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The American Journal of Managed Care May 2017
Drivers of Excess Costs of Opioid Abuse Among a Commercially Insured Population
Lauren M. Scarpati, PhD; Noam Y. Kirson, PhD; Miriam L. Zichlin, MPH; Zitong B. Jia, BA; Howard G. Birnbaum, PhD; and Jaren C. Howard, PharmD
Critical Incident Stress Debriefing After Adverse Patient Safety Events
Reema Harrison, PhD, MSc, BSc, and Albert Wu, MD, MPH
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Ian Randall, PhD; Charles Maynard, PhD; Gary Chan, PhD; Beth Devine, PhD; and Chris Johnson, PhD
State Prescription Drug Monitoring Programs and Fatal Drug Overdoses
Young Hee Nam, PhD; Dennis G. Shea, PhD; Yunfeng Shi, PhD; and John R. Moran, PhD
Disparities in Diabetes and Hypertension Care for Individuals With Serious Mental Illness
Junqing Liu, PhD; Jonathan Brown, PhD; Suzanne Morton, MPH; D.E.B. Potter, MS; Lisa Patton, PhD; Milesh Patel, MS; Rita Lewis, MPH; and Sarah Hudson Scholle, DrPH
The Cost of Adherence Mismeasurement in Serious Mental Illness: A Claims-Based Analysis
Jason Shafrin, PhD; Felicia Forma, BSc; Ethan Scherer, PhD; Ainslie Hatch, PhD; Edward Vytlacil, PhD; and Darius Lakdawalla, PhD
Prescription Opioid Registry Protocol in an Integrated Health System
G. Thomas Ray, MBA; Amber L. Bahorik, PhD; Paul C. VanVeldhuisen, PhD; Constance M. Weisner, DrPH, MSW; Andrea L. Rubinstein, MD; and Cynthia I. Campbell, PhD, MPH
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Opioid Prescribing for Chronic Pain in a Community-Based Healthcare System
Robert J. Romanelli, PhD; Laurence I. Ikeda, MD; Braden Lynch, PharmD; Terri Craig, PharmD; Joseph C. Cappelleri, PhD; Trevor Jukes, MS; and Denis Y. Ishisaka, PharmD
Medicaid Prior Authorization and Opioid Medication Abuse and Overdose
Gerald Cochran, PhD; Adam J. Gordon, MD, MPH; Walid F. Gellad, MD, MPH; Chung-Chou H. Chang, PhD; Wei-Hsuan Lo-Ciganic, PhD, MS, MSPharm; Carroline Lobo, MS; Evan Cole, PhD; Winfred Frazier, MD; Ping

Opioid Prescribing for Chronic Pain in a Community-Based Healthcare System

Robert J. Romanelli, PhD; Laurence I. Ikeda, MD; Braden Lynch, PharmD; Terri Craig, PharmD; Joseph C. Cappelleri, PhD; Trevor Jukes, MS; and Denis Y. Ishisaka, PharmD
This study identified populations with non-cancer chronic pain to determine which patients may be more likely to receive an opioid prescription in an outpatient setting.
Prescriptions for nonanalgesics were most common in patients with headaches/migraines (86.3%) (Table 2). Patients were prescribed, on average, 1.8 unique nonanalgesic medications; those with headaches/migraines and unclassified pain received the highest average number of nonanalgesic medications (mean = 2.6 each for arthritis/joint pain and unclassified pain). 

Opioid Prescribing by Number and Type of CP Conditions 

Among patients with a single CP type, the highest prevalence of receiving an opioid, after controlling for other covariates, was for back/cervical pain (71%) (Figure). For each CP category, the adjusted prevalence of receiving an opioid increased linearly as the number of CP conditions increased: arthritis/joint pain (OR, 1.39; 95% CI, 1.36-1.42; P <.001), back/cervical pain (OR, 1.07; 95% CI, 1.05-1.09; P <.001), neuropathies/neuralgias (OR, 1.65; 95% CI, 1.61-1.69; P <.001), headaches/migraines (OR, 1.51; 95% CI, 1.47-1.56; P <.001), and unclassified pain (OR, 1.48; 95% CI, 1.44-1.53; P <.001). 

Patient Demographics and Characteristics Associated With Receiving an Opioid Prescription 

We found several patient demographics and characteristics to be associated with receipt of an opioid prescription (Table 3). After statistical adjustment, older patients (≥66 years vs 18-45 years), those with moderate chronic disease burden (CCI score = 2-3 vs 0), women, Asians (vs NHW), and commercially insured beneficiaries (vs all other insurance types) had lower odds of receiving an opioid. Patients with a greater total number of CP conditions had higher odds of receiving an opioid. 

Because of the potential correlation between age, CCI score, and insurance type (eg, older individuals tend to have more comorbidities and are more likely to be Medicare beneficiaries), we performed analyses to examine the effect of CCI and payer type on the relationship between age and receipt of an opioid. The presence or absence of these covariates had minimal effect on model coefficients within the age category (data not shown). 

DISCUSSION 

In this cross-sectional analysis of EHR prescribing data from a community-based ambulatory healthcare system setting, we found differences in opioid prescribing to patients by number and type of CP conditions. Among patients with 1 CP condition, those with back/cervical pain had the highest prevalence of receiving an opioid, whereas those with neuropathies/neuralgias and headache/migraines had the lowest prevalence; these latter groups more frequently received nonanalgesic medications (eg, antiepileptic or antimigraine medications). The prevalence of receiving an opioid increased linearly with the number of CP conditions per patient, reaching more than 60% for those with 3, more than 70% for those with 4, and approximately 80% for those with all 5 CP conditions; however, few patients had conditions within 4 or all 5 CP categories (4.5% and 0.8%, respectively). 

Our study is consistent with previous studies showing that patients with back pain are more likely to receive an opioid than those with other pain conditions.19,22 Back pain is one of the most common reasons for a visit to a doctor’s office, composing approximately one-fourth of all encounters.23 Higher rates of opioid prescribing among patients with back pain may be due to the paucity of effective alternative pharmacological agents, particularly for back pain lasting more than 4 weeks.24 In general, opioid prescribing for all types of chronic musculoskeletal pain has increased 2-fold between 1980 and 2000 (8% to 16%).25,26 

These trends reflect an increased availability of newly marketed pain products in the 1990s and changes to state medical board opioid regulations around the same time, which relaxed opioid prescribing practices for CP.27 It is notable that more than half of patients with only unclassified pain—inclusive of conditions like fibromyalgia and pelvic pain—received an opioid; these patients had the highest prevalence of prescriptions for long-acting opioids (14.2%). Current guidelines do not support the use of most opioids in unclassified painful conditions where the harms may outweigh potential benefits, regardless of whether other treatments had been previously tried.8 The exception is tramadol, which has serotonin and norepinephrine reuptake inhibitory effects and is used in the treatment of fibromyalgia. 

In multivariate analyses, we found that older age and higher CCI score were negatively associated with receiving an opioid. Although older individuals may be expected to have a greater need for pain medications due to higher prevalence of painful conditions and greater overall disease burden,28 certain medications, including opioids, are not recommended in the elderly population due to increased risks.29 For example, opioid-related risks, such as respiratory depression, tend to be potentiated in older patients.30-32 Even minor side effects, including opioid-induced drowsiness or sedation, may have more serious consequences in this population. Similarly, older patients and those with a higher CCI may be more likely to have underlying liver or renal disease, which can impact opioid metabolism and lead to harmful effects.31 

We also found that for most racial/ethnic groups, men received an opioid prescription more often than women. This trend has been demonstrated in other studies of CP.19,20 We further showed that among men, there were no significant differences in the adjusted prevalence of receiving an opioid for NHWs, African Americans, or Hispanics; however, among women, African Americans were more likely than NHWs to receive an opioid. Notably, East/Southeast Asians and Asian Indians of both genders had the lowest prevalence of receiving opioid prescriptions. 

We are unaware of studies on this topic among Asians receiving treatment for CP in ambulatory settings, but the results of a small prospective cohort study from an inpatient postoperative setting showed that Chinese patients required lower opioid doses, yet were more likely to experience opioid-induced pruritus than a matched group of Caucasians.21 Differences in opioid metabolism have been described previously for Asians relative to Caucasians33-35; however, sociocultural factors may also explain disparities in opioid prescribing.36 Future studies are needed to understand whether physicians are less likely to prescribe opioids to Asians because of perceived risks or if Asians are less accepting of these medications. 

In our analysis, Medicaid beneficiaries were more likely than patients with other insurance types to receive opioids, even after controlling for other factors. CMS has reported that these beneficiaries are twice as likely to receive an opioid prescription than non-Medicaid patients.37 Another notable finding was that the number of nonpain medications prescribed was positively associated with an increase in opioid prescribing. This is contrary to expectations, but may be related to higher levels of comorbidity in patients who receive opioids. Further investigation of this finding is required.

To our knowledge, this is the first study to evaluate opioid prescribing across a range of conditions with distinct CP categories. We analyzed data from a large ambulatory care cohort and used rigorous methods to classify and identify patients with painful chronic conditions. Furthermore, data were derived from a mixed-payer organization with no single formulary, making it an appropriate setting for evaluating patterns in opioid prescribing. 

Limitations 

This was a cross-sectional analysis and causal inferences are restricted. Also, the study population was from a relatively small geographic area and generalizability to other parts of the United States is unknown; however, as a mixed-payer healthcare system, the setting is like many others in the nation. The findings of this study are reliant on the accuracy of, and frequency at which physicians document, information in the EHR. Because pharmacy data were not available on the majority of the population, we relied on prescribing data, meaning we cannot know what medications patients actually filled or consumed. We also cannot know whether nonanalgesic medications were prescribed to treat pain or comorbid conditions, such as epilepsy, depression, or anxiety. We did not specifically collect information on the type of provider who prescribed the drug, as the focus of this study was not on provider-level attributes of opioid prescribing. Lastly, we did not have information on over-the-counter medications, such as NSAIDs or acetaminophen, which were potentially used by patients to treat CP and may have influenced whether a prescription pain medication was warranted. 

CONCLUSIONS 

In this cross-sectional analysis in an ambulatory healthcare setting, opioid prescribing to patients varied by type of CP condition. The prevalence of receiving an opioid increased linearly with the number of CP conditions. Opioid prescriptions for men, those with back/cervical pain, and Medicaid beneficiaries were particularly prevalent. The identification of populations likely to receive an opioid for CP should be of interest to healthcare systems to ensure these drugs are used appropriately and safely.

Author Affiliations: Palo Alto Medical Foundation Research Institute (RJR), Palo Alto, CA; Sutter Health (RJR, TJ, DYI), Sacramento, CA; Pfizer, Inc (LI, BL, TC, JCC), New York, NY.

Source of Funding: This study was sponsored by Pfizer; Sutter Health received financial support from Pfizer in connection with this study and the development of this manuscript.

Author Disclosures: Dr Romanelli and Mr Jukes are employees of Sutter Health and paid consultants to Pfizer in connection with this study and the development of this manuscript. This study was funded by a grant from Pfizer. Dr Ishisaka was an employee of Sutter Health at the time the study was conducted and is currently an employee of Blue Shield of California. Drs Ikeda, Lynch, Craig, and Cappelleri are employees of Pfizer. 

Authorship Information: Concept and design (JCC, TC, DYI, LI, TJ, BL, RJR); acquisition of data (TJ, RJR); analysis and interpretation of data (JCC, TC, DYI, BL, LI, TJ, RJR); drafting of the manuscript (TC, TJ, RJR); critical revision of the manuscript for important intellectual content (JCC, TC, DYI, LI, BL, RJR); statistical analysis (JCC, RJR); provision of patients or study materials (); obtaining funding (TC, LI); administrative, technical, or logistic support (TC, BL); and supervision (BL). 

Address Correspondence to: Robert J. Romanelli, PhD, MPH, Palo Alto Medical Foundation Research, 795 El Camino Real, Ames Bldg, Palo Alto, CA 94301. E-mail: romanellir@pamfri.org. 
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