Primary Care Opioid Taper Plans Are Associated with Sustained Opioid Dose Reduction

Reducing Central Nervous System-Active Medications to Prevent Falls and Injuries Among Older Adults: A Cluster Randomized Clinical Trial

Importance

High-risk medications that contribute to adverse health outcomes are frequently prescribed to older adults. Deprescribing interventions reduce their use, but studies are often not designed to examine effects on patient-relevant health outcomes.

Objective

To test the effect of a health system-embedded deprescribing intervention targeting older adults and their primary care clinicians for reducing the use of central nervous system-active drugs and preventing medically treated falls.

Design, Setting, and Participants

In this cluster randomized, parallel-group, clinical trial, 18 primary care practices from an integrated health care delivery system in Washington state were recruited from April 1, 2021, to June 16, 2022, to participate, along with their eligible patients. Randomization occurred at the clinic level. Patients were community-dwelling adults aged 60 years or older, prescribed at least 1 medication from any of 5 targeted medication classes (opioids, sedative-hypnotics, skeletal muscle relaxants, tricyclic antidepressants, and first-generation antihistamines) for at least 3 consecutive months.

Intervention

Patient education and clinician decision support. Control arm participants received usual care.

Main Outcomes and Measures

The primary outcome was medically treated falls. Secondary outcomes included medication discontinuation, sustained medication discontinuation, and dose reduction of any and each target medication. Serious adverse drug withdrawal events involving opioids or sedative-hypnotics were the main safety outcome. Analyses were conducted using intent-to-treat analysis.

Results

Among 2367 patient participants (mean [SD] age, 70.6 [7.6] years; 1488 women [63%]), the adjusted cumulative incidence rate of a first medically treated fall at 18 months was 0.33 (95% CI, 0.29-0.37) in the intervention group and 0.30 (95% CI, 0.27-0.34) in the usual care group (estimated adjusted hazard ratio, 1.11 (95% CI, 0.94-1.31) (P = .11). There were significant differences favoring the intervention group in discontinuation, sustained discontinuation, and dose reduction of tricyclic antidepressants at 6 months (discontinuation adjusted rate: intervention group, 0.23 [95% CI, 0.18-0.28] vs usual care group, 0.13 [95% CI, 0.09-0.17]; adjusted relative risk, 1.79 [95% CI, 1.29-2.50]; P = .001) and secondary time points (9, 12, and 15 months).

Conclusions and Relevance

In this randomized clinical trial of a health system-embedded deprescribing intervention targeting community-dwelling older adults prescribed central nervous system-active medications and their primary care clinicians, the intervention was no more effective than usual care in reducing medically treated falls. For health systems that attend to deprescribing as part of routine clinical practice, additional interventions may confer modest benefits on prescribing without a measurable effect on clinical outcomes.

Trial Registration

ClinicalTrials.gov Identifier: NCT05689554.

Impact of 30-day prescribed opioid dose trajectory on fatal overdose risk: A population-based, statewide cohort study

BACKGROUND

Both increases and decreases in patients' prescribed daily opioid dose have been linked to increased overdose risk, but associations between 30-day dose trajectories and subsequent overdose risk have not been systematically examined.

OBJECTIVE

To examine the associations between 30-day prescribed opioid dose trajectories and fatal opioid overdose risk during the subsequent 15 days.

DESIGN

Statewide cohort study using linked prescription drug monitoring program and death certificate data. We constructed a multivariable Cox proportional hazards model that accounted for time-varying prescription-, prescriber-, and pharmacy-level factors.

PARTICIPANTS

All patients prescribed an opioid analgesic in California from March to December, 2013 (5,326,392 patients).

MAIN MEASURES

Dependent variable: fatal drug overdose involving opioids. Primary independent variable: a 16-level variable denoting all possible opioid dose trajectories using the following categories for current and 30-day previously prescribed daily dose: 0-29, 30-59, 60-89, or ≥90 milligram morphine equivalents (MME).

KEY RESULTS

Relative to patients prescribed a stable daily dose of 0-29 MME, large (≥2 categories) dose increases and having a previous or current dose ≥60 MME per day were associated with significantly greater 15-day overdose risk. Patients whose dose decreased from ≥90 to 0-29 MME per day had significantly greater overdose risk compared to both patients prescribed a stable daily dose of ≥90 MME (aHR 3.56, 95%CI 2.24-5.67) and to patients prescribed a stable daily dose of 0-29 MME (aHR 7.87, 95%CI 5.49-11.28). Patients prescribed benzodiazepines also had significantly greater overdose risk; being prescribed Z-drugs, carisoprodol, or psychostimulants was not associated with overdose risk.

CONCLUSIONS

Large (≥2 categories) 30-day dose increases and decreases were both associated with increased risk of fatal opioid overdose, particularly for patients taking ≥90 MME whose opioids were abruptly stopped. Results align with 2022 CDC guidelines that urge caution when reducing opioid doses for patients taking long-term opioid for chronic pain.

A health-system-embedded deprescribing intervention targeting patients and providers to prevent falls in older adults (STOP-FALLS trial): study protocol for a pragmatic cluster-randomized controlled trial

BACKGROUND

Central nervous system (CNS) active medications have been consistently linked to falls in older people. However, few randomized trials have evaluated whether CNS-active medication reduction reduces falls and fall-related injuries. The objective of the Reducing CNS-active Medications to Prevent Falls and Injuries in Older Adults (STOP-FALLS) trial is to test the effectiveness of a health-system-embedded deprescribing intervention focused on CNS-active medications on the incidence of medically treated falls among community-dwelling older adults.

METHODS

We will conduct a pragmatic, cluster-randomized, parallel-group, controlled clinical trial within Kaiser Permanente Washington to test the effectiveness of a 12-month deprescribing intervention consisting of (1) an educational brochure and self-care handouts mailed to older adults prescribed one or more CNS-active medications (aged 60 + : opioids, benzodiazepines and Z-drugs; aged 65 + : skeletal muscle relaxants, tricyclic antidepressants, and antihistamines) and (2) decision support for their primary health care providers. Outcomes are examined over 18-26 months post-intervention. The primary outcome is first incident (post-baseline) medically treated fall as determined from health plan data. Our sample size calculations ensure at least 80% power to detect a 20% reduction in the rate of medically treated falls for participants receiving care within the intervention (n = 9) versus usual care clinics (n = 9) assuming 18 months of follow-up. Secondary outcomes include medication discontinuation or dose reduction of any target medications. Safety outcomes include serious adverse drug withdrawal events, unintentional overdose, and death. We will also examine medication signetur fields for attempts to decrease medications. We will report factors affecting implementation of the intervention.

DISCUSSION

The STOP-FALLS trial will provide new information about whether a health-system-embedded deprescribing intervention that targets older participants and their primary care providers reduces medically treated falls and CNS-active medication use. Insights into factors affecting implementation will inform future research and healthcare organizations that may be interested in replicating the intervention.

TRIAL REGISTRATION

ClinicalTrial.gov NCT05689554. Registered on 18 January 2023, retrospectively registered.

Recommended practices and ethical considerations for natural language processing-assisted observational research: A scoping review

An increasing number of studies have reported using natural language processing (NLP) to assist observational research by extracting clinical information from electronic health records (EHRs). Currently, no standardized reporting guidelines for NLP-assisted observational studies exist. The absence of detailed reporting guidelines may create ambiguity in the use of NLP-derived content, knowledge gaps in the current research reporting practices, and reproducibility challenges. To address these issues, we conducted a scoping review of NLP-assisted observational clinical studies and examined their reporting practices, focusing on NLP methodology and evaluation. Through our investigation, we discovered a high variation regarding the reporting practices, such as inconsistent use of references for measurement studies, variation in the reporting location (reference, appendix, and manuscript), and different granularity of NLP methodology and evaluation details. To promote the wide adoption and utilization of NLP solutions in clinical research, we outline several perspectives that align with the six principles released by the World Health Organization (WHO) that guide the ethical use of artificial intelligence for health.

Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.

Deprescribing intervention activities mapped to guiding principles for use in general practice: a scoping review

OBJECTIVE

To identify and characterise activities for deprescribing used in general practice and to map the identified activities to pioneering principles of deprescribing.

SETTING

Primary care.

DATA SOURCES

Medline, EMBASE (Ovid), CINAHL, Australian New Zealand Clinical Trials Registry (ANZCTR), Clinicaltrials.gov, ISRCTN registry, OpenGrey, Annals of Family Medicine, BMC Family Practice, Family Practice and British Journal of General Practice (BJGP) from inception to the end of June 2021.

STUDY SELECTION

Included studies were original research (randomised controlled trial, quasi-experimental, cohort study, qualitative and case studies), protocol papers and protocol registrations.

DATA EXTRACTION

Screening and data extraction was completed by one reviewer; 10% of the studies were independently reviewed by a second reviewer. Coding of full-text articles in NVivo was conducted and mapped to five deprescribing principles.

RESULTS

Fifty studies were included. The most frequently used activities were identification of appropriate patients for deprescribing (76%), patient education (50%), general practitioners (GP) education (48%), and development and use of a tapering schedule (38%). Six activities did not align with the five deprescribing principles. As such, two principles (engage practice staff in education and appropriate identification of patients, and provide feedback to staff about deprescribing occurrences within the practice) were added.

CONCLUSION

Activities and guiding principles for deprescribing should be paired together to provide an accessible and comprehensive guide to deprescribing by GPs. The addition of two principles suggests that practice staff and practice management teams may play an instrumental role in sustaining deprescribing processes within clinical practice. Future research is required to determine the most of effective activities to use within each principle and by whom.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co‐administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

Longitudinal Dose Trajectory Among Patients Tapering Long-Term Opioids

OBJECTIVE

To evaluate the dose trajectory of new opioid tapers and estimate the percentage of patients with sustained tapers at long-term follow-up.

DESIGN

Retrospective cohort study.

SETTING

Data from the OptumLabs Data Warehouse® which includes de-identified medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees, representing a diverse mixture of ages, ethnicities, and geographical regions across the United States.

SUBJECTS

Patients prescribed stable, higher-dose opioids for ≥12 months from 2008 to 2018.

METHODS

Tapering was defined as ≥15% relative reduction in average MME/day during any of six overlapping 60-day periods in the initial 7 months of follow-up after the period of stable baseline dosing. Average monthly dose was ascertained during consecutive 60-day periods up to 16 months of follow-up. Linear regression estimated the geometric mean relative dose by tapering status and follow-up duration. Poisson regression estimated the percentage of tapered patients with sustained dose reductions at follow-up and patient-level predictors of failing to sustain tapers.

RESULTS

The sample included 113,618 patients with 203,920 periods of stable baseline dosing (mean follow-up = 13.7 months). Tapering was initiated during 37,170 follow-up periods (18.2%). After taper initiation, patients had a substantial initial mean dose reduction (geometric mean relative dose .73 [95% CI: .72-.74]) that was sustained through 16 months of follow-up; at which point, 69.8% (95% CI: 69.1%-70.4%) of patients who initiated tapers had a relative dose reduction ≥15%, and 14.2% (95% CI: 13.7%-14.7%) had discontinued opioids. Failure to sustain tapers was significantly less likely among patients with overdose events during follow-up (adjusted incidence rate ratio [aIRR]: .56 [95% CI: .48-.67]) and during more recent years (aIRR: .93 per year after 2008 [95% CI: .92-.94]).

CONCLUSIONS

In an insured and Medicare Advantage population, over two-thirds of patients who initiated opioid dose tapering sustained long-term dose reductions, and the likelihood of sustaining tapers increased substantially from 2008 to 2018.