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.

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.

Opioid Dose Trajectories and Associations With Mortality, Opioid Use Disorder, Continued Opioid Therapy, and Health Plan Disenrollment.

Importance: Uncertainty remains about the longer-term benefits and harms of different opioid management strategies, such as tapering and dose escalation. For instance, opioid tapering could help patients reduce opioid exposure to prevent opioid use disorder, but patients may also seek care elsewhere and engage in nonprescribed opioid use. Objective: To evaluate the association between opioid dose trajectories observed in practice and patient outcomes. Design, Setting, and Participants: This retrospective cohort study was conducted in 3 health systems in Colorado and Wisconsin. The study population included patients receiving long-term opioid therapy between 50 and 200 morphine milligram equivalents between August 1, 2014, and July 31, 2017. Follow-up ended on December 31, 2019. Data were analyzed from January 2020 to August 2022. Exposures: Group-based trajectory modeling identified 5 dosing trajectories over 1 year: 1 decreasing, 1 high-dose increasing, and 3 stable. Main Outcomes and Measures: Primary outcomes assessed after the trajectory period were 1-year all-cause mortality, incident opioid use disorder, continued opioid therapy at 1 year, and health plan disenrollment. Associations were tested using Cox proportional hazards regression and log-binomial models, adjusting for baseline covariates. Results: A total of 3913 patients (mean [SD] age, 59.2 [14.4] years; 2767 White non-Hispanic [70.7%]; 2237 female patients [57.2%]) were included in the study. Compared with stable trajectories, the decreasing dose trajectory was negatively associated with opioid use disorder (adjusted hazard ratio [aHR], 0.40; 95% CI, 0.29-0.55) and continued opioid therapy (site 1: adjusted relative risk [aRR], 0.39; 95% CI, 0.34-0.44), but was positively associated with health plan disenrollment (aHR, 1.66; 95% CI, 1.24-2.22). The decreasing trajectory was not associated with mortality (aHR, 1.28; 95% CI, 0.87-1.86). In contrast, the high-dose increasing trajectory was positively associated with mortality (aHR, 2.19; 95% CI, 1.44-3.32) and opioid use disorder (aHR, 1.81; 95% CI, 1.39-2.37) but was not associated with disenrollment (aHR, 0.90; 95% CI, 0.56-1.42) or continued opioid therapy (site 1: aRR, 0.98; 95% CI, 0.94-1.03). Conclusions and Relevance: In this cohort study, decreasing opioid dose was associated with reduced risk of opioid use disorder and continued opioid therapy but increased risk of disenrollment compared with stable dosing, whereas the high-dose increasing trajectory was associated with an increased risk of mortality and opioid use disorder. These findings can inform opioid management decision-making.

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.

Transition to Virtual Asthma Care During the COVID-19 Pandemic: An Observational Study.

BACKGROUND: The COVID-19 pandemic increased reliance on virtual care for patients with persistent asthma. OBJECTIVE: This retrospective cohort study assessed changes from in-person to virtual care during the pandemic. In patients with persistent asthma, compared with the same period before the pandemic. METHODS: Kaiser Permanente Colorado members aged 18 to 99 years with persistent asthma were evaluated during two periods (March to October 2019 and March to October 2020). Comparison of asthma exacerbations (hospitalizations, emergency department visits, and courses of oral prednisone) and asthma medication metrics were evaluated between the two periods and by type of care received during the pandemic (no care, virtual care only, in-person care only, or a mix of virtual and in-person care). Population characteristics by type of care received during the pandemic were also evaluated. RESULTS: Among 7,805 adults with persistent asthma, those who used more virtual care or sought no care during the pandemic were younger and had fewer comorbidities, mental health diagnoses, or financial barriers. Exacerbations decreased (0.264 to 0.214; P <.001) as did courses of prednisone (0.213 to 0.169). Asthma medication adherence (0.53 to 0.54; P <.001) and the asthma medication ratio, a quality-of-care metric (0.755 to 0.762; P = .019), increased slightly. Patients receiving a mix of in-person and virtual care had the highest rate of exacerbations (0.83) and a lower asthma medication ratio (0.74) despite having the highest adherence (.57). CONCLUSIONS: Despite an increase in virtual care, asthma exacerbations decreased except among individuals who received both in-person and virtual care, likely because they had more severe disease.

Development and validation of a prediction model for opioid use disorder among youth.

BACKGROUND: Youth are vulnerable to opioid use initiation and its complications. With growing rates of opioid overdose, strategies to identify youth at risk of opioid use disorder (OUD) to efficiently focus prevention interventions are needed. This study developed and validated a prediction model of OUD in youth aged 14-18 years. METHODS: The model was developed in a Colorado healthcare system (derivation site) using Cox proportional hazards regression analysis. Model predictors and outcomes were identified using electronic health record data. The model was externally validated in a separate Denver safety net health system (validation site). Youth were followed for up to 3.5 years. We evaluated internal and external validity using discrimination and calibration. RESULTS: The derivation cohort included 76,603 youth, of whom 108 developed an OUD diagnosis. The model contained 3 predictors (smoking status, mental health diagnosis, and non-opioid substance use or disorder) and demonstrated good calibration (p = 0.90) and discrimination (bootstrap-corrected C-statistic = 0.76: 95 % CI = 0.70, 0.82). Sensitivity and specificity were 57 % and 84 % respectively with a positive predictive value (PPV) of 0.49 %. The validation cohort included 45,790 youth of whom, 74 developed an OUD diagnoses. The model demonstrated poorer calibration (p < 0.001) but good discrimination (C-statistic = 0.89; 95 % CI = 0.84, 0.95), sensitivity of 87.8 % specificity of 68.6 %, and PPV of 0.45 %. CONCLUSIONS: In two Colorado healthcare systems, the prediction model identified 57-88 % of subsequent OUD diagnoses in youth. However, PPV < 1% suggests universal prevention strategies for opioid use in youth may be the best health system approach.

Predictors of Hyperkalemia and Hypokalemia in Individuals with Diabetes: a Classification and Regression Tree Analysis.

BACKGROUND: Both hyperkalemia and hypokalemia can lead to cardiac arrhythmias and are associated with increased mortality. Information on the predictors of potassium in individuals with diabetes in routine clinical practice is lacking. OBJECTIVE: To identify predictors of hyperkalemia and hypokalemia in adults with diabetes. DESIGN: Retrospective cohort study, with classification and regression tree (CART) analysis. PARTICIPANTS: 321,856 individuals with diabetes enrolled in four large integrated health care systems from 2012 to 2013. MAIN MEASURES: We used a single serum potassium result collected in 2012 or 2013. Hyperkalemia was defined as a serum potassium ≥ 5.5 mEq/L and hypokalemia as < 3.5 mEq/L. Predictors included demographic factors, laboratory measurements, comorbidities, medication use, and health care utilization. KEY RESULTS: There were 2556 hypokalemia events (0.8%) and 1517 hyperkalemia events (0.5%). In univariate analyses, we identified concordant predictors (associated with increased probability of both hyperkalemia and hypokalemia), discordant predictors, and predictors of only hyperkalemia or hypokalemia. In CART models, the hyperkalemia "tree" had 5 nodes and a c-statistic of 0.76. The nodes were defined by prior potassium results and eGFRs, and the 5 terminal "leaves" had hyperkalemia probabilities of 0.2 to 7.2%. The hypokalemia tree had 4 nodes and a c-statistic of 0.76. The hypokalemia tree included nodes defined by prior potassium results, and the 4 terminal leaves had hypokalemia probabilities of 0.3 to 17.6%. Individuals with a recent potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no hypokalemia in the previous year had a < 1% rate of either hypokalemia or hyperkalemia. CONCLUSIONS: The yield of routine serum potassium testing may be low in individuals with a recent serum potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no recent history of hypokalemia. We did not examine the effect of recent changes in clinical condition or medications on acute potassium changes.

Adults With Asthma Experience No Increase in Asthma-related Exacerbations When Digital Communication Technology Tools Are Employed to Offset Provider Workload: A Pragmatic Randomized Trial.

BACKGROUND: Challenges to health care efficiency are increasingly addressed with the help of digital communication technology tools (DCTs). OBJECTIVE: The objective of this study was to test whether DCT, compared with Usual Care, can reduce health care clinician burden without increasing asthma-related exacerbations among patients with asthma in a large integrated health care system. RESEARCH DESIGN: The (Breathewell) program was a pragmatic, randomized trial at (Kaiser Permanente Colorado), where asthma nurses screen patients for poor symptom control when beta2-agonist refill requests came within 60 days of previous fill or in the absence of a controller medication fill within 4 months (beta2-agonist overfill). A total of 14,978 adults with asthma were randomized to Usual Care or 1 of 2 DCT intervention groups (Text/Phone call or Email). SUBJECTS: Participants included adults 18 and older with an asthma diagnosis at the time of randomization and no history of chronic obstructive pulmonary disease. MEASURES: Primary outcome measures included asthma-related health care resource utilization (eg, asthma nurse contacts), medication use, and exacerbations. RESULTS: A total of 1933 patients had 4337 events which met beta2-agonist overfill criteria. Of the 2874 events in the intervention arm, 1188 (41%) were resolved by DCT contact and did not require additional clinician contact. Asthma medication use and exacerbations over 12 months did not differ among the 3 groups. CONCLUSIONS: DCT tools can successfully contact adult asthma patients to screen for symptoms and facilitate intervention. The absence of differences in medication fills and health care utilization indicates that the strategic replacement of nursing interventions by digital outreach did not reduce treatment adherence or compromise health care outcomes.

Refill Reminder Preference and Inhaled Corticosteroid Adherence Among Patients with Asthma.

CONTEXT: Refill reminders can help patients improve adherence to inhaled corticosteroid (ICS) therapy. However, little is known about patient preferences for reminder type or whether patients who express a preference differ from patients who do not. OBJECTIVES: To describe patient preferences for ICS prescription refill reminder type and to compare baseline ICS therapy adherence, measured as proportion of days covered (PDC) 1 year before initiating preference-based reminders, between patients who did and did not express a preference. DESIGN: This substudy within a randomized multi-intervention study was conducted at Kaiser Permanente Colorado. Adults with asthma randomized to intervention were offered the opportunity to choose text, telephone, or email reminders. Patients who did and did not provide a preference were compared by baseline characteristics using log-binomial models. MAIN OUTCOME MEASURE(S): The primary outcomes were reminder preference and type. RESULTS: A total of 1497 of 4545 patients (32.9%) expressed a preference; 789 (52.7%) chose text. The adjusted relative risk (aRR) of not providing a preference increased with decreasing PDC (PDC of 0.50 to < 0.80: aRR, 1.14; 95% confidence interval [CI], 1.04-1.25; PDC < 0.5: aRR, 1.76; 95% CI, 1.59-1.95) compared with patients with a PDC of 0.80 or greater. CONCLUSION: Among patients who expressed a preference, text reminders were preferred. Patients who expressed a preference had higher baseline adherence. Further research is needed to determine whether expressing a preference for a refill reminder type is itself associated with adherence. Given that offering the opportunity to choose a reminder type only engaged a subset of patients, further work is needed to understand how best to leverage technology-enabled communication outreach to help patients optimize adherence.

Technology-Enabled Outreach to Patients Taking High-Risk Medications Reduces a Quality Gap in Completion of Clinical Laboratory Testing.

Clinical laboratory quality improvement (QI) efforts can include population test utilization. The authors used a health care organization's Medical Data Warehouse (MDW) to characterize a gap in guideline-concordant laboratory testing recommended for safe use of antirheumatic agents, then tested the effectiveness of laboratory-led, technology-enabled outreach to patients at reducing this gap. Data linkages available through the Kaiser Permanente Colorado MDW and electronic health record were used to identify ambulatory adults taking antirheumatic agents who were due/overdue for alanine aminotransferase (ALT), aspartate aminotransferase (AST), complete blood count (CBC), or serum creatinine (SCr) testing. Outreach was implemented using an interactive voice response system to send patients text or phone call reminders. Interrupted time series analysis was used to estimate reminder effectiveness. Rates of guideline-concordant testing and testing timeliness in baseline vs. intervention periods were determined using generalized linear models for repeated measures. Results revealed a decrease in percentage of 3763 patients taking antirheumatic agents due/overdue for testing at any given time: baseline 24.3% vs. intervention 17.5% (P < 0.001). Among 3205 patients taking conventional antirheumatic agents, concordance for all ALT testing was baseline 52.8% vs. intervention 65.4% (P < 0.001) among patients chronically using these agents and baseline 20.6% vs. intervention 26.1% (P < 0.001) among patients newly starting these agents. The 95th percentiles for days to ALT testing were baseline 149 vs. intervention 117 among chronic users and baseline 134 vs. intervention 92 among new starts. AST, CBC, and SCr findings were similar. Technology-enabled outreach reminding patients to obtain laboratory testing improves health care system outcomes.

Randomized Clinical Trial of a Clinical Decision Support Tool for Improving the Appropriateness Scores for Ordering Imaging Studies in Primary and Specialty Care Ambulatory Clinics.

OBJECTIVE. The objective of our study was to evaluate whether the use of a clinical decision support (CDS) tool improved the appropriateness scores of orders for advanced imaging in clinical practice. MATERIALS AND METHODS. We used a stepped-wedge, cluster randomized clinical trial to evaluate the effectiveness of a CDS tool in an integrated health care system. Clinicians entered structured indications for each CT and MRI order, and the indications were electronically scored against appropriateness criteria to assign an appropriateness score. We compared the proportion of orders with adjusted appropriateness scores of 7 or greater (on a 1-9 scale) before and after activation of best practice alerts (BPAs) triggered for orders with low or marginal appropriateness scores. Secondary outcomes included the rate per month of orders for advanced imaging and the proportion of orders for which the radiology department requested changes. RESULTS. Between October 2015 and February 2016, 941 clinicians ordered 22,279 CT or MRI studies that met eligibility criteria. Before activation of the BPA, the mean proportion of appropriate orders (adjusted for time and clinic effect) was 77.0% (95% CI, 75.5-78.4%), which increased to 80.1% (95% CI, 78.7-81.5%) after activation (p = 0.001). There was no significant change in the rate of orders per month for advanced imaging. The proportion of order changes requested by the radiology department decreased from 5.7% (95% CI, 5.6-5.9%) before CDS implementation to 5.3% (95% CI, 5.1-5.5%) after CDS implementation (p < 0.001). CONCLUSION. Using an evidence-based CDS tool in clinical practice was associated with a modest but significant improvement in the appropriateness scores of advanced imaging orders.

Association Between Opioid Dose Variability and Opioid Overdose Among Adults Prescribed Long-term Opioid Therapy.

Importance: Attempts to discontinue opioid therapy to reduce the risk of overdose and adhere to prescribing guidelines may lead patients to be exposed to variability in opioid dosing. Such dose variability may increase the risk of opioid overdose even if therapy discontinuation is associated with a reduction in risk. Objective: To examine the association between opioid dose variability and opioid overdose. Design, Setting, and Participants: A nested case-control study was conducted in a large Colorado integrated health plan and delivery system from January 1, 2006, through June 30, 2018. Cohort members were individuals prescribed long-term opioid therapy. Exposures: Dose variability was defined as the SD of the milligrams of morphine equivalents across each patient's follow-up and categorized based on the quintile distribution of the SD in the cohort (0-5.3, 5.4-9.1, 9.2-14.6, 14.7-27.2, and >27.2 mg of morphine equivalents). Main Outcomes and Measures: Opioid overdose cases were identified using International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Each case patient with overdose was matched to up to 20 control patients using risk set sampling. Conditional logistic regression models were used to generate matched odds ratios and 95% CIs, adjusted for age, sex, race/ethnicity, drug or alcohol use disorder, tobacco use, benzodiazepine dispensings, medical comorbidities, mental health disorder, opioid dose, and opioid formulation. Results: In a cohort of 14 898 patients (mean [SD] age, 56.3 [16.0] years; 8988 [60.3%] female) prescribed long-term opioid therapy, 228 case patients with incident opioid overdose were matched to 3547 control patients. The mean (SD) duration of opioid therapy was 36.7 (33.7) months in case patients and 33.0 (30.9) months in control patients. High-dose variability (SD >27.2 mg of morphine equivalents) was associated with a significantly increased risk of overdose compared with low-dose variability (matched odds ratio, 3.32; 95% CI, 1.63-6.77) independent of opioid dose. Conclusions and Relevance: Variability in opioid dose may be a risk factor for opioid overdose, suggesting that practitioners should seek to minimize dose variability when managing long-term opioid therapy.

Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process.

CONTEXT.­: The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization. Cross-department, multidisciplinary collaboration to address gaps and improve patient and system outcomes is beneficial. OBJECTIVE.­: To demonstrate medical data warehouse utility for characterizing laboratory-associated quality gaps amenable to preanalytic or postanalytic interventions. DESIGN.­: A multidisciplinary team identified quality gaps. Medical data warehouse data were queried to characterize gaps. Organizational leaders were interviewed about quality improvement priorities. A decision aid with elements including national guidelines, local and national importance, and measurable outcomes was completed for each gap. RESULTS.­: Gaps identified included (1) test ordering; (2) diagnosis, detection, and documentation, and (3) high-risk medication monitoring. After examination of medical data warehouse data including enrollment, diagnoses, laboratory, pharmacy, and procedures for baseline performance, high-risk medication monitoring was selected, specifically alanine aminotransferase, aspartate aminotransferase, complete blood count, and creatinine testing among patients receiving disease-modifying antirheumatic drugs. The test utilization gap was in monitoring timeliness (eg, >60% of patients had a monitoring gap exceeding the guideline recommended frequency). Other contributors to selecting this gap were organizational enthusiasm, regulatory labeling, and feasibility of a significant laboratory role in addressing the gap. CONCLUSIONS.­: A multidisciplinary process facilitated identification and selection of a laboratory medicine quality gap. Medical data warehouse data were instrumental in characterizing gaps.

Add-On Antihypertensive Medications to Angiotensin-Aldosterone System Blockers in Diabetes: A Comparative Effectiveness Study.

BACKGROUND AND OBJECTIVES: In individuals with diabetes, the comparative effectiveness of add-on antihypertensive medications added to an angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker on the risk of significant kidney events is unknown. DESIGN, SETTING PARTICIPANTS, & MEASUREMENTS: We used an observational, multicenter cohort of 21,897 individuals with diabetes to compare individuals who added ß-blockers, dihydropyridine calcium channel blockers, loop diuretics, or thiazide diuretics to angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. We examined the hazard of significant kidney events, cardiovascular events, and death using Cox proportional hazard models with propensity score weighting. The composite significant kidney event end point was defined as the first occurrence of a ≥30% decline in eGFR to an eGFR<60 ml/min per 1.73 m2, initiation of dialysis, or kidney transplant. The composite cardiovascular event end point was defined as the first occurrence of hospitalization for acute myocardial infarction, acute coronary syndrome, stroke, or congestive heart failure; coronary artery bypass grafting; or percutaneous coronary intervention, and it was only examined in those free of cardiovascular disease at baseline. RESULTS: Over a maximum of 5 years, there were 4707 significant kidney events, 1498 deaths, and 818 cardiovascular events. Compared with thiazide diuretics, hazard ratios for significant kidney events for ß-blockers, calcium channel blockers, and loop diuretics were 0.81 (95% confidence interval, 0.74 to 0.89), 0.67 (95% confidence interval, 0.58 to 0.78), and 1.19 (95% confidence interval, 1.00 to 1.41), respectively. Compared with thiazide diuretics, hazard ratios of mortality for ß-blockers, calcium channel blockers, and loop diuretics were 1.19 (95% confidence interval, 0.97 to 1.44), 0.73 (95% confidence interval, 0.52 to 1.03), and 1.67 (95% confidence interval, 1.31 to 2.13), respectively. Compared with thiazide diuretics, hazard ratios of cardiovascular events for ß-blockers, calcium channel blockers, and loop diuretics compared with thiazide diuretics were 1.65 (95% confidence interval, 1.39 to 1.96), 1.05 (95% confidence interval, 0.80 to 1.39), and 1.55 (95% confidence interval, 1.05 to 2.27), respectively. CONCLUSIONS: Compared with thiazide diuretics, calcium channel blockers were associated with a lower risk of significant kidney events and a similar risk of cardiovascular events.

Improvements in access and care through the Affordable Care Act.

OBJECTIVES: To examine the impact of enrolling in a healthcare plan through the Affordable Care Act (ACA) healthcare exchanges on self-reported access to care. STUDY DESIGN: Cohort study using self-reported data of patients newly enrolled in Kaiser Permanente California and Kaiser Permanente Colorado through the ACA healthcare exchanges for coverage beginning January 1, 2014. METHODS: Baseline and follow-up surveys conducted via mail and telephone, with response rates of 45% and 51%, respectively. RESULTS: We found significant increases in the percentage of people who reported having a personal healthcare provider (59% vs 73%; P <.01) and significant decreases in those who reported delaying needed medical care due to costs (37% vs 25%; P <.01) before and after ACA enrollment. There was also a significant increase in the percentage of patients who reported receiving a flu shot during the prior year (41% vs 52%; P <.01). Among the people who reported having less than 4 months of healthcare coverage in 2013, these improvements were even more pronounced. This group also showed significant increases in the percentages who felt they had a place to go when they needed medical care (43% vs 56%; P <.01) and who reported they received advice to quit smoking or using tobacco (46% vs 72%; P <.05). CONCLUSIONS: These findings are an important addition to the evidence base that the ACA is improving the healthcare experience and reducing barriers due to costs for individuals obtaining insurance coverage through the healthcare exchanges.

Use of Risk Models to Predict Death in the Next Year Among Individual Ambulatory Patients With Heart Failure.

Importance: The clinical practice guidelines for heart failure recommend the use of validated risk models to estimate prognosis. Understanding how well models identify individuals who will die in the next year informs decision making for advanced treatments and hospice. Objective: To quantify how risk models calculated in routine practice estimate more than 50% 1-year mortality among ambulatory patients with heart failure who die in the subsequent year. Design, Setting, and Participants: Ambulatory adults with heart failure from 3 integrated health systems were enrolled between 2005 and 2008. The probability of death was estimated using the Seattle Heart Failure Model (SHFM) and the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk calculator. Baseline covariates were collected from electronic health records. Missing covariates were imputed. Estimated mortality was compared with actual mortality at both population and individual levels. Main Outcomes and Measures: One-year mortality. Results: Among 10 930 patients with heart failure, the median age was 77 years, and 48.0% of these patients were female. In the year after study enrollment, 1661 patients died (15.9% by life-table analysis). At the population level, 1-year predicted mortality among the cohort was 9.7% for the SHFM (C statistic of 0.66) and 17.5% for the MAGGIC risk calculator (C statistic of 0.69). At the individual level, the SHFM predicted a more than 50% probability of dying in the next year for 8 of the 1661 patients who died (sensitivity for 1-year death was 0.5%) and for 5 patients who lived at least a year (positive predictive value, 61.5%). The MAGGIC risk calculator predicted a more than 50% probability of dying in the next year for 52 of the 1661 patients who died (sensitivity, 3.1%) and for 63 patients who lived at least a year (positive predictive value, 45.2%). Conversely, the SHFM estimated that 8496 patients (77.8%) had a less than 15% probability of dying at 1 year, yet this lower-risk end of the score range captured nearly two-thirds of deaths (n = 997); similarly, the MAGGIC risk calculator estimated a probability of dying of less than 25% for the majority of patients who died at 1 year (n = 914). Conclusions and Relevance: Although heart failure risk models perform reasonably well at the population level, they do not reliably predict which individual patients will die in the next year.

The Contemporary Safety and Effectiveness of Lower Extremity Bypass Surgery and Peripheral Endovascular Interventions in the Treatment of Symptomatic Peripheral Arterial Disease.

BACKGROUND: Treatment for symptomatic peripheral artery disease includes lower extremity bypass surgery (LEB) and peripheral endovascular interventions (PVIs); however, limited comparative effectiveness data exist between the 2 therapies. We assessed the safety and effectiveness of LEB and PVI in patients with symptomatic claudication and critical limb ischemia. METHODS AND RESULTS: In a community-based clinical registry at 2 large integrated healthcare delivery systems, we compared 883 patients undergoing PVI and 975 patients undergoing LEB between January 1, 2005 and December 31, 2011. Rates of target lesion revascularization were greater for PVI than for LEB in patients presenting with claudication (12.3±2.7% and 19.0±3.5% at 1 and 3 years versus 5.2±2.4% and 8.3±3.1%, log-rank P<0.001) and critical limb ischemia (19.1±4.8% and 31.6±6.3% at 1 and 3 years versus 10.8±2.5% and 16.0±3.2%, log-rank P<0.001). However, in comparison with PVI, LEB was associated with increased rates of complications up to 30 days following the procedure (37.1% versus 11.9%, P<0.001). There were no differences in amputation rates between the 2 groups. Findings remained consistent in sensitivity analyses by using propensity methods to account for treatment selection. CONCLUSIONS: In patients with symptomatic peripheral artery disease, in comparison with LEB, PVI was associated with fewer 30-day procedural complications, higher revascularization rates at 1 and 3 years, and no difference in subsequent amputations.