Running head: OPIOID MANAGEMENT

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Opioid Management: Provider Education
Jessica Wagner
Arizona State University

OPIOID MANAGEMENT

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Abstract

Over the last two decades, opioid prescription and prevalence has increased to account
for over 33,000 deaths per year (Soelberg, Brown, Du Vivier, Meyer & Ramachandran, 2017).
This is not only due to overdose, but misuse, abuse, and addiction. The abrupt increase in
prescriptions, pills dispensed, and opioid-related deaths have encouraged the involvement of
multiple entities. In 2016, the opioid crisis gained the attention of communities that released
guidelines to regulate prescription of opioid pain management. Such entities include the Center
for Disease Control and Prevention (CDC), National Institute on Drug Abuse, Agency for
Healthcare Research and Quality (AHRQ), Arizona Department of Health Services (AZDHS),
and Substance Abuse and Mental Health Services Administration (SAMHSA). Evidence shows
that prescribing practices between providers vary. It also shows that providers lack knowledge of
appropriate opioid prescribing and management. To address this problem, provider education on
an opioid policy is the most effective way to uniform opioid prescribing.
Keywords: opioid management, opioid prescribing, prescribing providers, opioid policy

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Opioid Management: Provider Education
Opioid abuse, misuse, addiction and overdose have been gradually rising since the 1990’s
until 2015 when drug overdose was the leading cause of accidental death in the United States
(ASAM, 2016). This number comes not only from the misuse, but the inappropriate prescribing
of opioids from providers that lack the knowledge and comfort in these medications. This allows
for over prescription of opioids, improper disposal, and incomplete follow up from the provider.
The AZDHS addressed all these inconsistences by administering a new policy outlining
prescribing guidelines (2018). Therefore, adherence to a clinic-specific policy, following the
AZDHS guidelines, will increase provider comfort and knowledge in prescribing opioids thereby
reducing the number of inappropriate prescriptions.
Background
The opioid crisis has been addressed multiple times in recent years. In October of 2017,
The Federal Response to the Opioid Crisis discussed two problems leading to the opioid crisis;
the rise in opioid analgesic prescriptions since the 1990’s, and the lack of healthcare providers
that are properly educated by evidence and trained to engage patients in a medication-assisted
treatment (MAT) to the full capacity. For example, SAMHSA and the CDC have programs that
center around educating the public and providers on the opioid crisis and necessity for opioid
management. SAMHSA requires specialized training or board certification from Addiction
Medicine or Addiction Psychiatry before prescribing buprenorphine, which has been shown to be
an effective long-term treatment option for opioid dependence (“The prescription opioid,” 2011).
The CDC provides resources and training on opioid prescriptions through two programs;
Prescription Drug Overdose: Prevention for States and Data-Driven Prevention Initiative (DDPI)
and Prescription Drug Monitoring Programs (PDMP) (2018). These include education on

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insurance practices for opioid prescribing, policies, and laws, such as naloxone administration,
and Good Samaritan laws.
SAMHSA currently funds states with $11 million to train providers on opioid overdose
(“The Federal response,” 2017). The “Opioid Overdose Prevention Toolkit” was released in
2013 and can be used by people of the community and family members, along with trained
professionals. It focuses on five steps which are: call for help, checks for signs of opioid
overdose, support the person’s breathing, administer naloxone, and monitor the person’s
response (“Opioid overdose prevention”, 2016). More recently, $46 million in grants were
awarded to help fund 22 states in training individuals that work with communities at high risk for
opioid overdose.
The CDC emphasizes the importance of distinguishing the difference between acute and
chronic pain, and pain that can be treated with opioids verses pain that can be treated with other
pain management strategies (“Guideline for prescribing,” 2017). Prescribing nonpharmacological pain management options should be the first treatment approach. This may
include physical therapy, massage, or acupuncture. Next, medication treatment consists of nonsteroid anti-inflammatories and steroid injections. Obtainable pain management goals should be
mutually established by the patient and provider. The CDC recommends using immediate-release
opioids first- beginning with a low dose and going slow with increasing the dose as needed
(“CDC guideline,” 2016). This recommended protocol should be discussed with the patient when
the pain management goals are set. If indicated for acute pain, opioids should be restricted to 3-5
days with a limited quantity. Follow-up is then recommended to reassess pain management
needs. An informed consent, instead of a pain contract is recommended to all patients that are
being prescribed an opioid analgesic (“AZ opioid prescribing guidelines”, 2018). The informed

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consent should discuss the side effects, risk factors for opioid addiction, other medication
contraindications and dose escalation for opioid prescribing. Providers and patients should
discuss chronic pain management options beyond the 5-day prescription limit (“CDC guideline,”
2016). Chronic pain management follow-up is recommended every 3 months, or more if needed.
At this point, it is recommended the provider and patient discuss the benefits verses risks of
continuing opioid therapy. The discussion will include the option of combining the therapy with
other non-opioid pharmacological and non-pharmacological interventions. If it is determined to
be necessary to increase the opioid dosage, providers should follow the guidelines carefully,
increasing dosage to >= 50 morphine milligram equivalents (MME) per day and advise avoiding
increasing dosage to >= 90 MME/day (“CDC guideline,” 2016).
Prevalence
The necessity for opioid management has become prevalent because of the rising
numbers in overdose, use, misuse, and over prescription of opioids. In 2012, 259 million
prescriptions were written for opioids alone (ASAM, 2016). According to the CDC, there was a
30% increase in opioid overdoses from July 2016 to September 2017 (“Opioid overdoses
treated,” 2018). In addition, deaths from opioids have multiplied by five times since 1999.
Arizona reports 6,369 suspected opioid overdoses with 996 ending in death and 629 cases of
neonatal abstinence syndrome from June 15, 2017 to March 8, 2018 (“Opioid epidemic,” 2018).
Over half of these cases were in Maricopa county, followed by Pima County (“Opioid report,”
2018). Death rates among men are more common than women, but that gap is closing.
Methadone, Oxycodone and Hydrocodone are the most common drugs associated with overdose
deaths (“Opioid report,” 2018).

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Overdose is not the only cause of these numbers. Addiction, misuse, abuse, and over
prescription contribute to the opioid crisis (“Prescription opioid overdose data”, 2017). Misuse is
defined as using opioids without a prescription or using prescribed opioids through a different
route or frequency than was prescribed. It also includes using it for the feeling or experience the
drugs yield (Hoffman, Lewis, & Nixon, 2017). Because these numbers have grown so rapidly
over recent years, many statements, policies and guidelines have been published to help
providers when prescribing opioids for the original purpose of pain management. However, with
multiple guidelines and recommendations, a single policy for providers at the same practice
would be the most efficient way to ensure continuity of opioid management.
PICO
With the many published guidelines and recommendations on managing controlled
prescriptions, providers often select the criteria that aligns with personal preferences. This can
lead to inconsistencies in prescribing and managing opioids among prescribers in practice. At an
outpatient primary care practice in Southeast Arizona, the 5 physicians and 1 physician assistant
prescribe opioids based on personal prescribing preferences. There is no single policy or
procedure in place for management of patients requiring opioid treatment. Each provider
prescribes opioids using their own discretion. Therefore, several gaps in the process have been
identified. This makes it difficult to manage patients’ opioid prescriptions and in turn, acute and
chronic pain. Typically, each provider has the patient sign a pain contract, along with an annual
urine drug screen. The providers check the prescription drug monitoring program (PDMP)
anywhere from monthly to yearly. The patients follow up as needed or as the provider sees fit.
There is no reminder or tracking in the electronic medical record that indicates when the patient
is due for refills, follow up appointments, urine drug screens. This leads to no reassessment of

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opioid need and inadequate follow up of opioid pain management. Currently, with no policy or
guidelines, there is no uniform compliance to opioid management. Therefore, the PICO question
becomes: in healthcare providers prescribing opioids, how does education on an opioid
management policy vs not, affect opioid management and policy compliance?
Search Strategy
The initial search for this literature review included databases Pubmed, Academic Search
Premier, GoogleScholar, Lippincott Williams & Wilkins, and Guideline.gov. Keywords that were
used included; provider education, opioid policy, opioid management and prescribing
management. The population was focused on providers with an outcome of opioid prescribing
practices and the effect of opioid management programs. The term opioid prescribing
management was used in Pubmed which yielded 1262 results (Appendix B, Table B1). This was
narrowed down by selecting data that occurred in the last five years, while using the terms
integrated opioid dependence management to narrow the criteria to opioid management
programs that yielded 52 results (Appendix B, Table B2).
Google Scholar was searched using palliative care opioid admission which yielded
18,000 results (Appendix C, Table C1). The search was moved to Academic Search Premier
using the terms palliative care opioid management under the criteria of being current within the
last five years that yielded seven results (Appendix C, Table C2). Academic Search Premier was
searched again using key terms opioid policy with no date restrictions, yielding 216 results
(Appendix D, Table D1). This was narrowed down using the terms chronic opioid policy and
restricting articles within the last five years that yielded five results (Appendix D, Table D2).
Several articles were chosen from the brief abstract and results, but then upon accessing
the full article that was in Greek and German, they were discarded. Articles were chosen that are

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in the English language only. After each article was chosen, a review of the references would be
conducted. These referred to entities such as Pain Medicine, CDC guidelines, National Institute
on Drug Abuse, and Agency for Healthcare Research and Quality. Articles were then chosen
based on relevance to address the PICO question.
Synthesis
The studies selected ranged from level II to IV evidence due to lack of a control group.
Of the 10 studies chosen, three studies were cross-sectional with level IV evidence. Two were
cohort studies of level IV evidence, and three randomized control trials of level I and II evidence.
Finally, one study was a systematic review of level II evidence and one meta-analysis of level III
evidence.
Six of the ten studies addressed screening tools for opioid management interventions such
as the Opioid Compliance Checklist (OCC) and the Screener and Opioid Assessment for Patients
with Pain (SOAPP) (Appendix E). Six of the articles addressed interventions for opioid
management through clinic settings such as the opioid reassessment clinic (ORC) or
multidisciplinary care (Appendix E). Five of the articles included interventions that had an
opioid policy, opioid taper, or a tool to reduce inappropriate medications (TRIM) (Appendix E).
Nine of the studies were conducted in the United States, with one being conducted in several
clinics across France. Although conducted in two countries, the demographic homogeneity is
present across all studies as the criteria to be in a study included taking prescribed opioid therapy
and being over the age of 18 years old.
Two articles had potential for bias, as the authors were employed by the company
funding and conducting the study. Besides that, all other studies were funded through
government health agencies, with the addition of one pharmaceutical company. Two studies

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showed attrition rates that were lower than 20% (Appendix E). All tools used across the studies
reported reliability and validity.
From these interventions, there was a wide array of dependent variables measured.
Frequent dependent variables utilized opioid use, patient satisfaction, patient follow-up, provider
education, and total daily dose (TDD) of oral morphine equivalent (OME). Other variables
included provider satisfaction, prediction of opioid abuse, medication reconciliation, and if the
interventions took place in a primary care setting. The studies had a broad range of time from
three months to two years. Many studies measured outcomes using self-report or selfquestionnaires, along with comparing OME or TDD of opioids. The majority of the findings
were statistically significant with a p value <.05. If the results were not shown to be statistically
significant, the quality of evidence and findings were considered for future practice.
Conclusion About the Evidence
Multidisciplinary care was the most common intervention across the studies. Primary
care with a multidisciplinary approach had a consistent increase in patient satisfaction, patient
follow-up, and decrease in opioid use. Patients in primary care had a greater success in opioid
abstinence, follow-up and adherence to prescribed opioid therapy, decreasing chances of misuse.
The two studies that initiated an opioid policy saw decrease in opioid use by mouth. However,
there was an increase in overall opioid use, namely long acting opioids and opioids used by
intravenous route (Appendix E). The ORC and opioid taper saw a decrease in opioid use. These
two studies, along with one of the opioid policies saw a decrease in TDD of OME. Two studies
addressed the need for provider education in not only prescribing and dosing, but also informing
patients on proper disposal of opioids.
Contribution of Theory

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Bandura’s theory of self-efficacy is applicable to the topic of opioid management and
education (Bandura, 1977). Opioid management is often inconsistent, especially among primary
care providers that may be unfamiliar with this territory. Through the theory of self-efficacy, it is
shown that new information should be taught, demonstrated, then taught back to another person
such as a patient (Smith, & Liehr, 2014). This would apply when implementing new opioid
guidelines. This process helps the learner know that the task can be done and reinforces success.
Bandura’s theory focuses on interventions that change behavior, and in turn, change knowledge
and clinical practice.
Evidence Based Practice Model
The Iowa Model of Evidence- Based Practice to Promote Quality Care is the model to
use when initiating a new protocol (Melnyk & Fineout-Overholt, 2015). It guides the user
through the steps to start, research, initiate, and then evaluate a change in practice (Appendix F).
A primary care clinic has identified a need to establish an opioid use practice guideline to
comply with the CDC and AZDHS guidelines (2018). A team of 5 family practice Medical
Doctors (MD) and 1 Physician Assistant (PA) have agreed to participate in this project about
these new guidelines. A PICO question was formed to search for the best evidence and practice
for opioid prescribing. Evidenced-based prescribing guidelines, a pain algorithm and an
informed consent derived from the AZDHS will be provided to the 6 prescribing providers. Ten
articles were chosen, and then critically appraised to analyze the best evidence, outcomes, and
practices in initiating an opioid policy. The measurement tool is a self-questionnaire that has
been adapted from the Arizona Department of Health Services questionnaire. (“Arizona pain and
addiction curriculum”, 2019). The pre, post and 6-week follow-up questionnaire will include
questions regarding provider knowledge and comfort in opioid prescribing, procedures in opioid

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management, and frequency in prescribing, follow up, and referring to other pain management
options. The next step is obtaining institutional review board approval.
Brief Potential Plan
An opioid policy that includes evidenced-based prescribing guidelines, a pain algorithm
and an informed consent derived from the AZDHS, will be provided to the 6 prescribing
providers using the CDC and the 2018 AZ Opioid Prescribing Guidelines (2018). This will be
presented in a PowerPoint presentation and handouts to the stakeholders in the primary care
practice. The key stakeholders are 5 MDs and 1 PA in the private primary care clinic in
Southeast Arizona. Additional stakeholders include medical assistants, office managers, and
receptionists. A pre-questionnaire will be administered to the key stakeholders that measures the
knowledge of providers in prescribing, management, and beliefs regarding opioids. For example,
the self-questionnaire will include questions regarding knowledge and comfort in opioid
prescribing, procedures in opioid management, and frequency in prescribing, follow up, and
referring to other pain management options.
The policy guidelines in opioid prescribing and management will be presented through
PowerPoint presentation and handouts. This will include the AZ Opioid Prescribing guidelines,
CDC recommendations and other tools that can be utilized to manage opioid prescriptions
(2018). The same self-questionnaire will be administered after the presentation to measure how
education on the policy influenced views and practices on prescribing opioids. Another selfquestionnaire will be administered after six weeks to measure the providers prescribing practices
after education and implementation on the opioid management guidelines.
Summary with Proposed Implications

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An opioid policy can streamline management and prescription of opioids. The
implementation of a policy will condense provider and clinic expectations to one uniform policy
that can be followed by every member of the clinic, including the patients. Education would
consist of clearly outlining the prescribing and management practices of the clinic. Education on
opioid management guidelines, pain algorithm and informed consent reiterates prescribing
restrictions produced by the CDC and AZDHS(2018). This will reduce the number of
inappropriate prescriptions and decrease opioid abuse and misuse.
All providers in the clinic will have one policy to follow, making it efficient to manage
opioid prescriptions and patients with pain in primary care. Every member of the healthcare team
would be aware of the new guidelines, therefore taking a multidisciplinary care approach to
management of opioids. This approach increases patient satisfaction, patient follow up, and
adherence to opioid management programs.
Results
The sample consisted of 2 (33%) females and 4 (66%) males. 1 (17%) of the participants
was a Physician Assistant and 5 (83%) were Medical Doctors. The average years of clinical
experience was 24.33 (SD=8.41).
There were two tests that were used. The Wilcoxon signed rank test was used for the 6
participants that completed the pre-questionnaire and post-questionnaire. The statistically
significant result showed a decrease in the question “confidence that opioids are not effective for
long-term chronic pain”, (p=.034). There was one clinically significant result showing an
increase in the question “I know community resources to treat patients with pain and/or
addiction”, (p=.071). The second test that was used measured 3 data collection times; prequestionnaire, post-questionnaire and 6-week post-questionnaire. There were 4 participants that

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completed all three questionnaires. There was one statistically significant result that showed an
increase in the question “I am currently satisfied with my knowledge of managing patients with
chronic pain”, (p=.039).
Discussion
Overall, the results showed an increase in provider knowledge and comfort in treating
patients with pain. The results showed a decrease in provider confidence that opioids are not
effective for long-term chronic pain. In other words, after the intervention, the providers had
increased knowledge that opioids are not effective for long-term chronic pain. The results also
showed that providers had increased satisfaction with their knowledge of managing patients with
chronic pain. There also was an increase in providers’ knowing community resources to treat
patients with pain and addiction.
Barriers included the clinic’s resistance to change and lack of time for project
implementation. The attrition rate of 40% is attributed to lack of provider follow-up. Project
sustainability is based on the provider and clinic willingness to adopt and continue using the
prescribing guidelines. Current recommendations based off this project is to implement an opioid
policy in all primary care clinics to include prescribing guidelines, pain algorithm and an
informed consent.
Conclusion
This project, utilizing the CDC and 2018 AZ Opioid Prescribing Guidelines, created a
policy that included guidelines, a pain algorithm, and informed consent for the primary care
providers (“Arizona opioid prescribing guidelines”, 2018). All information was presented via
PowerPoint and paper handouts. A pre, post and 6-week follow-up questionnaire included
questions regarding provider knowledge and comfort in opioid prescribing, procedures in opioid

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management, and frequency in prescribing, follow up, and referring to other pain management
options. The data collected from the pre-questionnaire and post-questionnaires showed that there
was an increase in provider knowledge and satisfaction when prescribing opioids after the
intervention.
In summary, this project made the 2018 AZ Opioid Prescribing Guidelines into a useable,
manageable set of guidelines that is easily applicable into a primary care practice.

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References

Arizona opioid prescribing guidelines. (2018). Arizona Department of Health Services.
https://www.azdhs.gov/documents/audiences/clinicians/clinical-guidelinesrecommendations/prescribing-guidelines/az-opioid-prescribing-guidelines.pdf
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84, 191-215.
Becker, W., Edmond, S., Cervone, D., Manhapra, A., Sellinger, J., Moore, B., & Edens, E.
(2017). Evaluation of an integrated, multidisciplinary program to address unsafe use of
opioids prescribed for pain. Pain Medicine, pnx041, https://doiorg.ezproxy1.lib.asu.edu/10.1093/pm/pnx041
Carrieri, P., Michel, L., Lions, C., Cohen, J., Vray, M., Mora, M., et al. (2014) Methadone
induction in primary care for opioid dependence: A pragmatic randomized trial. PLoS
ONE 9(11). https://doi.org/10.1371/journal.pone.0112328
CDC guideline for prescribing opioids for chronic pain. (2016). Agency for Healthcare Research
and Quality. https://www.guideline.gov/summaries/summary/50153/cdc-guideline-forprescribing-opioids-for-chronic-pain---united-states2016?q=cdc+guideline+for+prescribing+opioids
Chou, R., Deyo, R., Devine, B., Hansen, R., Sullivan, S., Jarvik, J., Blazina, I., Dana, T.,
Bougatsos, C., & Turner, J. (2014). The effectiveness and risks of long-term opioid
treatment of chronic pain. Agency for Healthcare Research and Quality: Evidence
Reports/Technology Assessments, No.
218. https://www.ncbi.nlm.nih.gov/books/NBK258809/

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The federal response to the opioid crisis. (2017). National Institute on Drug Abuse.
https://www.drugabuse.gov/about-nida/legislative-activities/testimony-tocongress/2017/federal-response-to-opioid-crisis
Fried, T., Niehoff, K., Street, R., Charpentier, P., Rajeevan, N., Miller, P., Goldstein, M.,
O’Leary, J., & Fenton, B. (2017). Effect of the tool to reduce inappropriate medications
on medication communication and deprescribing. Journal of the American Geriatrics
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Prevention. https://www.cdc.gov/drugoverdose/pdf/guidelines_factsheet-a.pdf
Hoffman, L., Lewis, B., & Nixon, Sara. (2017). Opioid misuse trends in treatment seeking
populations: Revised prescription opioid policy and temporally corresponding changes.
Substance Use and Misuse. 52(14), 1850-1858. Doi: 10.1080/10826094.2017.1316291
Jamison, R., Martel, M., Huang, C., Jurcik, D., & Edwards, R. (2016). Efficacy of the opioid
compliance checklist to monitor chronic pain patients receiving opioid therapy in primary
care. The Journal of Pain, 17(4):414-23. doi: 10.1016/j.jpain.2015.12.004
Lagisetty, P., Klasa, K., Bush, C., Heisler, M., Chopra, V., & Bohnert, A. (2017). Primary care
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Madsen, A., Stark, Lauren, M., Has, P., Emerson, J., Schulkin, J., & Matteson, K. (2018). Opioid
knowledge and prescribing practices among obstetrician-gynecologists. Obstetrics &
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Healthcare: A Guide to Best Practice (3rd ed.). Lippincott, Williams & Wilkins.
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(ASAM). https://www.asam.org/docs/default-source/advocacy/opioid-addiction-diseasefacts-figures.pdf
Opioid epidemic. (2018). Arizona Department of Health Services.
http://www.azdhs.gov/prevention/womens-childrens-health/injury-prevention/opioidprevention/index.php
Opioid overdose prevention toolkit. (2016). Substance Abuse and Mental Health Services
Administration. https://store.samhsa.gov/shin/content//SMA16-4742/SMA16-4742.pdf
Opioid overdoses treated in emergency departments. (2018). Centers for Disease Control and
Prevention. https://www.cdc.gov/vitalsigns/opioid-overdoses/index.html
Opioid report. (2018). Arizona Department of Health Services.
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Page, J., Traver, R., Patel, S., & Saliba, C. (2018). Implementation of a proactive pilot health
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Prescription opioid overdose data. (2017). Centers for Disease Control and Prevention.
https://www.cdc.gov/drugoverdose/data/overdose.html
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Substance Abuse and Mental Health Services Administration.
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Riggs, C., Billups, S., Flores, S., Patel, R., Heilmann, R., & Milchak, J. (2017). Opioid use for
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Soelberg, C., Brown, R., Du Vivier, D., Meyer, J. & Ramachandran, B. (2017). The US opioid
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Appendix A

Table A1
PubMed Database Screenshot

Table A2
PubMed Database Screenshot

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Appendix B

Table B1
GoogleScholar Database Screenshot

Table B2
Academic Search Premier Database Screenshot

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Appendix C

Table C1
Academic Search Premier Database Screenshot

Table C2
Academic Search Premier Database Screenshot

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Appendix D

Table 1
Evaluation Table: Opioid Management
Citation

Becker, W., et al. (2017).
Country: U.S.
Fund: VA’s Office of Research and
Development, Health
Services Research, Substance
Use Disorder QUERI
Bias: none

Theory/
Concep
tual
Frame
work
Physiol
ogic
model

Design/
Method

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Findings/
Results

Level/Qualit
y of
Evidence;

Cohort
study
CG= none
Purpose:
To describe
the
preliminary
efficacy of
the ORC

n= 87
CG= none
mean age- 56.2
Pt. type84% pts hx of
substance
abuse/dependenc
e, 70% pts
current misuse
of rx o, 22% new
substance use
disorder dx
Setting-ORC

IVinvolvemen
t in ORC
DV- mean
change in
MEDD,
patient
satisfaction,
number of
pt.s
engaged
ORC
treatment

Medical record
referral from
PCP;
motivational
interviewing

Not
identitif
edcompar
e pre
and post
MEDD

Pt.s preORC admit
mean of
202.8mg
MEDD,
post ORC
169.4mg
MEDD, pt.
satisfaction
3.8/5,

LOE: IV
Limitations:
Not shown
in
statistically
significant,
no CG

Citation
Theory/ Design/
Sample/ Setting
Major
Measurement/ Data
Findings/
Level/Qualit
Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

Carrieri, et al. (2014)
Country: France
Fund: French National Agency for
Research on Aids and Viral
Hepatitis and French Ministry
of Health
Bias: None

Citation

Chou, R., et al. (2014).
Country: U.S.
Fund: Agency for Healthcare Research
and Quality
Bias: none

Concep
tual
Frame
work
Physiol
ogic
model

Concep
tual
Frame
work

Qualita
tive
Docum
ent
analysi
s

23

Method

Randomize
d Control
trial
Purpose:
compare
effectivene
ss of
methadone
tx between
primary
care and
specialized
care

Design/
Method/
Sampling
(Grounded
Theory,
phenomeno
logy,
Narrative
…)
Descriptive
exploratory
; grounded
theory
Purpose:
review

N= 221
Primary care,
specialized care
Attrition: 17%

Sample/Setting
(describe)

N=39 studies
Articles are
about long-term
o therapy for
chronic pain
Exclusion:

Variables &
Definitions

Instrumentatio
n

IVsupervised
methadone
treatment
for 2 weeks
DVabstinence
scoring, pt.
outcomes,
provider
outcomes

Self-reported
abstinence
from street
opioids, pt.
retention,
satisfaction

Major
Variables
Studied and
Their
Definitions
Risks of O
vs placebo
in pt.s with
chronic
pain

Measurement/
Instrumentatio
n
(focus group,
1:1,
researcher(s)
Systematic
review via
questionnaire

Analysi
s
(stats
used)
Intentio
n to
treat

Results

y of
Evidence;

Abstinent:
55%
primary
care, 33%
specialized
care, ↑ pt.
satisfaction
in primary
care, pt.
involvemen
t lower in
specialized
care,

LOE: II
Better
outcomes
with o
management
in primary
care

Data
Analysi
s

Findings/
Themes

Quality of
Evidence

Long
term o
use ↑
risk of
abuse/d
ependen

Buccal
fentanyl or
intranasal
fentanyl
more
effective

LOE: II
No
difference in
dose
escalation
vs.

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

24

current
evidence
on the
effectivene
ss and
harms of O
therapy for
chronic
pain (>=1
year)

conference
abstracts, nonenglish
language,
nonhuman
subjects

ce,
↑OD,
↑fractur
es, ↑MI,
↑use of
ED
medicat
ions or
testoster
one
replace
ment,

Citation

Theory/
Concep
tual
Frame
work

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Fried, T., et al. (2017).
Country: U.S.
Fund: Donaghue Foundation and Yale
University School of Medicine
Bias: none

Physiol
ogic

Randomize
d clinical
trial
Purpose:
determine
effectivene
ss of the
web tool,
TRIM
linking to
electronic
health
record

n=64
CG=64
veteran, 65 or
older prescribed
7 or more
medications
random receipt
of TRIM or
usual care

IV:
Involvemen
t in TRIM
DV:
physician
outcomes,
patient
outcomes

PACIC
Changes in
medications

Chisquare,
Kruskal
-Wallis,
p<.10

than oral O
in acute
pain, no
difference
in methods
for o
discontinua
tion, OCC
inconsisten
t accuracy,
SOAPP 6
sensitivity
.73, 8 .at 68
Findings/
Results

maintenance
of O on
pain,
function,
risk of
withdrawal
due to o
misuse
A lot of
questionsinsufficient/l
ow evidence

Statistically
significant:
↑ PACIC
>10, ↑ 1+
clinician
recommend
ation, ↑pt.
active
participatio
n, ↑pt. and
clinician
medication
communica
tion, ↑
clinician
facilitative

LOE: II
Statistically
significant,
48.4% errors
corrected via
medication
reconciliatio
n

Level/Qualit
y of
Evidence

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

Citation

Hoffman, L., et al. (2017).
Country: U.S.
Fund: National Institute on Drug
Abuse and National Institute on
Alcohol Abuse and Alcoholism
Bias: none

Citation

Jamison, R., et al. (2016).
Country: U.S.
Fund: Mallinckrodt and Pfizer
Bias: none

25
communica
tion,
Findings/
Results

Theory/
Concep
tual
Frame
work
physiol
ogic

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Level/Qualit
y of
Evidence

Design:
Crosssectional
Purpose:
changes in
O misuse
among pt.’s
with new
legislative
response

n= 396
two Florida
based in pt.
cohorts

IVlegislative
response
DV- pre
and post
policy
opioid use;
any O, Rx
O, illicit O;
PO and
Intravenous

Self- report
questionnaire
R- not tested

t-tests
chi
square
analyses
Fisher’s
exact
stats

post policy
use:
any O:
↑24.21%
Rx O:
↑20.96%
Illicit O:
↑5.85%
PO:
↓37.6%
Intravenous
: ↑34.43%

LOE: IV
No CG
Increase in
overall o use
after policy
limit;
namely
intravenous

Theory/
Concep
tual
Frame
work
physiol
ogic

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Findings/
Results

Level/Qualit
y of
Evidence

Metanalysi
s
Purpose:
Assess the
efficacy of
the OCC
for
managing
chronic

n= 177
CG: (original
study n=157)
female: 106
male: 71
patients
prescribed O in
primary care

IVquestionnai
res
DV- pt.’s
selfreported
answers

OCC, BPI,
PDI (R .91),
HADS (.83),
SOAPP-R
(sensitivity
.86), ABC,
urine
toxicology,

Multiva
riate
logistic
regressi
on
models

“Run out of
your pain
medication
early”AUC .606
Missed any
scheduled
medical
appointmen

LOE: III
Questions 5
&6 best
identifying o
misuse at
baseline
**Pt.s in
PCP had
lower drug

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

Citation

Lagisetty, P., et al. (2017).
Country: U.S.
Fund: None identified
Bias: none

Citation

Theory/
Concept
ual
Framew
ork
physiol
ogic

Theory/
Concept
ual
Framew
ork

pain
patients
using O
compared
to an
original
study
Design/
Method

26
ts”AUC.607

misuse,
OCC 3x,
then
Questions
1,5,6

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Findings/
Results

Level/Qualit
y of
Evidence

Systematic
review
Purpose:
analyze
current
primary
care OUD
MAT
program
interventio
ns and
processes
that lead to
improved
pt.
outcomes

N= 35
10 randomized
control trials, 25
quasiexperimental
interventions in
primary care in 8
countries

IVinterventio
ns;
organizatio
n, process,
environme
nt, person,
technology
DV- % of
studies
with
common
themes

Evaluation
tables

Not
identifie
d,
commo
n
themes

↑pt.
retention,
consistent
need for
physician
education,

LOE: II
A lot of
themes
running
throughout,
overall best
results with
multidiscipli
nary care

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Findings/
Results

Level/Qualit
y of
Evidence

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

27

Madsen, A., et al. (2018).
Country: U.S.
Fund: Maternal and Child Health
Bureau, Health resources and services
administration, Department of Health
and Human Services
Bias: none

physiol
ogic

Cross
sectional
survey,
mixed
methods
Purpose:
to discover
OBGYN’s
knowledge
and
practice for
rx O

n= 300
CG= n/a
179 responded
OBGYN fellows
pat of the
Collaborative
Ambulatory
Research
Network

IVquestionnai
re- 1.
Screening
for
dependence
2. Rx the
smallest
amount
required 3.
Tailoring
Rx 4.
Counseling
on proper
disposal
DVproviders
responses

Survey; tested
on group of
volunteer
physicians- no
adjustments
made

Pearson
X2,
Fisher
exact
test, ttest

Provider
responses:
74% rx for
smallest #
of pills
p=.004,
56% aware
of proper
disposal,
19% know
misuse
source
from friend
or family

Citation

Theory/
Concept
ual
Framew
ork
physiol
ogic

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Findings/
Results

Cohort
Study
Purpose:
evaluate
effect of
voluntary
O tapering
program on
MEDD

n=113
CG= none
attrition: 7%
due to no
provider
response
inclusion:
providers with
>90 days of
pharmacy claims

IVenrollment
in O
tapering
program
DVMEDD

Pharmacy
records; ICD10-CM codes

Doesn’t
specify;
compar
e
MEDD
before
and
after
program
over 3

Change in
MEDD by
pt.: 0%,
↓3.6%,
↓4.5%,
↓42.9%,
↓45.5%,
↓46.1%
No
program

Page, J., et al. (2018).
Country: U.S.
Fund: Moda Health
Bias: Authors were employed by
Moda Health

LOE: IV
But
measuremen
t of
prescriber
knowledge
….
Not
statistically
significant,
but
important;
22% O
dependence
screening,
62% tailor O
Rx, 17%
counsel on
proper
disposal
Level/Qualit
y of
Evidence
LOE: IV
Restrictions
: 6 in
program,
study
measured
MEDD for
all 113
participants

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

28
with MEDD >0

Citation

Riggs, C., et al. (2017).
Country: U.S.
Fund: Department of Pharmacy at
Kaiser Permanente Colorado
Bias: authors employed by Kaiser
Permanente Colorado

Theory/
Concept
ual
Framew
ork
physiol
ogic

months

Design/
Method

Sample/ Setting

Major
Variables
&
Definitions

Measurement/
Instrumentatio
n

Data
Analysi
s

Crosssectional
Purpose:
compare
average
total daily
dose of O
purchased
by Kaiser
Permanente
Colorado
Medicaid
pt.s before
and after
Medicaid
shortacting O
quantity
limit

n= 2,
449 pts
CG= none
Age- 45.2

IVMedicaid O
quantity
limit
DV- # of O
purchased
before and
after
quantity
limit

Electronic
medical and
pharmacy
records to
assess
medication use

Wilcox
on’s
two
sample
test and
signedrank
test, chi
square
tests,
McNem
ar’s test

Kaiser
Permanente
Colorado
Medicaid pt.s
Inclusion: pt. to
purchase at least
1 short-acting O
using Medicaid
at KP pharmacy

change in
MEDD:
↓ in 10.3%,
0% in
20.6%, ↑ in
67.3%
Findings/
Results

Postperiod
TDD
OME: ↓
10mg, p
<.0001
Longacting o:
↑3.5%
P=.060,
Any
adjuvant
nonopioid:
↓10.9%, p=
<.001

Level/Qualit
y of
Evidence
LOE: IV
No CG
Statistically
significant ↓
in nonopioid
rx and TDD
OME,
↑ in long
acting
opiods,
pvalue not
significant

Key: ↓- decrease; ↑- increase; ABC-addiction behavior checklist; AUC- area under curve; BPI- brief pain inventory; CG- control group; DV-dependent variable;
DX-diagnosis; ED- erectile dysfunction; HADS- hospital anxiety and depression scale; HX-history; IV- independent variable; LOE- level of evidence; MATmedication-assisted treatment; MEDD- morphine equivalent daily dose; MI- myocardial infarction; N-number of studies; n- number of participants; O-opioid;
OBGYN- Obstetrician/Gynecologist; OCC-Opioid Compliance Checklist; OD- overdose; OME- oral morphine equivalent; ORC-opioid reassessment clinic;
OUD- Opioid Use Disorder; PACIC- patient assessment of care for chronic conditions; PCP- primary care provider; PDI- pain disability index; PO- by mouth;
PT-patient; R- reliability; RX-prescription; SOAPP-R- screener and opioid assessment for pain patients revised; TDD- total daily dose; TRIM- Tool to Reduce
Inappropriate Medications;

OPIOID MANAGEMENT

29
Appendix E

Table E1

Hoffman, L., et
al.

Jamison, R., et
al.

Lagisetty, P, et
al.

Madsen, A., et
al.

Page, J., et al.

Riggs, C., et al.

2017

2014

2014

2017

2017

2016

2017

2018

2018

2017

IV
CH

II
RCT

II
SR

II
RCT

IV
CS

III
MA

I
RCT,
QE,
OT

IV
CS,
MM

IV
CH

IV
CS

Basics

Design

Fried, T., et al.

LOE

Chou, R., et al.

Year

Carrieri, et al.

Studies

Becker, W., et al.

Synthesis Table: Opioid management

Mean
Age
Attrition

Major
Findings

Interventions

Bias
# of
participa
nts
policy

56.2

45.2

17%

7%
X

87

221

39

128

177

35

179

113

X

O taper

X

OCC
SOAPP

X
X

ORC
TRIM

X

MDC

X

X

O use

↓

↓

2449
X

X
X
X

X

X
X
I

X

X

↑IV, ↓
PO,
↑overall

Pr. S
Pt. S

396

↓

I
↑,

3.8/5

↑

↑

↑

KEY: ↓ - Decreased, ↑ - Increased, CH- Cohort study, CS- cross-sectional study, I- insufficient evidence, LOElevel of evidence, MA- meta-analysis, MDC- multidisciplinary care, MM- mixed methods study, O- opioid,
OCC- opioid compliance checklist, OME- oral morphine equivalent, ORC- opioid reassessment clinic, OTobservational trials, Pt.- Patient, Pr- provider, QE- quasi experimental, RCT- randomized control trial, Ssatisfaction, SOAPP- screener and opioid assessment for patients with pain, SR- systematic review, TDD- total
daily dose, TRIM- Tool to Reduce Inappropriate Medications

↓, ↑long
acting
opioids

OPIOID MANAGEMENT
need for
provider
education
Predictio
n of
abuse
TDD
OME
Med.
Rec.
Pt.
followup
Primary
care

30
X

I

X

X

↓

↓
↑
↑

X

X
↑

↑

X

X

KEY: ↓ - Decreased, ↑ - Increased, CH- Cohort study, CS- cross-sectional study, I- insufficient evidence, LOElevel of evidence, MA- meta-analysis, MDC- multidisciplinary care, MM- mixed methods study, O- opioid,
OCC- opioid compliance checklist, OME- oral morphine equivalent, ORC- opioid reassessment clinic, OTobservational trials, Pt.- Patient, Pr- provider, QE- quasi experimental, RCT- randomized control trial, Ssatisfaction, SOAPP- screener and opioid assessment for patients with pain, SR- systematic review, TDD- total
daily dose, TRIM- Tool to Reduce Inappropriate Medications

↓

OPIOID MANAGEMENT

Iowa model of EBP

31
Appendix F