The prevalence of diagnosed opioid abuse in commercial and Medicare managed care populations

Role of primary care in opioid prescribing for older head and neck cancer survivors

BACKGROUND

Older head and neck cancer (HNC) survivors have concerning rates of potentially unsafe opioid prescribing. Identifying the specialties of opioid prescribers for HNC survivors is critical for targeting the settings for opioid safety interventions. This study hypothesized that oncology and surgery providers are primarily responsible for opioid prescriptions in the year after treatment but that primary care providers (PCPs) are increasingly involved in prescribing over time.

METHODS

Using linked Surveillance, Epidemiology, and End Results-Medicare data, a retrospective analysis was conducted of adults aged >65 years diagnosed between 2014 and 2017 with stage I-III HNC and who had ≥6 months of treatment-free follow-up through 2019. Starting at treatment completion, opioid fills were assigned to a prescriber specialty: oncology, surgery, primary care, pain management, or other. Prescriber patterns were summarized for each year of follow-up. Multinomial logistic regression models captured the likelihood of opioids being prescribed by each specialty.

RESULTS

Among 5135 HNC survivors, 2547 (50%) had ≥1 opioid fill (median, 2.1-year follow-up). PCPs prescribed 47% of all fills (42%-55% each year). PCPs prescribed opioids to 45% of survivors with ≥1 opioid fill, which was a greater share than other specialties. PCPs prescribed longer supplies of opioids (median, 20 days/fill; median, 30 days/year) than oncologists or surgeons. The likelihood of an opioid being prescribed by an oncology provider was four times lower than that of it being prescribed by a PCP.

CONCLUSIONS

PCP involvement in opioid prescribing remains high throughout HNC survivorship. Interventions to improve the safety of opioid prescribing should target primary care, as is typical for opioid reduction efforts in the noncancer population.

Opioid Prescribing by Emergency Physicians: Trends Study of Medicare Part D Prescriber Data 2013-2019

BACKGROUND

Emergency physicians play a critical role in mitigating the opioid epidemic in public health.

OBJECTIVES

To analyze the prescribing of emergency physicians for opioids among Medicare beneficiaries enrolled in the Part D program from 2013 to 2019.

METHODS

We conducted a retrospective, cross-sectional, descriptive analysis of Medicare Part D prescriber data, focusing on opioid claims between 2013 and 2019. The primary outcome variables evaluated included proportion of opioid claims, trends of the most prescribed opioids, cost of opioid claims, and days' supply per claim.

RESULTS

A total of 63,586 emergency physicians were identified over the study period. Opioid prescription by emergency physicians decreased from 14.45% to 11.55%, and the cost spent on opioid drugs declined by 50%. The use of drugs such as hydrocodone-acetaminophen and oxycodone-acetaminophen declined substantially, whereas tramadol and acetaminophen-codeine prescription increased. The opioid prescribing rate and days' supply also decreased.

CONCLUSIONS

The decline in traditional opioid agents such as hydrocodone-acetaminophen was partly offset by an increase in opioids like tramadol, which carry additional potential adverse events. Opioid prescribing rate, average days' supply, and cost of opioid drugs significantly decreased from 2015 to 2019, after a spike in 2015. All regions observed a decrease in emergency physicians, but opioid prescribing rates varied across regions. These trends highlight successful opioid stewardship practices in some areas and the need for further development in others. This information can aid in designing tailored guidelines and policies for emergency physicians to promote effective opioid stewardship practices.

Detecting Problematic Opioid Use in the Electronic Health Record: Automation of the Addiction Behaviors Checklist in a Chronic Pain Population

Importance

Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Large data sets, such as electronic health records, are required for conducting studies that assist with identification and management of problematic opioid use.

Objective

Determine whether regular expressions, a highly interpretable natural language processing technique, could automate a validated clinical tool (Addiction Behaviors Checklist1) to expedite the identification of problematic opioid use in the electronic health record.

Design

This cross-sectional study reports on a retrospective cohort with data analyzed from 2021 through 2023. The approach was evaluated against a blinded, manually reviewed holdout test set of 100 patients.

Setting

The study used data from Vanderbilt University Medical Center's Synthetic Derivative, a de-identified version of the electronic health record for research purposes.

Participants

This cohort comprised 8,063 individuals with chronic pain. Chronic pain was defined by International Classification of Disease codes occurring on at least two different days.18 We collected demographic, billing code, and free-text notes from patients' electronic health records.

Main Outcomes and Measures

The primary outcome was the evaluation of the automated method in identifying patients demonstrating problematic opioid use and its comparison to opioid use disorder diagnostic codes. We evaluated the methods with F1 scores and areas under the curve - indicators of sensitivity, specificity, and positive and negative predictive value.

Results

The cohort comprised 8,063 individuals with chronic pain (mean [SD] age at earliest chronic pain diagnosis, 56.2 [16.3] years; 5081 [63.0%] females; 2982 [37.0%] male patients; 76 [1.0%] Asian, 1336 [16.6%] Black, 56 [1.0%] other, 30 [0.4%] unknown race patients, and 6499 [80.6%] White; 135 [1.7%] Hispanic/Latino, 7898 [98.0%] Non-Hispanic/Latino, and 30 [0.4%] unknown ethnicity patients). The automated approach identified individuals with problematic opioid use that were missed by diagnostic codes and outperformed diagnostic codes in F1 scores (0.74 vs. 0.08) and areas under the curve (0.82 vs 0.52).

Conclusions and Relevance

This automated data extraction technique can facilitate earlier identification of people at-risk for, and suffering from, problematic opioid use, and create new opportunities for studying long-term sequelae of opioid pain management.

Two data-driven approaches to identifying the spectrum of problematic opioid use: A pilot study within a chronic pain cohort

BACKGROUND

Although electronic health records (EHR) have significant potential for the study of opioid use disorders (OUD), detecting OUD in clinical data is challenging. Models using EHR data to predict OUD often rely on case/control classifications focused on extreme opioid use. There is a need to expand this work to characterize the spectrum of problematic opioid use.

METHODS

Using a large academic medical center database, we developed 2 data-driven methods of OUD detection: (1) a Comorbidity Score developed from a Phenome-Wide Association Study of phenotypes associated with OUD and (2) a Text-based Score using natural language processing to identify OUD-related concepts in clinical notes. We evaluated the performance of both scores against a manual review with correlation coefficients, Wilcoxon rank sum tests, and area-under the receiver operating characteristic curves. Records with the highest Comorbidity and Text-based scores were re-evaluated by manual review to explore discrepancies.

RESULTS

Both the Comorbidity and Text-based OUD risk scores were significantly elevated in the patients judged as High Evidence for OUD in the manual review compared to those with No Evidence (p = 1.3E-5 and 1.3E-6, respectively). The risk scores were positively correlated with each other (rho = 0.52, p < 0.001). AUCs for the Comorbidity and Text-based scores were high (0.79 and 0.76, respectively). Follow-up manual review of discrepant findings revealed strengths of data-driven methods over manual review, and opportunities for improvement in risk assessment.

CONCLUSION

Risk scores comprising comorbidities and text offer differing but synergistic insights into characterizing problematic opioid use. This pilot project establishes a foundation for more robust work in the future.

Provider Continuity in the Prescribing of Buprenorphine/Naloxone Within Medicare Part D

OBJECTIVES

Efforts to improve buprenorphine access for opioid use disorder have focused on increasing the number of waivered providers. However, it is unknown how efforts to increase initial prescribing result in a sustained pool of prescribers. We examine the prevalence of year-to-year provider-level buprenorphine prescribing, and provider- and state-level factors associated with provider continuity.

METHODS

Providers prescribing buprenorphine/naloxone within the Medicare Part D claims database were evaluated from 2013 to 2017 with prescriber continuity measured as prescriptions made in consecutive years from the same provider (N = 14,222 unique providers; 6670 in 2013).

RESULTS

The number of providers prescribing buprenorphine/naloxone within Medicare Part D increased from 2013 to 2017. The majority of providers prescribed buprenorphine/naloxone to 10 or fewer beneficiaries. Approximately 84% of providers prescribing buprenorphine/naloxone in 1 year prescribed it in the following year. Continuous prescribing from 2013 to 2017 was 59.4%, which was 86% the rate of a comparator chronic health medication (ie, lisinopril). Survival analyses indicated that female providers (adjusted hazard ratios [AHR] = 1.30, P < 0.001) and clinical neuroscience specialties such as psychiatry (AHR = 1.21, P < 0.001) exhibited greater discontinuation rates, whereas those with higher buprenorphine/naloxone beneficiary loads (AHR = 0.50, P < 0.001) and in states with a greater increase in overdose mortality rates (AHR = 0.88, P < 0.05) showed lower discontinuation rates.

CONCLUSIONS

These data support evidence that providers who begin prescribing buprenorphine continue prescribing, although short of maximum capacity. Efforts to help providers become waivered, understand the impact of overdose fatalities in their area, and prescribe to multiple patients are likely to generate an enduring positive contribution to the number of treated patients.

Removal of prior authorization for medication-assisted treatment: impact on opioid use and policy implications in a Medicare Advantage population

BACKGROUND: More than 30% of Medicare beneficiaries and 40% of patients dually eligible for Medicare and Medicaid use opioids. With an estimated 8%-12% of patients developing an opioid use disorder (OUD) after initiating opioids, opioid misuse is a significant public health challenge, especially among high-risk Medicare populations. Medication-assisted treatment (MAT) is the use of medications for the treatment of OUD and to prevent relapse to opioid use. MAT is the most effective treatment for OUD. There are a variety of barriers to MAT therapy that may delay access to treatment. OBJECTIVE: To study the impact of the removal of prior authorization requirements for MAT medications on MAT utilization, opioid utilization, and clinical outcomes, including emergency department visits, inpatient admission, relapse rates, behavioral health services, and nonopioid pain medication utilization, among opioid-using individuals with Medicare Advantage Prescription Drug (MAPD) coverage. METHODS: This retrospective, cross-sectional study used administrative medical, pharmacy, and enrollment data to identify chronic opioid users and a subset cohort initiating MAT use in 2017, when prior authorization requirements were in effect, and 2018 after removal of prior authorization requirements. Opioid and MAT utilization and clinical outcomes from emergency department visits were also examined before and after prior authorization requirements. A logistic regression analysis was conducted to examine the impact of the policy change on relapse rates, comparing relapse rates in 2017 and 2018, after controlling for potentially confounding demographic and clinical factors. RESULTS: This policy change was followed by a decrease in opioid utilization, an increase in MAT initiation, and a 4% decline in relapse rates. Patients initiating MAT after removal of prior authorizations had a 19% decrease in likelihood of relapse, and those with an OUD diagnosis were 47% less likely to relapse. The majority of MAT recipients were aged younger than 65 years, had a mental or behavioral health disorder diagnosis, and initially used relatively low doses (< 90 MME) of prescription opioids. There were no statistically significant differences in the use of behavioral health services or the use of nonopioid medications from 2017 to 2018. CONCLUSIONS: Utilization management policies should ensure appropriate MAT use, while minimizing impediments to access. Providing patients with evidence-based therapy effective for the treatment of OUD is essential to patient recovery and combating the consequences of the opioid epidemic. Further strides are needed to eliminate additional obstacles to OUD care. DISCLOSURES: No outside funding supported this study. All authors are or were employees of Humana, Inc., at the time of the study and have no other potential conflicts of interest to disclose.

The Influence of an Opioid Use Disorder on Initiating Physical Therapy for Low Back Pain: A Retrospective Cohort

OBJECTIVES

Low back pain (LBP) is common among patients with an opioid use disorder (OUD). The extent to which patients with an OUD initiate physical therapy for LBP is unknown. The aim of this study was to examine the association between a history of an OUD and initiation of physical therapy for LBP within 60 days of a primary care provider (PCP) visit for this condition.

METHODS

Claims from a single state-wide all payer claims database from June 30, 2013 and August 31, 2015 were used to establish a retrospective cohort of patients who consulted a PCP for a new episode of LBP. The outcome measure was patients who had at least 1 physical therapy claim within 60-days after the PCP visit. After propensity score matching on covariates, logistic regression was used to compare the outcome of patients with a history of an OUD to patients without an OUD.

RESULTS

Propensity score matching resulted in 1360 matched pairs of participants. The mean age was 47.2 years (15.9) and 55.9% were female. Compared to patients without an OUD, patients with an OUD were less likely to initiate physical therapy for LBP (adjusted odds ratio  = 0.65, 95% confidence intervals:0.49-0.85).

CONCLUSIONS

After a visit to a PCP for a new episode of care for LBP, patients with a history of an OUD are less likely to initiate physical therapy.

Trends in chronic opioid therapy among survivors of head and neck cancer

BACKGROUND

Survivors of head and neck cancer (HNC) have increased risk of opioid misuse.

METHODS

Using Surveillance, Epidemiology and End-Results-Medicare data, we matched adults ≥66 years diagnosed with HNC 2008-2015 with cancer-free controls. We computed odds ratios (OR) for receipt of chronic opioid therapy (COT, claims for ≥90 consecutive days) for HNC survivors compared to controls each year after matching through 2016.

RESULTS

The cohort of HNC survivors declined from 5107 in the first year after diagnosis to 604 in the sixth year after diagnosis. For 5 years, rates of COT among HNC survivors exceeded that of controls. Differences between survivors and controls declined each year (ORs: year 1, 4.36; year 2, 2.60; year 3, 2.18; year 4, 1.85; and year 5, 1.35; all P-values <.05).

CONCLUSIONS

Among older HNC survivors, cancer-associated opioid use in the first years after diagnosis suggests that the benefit of opioids must balance the risk of opioid misuse.

Association between Opioid Prescribing in Medicare and Pharmaceutical Company Gifts by Physician Specialty

BACKGROUND

The association between pharmaceutical industry promotion and physician opioid prescribing is poorly understood. Whether the influence of industry gifts on prescribing varies by specialty is unknown.

OBJECTIVE

To examine the relationship between opioid-related gifts to physicians and opioid prescribing in the subsequent year across 7 physician specialties.

DESIGN

Panel study using data from 2014 to 2016.

PARTICIPANTS

236,103 unique Medicare Part D physicians (389,622 physician-years) who received any gifts from pharmaceutical companies measured using Open Payments and prescribed opioids in the subsequent year.

MAIN MEASURES

Amounts paid by pharmaceutical companies for opioid-related gifts including meals and lodging; quartile of opioid prescribing as a percent of total prescribing compared with other same-specialty physicians.

KEY RESULTS

In 2014-2015, 14.1% of physician received opioid-related gifts from the industry with 2.6% receiving > $100. Gifts varied by specialty and were concentrated among two pharmaceutical companies responsible for 60% of the value of opioid-related gifts. Receiving opioid-related gifts was associated with greater prescribing of opioids compared with same-specialty physicians in the next year. Primary care physicians are nearly 3.5 times as likely to be in the highest quartile of prescribing versus the lower quartiles if they were paid ≥ $100. Psychiatrists and neurologists were 7 to 13 times as likely to be in a higher quartile of opioid prescribing compared with colleagues who were paid $0 in the preceding year.

CONCLUSIONS

The value of opioid-related gifts given to physicians varies substantially by provider specialty, as does the relationship between payment amounts and prescriber behavior in the following year.

Exploratory descriptive analysis of opioid prescribing prevalence of nurse practitioners and the specialties associated with the top prescribers

BACKGROUND

Opioid prescription drug abuse is increasingly becoming a concern beyond the United States. Little is known regarding nurse practitioners' opioid prescribing patterns or settings.

AIM

To examine nurse practitioners' opioid prescription patterns.

METHODS

We conducted a retrospective cross-sectional descriptive study of the 2016 Medicare Part D Prescriber Public Use File and analysed the association between the number of nurse practitioners and the number of opioid prescriptions. We conducted Web searches on the top 1% of prescribers to obtain the specialty areas in which nurse practitioners worked.

RESULTS

There was no significant correlation between the prevalence of nurse practitioners and the opioid prescription rates among the states in the United States. Most nurse practitioners do not prescribe opioids. Opioid prescription is highly concentrated among nurse practitioners, as 1% of nurse practitioners account for one third of opioids prescribed by nurse practitioners. Most of the top 1% opioid prescribers practice in specialty care with board-certified pain medicine physicians.

CONCLUSIONS

The prevalence of nurse practitioners is not likely a significant contributing factor to the opioid epidemic. Rather than increased scrutiny of opioid prescribing, a better approach to curb the opioid crisis might be to facilitate collaboration among physicians, nurse practitioners and patients.

Preexisting Opioid Use Disorder and Outcomes After Lower Extremity Arthroplasty: A Multistate Analysis, 2007–2014

Objective

The aim of this study was to examine the association of preexisting opioid use disorder and postoperative outcomes in patients undergoing total hip or knee arthroplasty (THA and TKA, respectively) in the overall population and in the Medicare-only population.

Methods

This retrospective cohort study examined data from the State Inpatient Databases of the Healthcare Cost and Utilization Project for the years 2007–2014 from California, Florida, New York, Maryland, and Kentucky. We compared patients with and without opioid use disorders on unadjusted rates and calculated adjusted odds ratios (aORs) of in-hospital mortality, postoperative complications, length of stay, and 30-day and 90-day readmission status; analyses were repeated in a subgroup of Medicare insurance patients only.

Subjects

After applying our exclusion criteria, our study included 1,422,210 adult patients undergoing lower extremity arthroplasties, including 818,931 Medicare insurance patients. In our study, 0.4% of THA patients and 0.3% of TKA patients had present-on-admission opioid use disorder.

Results

Opioid use disorder patients were at higher risk for in-hospital mortality (aOR = 3.10), 30- and 90-day readmissions (aORs = 1.81, 1.81), and pulmonary and infectious complications (aORs = 1.25, 1.96).

Conclusions

Present-on-admission opioid use disorder was a risk factor for worse postoperative outcomes and increased health care utilization in the lower extremity arthroplasty population. Opioid use disorder is a potentially modifiable risk factor for mortality, postoperative complications, and health care utilization, especially in the at-risk Medicare population.

Documented opioid use disorder and its treatment in primary care patients across six U.S. health systems

BACKGROUND

The United States is in the middle of an opioid overdose epidemic, and experts are calling for improved detection of opioid use disorders (OUDs) and treatment with buprenorphine or extended release (XR) injectable naltrexone, which can be prescribed in general medical settings. To better understand the magnitude of opportunities for treatment among primary care (PC) patients, we estimated the prevalence of documented OUD and medication treatment of OUD among PC patients.

METHODS

This cross-sectional study included patients with ≥2 visits to PC clinics across 6 healthcare delivery systems who were ≥16 years of age during the study period (fiscal years 2014-2016). Diagnoses, prescriptions, and healthcare utilization were ascertained from electronic health records and insurance claims (5 systems that also offer health insurance). Documented OUDs were defined as ≥1 International Classification of Diseases code for OUDs (active or remission), and OUD treatment was defined as ≥1 prescription(s) for buprenorphine formulations indicated for OUD or naltrexone XR, during the 3-year study period. The prevalence of documented OUD and treatment (95% confidence intervals) across health systems were estimated, and characteristics of patients by treatment status were compared. Prevalence of OUD and OUD treatment were adjusted for age, gender, and race/ethnicity. Combined results were also adjusted for site.

RESULT

Among 1,403,327 eligible PC patients, 54-62% were female and mean age ranged from 46 to 51 years across health systems. The 3-year prevalence of documented OUD ranged from 0.7-1.4% across the health systems. Among patients with documented OUD, the prevalence of medication treatment (primarily buprenorphine) varied across health systems: 3%, 12%, 16%, 20%, 22%, and 36%.

CONCLUSION

The prevalence of documented OUD and OUD treatment among PC patients varied widely across health systems. The majority of PC patients with OUD did not have evidence of treatment with buprenorphine or naltrexone XR, highlighting opportunities for improved identification and treatment in medical settings. These results can inform initiatives aimed at improving treatment of OUD in PC. Future research should focus on why there is such variation and how much of the variation can be addressed by improving access to medication treatment.

Prevalence and treatment of opioid use disorders among primary care patients in six health systems

BACKGROUND

The U.S. experienced nearly 48,000 opioid overdose deaths in 2017. Treatment of opioid use disorder (OUD) with buprenorphine is a recommended part of primary care, yet little is known about current U.S. practices in this setting. This observational study reports the prevalence of documented OUD and OUD treatment with buprenorphine among primary care patients in six large health systems.

METHODS

Adults with ≥2 primary care visits during a three-year period (10/1/2013-9/30/2016) in six health systems were included. Data were obtained from electronic health record and claims data, with measures, assessed over the three-year period, including indicators for documented OUD from ICD 9 and 10 codes and OUD treatment with buprenorphine. The prevalence of OUD treatment was adjusted for age, gender, race/ethnicity, and health system.

RESULTS

Among 1,368,604 primary care patients, 13,942 (1.0 %) had documented OUD, and among these, 21.0 % had OUD treatment with buprenorphine. For those with documented OUD, the adjusted prevalence of OUD treatment with buprenorphine varied across demographic and clinical subgroups. OUD treatment was lower among patients who were older, women, Black/African American and Hispanic (compared to white), non-commercially insured, and those with non-cancer pain, mental health disorders, greater comorbidity, and more opioid prescriptions, emergency department visits or hospitalizations.

CONCLUSIONS

Among primary care patients in six health systems, one in five with an OUD were treated with buprenorphine, with disparities across demographic and clinical characteristics. Less buprenorphine treatment among those with greater acute care utilization highlights an opportunity for systems-level changes to increase OUD treatment.

Analysis of psychiatrists' prescription of opioid, benzodiazepine, and buprenorphine in Medicare Part D in the United States

INTRODUCTION

The opioid epidemic is a severe problem in the world, especially in the United States, where prescription opioid overdose accounts for a quarter of drug overdose deaths.

OBJECTIVE

To describe psychiatrists' prescription of opioid, benzodiazepine, and buprenorphine in the United States.

METHODS

We conducted a retrospective cross-sectional study of the 2016 Medicare Part D claims data and analyzed psychiatrists' prescriptions of: 1) opioids; 2) benzodiazepines, whose concurrent prescription with opioids can cause overdose death; 3) buprenorphine, a partial opioid agonist for treating opioid addiction; 4) and naltrexone microsphere, a once-monthly injectable opioid antagonist to prevent relapse to opioid dependence. Prescribers with 11 or more claims were included in the analysis.

RESULTS

In Medicare Part D in 2016, there were a total of 1,131,550 prescribers accounting for 1,480,972,766 total prescriptions and 78,145,305 opioid prescriptions, including 25,528 psychiatrists (2.6% of all prescribers) accounting for 44,684,504 total prescriptions (3.0% of all prescriptions) and 131,115 opioid prescriptions (0.2% of all opioid prescriptions). Psychiatrists accounted for 17.3% of benzodiazepine, 16.3% of buprenorphine, and 33.4% of naltrexone microsphere prescriptions. The opioid prescription rate of psychiatrists was much lower than that of all prescribers (0.3 vs 5.3%). The buprenorphine prescription rate of psychiatrists was much higher than that of all prescribers (2.3 vs. 0.1%). There was a substantial geographical variation across the United States.

CONCLUSIONS

The results show that, proportionally, psychiatrists have lower rates of opioid prescription and higher rates of benzodiazepine and buprenorphine prescription.

Trends in prior receipt of prescription opioid or adjuvant analgesics among patients with incident opioid use disorder or opioid-related overdose from 2006 to 2016

BACKGROUND

With increasing efforts to scrutinize and reduce opioid prescribing, limited data exist on the recent trend in receipt of prescription pain medications before diagnosis of opioid use disorder (OUD) or opioid-related overdose (OD).

METHODS

Using 2005-2016 Truven MarketScan Commercial Claims databases, we assessed trends in annual 1) incidence of OUD or OD and 2) prevalence of receipt of prescription opioids or four commonly-prescribed adjuvant analgesics among patients newly diagnosed with OUD/OD. Trends were examined in the overall sample and by 3 age groups, including youths (≤18 years), adults (19-64 years), and older adults (≥65 years).

RESULTS

The incidence of diagnosed OUD or OD increased more than 3-fold from 4.99 to 23.81 per 10,000 persons from 2006 to 2016, with the highest increase (14.18-fold) seen in older adults, followed by adults (3.53-fold), and youths (0.16-fold). Between 2006 and 2016, the proportion of patients with incident OUD/OD who received anticonvulsant adjuvant analgesics in the year before diagnosis increased (from 23.4% to 34.3% [P-trend = .005]) whereas the proportion receiving high-dose prescriptions opioids decreased (from 45.5% to 34.8% [P-trend =< .001]). A decreasing trend was observed in general for tricyclic antidepressants and serotonin and norepinephrine reuptake inhibitors.

DISCUSSION

In US commercially insured patients newly diagnosed with OUD/OD, receipt of high-dose opioid prescriptions preceding the diagnosis decreased over time, paralleled by increased use of anticonvulsants commonly prescribed for pain conditions. Further investigations are warranted to understand how prescribed and anticonvulsants contribute to the development of OUD/OD.

Association Between Preoperative Opioid and Benzodiazepine Prescription Patterns and Mortality After Noncardiac Surgery

Importance

The number of patients prescribed long-term opioids and benzodiazepines and complications from their long-term use have increased. Information regarding the perioperative outcomes of patients prescribed these medications before surgery is limited.

Objective

To determine whether patients prescribed opioids and/or benzodiazepines within 6 months preoperatively would have greater short- and long-term mortality and increased opioid consumption postoperatively.

Design, Setting, and Participants

This retrospective, single-center, population-based cohort study included all patients 18 years or older, undergoing noncardiac surgical procedures at a national hospital in Iceland from December 12, 2005, to December 31, 2015, with follow-up through May 20, 2016. A propensity score-matched control cohort was generated using individuals from the group that received prescriptions for neither medication class within 6 months preoperatively. Data analysis was performed from April 10, 2018, to March 9, 2019.

Exposures

Patients who filled prescriptions for opioids only, benzodiazepines only, both opioids and benzodiazepines, or neither medication within 6 months preoperatively.

Main Outcomes and Measures

Long-term survival compared with propensity score-matched controls. Secondary outcomes were 30-day survival and persistent postoperative opioid consumption, defined as a prescription filled more than 3 months postoperatively.

Results

Among 41 170 noncardiac surgical cases in 27 787 individuals (16 004 women [57.6%]; mean [SD] age, 56.3 [18.8] years), a preoperative prescription for opioids only was filled for 7460 cases (17.7%), benzodiazepines only for 3121 (7.4%), and both for 2633 (6.2%). Patients who filled preoperative prescriptions for either medication class had a greater comorbidity burden compared with patients receiving neither medication class (Elixhauser comorbidity index >0 for 16% of patients filling prescriptions for opioids only, 22% for benzodiazepines only, and 21% for both medications compared with 14% for patients filling neither). There was no difference in 30-day (opioids only: 1.3% vs 1.0%; P = .23; benzodiazepines only: 1.9% vs 1.5%; P = .32) or long-term (opioids only: hazard ratio [HR], 1.12 [95% CI, 1.01-1.24]; P = .03; benzodiazepines only: HR, 1.11 [95% CI, 0.98-1.26]; P = .11) survival among the patients receiving opioids or benzodiazepines only compared with controls. However, patients prescribed both opioids and benzodiazepines had greater 30-day mortality (3.2% vs 1.8%; P = .004) and a greater hazard of long-term mortality (HR, 1.41; 95% CI, 1.22-1.64; P < .001). The rate of persistent postoperative opioid consumption was higher for patients filling prescriptions for opioids only (43%), benzodiazepines only (23%), or both (66%) compared with patients filling neither (12%) (P < .001 for all).

Conclusions and Relevance

The findings suggest that opioid and benzodiazepine prescription fills in the 6 months before surgery are associated with increased short-and long-term mortality and an increased rate of persistent postoperative opioid consumption. These patients should be considered for early referral to preoperative clinic and medication optimization to improve surgical outcomes.

An examination of opioid prescription for Medicare Part D patients among family practice prescribers

BACKGROUND

In the USA, opioid overdose accounted for more than 60% of drug overdose deaths in 2015. Of these deaths, 40% were due to use of prescription opioids.

OBJECTIVES

The aims of the study were to (i) study family medicine physician opioid-prescribing rate and duration of prescription, (ii) study the distribution of prescription by medication potency, (iii) study opioid-prescribing trends in health care shortage areas and (iv) study the association between extreme high prescribing rates and medical board discipline.

METHODS

This is a retrospective cross-sectional study of the 2015 Medicare Part D claim data.

RESULTS

Family practitioners have opioid prescription rates (5.6%) similar to medical subspecialists (6.0%), but lower than pain specialists (53.2%) and surgical specialists (36.6%). Family practitioners have an average opioid prescription duration (21.5 days) similar to medical subspecialists (23.1 days) and pain specialists (27.1 days), but longer than surgical specialists (8.9 days). Family practitioners tend to prescribe lower potency opioids. Family practitioners in rural health care shortage areas have a higher opioid prescription rate than other family practitioners (6.5% versus 5.6%). Among the 52 family practitioners who prescribed opioids as frequently as pain specialists, 26 of the 52 (50%) were certified in pain management or worked with a partner certified in pain management. Of the other 26 family practitioners, 3 (12%) had medical board disciplinary actions regarding opioid prescription.

CONCLUSIONS

While monitoring extreme prescribers is important and needs to be continued, the next step in policies to reduce prescription opioids will require systemic change, especially providing support for family practitioners in rural health care shortage areas.

Provider-directed marketing may increase prescribing of medications for opioid use disorder

BACKGROUND

Opioid use disorder (OUD) has become an increasingly grave public health concern, especially in the United States where approximately 80% of the global opioid supply is consumed. Despite greater awareness of the present overdose crisis, potentially life-saving OUD pharmacotherapy (medications for opioid use disorder or MOUD) utilization remains low. This study examines the extent of provider-directed marketing (detailing) for MOUD drugs and identifies any associations between a provider's receipt of detailing and their prescribing of MOUD drugs to Medicare Part D beneficiaries.

METHOD

We combined Open Payments data on all provider-directed payments from pharmaceutical manufacturers with physician-level data on all MOUD prescriptions filled in Medicare Part D. We estimated the adjusted difference in Medicare days supply for all MOUD drugs (collectively) and separately for each MOUD drug that was associated with receipt of payments.

RESULTS

The Open Payments data show that $7.0 million MOUD-specific promotional payments were made by pharmaceutical manufacturers to 12,056 US physicians from 2014 to 2016, which is <1/6th of the $50.3 million made in overall non-MOUD opioid-related promotional payments to 76,992 US physicians during that same period. Prescribers who received any MOUD-specific payments prescribed 1080 daily MOUD-related doses per year more than peers who did not receive any MOUD-specific payments (p < 0.001). The data also show the relatively greater association between receipt of detailing and Suboxone prescriptions compared to Vivitrol.

CONCLUSIONS

Provider-directed marketing by MOUD manufacturers has been found to be significantly and positively associated with incidence of MOUD prescribing in Medicare Part D, as well as with the quantity of MOUD prescribed.

Comparison of implant related complications amongst patients with opioid use disorder and non-users following total knee arthroplasty

BACKGROUND

The influence of opioid use disorder on implant related complications, infection and readmission rates, and total global episode-of-care costs following primary total knee arthroplasty (TKA) is limited.

AIM

To examine whether opioid abuse in patients undergoing primary TKA.

METHODS

A retrospective analysis of the Medicare dataset, using the PearlDiver database, from 2005-2014 comparing outcomes in patients with opioid abusers (OUD) to non-opioid abusers (NOU) undergoing primary TKA was performed. Patient outcomes were analyzed including implant complications, readmission rates, and day-of-surgery and 90-d cost. Statistical analysis was performed with R (University of Auckland, New Zealand) calculating odds-ratio (OR) along with their respective 95% confidence interval (95%CI) and P-values.

RESULTS

The OUD group was at greater odds of having implant related complications overall (20.84% vs 11.25%; OR: 2.07; 95%CI: 1.93-2.23; P < 0.001). Revision (OR: 2.07; 95%CI: 1.11-3.84; P < 0.001), infection (OR: 1.92; 95%CI: 1.72–2.18; P < 0.001), periprosthetic fractures (OR: 1.83; 95%CI: 1.16-4.79; P < 0.001), and 90-d readmission rates (OR: 1.47, 95%CI: 1.35-1.61, P < 0.001) were also significantly increased. OUD patients also incurred in higher day-of-surgery and total global 90-d episode-of-care costs compared to NOU.

CONCLUSION

Patients with OUD show an increased risk of complications compared to the non-opioid users group. Appropriate recognition, pre-surgical optimization, and patient education are essential to mitigate these complications and improve patient outcome.

Trends in Opioid Use Among Older Survivors of Colorectal, Lung, and Breast Cancers

PURPOSE

Cancer survivors may be at increased risk for opioid-related harms. Trends in opioid use over time since diagnosis are unknown.

METHODS

Using data from SEER and Medicare, we conducted multilevel logistic regression analyses to compare chronic opioid use (≥ 90 consecutive days) among opioid-naïve survivors of colorectal, lung, and breast cancers diagnosed from 2008 to 2013 and matched with noncancer controls. Among cases and controls with chronic use, we compared rates of high-dose opioid use (average ≥ 90 morphine milligram equivalents daily).

RESULTS

We included 46,789 survivors and 138,136 noncancer controls. In the first year after the index date (survivor's diagnosis date), chronic use among colorectal and lung cancer survivors exceeded chronic use among controls (colorectal cancer: odds ratio, 1.34; 95% CI, 1.22 to 1.47; lung cancer: odds ratio, 2.55; 95% CI, 2.34 to 2.77). Differences in chronic use between survivors and controls declined each year after the index date. Chronic use among breast cancer survivors was less than that of controls each year after the index date. Survivors with chronic use were more likely to have a high daily dose than controls with chronic use in the first 3 to 5 years.

CONCLUSION

Among three large populations of older cancer survivors, chronic opioid use varied by cancer. However, by 6 years after diagnosis, survivors were no longer more likely to be chronic users than controls. Strategies for appropriate pain management during and after cancer treatment should take into account the risks associated with chronic high-dose opioid use.

County-level access to opioid use disorder medications in medicare Part D (2010-2015)

OBJECTIVE

To identify geographic disparities in access to opioid use disorder (OUD) treatment medications and county demographic and economic characteristics associated with access to buprenorphine and oral naltrexone prescribers in Medicare Part D.

DATA SOURCES/STUDY SETTING

We utilized data from the Medicare Part D Prescription Drug Event Standard Analytic File (2010-2015).

STUDY DESIGN/DATA COLLECTION

We used logistic regression to examine county-level access to OUD medication prescribers.

PRINCIPAL FINDINGS

There was a 5.6 percentage point increase in counties with access to an OUD prescriber over the study period. However, in 2015, 60 percent of US counties lacked access to a Medicare Part D buprenorphine prescriber and over 75 percent lacked access to an oral naltrexone prescriber. Increased access to OUD prescribers was largely concentrated in urban counties. Results of logistic regression indicate regional differences and potential racial disparities in access to OUD prescribers.

CONCLUSIONS

To improve access to buprenorphine and naltrexone treatment for Medicare Part D enrollees, CMS may consider implementing educational and training initiatives focused on OUD treatment, offering training to obtain a buprenorphine waiver at no cost to providers, and sending targeted information to providers in low OUD treatment capacity areas.

The Prevalence and Cost of Medicare Beneficiaries Diagnosed and At Risk for Opioid Abuse, Dependence, and Poisoning

BACKGROUND

Reliance on prescription opioids to manage pain has been associated with increases in diversion, overdose, and addiction. Prevalence of misuse and abuse has been shown to be higher among government-insured populations than commercially insured populations. However, the prevalence and costs of misuse/abuse among the Medicare fee-for-service (FFS) population has not been studied.

OBJECTIVES

To (a) determine the prevalence and costs of prescription opioid misuse/abuse and (b) evaluate the prevalence and costs associated with those identified as at risk for opioid misuse/abuse in Medicare FFS beneficiaries.

METHODS

This retrospective case-control study used Medicare claims data for the calendar years of 2010 and 2011 and included Medicare beneficiaries aged at least 18 years. The index date was the date of first diagnosed misuse/abuse or at risk for abuse and had to occur between July 1, 2010, and June 30, 2011, and beneficiaries had to have at least 6 months continuous eligibility before and after the index date. Matching (1:1) was used for comparing opioid misusers/abusers with nonabuser controls, as well as comparing patients at risk for opioid abuse with controls not at risk for abuse. Controls were matched to cases by gender, age, disability, and geographic region. The index date of the control patient was set equal to the index date of the matched case.

RESULTS

Prevalence of misuse/abuse in the Medicare FFS population was 13.1 per 1,000 persons, with the majority among patients receiving Medicare based on disability (76.2%). The prevalence of at risk for misuse/abuse was 117.4 per 1,000 persons. Approximately half of the Medicare FFS patients used an opioid. Overall total annual unadjusted mean costs of health care resources were significantly greater for abusers than for matched controls ($46,194 vs. $21,964; P < 0.0001), with a mean annual excess cost of $24,230. The overall total adjusted 6-month post-index mean costs of health care resources for abusers was significantly greater than that of matched controls ($33,942 vs. $10,754; P < 0.0001), with a mean excess cost of $23,188.

CONCLUSIONS

The prevalence of diagnosed abuse among Medicare FFS population (13.1 per 1,000 persons) was higher than other payer groups studied using similar ICD-9-CM codes, and the majority of abuse was among those receiving Medicare based on disability (76.2%). The prevalence of at-risk abuse was 9 times higher than the prevalence of diagnosed abuse. As with other studies, health care resource utilization and costs were significantly greater for diagnosed abuse than matched controls.

DISCLOSURES

This study was sponsored by Pfizer. Roland is a Pfizer employee and stockholder and was involved in all aspects of the study as part of a mid-career fellowship in pharmacoeconomics with the University of Utah. Ye and Stevens are employees of University of Utah, and Oderda was an employee of University of Utah, which received financial support from Pfizer in connection with the development of this manuscript. Oderda also reports consulting fees from Pfizer, Trevena, and Pacira, unrelated to this study. The results of this study were presented at the Academy of Managed Care Pharmacy Nexus 2015; October 26-29, 2015; Orlando, FL, and the AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016; April 19-22, 2016; San Francisco, CA.

Incidence of Drug Abuse in Revision Total Knee Arthroplasty Population

Substance abuse can have strong negative impacts on surgical outcomes. Therefore, this study assessed the effects of drug abuse in total knee arthroplasty (TKA) patients. Specifically, we identified revision TKA (RTKA): (1) incidence, (2) causes, (3) time to revision, and (4) patient demographics in patients with a history of drug abuse. The Medicare database within the PearlDiver Supercomputer (Warsaw, IN) was queried to identify 2,159,221 TKAs performed between 2005 and 2012. Drug abuse was subdivided into cocaine, cannabis, opioids, sedatives/hypnotics/anxiolytics (SHA), amphetamines, and alcohol abusers. The effect of drug use on the incidence and cause for RTKA, time to revision, as well as patient demographics were correlated using multivariate, analysis of variance, and regression analyses. There was a significant increase in the number of primary TKAs in cocaine (p = 0.011), cannabis (p < 0.001), opioid (p < 0.001), SHA (p < 0.001), amphetamine (p < 0.001), and alcohol (p < 0.001) users. Amphetamine users had the fastest mean time to revision (691 days, standard deviation: 679 days). At 30-, 90-day, and 6-month postoperative, cocaine had the highest proportion of patients requiring RTKA (7, 12, and 20%, respectively), and at 1-year alcohol abusers (38%, p < 0.001). Infection was the most common cause of revision in all drug abuse/dependent cohorts. Age distributions varied significantly by group for primary TKA (p < 0.001). Comorbidity status was similar in all RTKA patients as determined by comparison of the mean Charlson comorbidity index scores (p = 0.091). Based on these results, drug abuse patients are at increased risk for RTKA. These high-risk patients should, therefore, be appropriately risk stratified and receive comprehensive postoperative pain management.

The Economic Burden of Abuse of Prescription Opioids: A Systematic Literature Review from 2012 to 2017

BACKGROUND

Abuse of prescription opioids [opioid use disorder (OUD), poisoning, and fatal and non-fatal overdose] is a public health and economic challenge that is associated with considerable morbidity and mortality in the USA and globally.

OBJECTIVE

To systematically review and summarize the health economics literature published over the last 5 years that describes the economic burden of abuse of prescription opioids.

METHODS

Findings from searches of databases including MEDLINE, Embase, and Cochrane CENTRAL as well as hand searches of multiple conference abstracts were screened against predefined inclusion criteria to identify studies reporting cost and healthcare resource utilization (HRU) data associated with abuse of prescription opioids.

RESULTS

A total of 49 unique studies were identified. Most of the studies examined direct costs and HRU, which were substantially higher for abusers of prescription opioids than non-abuser controls in several matched cohort analyses (US$20,343-US$28,718 vs US$9716-US$14,079 for mean direct combined annual healthcare costs reported in 6 studies). Although only a small number of studies reported indirect costs, these findings suggest a high societal burden related to productivity losses, absenteeism, morbidity, and mortality among those who abuse opioids. Studies of medication-assisted treatment demonstrated that factors such as adherence, dose, formulation (film or tablet), and relapse during treatment, were associated with direct costs and HRU among treated patients.

CONCLUSIONS

This systematic literature review shows that abuse of prescription opioids is characterized by substantial direct healthcare costs, medical utilization, and related societal costs. Future research should further investigate the indirect costs of opioid abuse.

The Economic Burden of Abuse of Prescription Opioids: A Systematic Literature Review from 2012 to 2017

BACKGROUND

Abuse of prescription opioids [opioid use disorder (OUD), poisoning, and fatal and non-fatal overdose] is a public health and economic challenge that is associated with considerable morbidity and mortality in the USA and globally.

OBJECTIVE

To systematically review and summarize the health economics literature published over the last 5 years that describes the economic burden of abuse of prescription opioids.

METHODS

Findings from searches of databases including MEDLINE, Embase, and Cochrane CENTRAL as well as hand searches of multiple conference abstracts were screened against predefined inclusion criteria to identify studies reporting cost and healthcare resource utilization (HRU) data associated with abuse of prescription opioids.

RESULTS

A total of 49 unique studies were identified. Most of the studies examined direct costs and HRU, which were substantially higher for abusers of prescription opioids than non-abuser controls in several matched cohort analyses (US$20,343-US$28,718 vs US$9716-US$14,079 for mean direct combined annual healthcare costs reported in 6 studies). Although only a small number of studies reported indirect costs, these findings suggest a high societal burden related to productivity losses, absenteeism, morbidity, and mortality among those who abuse opioids. Studies of medication-assisted treatment demonstrated that factors such as adherence, dose, formulation (film or tablet), and relapse during treatment, were associated with direct costs and HRU among treated patients.

CONCLUSIONS

This systematic literature review shows that abuse of prescription opioids is characterized by substantial direct healthcare costs, medical utilization, and related societal costs. Future research should further investigate the indirect costs of opioid abuse.

Trends in Opioid Use and Prescribing in Medicare, 2006-2012

OBJECTIVE

To determine characteristics and trends in opioid use, questionable use, and prescribing in Medicare.

STUDY SETTING

Opioid prescriptions filled through Medicare Part D for beneficiaries with full-year, fee-for-service Medicare coverage during 2006 to 2012.

STUDY DESIGN

Retrospective analysis of a 20 percent sample of Medicare claims data. Estimates are adjusted using multivariable regression analysis.

DATA COLLECTION

Opioid use, opioid abuse, questionable opioid use, and opioid prescribing by specialty.

PRINCIPAL FINDINGS

Opioid use in Medicare was stable from 2006 to 2012 on average. More than 1 in 3 beneficiaries filled an opioid prescription annually; about 1 in 10 were chronic opioid users. The distribution of opioid users shifted in favor of diagnoses often associated with chronic pain. Opioid users were increasingly likely to abuse opioids or display patterns of questionable use from 2006 to 2010, with a slowdown in later years. Average outcomes mask significant variation as the distribution of opioid use widened over the analysis period. Prescribing quantity and intensity varied by specialty. The largest quantity increases were among nurse practitioners and physician assistants.

CONCLUSIONS

Opioid utilization and prescribing are increasingly heterogeneous from 2006 to 2012. Future research should focus on explaining differential trends in utilization and prescribing.

Opioid Prescriptions in Older Medicare Beneficiaries After the 2014 Federal Rescheduling of Hydrocodone Products

OBJECTIVES

To examine how an October 2014 Drug Enforcement Administration policy reclassified hydrocodone product from schedule III to II has affected older adults, who are among the largest consumers of prescription opioids in the United States.

DESIGN

Retrospective cohort study.

SETTING

United States.

PARTICIPANTS

A 20% sample of Medicare Part D beneficiaries aged 65 and older from 2013 through 2015 (> 2,500,000 beneficiaries each year) MEASUREMENTS: From January 2013 to December 2015, we calculated the monthly prevalence of opioid prescriptions and the prevalence of individuals who received prescriptions for a 90-day supply or longer (prolonged), as well as hospitalizations related to opioid toxicity in 2013 and 2015.

RESULTS

From 2013 to 2015, the proportion of Medicare Part D enrollees who received a hydrocodone prescription in a year decreased from 21.9% to 18.3%. Monthly rates for hydrocodone prescriptions declined significantly in 2014. The risk of receiving prolonged opioid prescriptions decreased by approximately 7% in the multivariable analyses comparing 2015 to 2013 (prevalence ratio=0.93, 95% confidence interval (CI)=0.93-0.94). Medicare enrollees with an original entitlement because of disability or with Medicaid eligibility had smaller decreases in prolonged prescriptions and, unexpectedly, small increases in high-dose prescriptions. Opioid-related hospitalizations did not change significantly, but opioid-related hospitalizations without a documented opioid prescription increased (odds ratio=1.24, 95% CI=1.03-1.50).

CONCLUSION

The 2014 change in hydrocodone from schedule III to schedule II was associated with modest decreases in rates of opioid use in the elderly. The unexpected increase in opioid-related hospitalizations without documented opioid prescriptions may represent an increase in illegal use.

Rates and Risk Factors for Opioid Dependence and Overdose after Urological Surgery

PURPOSE

Effective pain management is a critical component of the perioperative process with opioids representing a mainstay of therapy. The opioid epidemic is a growing concern in the United States. The goal of this study was to quantify the risk of opioid dependence or overdose among patients undergoing urological surgery and to identify risk factors of opioid dependence or overdose.

MATERIALS AND METHODS

We retrospectively reviewed data on urological surgery from 2007 to 2011. Data sources included the HCUP (Healthcare Cost and Utilization Project) inpatient, ambulatory surgery and emergency department data sets. Outcomes of postoperative opioid dependence and overdose were identified by previously validated ICD-9 codes. Multivariable logistic regression adjusted for surgical procedure was performed to identify predictors of opioid dependence or overdose following urological surgery.

RESULTS

Overall 675,527 patients underwent urological surgery, of whom 0.09% were diagnosed with opioid dependence or overdose. Patients in whom opioid dependence or overdose developed were younger (median age 51 vs 62 years), carried nonprivate insurance (69.6% vs 66%), underwent an inpatient procedure (81.0% vs 42.4%) and had a longer length of stay (median 3 vs 0 days) and a history of depression (14.4% vs 3.4%) or chronic obstructive pulmonary disease (20.3% vs 8.9%, all p <0.001). On adjusted multivariable analysis these factors remained independent risk factors for opioid dependence or overdose.

CONCLUSIONS

Postoperative opioid dependence or overdose affects 1 of 1,111 urological surgery patients. Risk factors for opioid dependence or overdose included younger age, inpatient surgery and increasing hospitalization duration, baseline depression, tobacco use and chronic obstructive pulmonary disease as well as insurance provider, including Medicaid, Medicare (age less than 65 years) and noninsured status.

Opioid-Prescribing Patterns of Emergency Physicians and Risk of Long-Term Use

BACKGROUND

Increasing overuse of opioids in the United States may be driven in part by physician prescribing. However, the extent to which individual physicians vary in opioid prescribing and the implications of that variation for long-term opioid use and adverse outcomes in patients are unknown.

METHODS

We performed a retrospective analysis involving Medicare beneficiaries who had an index emergency department visit in the period from 2008 through 2011 and had not received prescriptions for opioids within 6 months before that visit. After identifying the emergency physicians within a hospital who cared for the patients, we categorized the physicians as being high-intensity or low-intensity opioid prescribers according to relative quartiles of prescribing rates within the same hospital. We compared rates of long-term opioid use, defined as 6 months of days supplied, in the 12 months after a visit to the emergency department among patients treated by high-intensity or low-intensity prescribers, with adjustment for patient characteristics.

RESULTS

Our sample consisted of 215,678 patients who received treatment from low-intensity prescribers and 161,951 patients who received treatment from high-intensity prescribers. Patient characteristics, including diagnoses in the emergency department, were similar in the two treatment groups. Within individual hospitals, rates of opioid prescribing varied widely between low-intensity and high-intensity prescribers (7.3% vs. 24.1%). Long-term opioid use was significantly higher among patients treated by high-intensity prescribers than among patients treated by low-intensity prescribers (adjusted odds ratio, 1.30; 95% confidence interval, 1.23 to 1.37; P<0.001); these findings were consistent across multiple sensitivity analyses.

CONCLUSIONS

Wide variation in rates of opioid prescribing existed among physicians practicing within the same emergency department, and rates of long-term opioid use were increased among patients who had not previously received opioids and received treatment from high-intensity opioid prescribers. (Funded by the National Institutes of Health.).

Characteristics of High-Cost Patients Diagnosed with Opioid Abuse

BACKGROUND

Prescription opioid abuse is associated with substantial economic burden, with estimates of incremental annual per-patient health care costs of diagnosed opioid abuse exceeding $10,000 in prior literature. A subset of patients diagnosed with opioid abuse has disproportionately high health care costs, but little is known about the characteristics of these patients. 

OBJECTIVE

To describe the characteristics of a subset of patients diagnosed with opioid abuse with disproportionately high health care costs to assist physicians and managed care organizations in targeting interventions at the costliest patients.

METHODS

This retrospective claims data analysis identified patients aged 12 to 64 years diagnosed with opioid abuse/dependence in the OptumHealth Reporting and Insights medical and pharmacy claims database, Quarter 1 (Q1) 1999-Q1 2012. Inclusion criteria required that patients had a diagnosis of opioid abuse during or after Q1 2006, no prior diagnoses of opioid abuse, and continuous non-HMO coverage over an 18-month study period. The study period comprised a 12-month observation period centered on the date of the first opioid abuse diagnosis (index date) and a 6-month baseline period immediately preceding the observation period. Patients in the top 20% of total health care costs in the observation period were classified as "high-cost patients," and the remaining patients were classified as "lower-cost patients." Patient characteristics, comorbidities, health care resource use, and health care costs were compared between high-cost patients and lower-cost patients using chi-square tests for dichotomous variables and Wilcoxon rank-sum tests for continuous variables. In addition, multivariate regression was used to assess the relationship between patient characteristics in the baseline period and total health care costs in the observation period among all patients diagnosed with opioid abuse. 

RESULTS

9,291 patients diagnosed with opioid abuse met the inclusion criteria. The 20% of patients classified as high-cost patients accounted for approximately two thirds of the total health care costs of patients diagnosed with opioid abuse. Compared with lower-cost patients, high-cost patients were older (42.5 vs. 36.1; P  less than  0.001) and more likely to be female (55.9% vs. 42.9%; P  less than  0.001). They had a higher comorbidity burden at baseline, as reflected in the Charlson Comorbidity Index (0.8 vs. 0.2; P  less than  0.001), and rates of conditions such as chronic pulmonary disease (12.9% vs. 5.6%; P  less than  0.001) and mild/moderate diabetes (8.4% vs. 3.4%; P  less than  0.001). High-cost patients also had higher rates of nonopioid substance abuse diagnoses (12.4% vs. 8.9%; P  less than  0.001) and psychotic disorders (26.5% vs. 13.6%; P  less than  0.001). In the observation period, high-cost patients continued to have higher rates of nonopioid substance abuse diagnoses (53.0% vs. 47.2%; P  less than  0.001) and psychotic disorders (67.1% vs. 47.5%; P  less than  0.001). In addition, they had greater medical resource use across all places of service (i.e., inpatient, emergency department, outpatient, drug/alcohol rehabilitation facility, and other) compared with lower-cost patients. The mean observation period health care costs of high-cost patients was $89,177 compared with $11,653 for lower-cost patients (P  less than  0.001). High-cost patients had higher medical costs linked to claims with an opioid abuse diagnosis in absolute terms, but the share of total medical costs attributed to such claims was lower among high-cost patients than among lower-cost patients. While many baseline characteristics were found to have a statistically significant (P  less than  0.05) association with observation period health care costs, only 27.3% of the variation in observation period health care costs was explained by patient characteristics in the baseline period.

CONCLUSIONS

This study found that the costliest patients diagnosed with opioid abuse had high rates of preexisting and concurrent chronic comorbidities and mental health conditions, suggesting potential indicators for targeted intervention and a need for greater awareness and screening of comorbid conditions. Opioid abuse may exacerbate existing conditions and make it difficult for patients to adhere to treatment plans for those underlying conditions. Baseline patient characteristics explained only a small share of the variation in observation period health care costs, however. Future research should explore the degree to which other factors not captured in administrative claims data (e.g., severity of abuse) can explain the wide variation in health care costs among opioid abusers.

Enrollment factors and bias of disease prevalence estimates in administrative claims data

PURPOSE

Considerations for using administrative claims data in research have not been well-described. To increase awareness of how enrollment factors and insurance benefit use may contribute to prevalence estimates, we evaluated how differences in operational definitions of the cohort impact observed estimates.

METHODS

We conducted a cross-sectional study estimating the prevalence of five gastrointestinal conditions using MarketScan claims data for 73.1 million enrollees. We extracted data obtained from 2009 to 2012 to identify cohorts meeting various enrollment, prescription drug benefit, or health care utilization characteristics. Next, we identified patients meeting the case definition for each of the diseases of interest. We compared the estimates obtained to evaluate the influence of enrollment period, drug benefit, and insurance usage.

RESULTS

As the criteria for inclusion in the cohort became increasingly restrictive the estimated prevalence increased, as much as 45% to 77% depending on the disease condition and the definition for inclusion. Requiring use of the insurance benefit and a longer period of enrollment had the greatest influence on the estimates observed.

CONCLUSIONS

Individuals meeting case definition were more likely to meet the more stringent definition for inclusion in the study cohort. This may be considered a form of selection bias, where overly restrictive inclusion criteria definitions may result in selection of a source population that may no longer represent the population from which cases arose.

The Burden of Undiagnosed Opioid Abuse Among Commercially Insured Individuals

OBJECTIVES

Estimate the prevalence and healthcare costs of undiagnosed opioid abuse among commercially insured individuals.

STUDY DESIGN

Retrospective analysis of de-identified pharmacy and medical claims data and publicly-available survey data (no IRB approval required).

METHODS

This study focused on commercially insured individuals. Rates of prescription pain-reliever abuse/dependence ("abuse") among individuals ages ≥12 were calculated using National Survey on Drug Use and Health (NSDUH) public-use data for 2006-2011 and assumed to capture both diagnosed and undiagnosed opioid abuse. Rates of undiagnosed opioid abuse were calculated as the difference between NSDUH rates and published rates of diagnosed opioid abuse. OptumHealth Reporting and Insights claims data were used to estimate the healthcare costs of undiagnosed abuse. Diagnosed abusers ages 12-64 were identified using ICD-9-CM diagnosis codes for opioid abuse/dependence. Pre-diagnosis costs were assumed to be a proxy for undiagnosed opioid abuse costs. The ratio of undiagnosed to diagnosed abuse costs was calculated as the ratio of annual per-patient healthcare costs between pre-diagnosis and post-diagnosis periods.

RESULTS

While rates of diagnosed opioid abuse among commercially insured individuals increased from 0.07% in 2006 to 0.19% in 2011, rates of undiagnosed abuse decreased from 0.42% to 0.38% over the same time period. Annual per-patient healthcare costs of undiagnosed abusers were 69.2% of those of diagnosed abusers.

CONCLUSIONS

Per-patient healthcare costs of undiagnosed abusers among the commercially insured are estimated to be lower than those of diagnosed abusers. However, the higher prevalence of undiagnosed opioid abuse implies that undiagnosed abuse represents a substantial burden to commercial payers.

Effect of rivaroxaban versus warfarin on health care costs among nonvalvular atrial fibrillation patients: observations from rivaroxaban users and matched warfarin users

Introduction

New target-specific oral anticoagulants may have benefits, such as shorter hospital length of stay, compared to warfarin in patients with nonvalvular atrial fibrillation (NVAF). This study aimed to assess, among patients with NVAF, the effect of rivaroxaban versus warfarin on health care costs in a cohort of rivaroxaban users and matched warfarin users.

Methods

Health care claims from the Humana database from 5/2011 to 12/2012 were analyzed. Adult patients newly initiated on rivaroxaban or warfarin with ≥2 atrial fibrillation (AF) diagnoses (The International Classification of Diseases, Ninth Revision, Clinical Modification: 427.31) and without valvular AF were identified. Based on propensity score methods, warfarin patients were matched 1:1 to rivaroxaban patients. Patients were observed up to end of data, end of insurance coverage, death, a switch to another anticoagulant, or treatment nonpersistence. Health care costs [hospitalization, emergency room (ER), outpatient, and pharmacy costs] were evaluated using Lin’s method.

Results

Matches were found for all rivaroxaban patients, and characteristics of the matched groups (n = 2253 per group) were well balanced. Estimated mean all-cause and AF-related hospitalization costs were significantly lower for rivaroxaban versus warfarin patients (all-cause: $5411 vs. $7427, P = 0.047; AF-related: $2872 vs. $4147, P = 0.020). Corresponding estimated mean all-cause outpatient visit costs were also significantly lower, but estimated mean pharmacy costs were significantly higher for rivaroxaban patients ($5316 vs. $2620, P < 0.001). Although estimated mean costs of ER visits were higher for rivaroxaban users compared to those of warfarin users, differences were not statistically significant. Including anticoagulant costs, mean overall total all-cause costs were comparable for rivaroxaban versus warfarin users due to cost offset from a reduction in the number and length of hospitalizations and number of outpatient visits ($17,590 vs. $18,676, P = 0.542).

Conclusion

Despite higher anticoagulant cost, mean overall total all-cause and AF-related cost remains comparable for patients with NVAF treated with rivaroxaban versus warfarin due to the cost offset from reduced health care resource utilization.

Electronic supplementary material

The online version of this article (doi:10.1007/s12325-015-0189-1) contains supplementary material, which is available to authorized users.

Assessment of rescue opioid use in patients with post-bunionectomy pain treated with diclofenac potassium liquid-filled capsules

When used in multimodal analgesia for acute pain, nonsteroidal anti-inflammatory drugs (NSAIDs) may reduce the requirement for opioids during the perioperative period. To provide more insight into pain treatment during the outpatient period, we examined the use of opioid rescue medication (RM) and described the relationship between pain intensity and RM use in patients with acute pain after bunionectomy. Patients received placebo or 25 mg of a liquid-filled capsule version of the NSAID diclofenac potassium (DPLFC; n=188 patients/group) every 6 hours during the 48-hour inpatient period through the end of outpatient dosing on day 4. Opioid RM (hydrocodone/acetaminophen tablets, 5 mg/500 mg) was available as needed, but taken at least 1 hour post-study medication. Fewer patients taking DPLFC versus placebo requested opioid RM during the inpatient period (4.8%-44.7% versus 25.0%-90.4%) and also during the outpatient period (3.7%-16.0% versus 13.1%-46.4%). Moderate or severe pain after surgery (P=0.0307 and P=0.0002, respectively) or at second dose (P=0.0006 and P=0.0002, respectively) was predictive of RM use. Patients taking RM (placebo/DPLFC) reported more adverse events (RM 55.7%/40.6%; no RM 29.4%/26.0%). Most adverse events in the RM group were opioid-related. In summary, this study shows that DPLFC lowers the requirement for opioids, which is associated with a reduction in the occurrence of treatment side effects, while maintaining adequate analgesia for patients with moderate acute pain in both the outpatient and outpatient periods. Patients with more severe pain are more likely to use RM, but they still use fewer opioids when treated with DPLFC. This suggests that multimodal treatment using DPLFC and an opioid may offer an important clinical benefit in the treatment of acute pain, including in the home environment.

Automated prediction of risk for problem opioid use in a primary care setting

Identification of patients at increased risk for problem opioid use is recommended by chronic opioid therapy (COT) guidelines, but clinical assessment of risks often does not occur on a timely basis. This research assessed whether structured electronic health record (EHR) data could accurately predict subsequent problem opioid use. This research was conducted among 2,752 chronic noncancer pain patients initiating COT (≥70 days' supply of an opioid in a calendar quarter) during 2008 to 2010. Patients were followed through the end of 2012 or until disenrollment from the health plan, whichever was earlier. Baseline risk indicators were derived from structured EHR data for a 2-year period prior to COT initiation. Problem opioid use after COT initiation was assessed by reviewing clinician-documented problem opioid use in EHR clinical notes identified using natural language processing techniques followed by computer-assisted manual review of natural language processing-positive clinical notes. Multivariate analyses in learning and validation samples assessed prediction of subsequent problem opioid use. The area under the receiver operating characteristic curve (c-statistic) for problem opioid use was .739 (95% confidence interval = .688, .790) in the validation sample. A measure of problem opioid use derived from a simple weighted count of risk indicators was found to be comparably predictive of the natural language processing measure of problem opioid use, with 60% sensitivity and 72% specificity for a weighted count of ≥4 risk indicators.

PERSPECTIVE

An automated surveillance method utilizing baseline risk indicators from structured EHR data was moderately accurate in identifying COT patients who had subsequent problem opioid use.

The economic burden of diagnosed opioid abuse among commercially insured individuals

The abuse of prescription opioids imposes a substantial public health and economic burden. Recent research using administrative claims data has substantiated the prevalence and cost of opioid abuse among commercially insured individuals. Although administrative claims data are readily available and have been used to effectively answer research questions about the burden of illness for many different conditions, an important issue is the reliability, replicability, and generalizability of estimates derived from different databases. Therefore, this study sought to assess whether the findings of a recently published study of opioid abuse in a commercial claims database (original analysis) could be replicated in a different commercial claims database. The original analysis, which analyzed the prevalence and excess health care costs of diagnosed opioid abuse in the OptumHealth Reporting and Insights Database, was replicated by applying the same approach to the Truven MarketScan Commercial Claims and Encounters Database (replication analysis). In the replication analysis, the prevalence of diagnosed opioid abuse increased steadily from 15.8 diagnosed opioid abusers per 10,000 in 2009, to 26.6 diagnosed opioid abusers per 10,000 in 2012. Although the prevalence of diagnosed opioid abuse was higher than reported in the original analysis, the trend of increasing prevalence over time was consistent across analyses. Additionally, diagnosed abusers had excess annual per patient health care costs of $11,376 in the replication analysis, which was consistent with the excess annual per patient health care costs of diagnosed abuse of $10,627 reported in the original analysis. The replication analysis also found an upward trend in the prevalence of diagnosed opioid abuse over time and substantial excess annual per patient health care costs of diagnosed opioid abuse among commercially insured individuals, suggesting that these findings are generalizable to other commercially insured populations.