biostatistic

Differences in Opioid Prescribing Among Generalist Physicians,

Nurse Practitioners, and Physician Assistants

Michael I. Ellenbogen, MD,* and Jodi B. Segal, MD, MPH* ,†

*Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland; †Department of Health

Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA

Correspondence to: Michael Ellenbogen, MD, 600 N. Wolfe St, Meyer 8-134P, Baltimore, MD 21287, USA. Tel: 443-287-4362; Fax: 443-502-0923;

E-mail: [email protected].

Funding sources: We would like to acknowledge support for the statistical analysis from the National Center for Research Resources and the National

Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health through grant number 1UL1TR001079. Dr. Segal is supported

by the National Institute on Aging, grant K24AG049036.

Disclaimer: The funding source had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; prepa-

ration, review, or approval of the manuscript; or the decision to submit the manuscript for publication. The views expressed in this article are those of

the authors and do not necessarily reflect the position or policy of the National Institute on Aging.

Conflicts of interest: No financial disclosures were reported by the authors of this paper.

Abstract

Objective. To determine if there are differences in opioid prescribing among generalist physicians, nurse practitioners (NPs), and physician assistants (PAs) to Medicare Part D beneficiaries. Design. Serial cross-sectional analysis of pre- scription claims from 2013 to 2016 using publicly available data from the Centers for Medicare and Medicaid Services. Subjects. All generalist physicians, NPs, and PAs who provided more than 10 total prescription claims be- tween 2013 and 2016 were included. These prescribers were subsetted as practicing in a primary care, urgent care, or hospital-based setting. Methods. The main outcomes were total opioid claims and opioid claims as a proportion of all claims in patients treated by these prescribers in each of the three settings of interest. Binomial regression was used to generate marginal estimates to allow comparison of the volume of claims by these prescribers with adjust- ment for practice setting, gender, years of practice, median income of the ZIP code, state fixed effects, and relevant interaction terms. Results. There were 36,999 generalist clinicians (physicians, NPs, and PAs) with at least one year of Part D prescription drug claims data between 2013 and 2016. The number of adjusted total opioid claims across these four years for physicians was 660 (95% confidence interval [CI] ¼ 660–661), for NPs was 755 (95% CI ¼ 753– 757), and for PAs was 812 (95% CI ¼ 811–814). Conclusions. We find relatively high rates of opioid prescribing among NPs and PAs, especially at the upper margins. This suggests that well-designed interventions to improve the safety of NP and PA opioid prescribing, along with that of their physician colleagues, could be especially beneficial.

Key Words: Opioid Prescribing; Nurse Practitioners; Physician Assistant; Primary Care

Introduction

The volume of opioid prescriptions in the United States

has increased dramatically over the last two decades, and

evidence suggests that this has perpetuated opioid mis-

use, addiction, overdose, and drug-related deaths [1,2]. It

should be noted that the rate of death from natural and

semisynthetic opioids (which includes commonly pre-

scribed opioids like hydromorphone, hydrocodone, and

oxycodone) has increased only mildly over the last five

years, whereas deaths from synthetic opioids other than

methadone (including tramadol, pharmaceutical fenta-

nyl, illicitly produced fentanyl, and fentanyl derivatives)

have increased markedly [3]. Specifically, the age-

adjusted rate of drug overdose deaths involving synthetic

opioids other than methadone increased by 45% between

2016 and 2017 [3]. It can be difficult to determine if an

VC 2019 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: [email protected] 1

Pain Medicine, 0(0), 2019, 1–8

doi: 10.1093/pm/pnz005

Original Research Article

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opioid-related death is due to a pharmaceutically or illic-

itly manufactured drug or if the medication was pre-

scribed to the individual or diverted [4].

Over the last few years, there has been evidence of a

mild reversal in the trend [2,5]. The most recent Centers

for Disease Control and Prevention (CDC) report in July

2017 showed that opioid use peaked in 2010 at 782 mor-

phine milligram equivalents (MME) per capita and de-

creased to 640 MME per capita in 2015. However, this is

still three times the rate in 1999 [5]. In 2016, the CDC is-

sued guidelines for the use of opioids in chronic pain [6].

An analysis in 2018 showed that the decline in opioid

prescribing accelerated after these guidelines, but a causal

relationship could not be determined [7].

Previous work suggests that in the ambulatory setting,

quality of care by physicians, nurse practitioners (NPs),

and physician assistants (PAs) is equivalent [8]. Variation

in medication prescribing among these three types of

practitioners has not been extensively studied. To our

knowledge, differences in opioid prescribing among gen-

eralist physicians, NPs, and PAs have not been evaluated.

The number of graduates from NP and PA training

programs has increased recently [9], as has the number of

NPs and PAs per full-time equivalent (FTE) physicians in

certain generalist settings, including family medicine,

multispecialty groups, and hospital medicine groups [10].

Based on projections in 2013, the primary care NP and

PA workforce was projected to grow 58% and 30%, re-

spectively, between 2010 and 2020, faster than the pri-

mary care physician supply [11]. Thus, differences in

prescribing rates, particularly of opioids among general-

ist physicians, NPs, and PAs, are especially important.

We used publicly available data on Medicare Part D

prescribers to evaluate opioid prescribing among general-

ist physicians, NPs, and PAs. Beneficiaries with Medicare

have the option but are not required to choose a prescrip-

tion drug insurance plan for an additional cost [12].

Currently, 71% of Medicare beneficiaries are enrolled in

Medicare Part D plans [13]. We aimed to learn if there

are differences in opioid prescribing among generalist

physicians, NPs, and PAs to Medicare beneficiaries.

Methods

Data Sources We used the publicly available Medicare Part D Opioid

Prescriber Summary Files for 2013, 2014, 2015, and

2016 [14]. These files include the National Provider

Identification (NPI) number of every prescriber who

wrote a prescription for a beneficiary with Medicare Part

D insurance, as well as the prescriber’s full name, ZIP

code of practice, state, specialty, total prescription

claims, total opioid claims, and opioid prescribing rate.

For NPs and PAs, the specialty field lists their classifica-

tion (NP or PA) but not their clinical specialization. Data

for prescribers having between one and 10 opioid or total

prescription claims in a year were withheld. The

Medicare Physician Compare National Downloadable

File [15] provides information on each prescriber’s

organization’s legal name, gender, and years in practice.

These two data sets were merged by NPI number. Data

on median income of residents by ZIP code were

obtained from the United States Census Bureau [16] and

were merged with the data set.

Population We defined generalist physicians as those practicing in-

ternal medicine or family medicine, as labeled in the spe-

cialty field. We categorized practice environments as

primary care, urgent care/walk-in clinic, and hospital

medicine. Hospital medicine prescription claims repre-

sent only those written for Medicare Part D patients

upon discharge from a hospital. Because neither the

Opioid Prescriber Summary Files nor the Medicare

Physician Compare File provides specialty information

for NPs and PAs, we employed a string search strategy to

identify generalist NPs and PAs and also to determine

their practice environment using their organizations’ le-

gal names.

String searches positive for “internal,” “family,” or

“primary care” were categorized as primary care. String

searches positive for “minuteclinic,” “urgent care,” and

“immediate care” were categorized as urgent care/walk-

in clinic. Those positive for “hospitalist” were classified

as hospital medicine. This strategy was also used to cate-

gorize the practice environment of physicians, and only

physicians with a positive string search were included in

the analysis. Two organization legal names were utilized

for string searches. Prescribers with two different practice

settings defaulted to hospital medicine primarily and ur-

gent care/walk-in clinic secondarily. However, fewer

than 1% of physicians, NPs, and PAs were noted to prac-

tice in multiple settings. The accuracy of this search strat-

egy was checked by performing a web-based search using

the NPI number and full name to confirm practice setting

on 0.5% of the practitioners in the analysis sample.

Analyses Each prescriber’s total prescription claims and total opi-

oid claims were calculated for the period of January

2013 through December 2016, as the Opioid Prescriber

Summary Files only had claims on a yearly basis. Total

prescription claim counts for 2013 through 2016 for a

given provider excluded all prescription counts in years

for which the opioid claim counts were withheld. The

opioid claim proportion for each prescriber was gener-

ated as total opioid claims as a percentage of total pre-

scription claims for the period of 2013 to 2016.

We summarized the crude opioid prescription propor-

tions for each provider type in each practice setting (pri-

mary care, urgent care/walk-in clinic, hospital). We then

used generalized linear regression models with a binomial

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distribution to estimate the total opioid prescription

claims for each of the three prescriber types, controlling

for practice setting, gender, years of practice (in 10-year

increments), median income of the ZIP code (per quan-

tiles), and potentially relevant interaction terms

(Supplementary Data). State of practice was included as

a fixed effect. These models were used to generate mar-

ginal estimates of the total opioids prescribed by general-

ist physicians, NPs, and PAs over the four-year period.

The model was also run separately by year.

Two sensitivity analyses were performed. One re-

peated the binomial regression on a subset of states that

we inferred have few opioid-prescribing restrictions for

NPs and PAs. This included all states in which 90% or

more of the NPs and PAs prescribed opioids: Alaska,

Arizona, Connecticut, Idaho, Maryland, Montana,

North Dakota, New Mexico, Oregon, South Dakota,

Vermont, Washington, Wisconsin, and Wyoming. The

second sensitivity analysis replaced the opioid claim

counts that had been withheld from public release with a

count of five. Analyses were done using Stata 13

(StataCorp, College Station, TX, USA).

Results

There were 36,999 generalist clinicians (physicians, NP,

and PAs) with at least one year of Part D prescription

claims data between 2013 and 2016 who could be classi-

fied as practicing in a primary care, urgent care, or

hospital-based setting (Table 1).

Withheld Data Significantly more data were withheld from public re-

lease for low prescription counts for NPs and PAs than

for physicians. The percentage of physicians in a year

with withheld data ranged from 13.1% in 2015 to

14.1% in 2013. For NPs, it ranged from 20.0% in 2016

to 23.7% in 2014. For PAs, it ranged from 23.4% in

2015 to 25.2% in 2014.

Prescribers Providing No Opioids There were 63 physicians, 552 NPs, and 105 PAs with no

opioid claims by Medicare Part D beneficiaries (but a

nonzero number of total prescription claims) in each of

the four years studied. There were 1,859 physicians,

3,635 NPs, and 1,159 PAs who generated no opioid

claims (but a nonzero number of total prescription

claims) in at least one of the four years studied.

Prescription Claims by Practitioner Type The distributions of total opioid claims for all thee practi-

tioner types were extremely right-skewed but clustered

around zero (Figure 1). The variation in opioid prescrip-

tion proportions for PAs was higher than that of physi-

cians and NPs in all three practice environments

(Table 2). Opioid prescription proportions were lowest

in primary care and hospital-based settings for physi-

cians, but lowest in urgent care/walk-in clinics for NPs.

The mean opioid prescription proportions (as a propor-

tion of all prescription claims) for physicians in primary

care, urgent care/walk-in clinics, and hospital medicine

were 4.69, 6.72, and 6.66, relative to 7.10, 11.97, and

11.01 for PAs.

The adjusted total number of opioid claims across

these four years was 660 for physicians (95% confidence

interval [CI] ¼ 660–661), 755 for NPs (95% CI ¼ 753– 757), and 812 for PAs (95% CI ¼ 811–814). In the anal- ysis by year, there was a decreasing trend in prescribing

for each generalist type except for NPs between 2015

and 2016 (Figure 2). Also, physician opioid prescribing

was stable between 2015 and 2016.

NPs and PAs made up a disproportionate number of

the prescribers with the highest 5% of opioid prescrip-

tion proportions. PAs made up 43% of this group and

12% of the entire study sample. NPs made up 32% of

this group and 22% of the study sample. Physicians

made up 24% of this group and 66% of the study sam-

ple. A disproportionate number of those with the highest

5% of opioid prescribing proportions worked in an ur-

gent care setting. About 51% of this group was from the

urgent care setting, whereas prescribers from this setting

made up 20% of the study sample.

Sensitivity Analysis The sensitivity analysis examining the subset of states

with presumably fewer opioid prescribing restrictions for

NPs and PAs yielded predictions of 543 (95% CI ¼ 542– 544) for physicians, 775 (95% CI ¼ 771–780) for NPs, and 752 (95% CI ¼ 748–757) for PAs. The sensitivity

Table 1. Prescription claim counts

2013 2014 2015 2016

Aggregate (N ¼ 36,999) Opioid claims 26,991 28,614 30,570 30,425

Total claims 32,486 34,358 36,438 36,345

Practice location

Primary care (N ¼ 23,328) Opioid claims 18,884 19,689 20,632 20,749

Total claims 21,360 22,218 23,123 23,116

Urgent care (N ¼ 7,758) Opioid claims 4,421 4,963 5,676 5,491

Total claims 5,826 6,599 7,573 7,542

Hospital-based (N ¼ 5,913) Opioid claims 3,686 3,962 4,262 4,185

Total claims 5,300 5,541 5,742 5,687

Practitioner type

Physician (N ¼ 24,213) Opioid claims 20,047 20,572 20,838 20,707

Total claims 23,342 23,745 23,970 23,918

Nurse practitioner (N ¼ 8,171) Opioid claims 4,245 5,038 6,266 6,323

Total claims 5,556 6,599 7,943 7,900

Physician assistant (N ¼ 4,615) Opioid claims 2,699 3,004 3,466 3395

Total claims 3,588 4,014 4,525 4,527

Opioid Prescribing Differences Among Generalists 3

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analysis replacing missing data yielded predictions of 638

(95% CI ¼ 638–638) for physicians, 702 (95% CI ¼ 700–704) for NPs, and 760 (95% CI ¼ 758–762) for PAs (Supplementary Data).

Discussion

We compared opioid prescribing to Medicare Part D ben-

eficiaries by generalist physicians, NPs, and PAs practic-

ing in three different environments. Our identification

strategy found 24,213 generalist physicians working in

either primary care, urgent care, or hospital-based prac-

tice. There were 260,957 physicians practicing generalist

medicine (internal medicine or family medicine) in the

data set. This count is similar to the estimate of 225,000

active internal medicine and family medicine physicians

described in the 2016 Physician Specialty Data Report by the American Association of Medical Colleges [17]. Our

data set includes all physicians who were active in any of

the years from 2013 to 2016, which may explain the

small difference.

We found that the overall volume and proportion of

opioid prescribing are heavily right-skewed. This is con-

sistent with previous analyses of Medicare Part D opioid

prescribing [18] and also of California workers’ compen-

sation claims [19], which showed that 3% of physicians

were responsible for 55% of all schedule II controlled

substance prescriptions. We found that the mean num-

bers of opioid claims, as a proportion of all prescription

claims, from NPs and PAs in the primary care and

hospital-based settings are higher than that of physicians.

This is likely driven by the highest prescribing 25% of

NPs and PAs. Moreover, it is especially interesting given

that the lowest quartile of NPs and PAs had lower pro-

portions than physicians (Table 2). This may be attribut-

able to state-specific restrictions. As of October 2017,

Arkansas, Georgia, Hawaii, Kentucky, Louisiana,

Missouri, Oklahoma, South Carolina, Texas, and West

Virginia had limitations on opioid prescribing for NPs

and/or PAs (Table 3) [20–22]. Current restrictions on

opioid prescribing for NPs and PAs range from not

allowing them to prescribe schedule II opioids at all to re-

quiring additional training or limiting the supply of

opioids they can provide. However, over the last two

0 .0

0 2

.0 0

4 .0

0 6

.0 0

8 D

e n

si ty

0 1000 2000 3000 Total opioid claims

Generalist Physicians

0 .0

0 2

.0 0

4 .0

0 6

.0 0

8 D

e n

si ty

0 1000 2000 3000 Total opioid claims

Generalist Nurse Practitioners

0 .0

0 2

.0 0

4 .0

0 6

.0 0

8 D

e n

si ty

0 1000 2000 3000 Total opioid claims

Generalist Physician Assistants

Histograms of Total Opioids Claims by Practitioner Type, 2013-2016

Figure 1. Histogram of Total Opioid Claims by Practitioner Type, 2013–2016.

Table 2. Descriptive statistics of opioid prescription proportion

No. of Prescribers

Mean Opioid Rx Proportion (SD) Median

[Interquartile Range]

Primary care

MD 16,193 4.69 (3.82) 3.97 [2.52 5.91]

NP 4,372 5.26 (8.28) 3.16 [0.53 6.17]

PA 2,099 7.10 (10.57) 4.22 [1.92 7.42]

Urgent care

MD 2,283 6.72 (6.49) 5.27 [3.03 8.41]

NP 2,906 4.82 (9.73) 0.00 [0 5.43]

PA 1,987 11.97 (13.81) 7.28 [2.05 17.44]

Hospital medicine

MD 4,814 6.66 (4.61) 6.22 [4.01 8.64]

NP 447 8.06 (11.31) 4.57 [0 10.48]

PA 182 11.01 (14.92) 6.09 [0 15.19]

MD ¼ doctor of medicine; NP ¼ nurse practitioner; PA ¼ physician assistant.

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decades, states have been increasing the scope of practice

of NPs and PAs and decreasing prescribing limitations

[23,24]. For example, between 2001 and 2010, three

states (Hawaii, Kentucky, and Virginia) changed from

not allowing NPs to prescribe any controlled substances

to allowing them to prescribe schedules II through V

[24].

The marginal predictions show that overall opioid

prescribing by physicians, NPs, and PAs decreased from

2013 to 2016. This may be the result of increased aware-

ness of the adverse effects of overuse of opioids and the

concomitant efforts of the Drug Enforcement Agency

(DEA) and Centers for Medicare and Medicaid Services

(CMS) to crack down on high-volume opioid prescribing

[25,26]. This may also be due in part to the CDC guide-

lines on using opioids to treat chronic pain issued in

2016 [6]. Moreover, the decrease in NP and PA

prescribing was more marked, and this narrowed the dif-

ferential among prescriber types. The subgroup analysis

of states with more liberal NP and PA prescribing laws

had fewer opioid prescriptions overall but a larger dis-

parity among provider types. Notably, this analysis ex-

cluded states with the most opioid prescribing [27],

specifically Nevada, Florida, Kentucky, and West

Virginia.

Previous work has examined aggregate opioid pre-

scribing of NPs and PAs and compared it with that of

various medical specialties [18,28–30]. These studies an-

alyzed NPs and PAs of all specialties as one group.

However, these results are difficult to interpret because

there is enormous variation in opioid prescribing rates of

physicians among different specialties [29]. For example,

orthopedic surgeons and neurosurgeons prescribe opioids

at a higher rate than internists. One would expect trends

to be relatively similar for NPs and PAs in these special-

ties. Thus, it makes more sense to evaluate NP and PA

prescribing at a specialty level rather than in aggregate.

An examination of opioid prescribing in Oregon using its

prescription drug monitoring program found that NPs

provided more high-risk opioid prescriptions than physi-

cians and PAs [28]. However, this was thought to be due

to patients at high risk for opioid misuse being more

likely to seek out NPs.

To our knowledge, this is the first study to compare

opioid prescribing patterns of generalist NPs and PAs

with those of generalist physicians. This is an important

area of inquiry, as primary care physicians make up the

plurality of all physicians. A study of prescribers associ-

ated with fatalities in Utah showed that primary care pro-

viders were the most frequent opioid prescribers and also

the most frequent prescribers of opioids leading to fatali-

ties [31]. The overall proportion of opioid claims among

all prescription claims for primary care physicians in our

0

50

100

150

200

250

300

2013 2014 2015 2016

O pi

oi d

Co un

t

Margin Predic�ons of Total Opioid Counts by Year

Physician Nurse Prac�oner Physician Assistant

Figure 2. Margin predictions of total opioid counts.

Table 3. Independence of NPs and PAs by state, as of 2017

States with full independent

practice authority for NPs

Alaska, Arizona, Idaho, Iowa,

Montana, New Hampshire, New

Mexico, North Dakota, Oregon,

Rhode Island, Washington DC,

Washington State, Wyoming

States with full independent

practice authority for PAs

Alaska, Illinois – subject to

“Collaborative Agreement” with

physicians rather than supervised

by physicians

New Mexico – requires supervision

for PAs with fewer than 3 years of

clinical experience and for PAs

practicing specialty medicine

States with limitations on

opioid prescribing for NPs

and PAs

Arkansas, Georgia, Hawaii,

Kentucky, Louisiana, Missouri,

Oklahoma, South Carolina,

Texas, West Virginia

NP ¼ nurse practitioner; PA ¼ physician assistant.

Opioid Prescribing Differences Among Generalists 5

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sample is roughly 5%, which is consistent with previous

research [29]. We find that NPs and PAs prescribe a dis-

proportionately high quantity of opioids to Medicare

beneficiaries with Part D coverage. Of course, we do not

know if the patients seen by generalist physicians, NPs,

and PAs are similar with regard to need for opioids. We

do not know of any large-scale national studies compar-

ing the medical complexity or acuity of patients seen by

physicians with those seen by NPs or PAs in generalist

settings. However, it is important to acknowledge that

NPs and PAs may be serving different roles than physi-

cians in these three settings. For example, NPs and PAs in

primary care may be more likely to see the urgent visits

as opposed to the follow-up visits, which may be more

likely to be for acute pain. Additionally, NPs and PAs

may be responsible for managing routine medication re-

fill visits in the primary care setting, which could lead to

a disproportionate number of opioid prescriptions attrib-

uted to them.

There are a number of potential explanations for these

prescribing differences that could not be tested with our

data. One is that pharmaceutical companies may be tar-

geting and aggressively marketing the prescription of

opioids to NPs and PAs. In fact, recent evidence suggests

that Purdue Pharmaceuticals, which manufactures and

sells a number of opioids, did intentionally target NPs

and PAs practicing general medicine [32,33].

Alternatively, NPs and PAs who have recently trained or

practiced in a surgical subspecialty environment, where

higher rates of opioids are typically prescribed, may bring

those prescribing tendencies to a general medicine envi-

ronment when they change specialties.

Limitations One limitation of this work is that the data set does not

provide information on the size of opioid claims. In other

words, a prescription claim for a large supply of opiates

is treated identically to a claim for a small supply.

Another limitation is that we examined only prescrip-

tions filled by beneficiaries with Medicare Part D. Thus,

our results may not be generalizable regarding opioid

prescribing to the population under age 65 years or to

older patients in managed care Medicare plans. Previous

research [34] has suggested a relationship between pre-

scription of opioids during primary care visits and type of

insurance, but there have been no studies showing a

causal effect between insurance status and receipt of opi-

oid prescriptions.

Additionally, we only included in the analysis pre-

scribers who were identifiable as generalists by their

organizations’ legal names. Thus, many prescribers were

not included, and there is some risk of misclassification.

However, we did perform a check on the string search

strategy, which showed it to be accurate. A minor limita-

tion is that our data include opioid prescription propor-

tions from 2013 to 2016, but they do not include

physicians, NPs, and PAs who started practicing in 2016,

as these data are not yet available. Finally, the scope of

practice for NPs and PAs, including the ability to inde-

pendently prescribe opioids, has changed over the last de-

cade [24]. Overall, the scope of practice has expanded

for NPs and PAs. We did not evaluate specific changes in

state-level legislation related to NP and PA opioid pre-

scribing privileges throughout this period, though we did

control for state fixed effects and also performed a sensi-

tivity analysis on a subset of states.

Conclusions

Our findings have important policy implications. There

is a widely held belief that high opioid prescribing by

physicians is a driver of the opioid epidemic. The finding

of higher opioid prescribing by NPs and PAs suggests

that a well-crafted intervention to improve the safety of

NP and PA opioid prescribing at least equal to that re-

quired of physicians could be useful to help curb opioid

misuse, addiction, and diversion.

There are a number of policy solutions that could help

ameliorate this prescribing disparity. The accreditation

and licensing organizations for NPs and PAs could utilize

continued education requirements to ensure that clini-

cians are knowledgeable about opioid prescribing guide-

lines and best practices and also how to screen for opioid

misuse. Such requirements would also be beneficial for

physicians, and some states have already initiated them

[35]. It may be helpful if the CMS and DEA provided

prescribing data stratified by clinician type (physician,

NP, PA) and practice setting to help identify prescribing

patterns among individual prescribers and group practi-

ces. In January 2018, the DEA announced that it would

“surge” resources to identify prescribers and pharmacies

with outlier opioid prescribing behaviors [36]. We must

all recognize that being an outlier may not account for

unique practice settings, individualized patient pheno-

types, and other factors. Finally, all prescribing clinicians

and those who dispense opioids should work together as

a team to ensure they are appropriately up to date on

pain therapeutics, including applicable initial and ongo-

ing risk assessment, variable nonopioid medication, and

nonmedication alternatives. Physicians, NPs, and PAs

share an equal and corresponding responsibility to ensure

that they are compliant and competent with all regula-

tions and are providing the safest available options for

patients.

This analysis suggests that resources specifically tar-

geted to helping NPs and PAs could be especially effec-

tive at reducing opioid prescribing. Further research

should evaluate whether high-volume opioid prescribing

NPs and PAs tend to be associated with specific organiza-

tions with high-volume opioid prescribing physicians and

whether there is an association between high-volume opi-

oid prescribing and other low-value or high-risk health

care practices.

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Acknowledgements

We would like to thank Nayoung Rim, PhD, and

Jiangxia Wang, MS, MA, for technical assistance.

Supplementary Data

Supplementary Data may be found online at http://

painme dicine.oxfordjournals.org.

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