ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 2108

A Pragmatic Cluster-Randomized Controlled Trial of an Automated, Pharmacy-Based Intervention to Optimize Allopurinol Therapy in Gout

Ted R. Mikuls1, T C Cheetham2, Nazia Rashid2, Gerald D. Levy3, Artak Kerimian4, KJ Low2, Brian Coburn5, David T. Redden6, S. Louis Bridges Jr.7, Kenneth G. Saag6 and Jeffrey R. Curtis7, 1Medicine, University of Nebraska Medical Center, Omaha, NE, 2Pharmacy Analytical Services, Kaiser Permanente Southern California, Downey, CA, 3Rheumatology, Kaiser Permanente Southern California, Downey, CA, 4Ambulatory Care Pharmacy, Kaiser Permanente Southern California, Downey, CA, 5Internal Medicine - Rheumatology, University of Nebraska Medical Center, Omaha, NE, 6University of Alabama at Birmingham, Birmingham, AL, 7Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL

Meeting: 2015 ACR/ARHP Annual Meeting

Date of first publication: September 29, 2015

Keywords: , , ,

Session Information

Date: Monday, November 9, 2015

Title: Metabolic and Crystal Arthropathies I: Therapeutics

Session Type: ACR Concurrent Abstract Session

Session Time: 4:30PM-6:00PM

Background/Purpose:  
Gout is a common form of inflammatory arthritis, often treated with allopurinol
as a first-line urate lowering therapy.   We have designed a large cluster-randomized
study to examine the impact of a pharmacist-driven intervention as a means of
optimizing allopurinol administration in gout.  With enrollment and follow-up
ongoing, completed efforts have focused on the development and implementation
of the intervention and an interim assessment of its impact on allopurinol dose
escalation and serum urate (sUA) testing.

Methods:    An
expert panel defined allopurinol treatment algorithms relevant for gout
patients initiating therapy.  The panel considered several allopurinol
treatment decisions using the RAND/UCLA Appropriateness Method.  Endorsed
decisions were incorporated into an algorithm with pharmacist-led interventions
that includes patient outreach designed around gradual allopurinol dose
escalation with the goal of achieving and maintaining a sUA < 6.0 mg/dl.  Ambulatory
pharmacists conduct outreach primarily via telephone interactive voice
recognition (IVR) system to assess adherence, facilitate sUA testing, provide
education, and to adjust allopurinol dosing.    Medical offices in the Kaiser
Permanente Southern California health system were cluster randomized by
geographic proximity (n = 103 clusters) to deliver either the pharmacist led intervention
or usual care to patients receiving new allopurinol prescriptions.  All participants
received an introductory letter that included a gout information booklet and an
opt-out option.  The algorithm served as a guideline and the pharmacist was
allowed to deviate from the guideline based on clinical circumstances. 

Results:   Two
allopurinol treatment algorithms were developed, one for patients with CKD stage
I/II and one for patients with CKD stage III/IV (stage V excluded); both incorporated
a treat-to-target strategy of dose titration to achieve sUA ≤ 6.0 mg/dl.  To
date, 441 patients have enrolled in the intervention with 810 participants
receiving usual care; 71 patients have opted out.  Characteristics of gout
patients enrolled between July 2014 and May 2015 are shown in addition to the
number of allopurinol prescriptions dispensed, frequency of dose change, and sUA
testing.

Conclusion:  
To address the typically suboptimal titration of allopurinol, we are
conducting a large pragmatic cluster-randomized trial to examine a highly
automated, exportable, pharmacist-driven intervention to optimize allopurinol treatment
in gout.  Deploying a treatment algorithm developed with expert input, approximately
1 of every 4 intervention patients has received allopurinol dose escalation,
more than twice that observed in usual care.  Novel elements of this
intervention and its unique study design features will inform future gout care.

 

 

INTERVENTION (N=441)

CONTROL (N=810)

Demographics

 

 

Age, years, mean (SD)

58.3 (14.4)

57.9 (14.2)

Men, n (%)

  357 (80.9%)

666 (82.2%)

Race / ethnicity, n (%)

 

 

     Caucasian

  143 (32.4%)

243 (30.0%)

     Other

  298 (67.6%)

567 (70.0%)

Number of allopurinol prescriptions dispensed*

 

 

     One

48.1%

62.3%

     Two

23.4%

21.1%

     Three

19.3%

11.2%

Four or more    

9.3%

5.3%

Allopurinol dose changes during observation

 

 

     Dose increased

26.5%

12.9%

     Dose decreased

0.9%

0.3%

     No dose change

72.6%

86.7%

Serum urate (SU) measurements

 

 

     Baseline SU measured

78.1%

78.2%

     Follow-up SU measured

78.2%

43.8%

          
*Primarily dispensed as 100-day prescriptions

Disclosure: T. R. Mikuls, None; T. C. Cheetham, None; N. Rashid, None; G. D. Levy, None; A. Kerimian, None; K. Low, None; B. Coburn, None; D. T. Redden, None; S. L. Bridges Jr., None; K. G. Saag, None; J. R. Curtis, Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie, 2,Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie, 5.

To cite this abstract in AMA style:

Mikuls TR, Cheetham TC, Rashid N, Levy GD, Kerimian A, Low K, Coburn B, Redden DT, Bridges SL Jr., Saag KG, Curtis JR. A Pragmatic Cluster-Randomized Controlled Trial of an Automated, Pharmacy-Based Intervention to Optimize Allopurinol Therapy in Gout [abstract]. Arthritis Rheumatol. 2015; 67 (suppl 10). https://acrabstracts.org/abstract/a-pragmatic-cluster-randomized-controlled-trial-of-an-automated-pharmacy-based-intervention-to-optimize-allopurinol-therapy-in-gout/. Accessed .

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