Variability in opioid prescription monitoring and evidence of aberrant medication taking behaviors in urban safety-net clinics

Lange, Allison; Lasser, Karen E.; Xuan, Ziming; Khalid, Laila; Beers, Donna; Heymann, Orlaith; Shanahan, Christopher W.; Crosson, Julie; Liebschutz, Jane M.

doi:10.1097/01.j.pain.0000460314.73358.ff

Cited by 19 publications

(23 citation statements)

References 18 publications

(22 reference statements)

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“…Baseline characteristics of patients at three of the four participating sites have been published elsewhere (Khalid, et al, 2014; Lange, et al, 2015). At the adult primary care practice at Boston Medical Center, 42% of patients had ever had a controlled substance agreement, 64% had any urine drug testing in the past year, and 32% had at least two early refills of opioids in the past year.…”

Section: Resultsmentioning

confidence: 99%

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A Multicomponent Intervention to Improve Primary Care Provider Adherence to Chronic Opioid Therapy Guidelines and Reduce Opioid Misuse: A Cluster Randomized Controlled Trial Protocol

Lasser

Shanahan

Parker

et al. 2016

Journal of Substance Abuse Treatment

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Background Prescription opioid misuse is a significant public health problem as well as a patient safety concern. Primary care providers (PCPs) are the leading prescribers of opioids for chronic pain, yet few PCPs follow standard practice guidelines regarding assessment and monitoring. This cluster randomized controlled trial will determine whether four implementation strategies; nurse care management, use of a patient registry, academic detailing, and electronic tools, will increase PCP adherence to chronic opioid therapy guidelines and reduce opioid misuse among patients, relative to electronic tools alone. The implementation strategies and intervention content are based on the Chronic Care Model. Methods We include 53 PCPs from three Boston-area community health centers and one urban safety-net hospital-based primary care practice who have at least four patients meeting the following inclusion criteria: 1) age ≥ 18; 2) one or more completed visits to the primary care practice in the past year; 3) long-term opioid treatment defined as three or more opioid prescriptions written at least 21 days apart within six months and 4) an inpatient or outpatient ICD-9-CM diagnosis for musculoskeletal or neuropathic pain. We consider PCPs to be study subjects, and obtained a waiver of informed consent for patients because the study is promoting an established standard of care. We enrolled participants (PCPs) from December 2012 through March 2015. PCPs were randomized to receive the intervention, which includes four components: 1) nurse care management, 2) use of a patient registry, 3) academic detailing, and 4) electronic tools, or a control condition, which includes only the use of the electronic tools. The intervention PCPs receive the services of a nurse-managed registry for planning individual patient care and conducting population-based care for patients receiving opioids for chronic pain. In academic detailing visits, trained co-investigators provide intervention PCPs with individualized education to change prescribing practice. Electronic tools, located on a website external to the EMR, www.mytopcare.org, include validated instruments to assess patient status, and management resources to facilitate PCP adherence to suggested monitoring. Electronic tools are available to PCPs in both study arms. The primary outcomes are PCP adherence to chronic opioid therapy guidelines and patient opioid misuse. Secondary outcomes include measures of substance abuse, possible opioid diversion, and level of opioid risk among patients. We will follow PCPs and their estimated 1200 chronic pain patients for one year after study enrollment. To determine whether the intervention condition achieves greater adherence to guidelines and reduced opioid misuse after one year compared to the control condition, we will compare the baseline and follow-up measures of the individual patients, stratifying by intervention status and noting differences that are statistically significant at the p=0.05 level. Analyses will be based on intent-to-treat....

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Section: Resultsmentioning

confidence: 99%

“…Our definitions are based on outcomes from our prior studies and from other published literature (Hariharan, et al, 2007; Khalid et al, 2014; Lange et al, 2015; Reid, et al, 2002; Starrels, et al, 2011). A blinded data analyst will extract all study outcomes and exploratory variables from a clinical data warehouse.…”

Section: Methodsmentioning

confidence: 99%

A Multicomponent Intervention to Improve Primary Care Provider Adherence to Chronic Opioid Therapy Guidelines and Reduce Opioid Misuse: A Cluster Randomized Controlled Trial Protocol

Lasser

Shanahan

Parker

et al. 2016

Journal of Substance Abuse Treatment

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“…However, no randomized trial evaluated opioid abuse, addiction, or related outcomes with long‐term opioid therapy versus placebo or nonopioid therapy. In fact, a higher variability exists in the proposed long‐term use monitoring systems …”

Section: Discussionmentioning

confidence: 99%

OPRM1 influence on and effectiveness of an individualized treatment plan for prescription opioid use disorder patients

Muriel

Margarit

Planelles

et al. 2018

Annals of the New York Academy of Sciences

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Screening for opioid use disorder should be considered in chronic non-cancer pain (CNCP) patients with long-term use of opioids. The aim of our study was to assess the effectiveness of an individualized treatment plan (ITP) for prescription opioid dependence that included screening of pharmacogenetic markers. An observational prospective study was performed using prescription opioid-dependent CNCP outpatients (n = 88). Patients were divided into nonresponders, responders, or high responders according to their response to the ITP. Genotyping of OPRM1 (A118G), OPRD1 (T921C), COMT (G472A), ABCB1 (C3435T), and ARRB2 (C8622T) was performed by real-time PCR. Our ITP achieved a significant reduction of the morphine equivalent daily dose (MEDD) in 64% of responders, including 33% of high responders. Nonopioid medication or buprenorphine use was significantly higher at final versus basal visit. 118-AA OPRM1 patients required significantly lower MEDD at basal and final visits. Our ITP showed effectiveness and security in reducing MEDD in opioid-dependent patients, with good conversion to buprenorphine that was more pronounced in 118-AA OPRM1 patients.

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“…28 Similarly, only one patient between both groups had any documentation that a urine drug screen was utilized, consistent with prior work that providers infrequently order urine drug screens, though more recent studies show this may be improving. 9, 10, 29 …”

Section: Discussionmentioning

confidence: 99%

“…Little is known about how providers make decisions about opioid dosing (i.e., to continue, increase, or decrease a patient’s dose) when they write individual prescriptions. Prior studies examining risk factors for high-dose opioid use and opioid misuse have found that documentation of guideline-concordant practices for safe opioid prescribing is poor; 9, 10, 11, 12, 13 however, neither providers’ rationale for individual opioid prescriptions nor encounter-level factors associated with opioid dose increases have been previously studied.…”

Section: Introductionmentioning

confidence: 99%

Factors Associated with Opioid Dose Increases: A Chart Review of Patients’ First Year on Long-Term Opioids

et al. 2016

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OBJECTIVE To examine encounter-level factors associated with opioid dose increases during patients’ first year on opioid therapy for chronic pain. DESIGN Case-control study analyzing all opioid prescriptions for patients with chronic pain during their first year after opioid initiation. Cases were patients who experienced an overall dose escalation of ≥30 mg morphine equivalents over the 1-year period; controls did not experience overall dose escalation. Main measures were encounter type; opioid dose change; documented prescribing rationale; documentation of guideline-concordant opioid prescribing practices. Two coders reviewed all encounters associated with opioid prescriptions. Analysis of factors associated with dose increases and provider documentation of prescribing rationale was conducted using multiple logistic regression. RESULTS 674 encounters were coded for 66 patients (22 cases, 44 controls). Fifty-three percent of opioid prescriptions were associated with telephone encounters; 13% were associated with email encounters. No prescribing rationale was documented for 43% of all opioid prescriptions and 25% of dose increases. Likelihood of dose increase and documentation of prescribing rationale did not significantly differ for cases versus controls. Compared to face-to-face encounters, dose increases were significantly less likely for telephone (OR 0.18, 95%CI 0.11 – 0.28) and email (OR 0.23, 95%CI 0.12 – 0.47) encounters; documentation of prescribing rationale was significantly more likely for email (OR 5.06, 95%CI 1.87–13.72) and less likely for telephone (OR 0.30, 95%CI 0.18–0.51) encounters. CONCLUSION Most opioid prescriptions were written without face-to-face encounters. One quarter of dose increases contained no documented prescribing rationale. Documented encounter-level factors were not significantly associated with overall opioid dose escalation.

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Variability in opioid prescription monitoring and evidence of aberrant medication taking behaviors in urban safety-net clinics

Cited by 19 publications

References 18 publications

A Multicomponent Intervention to Improve Primary Care Provider Adherence to Chronic Opioid Therapy Guidelines and Reduce Opioid Misuse: A Cluster Randomized Controlled Trial Protocol

A Multicomponent Intervention to Improve Primary Care Provider Adherence to Chronic Opioid Therapy Guidelines and Reduce Opioid Misuse: A Cluster Randomized Controlled Trial Protocol

OPRM1 influence on and effectiveness of an individualized treatment plan for prescription opioid use disorder patients

Factors Associated with Opioid Dose Increases: A Chart Review of Patients’ First Year on Long-Term Opioids

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