professionals caring for older adults understand that medical issues are not the sole factors in the phenomenon of this "care complexity." Socioeconomic, cognitive, functional, and organizational factors play a significant role. Care complexity also affects family caregivers, providers, and healthcare systems and therefore society at large. The American Geriatrics Society (AGS) created a work group to review care to identify the most common components of existing healthcare models that address care complexity in older adults. This article, a product of that work group, defines care complexity in older adults, reviews healthcare models and those most common components within them and identifies potential gaps that require attention to reduce the burden of care complexity in older adults.

Deprescribing Education vs Usual Care for Patients With Cognitive Impairment and Primary Care Clinicians: The OPTIMIZE Pragmatic Cluster Randomized Trial.

Background: Individuals with dementia or mild cognitive impairment frequently have multiple chronic conditions (defined as ≥2 chronic medical conditions) and take multiple medications, increasing their risk for adverse outcomes. Deprescribing (reducing or stopping medications for which potential harms outweigh potential benefits) may decrease their risk of adverse outcomes. Objective: To examine the effectiveness of increasing patient and clinician awareness about the potential to deprescribe unnecessary or risky medications among patients with dementia or mild cognitive impairment. Design, Setting, and Participants: This pragmatic, patient-centered, 12-month cluster randomized clinical trial was conducted from April 1, 2019, to March 31, 2020, at 18 primary care clinics in a not-for-profit integrated health care delivery system. The study included 3012 adults aged 65 years or older with dementia or mild cognitive impairment who had 1 or more additional chronic medical conditions and were taking 5 or more long-term medications. Interventions: An educational brochure and a questionnaire on attitudes toward deprescribing were mailed to patients prior to a primary care visit, clinicians were notified about the mailing, and deprescribing tip sheets were distributed to clinicians at monthly clinic meetings. Main Outcomes and Measures: The number of prescribed long-term medications and the percentage of individuals prescribed 1 or more potentially inappropriate medications (PIMs). Analysis was performed on an intention-to-treat basis. Results: This study comprised 1433 individuals (806 women [56.2%]; mean [SD] age, 80.1 [7.2] years) in 9 intervention clinics and 1579 individuals (874 women [55.4%]; mean [SD] age, 79.9 [7.5] years) in 9 control clinics who met the eligibility criteria. At baseline, both groups were prescribed a similar mean (SD) number of long-term medications (7.0 [2.1] in the intervention group and 7.0 [2.2] in the control group), and a similar proportion of individuals in both groups were taking 1 or more PIMs (437 of 1433 individuals [30.5%] in the intervention group and 467 of 1579 individuals [29.6%] in the control group). At 6 months, the adjusted mean number of long-term medications was similar in the intervention and control groups (6.4 [95% CI, 6.3-6.5] vs 6.5 [95% CI, 6.4-6.6]; P = .14). The estimated percentages of patients in the intervention and control groups taking 1 or more PIMs were similar (17.8% [95% CI, 15.4%-20.5%] vs 20.9% [95% CI, 18.4%-23.6%]; P = .08). In preplanned subgroup analyses, adjusted differences between the intervention and control groups were -0.16 (95% CI, -0.34 to 0.01) for individuals prescribed 7 or more long-term medications at baseline (n = 1434) and -0.03 (95% CI, -0.20 to 0.13) for those prescribed 5 to 6 medications (n = 1578) (P = .28 for interaction; P = .19 for subgroup interaction for PIMs). Conclusions and Relevance: This large-scale educational deprescribing intervention for older adults with cognitive impairment taking 5 or more long-term medications and their primary care clinicians demonstrated small effect sizes and did not significantly reduce the number of long-term medications and PIMs. Such interventions should target older adults taking relatively more medications. Trial Registration: ClinicalTrials.gov Identifier: NCT03984396.

Preoperative Deprescribing for Medical Optimization of Older Adults Undergoing Surgery: A Systematic Review.

OBJECTIVE: To summarize the evidence for preoperative deprescribing and its effect on postoperative outcomes in older adults undergoing surgery. DESIGN: Systematic review. SETTING AND PARTICIPANTS: All available studies. METHODS: We searched EMBASE, Cumulative Index of Nursing and Allied Health (CINAHL), and PubMed from inception to January 12, 2021. Settings included outpatient settings during the waiting period for surgery (ie, preoperative clinic) through to the preoperative period in the hospital. Participants who were older adults, aged ≥65 years, undergoing planned or emergency surgery with deprescribing or medication-related interventions were included for review. RESULTS: We identified 3 different methods of deprescribing intervention delivery during the preoperative period: geriatrician-led (n = 2), interdisciplinary team-led (n = 8), and pharmacist-led (n = 6). Outcomes were related to health care utilization, patient outcomes, and medication changes; however, results were difficult to compare because of heterogeneous outcomes within the topics. Overall, results were either positive or neutral. CONCLUSIONS AND IMPLICATIONS: The evidence for deprescribing during the preoperative period for older adults undergoing surgery is weak because of the heterogeneity of intervention delivery and outcomes, inclusion of nonoperative cases in some studies, and low power. This review highlights the need for future research, which may consider the following: (1) interdisciplinary approach, (2) coordination of deprescribing efforts with primary care provider from the waiting period for surgery up to after hospital discharge, and (3) validated deprescribing criteria such as STOPP/START that is easy to implement. It is important to note that results yielded positive and neutral results, not negative ones, which should reassure clinicians to implement deprescribing for older adults during the surgical period. Additionally, policy initiatives such as integrated electronic medical records or increased reimbursement of deprescribing efforts for primary care providers and/or hospitals should be pursued to prevent adverse postoperative events for this population.

Assessment of Patient-Preferred Language to Achieve Goal-Aligned Deprescribing in Older Adults.

Importance: How clinicians communicate about deprescribing, the structured process of reducing or stopping unnecessary, potentially harmful, or goal-discordant medicines, may be associated with the extent to which older adults are willing to do it. Objective: To examine older adults' preferences regarding different rationales a clinician may use to explain why a patient should stop an unnecessary or potentially harmful medication. Design, Setting, and Participants: This cross-sectional survey study was conducted from March 25 to April 19, 2020, among a nationally representative, probability-based online survey panel (KnowledgePanel). KnowledgePanel members aged 65 years and older were recruited by random digit dialing and address-based sampling. Data were analyzed from May 4 to July 8, 2020. Exposures: The survey presented 2 vignettes involving hypothetical older adults. One described a statin being used for primary prevention by a person with functional impairment and polypharmacy. The second described a sedative-hypnotic, such as zolpidem, being used for insomnia by a person with good functional status. Main Outcomes and Measures: After each vignette, participants expressed preferences using a best-worst scaling method for 7 different phrases a clinician may use to explain why they should reduce or stop the medication. Conditional logistic regression was used to quantify respondents' relative preferences. Results: A total of 1193 KnowledgePanel members were invited, and 835 respondents (70.0%) completed the survey. The mean (SD) age was 73 (6) years, 414 (49.6%) were women, and 671 (80.4%) self-identified as White individuals. A total of 496 respondents (59.8%) had ever used a statin, and 124 respondents (14.9%) had ever used a sedative-hypnotic. For both medications, the most preferred phrase to explain deprescribing focused on the risk of side effects. For statins, this phrase was 5.8-fold (95% CI, 5.3-6.3) more preferred than the least preferred option, which focused on the effort (treatment burden) involved in taking the medicine. For sedative-hypnotics, the phrase about side effects was 8.6-fold (95% CI, 7.9-9.5) more preferred over the least preferred option, "This medicine is unlikely to help you function better." Conclusions and Relevance: These findings suggest that among older adults, the most preferred rationale for deprescribing both preventive and symptom-relief medicines focused on the risk of side effects. These results could be used to inform clinical practice and improve effective communications around deprescribing in older adults.