Project description:ImportanceTime pressure to provide a quick fix is commonly cited as a reason why opioids are frequently prescribed in the United States, but there is little evidence of an association between appointment timing and clinical decision-making. As the workday progresses and appointments run behind schedule, physicians may be more likely to prescribe opioids.ObjectiveTo estimate whether characteristics of appointment timing are associated with clinical decision-making about pain treatment.Design, setting, and participantsThis cross-sectional study of physician behavior used data from electronic health record systems in primary care offices in the United States to analyze primary care appointments occurring in 2017 for patients with a new painful condition who had not received an opioid prescription within the past year.Main outcomes and measuresThe association between treatment decisions and 2 dimensions of appointment timing (order of appointment occurrence and delay relative to scheduled start time) were assessed. The rates of opioid prescribing were measured and compared with rates of nonopioid pain medication (ie, nonsteroidal anti-inflammatory drugs) prescribing and referral to physical therapy. All rates were estimated within the same physician using physician fixed effects, adjusting for patient, appointment, and seasonal characteristics.ResultsAmong 678 319 primary care appointments (642 262 patients; 392 422 [61.1%] women) with 5603 primary care physicians, the likelihood that an appointment resulted in an opioid prescription increased by 33% as the workday progressed (1st to 3rd appointment, 4.0% [95% CI, 3.9%-4.1%] vs 19th to 21st appointment, 5.3% [95% CI. 5.1%-5.6%]; P < .001) and by 17% as appointments ran behind schedule (0-9 minutes late, 4.4% [95% CI, 4.3%-4.6%] vs ≥60 minutes late, 5.2% [95% CI, 5.0%-5.4%]; P < .001). Prescribing of nonsteroidal anti-inflammatory drugs and referral to physical therapy did not display similar patterns.Conclusions and relevanceThese findings suggest that, even within an individual physician's schedule, clinical decision-making for opioid prescribing varies by the timing and lateness of appointments.

Project description:BackgroundAfter decades of liberal opioid prescribing, multiple efforts have been made to reduce reliance upon opioids in clinical care. Little is known about the effects of opioid prescribing policies on outcomes beyond opioid prescribing.ObjectiveTo evaluate the combined effects of multiple opioid prescribing policies implemented in a safety-net primary care clinic in San Francisco, CA, in 2013-2014.DesignRetrospective cohort study and conditional difference-in-differences analysis of nonrandomized clinic-level policies.Patients273 patients prescribed opioids for chronic non-cancer pain in 2013 at either the treated (n=151) or control clinic (n=122) recruited and interviewed in 2017-2018.InterventionsPolicies establishing standard protocols for dispensing opioid refills and conducting urine toxicology testing, and a new committee facilitating opioid treatment decisions for complex patient cases.Main measuresOpioid prescription (active prescription, mean dose in morphine milligram equivalents [MME]) from electronic medical charts, and heroin and opioid analgesics not prescribed to the patient (any use, use frequency) from a retrospective interview.Key resultsThe interventions were associated with a reduction in mean prescribed opioid dose in the first three post-policy years (year 1 conditional difference-in-differences estimate: -52.0 MME [95% confidence interval: -109.9, -10.6]; year 2: -106.2 MME [-195.0, -34.6]; year 3: -98.6 MME [-198.7, -23.9]; year 4: -72.6 MME [-160.4, 3.6]). Estimates suggest a possible positive association between the interventions and non-prescribed opioid analgesic use (year 3: 5.2 absolute percentage points [-0.1, 11.2]) and use frequency (year 3: 0.21 ordinal frequency scale points [0.00, 0.47]) in the third post-policy year.ConclusionsClinic-level opioid prescribing policies were associated with reduced dose, although the control clinic achieved similar reductions by the fourth post-policy year, and the policies may have been associated with increased non-prescribed opioid analgesic use. Clinicians should balance the urgency to reduce opioid prescribing with potential harms from rapid change.

Project description:BACKGROUND:Systematic implementation of guidelines for opioid therapy management in chronic non-cancer pain can reduce opioid-related harms. However, implementation of guideline-recommended practices in routine care is subpar. The goal of this quality improvement (QI) project is to assess whether a clinic-tailored QI intervention improves the implementation of a health system-wide, guideline-driven policy on opioid prescribing in primary care. This manuscript describes the protocol for this QI project. METHODS:A health system with 28 primary care clinics caring for approximately 294,000 primary care patients developed and implemented a guideline-driven policy on long-term opioid therapy in adults with opioid-treated chronic non-cancer pain (estimated N = 3980). The policy provided multiple recommendations, including the universal use of treatment agreements, urine drug testing, depression and opioid misuse risk screening, and standardized documentation of the chronic pain diagnosis and treatment plan. The project team drew upon existing guidelines, feedback from end-users, experts and health system leadership to develop a robust QI intervention, targeting clinic-level implementation of policy-directed practices. The resulting multi-pronged QI intervention included clinic-wide and individual clinician-level educational interventions. The QI intervention will augment the health system's "routine rollout" method, consisting of a single educational presentation to clinicians in group settings and a separate presentation for staff. A stepped-wedge design will enable 9 primary care clinics to receive the intervention and assessment of within-clinic and between-clinic changes in adherence to the policy items measured by clinic-level electronic health record-based measures and process measures of the experience with the intervention. DISCUSSION:Developing methods for a health system-tailored QI intervention required a multi-step process to incorporate end-user feedback and account for the needs of targeted clinic team members. Delivery of such tailored QI interventions has the potential to enhance uptake of opioid therapy management policies in primary care. Results from this study are anticipated to elucidate the relative value of such QI activities.

Project description:IntroductionIn March 2016, the Centers for Disease Control and Prevention issued opioid prescribing guidelines for chronic noncancer pain. In response, in April 2016, the North Carolina Medical Board launched the Safe Opioid Prescribing Initiative, an investigative program intended to limit the overprescribing of opioids. This study focuses on the association of the Safe Opioid Prescribing Initiative with immediate and sustained changes in opioid prescribing among all patients who received opioid and opioid discontinuation and tapering among patients who received high-dose (>90 milligrams of morphine equivalents), long-term (>90 days) opioid therapy.MethodsControlled and single interrupted time series analysis of opioid prescribing outcomes before and after the implementation of Safe Opioid Prescribing Initiative was conducted using deidentified data from the North Carolina Controlled Substances Reporting System from January 2010 through March 2017. Analysis was conducted in 2019-2020.ResultsIn an average study month, 513,717 patients, including patients who received 47,842 high-dose, long-term opioid therapy, received 660,912 opioid prescriptions at 1.3 prescriptions per patient. There was a 0.52% absolute decline (95% CI= -0.87, -0.19) in patients receiving opioid prescriptions in the month after Safe Opioid Prescribing Initiative implementation. Abrupt discontinuation, rapid tapering, and gradual tapering of opioids among patients who received high-dose, long-term opioid therapy increased by 1% (95% CI= -0.22, 2.23), 2.2% (95% CI=0.91, 3.47), and 1.3% (95% CI=0.96, 1.57), respectively, in the month after Safe Opioid Prescribing Initiative implementation.ConclusionsAlthough Safe Opioid Prescribing Initiative implementation was associated with an immediate decline in overall opioid prescribing, it was also associated with an unintended immediate increase in discontinuations and rapid tapering among patients who received high-dose, long-term opioid therapy. Better policy communication and prescriber education regarding opioid tapering best practices may help mitigate unintended consequences of statewide policies.

Project description:BackgroundClinician utilization of practice guidelines can reduce inappropriate opioid prescribing and harm in chronic non-cancer pain; yet, implementation of "opioid guidelines" is subpar. We hypothesized that a multi-component quality improvement (QI) augmentation of "routine" system-level implementation efforts would increase clinician adherence to the opioid guideline-driven policy recommendations.MethodsOpioid policy was implemented system-wide in 26 primary care clinics. A convenience sample of 9 clinics received the QI augmentation (one-hour academic detailing; 2 online educational modules; 4-6 monthly one-hour practice facilitation sessions) in this non-randomized stepped-wedge QI project. The QI participants were volunteer clinic staff. The target patient population was adults with chronic non-cancer pain treated with long-term opioids. The outcomes included the clinic-level percentage of target patients with a current treatment agreement (primary outcome), rates of opioid-benzodiazepine co-prescribing, urine drug testing, depression and opioid misuse risk screening, and prescription drug monitoring database check; additional measures included daily morphine-equivalent dose (MED), and the percentages of all target patients and patients prescribed ≥90 mg/day MED. T-test, mixed-regression and stepped-wedge-based analyses evaluated the QI impact, with significance and effect size assessed with two-tailed p < 0.05, 95% confidence intervals and/or Cohen's d.ResultsTwo-hundred-fifteen QI participants, a subset of clinical staff, received at least one QI component; 1255 patients in the QI and 1632 patients in the 17 comparison clinics were prescribed long-term opioids. At baseline, more QI than comparison clinic patients were screened for depression (8.1% vs 1.1%, p = 0.019) and prescribed ≥90 mg/day MED (23.0% vs 15.5%, p = 0.038). The stepped-wedge analysis did not show statistically significant changes in outcomes in the QI clinics, when accounting for the comparison clinics' trends. The Cohen's d values favored the QI clinics in all outcomes except opioid-benzodiazepine co-prescribing. Subgroup analysis showed that patients prescribed ≥90 mg/day MED in the QI compared to comparison clinics improved urine drug screening rates (38.8% vs 19.1%, p = 0.02), but not other outcomes (p ≥ 0.05).ConclusionsAugmenting routine policy implementation with targeted QI intervention, delivered to volunteer clinic staff, did not additionally improve clinic-level, opioid guideline-concordant care metrics. However, the observed effect sizes suggested this approach may be effective, especially in higher-risk patients, if broadly implemented.Trial registrationNot applicable.

Dataset Information

The Implementation of a Clinic-Based Opioid Review Board to Address High-Risk Opioid Prescribing in Primary Care

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets