Evaluating the Effects of Opioid Prescribing Policies on Patient Outcomes in a Safety-net Primary Care Clinic

Christopher L Rowe,Alan Hubbard,Phillip Coffin,Jennifer Ahern,Mark Faul,Kellene Eagen

doi:10.1007/s11606-021-06920-4

Abstract

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.

Highlights

The USA continues to grapple with an unprecedented opioid overdose epidemic
The interventions were associated with a reduction in mean opioid dose in the first three post-policy years (Table 2 and Fig. 1)
We found that the interventions were associated with reductions in opioid dose in the first 3 years and possibly with increases in non-prescribed opioid analgesic use

Summary

Introduction

The USA continues to grapple with an unprecedented opioid overdose epidemic. Almost half a million people died from opioid-involved drug overdoses from 1999 to 2018, including nearly 50,000 deaths annually in recent years.[1,2] the crisis is dominated by overdoses involving illicitly manufactured fentanyl, nearly one-third of opioid overdose deaths involved prescription opioids in 2018.2,3Opioid stewardship measures aiming to limit supply and mitigate harms of prescription opioids in primary care settings have been a major component of the national response to the epidemic.[4,5,6,7,8,9,10,11] these measures, including the 2016 Centers for Disease Control and Prevention (CDC) opioid prescribing guidelines,[12] have corresponded with substantial reductions in opioid prescribing,[13,14,15,16,17] the rate of prescribing in the USA remains higher than any other nation and varies widely throughout the country.[13,18,19] Evidence regarding the effects of opioid prescribing policies is largely limited to opioid prescribing outcomes.[20,21,22,23,24,25,26] several studies have linked reduction or discontinuation of prescribed opioids to adverse patient outcomes, including dropping out of care,[27] illicit use of opioids,[28,29] and death by overdose and suicide.[30,31] In light of these risks, critical examination of the effects of specific policies on both opioid prescribing and unintended patient outcomes, such as illicit opioid use, is needed to identify strategies that are both effective and safe. KEY RESULTS: The interventions were associated with a reduction in mean prescribed opioid dose in the first three post-policy years (year 1 conditional difference-indifferences 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. CONCLUSIONS: Clinic-level opioid prescribing policies were associated with reduced dose, the control clinic achieved similar reductions by the fourth postpolicy year, and the policies may have been associated with increased non-prescribed opioid analgesic use

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Conclusion