Conference PaperPDF Available

Improving the management of chronic non-cancer pain in primary care: Results of a multifaceted quality improvement initiative

Springer Nature
Implementation Science
Authors:

Abstract

How the research advances dissemination and implementation research: The management of chronic pain poses a significant challenge for primary care practices, particularly those caring for medically underserved patient populations. Experience in the Veterans Health Administration (VHA) has demonstrated that implementation of a Stepped Care Model for Pain Management (SCM-PM) can improve outcomes for patients with chronic pain. In this project, we advance the dissemination and implementation research by describing the use of the Promoting Action on Research Implementation in Health Services (PARIHS) Framework to guide the adaptation, implementation, and dissemination of the SCM-PM to a non-VHA setting-a large, statewide Federally Qualified Health Center.
MEETI N G ABST R A C T Open Access
Improving the management of chronic non-cancer
pain in primary care: Results of a multifaceted
quality improvement initiative
Daren Anderson
1*
, Ianita Zlateva
1
, Brent Moore
2
From 7th Annual Conference on the Science of Dissemination and Implementation in Health
North Bethesda, MD, USA. 8-9 December 2014
How the research advances dissemination and imple-
mentation research: The management of chronic pain
poses a significant challenge for primary care practices,
particularly those caring for medically underserved
patient populations. Experience in the Veterans Health
Administration (VHA) has demonstrated that imple-
mentation of a Stepped Care Model for Pain Manage-
ment (SCM-PM) can improve outcomes for patients
with chronic pain. In this project, we advance the disse-
mination and implementation research by describing the
use of the Promoting Action on Research Implementa-
tion in Health Services (PARIHS) Framework to guide
the adaptation, implementation, and dissemination of
the SCM-PM to a non-VHA setting-a large, statewide
Federally Qualified Health Center.
Overall project implementation
Chronic pain is extremely common in safety-net prac-
tices. The Stepped Care Model for Pain Management
(SCM-PM) has been shown to improve outcomes in the
Veterans Health Administration (VHA) system. To
examine whether this model is transferable to non-VHA
settings we undertook a three-year quality improvement
project to adapt and implement the SCM-PM in a large,
statewide Federally Qualified Health Center.
This project used an observational mixed methods
evaluation framework and used the PARIHS Framework
to guide the design of the intervention. Study subjects
included all patients and providers (PCPs) of the health
center. The principal goals of the project were 1) to
improve the screening for and management of routine
pain complaints in primary care using basic tools and
protocols to improve the assessment, documentation,
treatment, and monitoring of pain; and 2) to provide
additional resources and supports for PCPs to assist in
managing more complex cases.
The use of opioid treatment agreements among
patients using opioids chronically (COT), increased from
49% to 64%. The number of COT patients with a urine
drug test within the preceding six months increased from
867 (66%) to 1,097 (86%). Patients with a completed pain
functional assessment increased from 428 (33%) to 589
(46%). The percentage of patients co-managed by an
onsite behavioral health provider increased from 22.5%
to 24.4%. Referrals to chiropractors also increased. There
was a decline in number of patients with pain receiving
any opioid prescriptions from 43% to 40%, and in those
receiving COT from 17.5% to 15.9%. The percentage of
patients with an episode of severe pain decreased from
74% to 61%. Surveys showed that CHCI PCPs expressed
increased confidence in their ability to manage pain
effectively and had an increase of 9.2% in pain manage-
ment knowledge scores.
Identifying patients with chronic non-cancer pain
in large datasets
To implement successfully the Stepped Care Model for
Pain Management (SCM-PM) at our statewide Federally
Qualified Health Center, we had to identify all patients
with chronic non-cancer pain (CNCP). A straightforward
method for identifying patients with CNCP solely using
structured electronic health record (EHR) data does not
exist. Individual data elements such as pain scores or
diagnostic codes (ICD9) are not sufficiently reliable or
comprehensive. Our objective was to develop and
* Correspondence: Daren@chc1.com
1
Weitzman Institute, Community Health Center Inc, Middletown, CT 06457
USA
Full list of author information is available at the end of the article
Anderson et al.Implementation Science 2015, 10(Suppl 1):A45
http://www.implementationscience.com/content/10/S1/A45
Implementation
Science
© 2015 Anderson et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://
creativecommons.org/licenses/b y/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/
zero/1.0/) applies to the data made available in this article, unless otherwise stated.
validate an accurate method to identify patients with
CNCP using EHR data.
We identified patients with CNCP in our EHR system
using a comprehensive set of data elements including
diagnostic codes, patient-reported pain scores, and pre-
scription opioid medications. Reviews of the medical
chart were used to evaluate the accuracy of these data
elements in all their combinations. Based on these eva-
luations we developed an algorithm to more accurately
identify patients with CNCP. The algorithmsresults
were validated by comparing them with the documenta-
tion of chronic pain by the patients treating clinician in
381 random patient charts.
The new algorithm, using pain scores, prescription
medications, and ICD9 codes had a sensitivity and spe-
cificity of 84.8% and 97.7%, respectively. The algorithm
was more accurate (95.0%) than pain scores (88.7%) or
ICD9 codes (93.2%) alone. The Receiver Operating
Characteristic was 0.981.
The newly developed and validated algorithm uses a
combination of readily available elements from the EHR
system to accurately identify patients with CNCP. By
applying the algorithm to our patient population, we
were able to gain a better understanding of the extent of
chronic pain and how it is managed in our health centers.
This helped us to better tailor our implementation efforts
to the needs of the patients with CNCP and their primary
care providers.
Pain care quality documentation chart reviews
The Veterans Health Administration (VHA) has engaged
in a system-wide transformational effort to implement
the Stepped Care Model of Pain Management (SCM-PM)
as its single standard of care for Veterans with painful
conditions. Successful organizational improvement
processes typically rely on reliable metrics to establish
targets for improvement and to monitor progress. This
project examined the utility of the measure of Pain Care
Quality (PCQ) documentation in evaluating implementa-
tion of the SCM-PM at one VHA healthcare system and
to explore its generalizability in a non-VHA Federally
Qualified Health Center undergoing a similar organiza-
tional improvement effort.
From 2009 to 2012 a comprehensive pain manage-
ment performance improvement approach was imple-
mented at the VHA. Two hundred progress notes per
year (July 2008 -June 2012) were randomly sampled
from VHA primary care prescribers of chronic opioid
therapy (COT). Using the PCQ extraction tool, each
note was reviewed and coded for the presence of key
dimensions of PCQ documentation, namely pain assess-
ment, treatment, and reassessment of outcomes. General
Estimating equations (GEE) controlling for provider and
facility, with post-hoc pair comparisons were used to
examine changes in PCQ items over the four years. This
approach was replicated in a multi-site FQHC for two
consecutive years (2011-2012).
Significant improvements were noted in pain reassess-
ment and patient education, with trends in improvement
noted for pain assessment and treatment planning.
Several specific dimensions of pain assessment and treat-
ment planning also improved significantly, including
documentation of functional assessments (p < 0.001).
Although post hoc comparisons generally documented
improvements over time, some variability across the four
years of observation suggest that these trends are not
entirely linear. Although none of the dimensions of PCQ
at the FQHC were significant, results suggest trends in a
positive direction across all dimensions of PCQ.
Authorsdetails
1
Weitzman Institute, Community Health Center Inc, Middletown, CT 06457
USA.
2
Department of Psychiatry, Yale University School of Medicine, New
Haven, CT 06510 USA.
Published: August 2015
doi:10.1186/1748-5908-10-S1-A45
Cite this article as: Anderson et al.: Improving the management of
chronic non-cancer pain in primary care: Results of a multifaceted quality
improvement initiative. Implementation Science 2015 10(Suppl 1):A45.
Submit your next manuscript to BioMed Central
and take full advantage of:
Convenient online submission
Thorough peer review
No space constraints or color figure charges
Immediate publication on acceptance
Inclusion in PubMed, CAS, Scopus and Google Scholar
Research which is freely available for redistribution
Submit your manuscript at
www.biomedcentral.com/submit
Anderson et al.Implementation Science 2015, 10(Suppl 1):A45
http://www.implementationscience.com/content/10/S1/A45
Page 2 of 2
20
Article
Objective: Previous research suggests that race/ethnicity predicts health-related quality of life (HRQL) in chronic pain populations but has not examined this in community settings. This study evaluated this association in 522 community-dwelling patients with chronic pain treated at a Federally Qualified Health Center (FQHC). Design: Cross-sectional secondary analysis. Setting: Six practice sites of an FQHC in New York. Subjects: One hundred forty-two non-Hispanic blacks, 121 non-Hispanic whites, 219 Hispanics, and 40 classified as "other" with severe chronic pain. Methods: Patients with chronic severe pain (three or more months with worst pain ≥ 4/10 or T-score > 60.5 on the Patient-Reported Outcomes Measurement Information System pain interference tool) were interviewed as part of a clinical trial. Race/ethnicity and other potential predictors of HRQL were assessed. Results: Mean age was 53.0 years, and 70.1% were women; 62.8% earned less than $10,000 per year, and 22.8% were Spanish-speaking with low acculturation. Mean worst pain during the past week was 8.6/10, and 39.6% used opioids. In multivariate analyses, race/ethnicity was not significantly associated with mental HRQL. Hispanics had significantly lower physical HRQL than non-Hispanic whites or blacks, but this difference was not clinically meaningful (mean T-scores = 33.9 [Hispanics], 35.8 [non-Hispanic whites], and 35.6 [non-Hispanic blacks]). Mental HRQL was predicted by depression, anxiety, pain disability, income, and physical HRQL; physical HRQL was predicted by race/ethnicity, anxiety, pain disability, age, care satisfaction, and mental HRQL. Conclusions: Race/ethnicity does not explain important variation in HRQL reported by diverse patients with chronic pain. Psychological distress, pain disability, age, and socioeconomic status predicted this health outcome. Future studies may clarify modifiers of these associations to guide treatment in FQHC populations.
ResearchGate has not been able to resolve any references for this publication.