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The American Journal of Managed Care April 2011
Effect of Emergency Department Crowding on Pneumonia Admission Care Components
Christopher Fee, MD; Ellen J. Weber, MD; Peter Bacchetti, PhD; and Carley A. Maak, MD
Effect of Emergency Department Crowding on Pneumonia Admission Care Components
Christopher Fee, MD; Ellen J. Weber, MD; Peter Bacchetti, PhD; and Carley A. Maak, MD
Primary Care and Communication in Shared Cancer Care: A Qualitative Study
Yvonne H. Sada, MD; Richard L. Street Jr, PhD; Hardeep Singh, MD, MPH; Rachel E. Shada, MHR; and Aanand D. Naik, MD
Relevance of Current Guidelines for Organizing an Anticoagulation Clinic
Adam J. Rose, MD, MSc; Elaine M. Hylek, MD, MPH; Al Ozonoff, PhD; Arlene S. Ash, PhD; Joel I. Reisman, AB; Patricia P. Callahan, RPh; Margaret M. Gordon, PharmD; and Dan R. Berlowitz, MD, MPH
Electronic Medical Records and Efficiency and Productivity During Office Visits
Michael F. Furukawa, PhD
Consumer Attitudes Toward Personal Health Records in a Beacon Community
Vaishali N. Patel, PhD, MPH; Erika Abramson, MD, MS; Alison M. Edwards, MStat; Melissa A. Cheung, MPH; Rina V. Dhopeshwarkar, MPH; and Rainu Kaushal, MD, MPH
Long-Acting Beta-Agonist Monotherapy Among Children and Adults With Asthma
Elizabeth A. Wasilevich, PhD, MPH; Sarah J. Clark, MPH; Lisa M. Cohn, MS; and Kevin J. Dombkowski, DrPH
Electronic Medical Records and Efficiency and Productivity During Office Visits
Michael F. Furukawa, PhD
Drug Testing, Chronic Pain, and Financial Conflicts of Interest
Mark Collen, BS; Reply by Harry L. Leider, MD, MBA; Jatinder 'JD' Dhaliwal, MBA; Elizabeth J. Davis, PhD; Mahesh Kulakodlu, MS; and Ami R. Buikema, MPH
Primary Care and Communication in Shared Cancer Care: A Qualitative Study
Yvonne H. Sada, MD; Richard L. Street Jr, PhD; Hardeep Singh, MD, MPH; Rachel E. Shada, MHR; and Aanand D. Naik, MD
Community-Based Health Information Technology Alliances: Potential Predictors of Early Sustainability
Lisa M. Kern, MD, MPH; Adam B. Wilcox, PhD; Jason Shapiro, MD; Kahyun Yoon-Flannery, MPH; Erika Abramson, MD; Yolanda Barron, MS; and Rainu Kaushal, MD, MPH
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Relevance of Current Guidelines for Organizing an Anticoagulation Clinic
Adam J. Rose, MD, MSc; Elaine M. Hylek, MD, MPH; Al Ozonoff, PhD; Arlene S. Ash, PhD; Joel I. Reisman, AB; Patricia P. Callahan, RPh; Margaret M. Gordon, PharmD; and Dan R. Berlowitz, MD, MPH
A Multimodal Blood Pressure Control Intervention in 3 Healthcare Systems
David J. Magid, MD, MPH; P. Michael Ho, MD, PhD; Kari L. Olson, BSc (Pharm), PharmD; David W. Brand, MSPH; Lesley K. Welch, PharmD; Karen E. Snow, PharmD; Anne C. Lambert-Kerzner, MSPH; Mary E. Plomon
Drug Testing, Chronic Pain, and Financial Conflicts of Interest
Mark Collen, BS; Reply by Harry L. Leider, MD, MBA; Jatinder 'JD' Dhaliwal, MBA; Elizabeth J. Davis, PhD; Mahesh Kulakodlu, MS; and Ami R. Buikema, MPH
A Multimodal Blood Pressure Control Intervention in 3 Healthcare Systems
David J. Magid, MD, MPH; P. Michael Ho, MD, PhD; Kari L. Olson, BSc (Pharm), PharmD; David W. Brand, MSPH; Lesley K. Welch, PharmD; Karen E. Snow, PharmD; Anne C. Lambert-Kerzner, MSPH; Mary E. Plomon
Consumer Attitudes Toward Personal Health Records in a Beacon Community
Vaishali N. Patel, PhD, MPH; Erika Abramson, MD, MS; Alison M. Edwards, MStat; Melissa A. Cheung, MPH; Rina V. Dhopeshwarkar, MPH; and Rainu Kaushal, MD, MPH
Long-Acting Beta-Agonist Monotherapy Among Children and Adults With Asthma
Elizabeth A. Wasilevich, PhD, MPH; Sarah J. Clark, MPH; Lisa M. Cohn, MS; and Kevin J. Dombkowski, DrPH
Electronic Health Record Functions Differ Between Best and Worst Hospitals
Shereef M. Elnahal, BA; Karen E. Joynt, MD; Steffanie J. Bristol, BS; and Ashish K. Jha, MD, MPH

Relevance of Current Guidelines for Organizing an Anticoagulation Clinic

Adam J. Rose, MD, MSc; Elaine M. Hylek, MD, MPH; Al Ozonoff, PhD; Arlene S. Ash, PhD; Joel I. Reisman, AB; Patricia P. Callahan, RPh; Margaret M. Gordon, PharmD; and Dan R. Berlowitz, MD, MPH
Anticoagulation clinics in an integrated healthcare system differed widely in their organization and management, but these differences were not consistently related to their performance.

Objective: To describe variations in the structure of anticoagulation clinic (ACC) care within the Veterans Health Administration (VA) and to identify structures of care that are associated with better site-level anticoagulation control.

 

Study Design: Questionnaire correlated with automated clinical data.

 

Methods: We characterized 90 VA ACCs using a questionnaire administered by the VA Central Office. Site descriptors included staffing levels, provider training, visit modalities, quality improvement programs, documentation, and care coordination. Patient outcomes were measured by site mean risk-adjusted percentage time in therapeutic range, a measure of anticoagulation control over time. Our study was powered to detect a 3% difference in risk-adjusted percentage time in therapeutic range, a small-to-moderate effect size, between sites with and without a certain characteristic.

 

Results: We observed considerable variation in the structure of ACC care. For example, 48 sites had fewer than 400 patients per provider, 25 sites had 400 to 599 patients per provider, and 17 sites had 600 patients or more per provider. However, none of the site characteristics measured were significantly related to anticoagulation control.

 

Conclusions: We found substantial variation in guideline-targeted organizational and management features of ACC care within the VA. However, no single feature was associated with better anticoagulation control. Current guidelines for organizing an ACC may have limited relevance for improving patient outcomes.

 

(Am J Manag Care.  2011;17(4):284-289)

Dedicated anticoagulation clinics (ACCs) improve anticoagulation control and patient outcomes.

  • Clinical guidelines recommend that ACCs should have certain features, but these recommendations are based on expert opinion rather than on empirical evidence of benefit.
  • In our study, 90 ACCs in an integrated system of care differed widely in their organization and management; however, none of these differences were consistently related to ACC performance as measured by anticoagulation control, an important intermediate outcome of anticoagulation care.
  • Current guidelines for organizing and managing an ACC may have limited relevance for improving outcomes.
Millions of patients receive oral anticoagulation therapy to treat or prevent thromboembolic disease.1 While effective management of warfarin sodium therapy is not easy, better anticoagulation control can improve outcomes and reduce adverse events.2 Indeed, a growing body of literature has shown that patients whose care is managed in  dedicated anticoagulation clinics (ACCs) have better outcomes than those managed in usual care.3-6 Clinical guidelines1,7 recommend that all ACCs should have certain features, including quality improvement programs, adequate documentation of care, sufficient training for providers, and a ratio of patients to providers of less than 400:1. However, there is little evidence as to which, if any, of these features contribute to the improved outcomes seen with ACC care.

Although oral anticoagulation therapy has been used for more than 5 decades, quality measurement has had little penetration into this field.2 Our group recently undertook the first systematic effort to profile riskadjusted anticoagulation control in an integrated health system. Within the Veterans Health Administration (VA), a system in which essentially all anticoagulation therapy is managed in an ACC, the mean percentage time in therapeutic range (TTR) varied widely among sites,8 with some sites performing more than 10% better or worse than would be expected based on the risk-adjustment model. Variations of this magnitude are associated with important differences in rates of stroke, venous thromboembolism, and major hemorrhage.9-13 To help all sites in the VA improve their performance, it is necessary to understand the site-level correlates of better or worse anticoagulation control.

Therefore, this study had the following 2 objectives: first, to describe differences in the organization and management of ACCs within the VA, and second, to assess whether these differences help explain sitelevel differences in anticoagulation control. We measured site characteristics using a survey of VA ACCs that examined structural features that seem likely to affect anticoagulation control, including staffing ratios, provider training protocols, and the existence of quality improvement programs.1,7 We hypothesized that these variables would be associated with anticoagulation control. In this study, either a positive finding or a negative finding would be useful because it can help determine whether enforcing conformity to any specific feature is likely to improve anticoagulation care and control in the VA.

METHODS

Data

The data for this study have been described elsewhere. The Veterans Affairs Study to Improve Anticoagulation8,14 included all patients who received oral anticoagulation therapy from the VA between October 1, 2006, and September 30, 2008. The study was approved by the institutional review board of the Bedford VA Medical Center, Bedford, Massachusetts.

We included international normalized ratio (INR) values when patients were “on warfarin” (ie, when a patient was in possession of warfarin or was having INR tests performed at least every 42 days). We defined the period of warfarin possession as the duration of the most recent VA prescription for warfarin, plus 30 days. We calculated percentage TTR using the method by Rosendaal et al,15 which assigns an INR value to each day by linear interpolation between successively observed INR values. Gaps of 56 days or more between INR values are not interpolated. The patient’s TTR equals the percentage of days for which the interpolated INR values lie between 2.0 and 3.0 (from 0%-100%).

Independent Variables of Site-Level Characteristics

There are 128 sites of care within the VA, each of which includes a hospital, an outpatient care center, and several outlying community-based clinics. Each site has a specialized ACC, which is usually run by clinical pharmacists under the supervision of a medical director.16 Therefore, essentially all anticoagulation care within the VA is delivered within specialized ACCs. In October 2006, VA Pharmacy Benefits Management surveyed all 128 VA sites of care for the organization and management of their ACCs. Topics included visit modalities (face to face, telephone, and mail), quality improvement programs, clinic staffing, provider training, documentation, and care coordination (the verbatim text of the questionnaire is given in the eAppendix [available at www.ajmc.com]). We abstracted our independent variables from the responses to the questionnaire.

Dependent Variable of Risk-Adjusted Anticoagulation Control

Site mean TTR was adjusted for case mix using a model that incorporates patient demographics, comorbid conditions that have an adverse effect on TTR, and general measures of comorbidity, including the number of medications and the number of hospitalizations. The derivation and validation of this model, which achieved an R2 of 13.3%, has been described previously.8,14 The model was used to calculate the expected mean TTR for each site (“E”) based on patient characteristics. The expected mean TTR was compared with the observed mean TTR for each site (“O”). Therefore, each site’s performance was characterized by an O minus E (“O − E”) score, our measure of risk-adjusted TTR (RA-TTR).

Statistical Analysis and Power

We began by first calculating the mean observed TTR and the mean expected TTR for each site of care and then computing an O − E score for each site. We compared O − E scores between sites with and without various organizational characteristics using unpaired t test and compared O − E scores for multilevel variables using analysis of variance. We did not adjust for multiple comparisons. With regard to statistical power, for a characteristic present at half of the sites, t test would have 80% power to detect a 3% difference in the O − E score (a small-to-moderate effect size). Analyses were performed using commercially available statistical software (SAS version 9.1; SAS Institute, Cary, North Carolina).

RESULTS

Study Sample

Of 128 sites in the VA, 28 were excluded because their data were insufficiently complete to fully assess TTR. Of the remaining 100 sites, 5 did not respond to the  questionnaire. Five other sites included more than 1 ACC, and the responses we received indicated that practices at the multiple ACCs of these 5 sites were not uniform. However, the dependent variable (RA-TTR) was assessed at the level of the overall site. Because we were unable to match our data for structure and outcomes, we excluded these 5 sites as well. This left 90 sites with complete data on structure and outcomes of care. The mean (SD) number of patients managed at each site was 1244 (799). The site mean TTR ranged from 38% to 69% (median, 58%). Site O − E scores ranged from −17% (ie, 17% below the expected value) to 12%.

Structure of Care and Relationship With Performance

We observed considerable variation in structure of care (Table 1). About half of the sites (n = 50) conducted most of their visits face to face; at other sites, most care was provided by telephone or mail. Most sites (n = 59) had some sort of quality improvement program, although only 7 sites used formal plan-do-check-act cycles. Most sites (n = 77) had some sort of support; 43 sites had clerical support. About half of the sites (n = 41) had a formal protocol for training new clinic providers. Many sites (n = 48) adhered to the recommended staffing ratio of less than 400 patients per provider (Table 2), although 17 sites had 600 or more patients per provider. Sites differed markedly for the perceived likelihood of being informed about a new drug-drug interaction.

Despite these differences in structure of care, we found no statistically significant predictors of site-level performance. A finding of marginal statistical significance was that 8 sites that did not allow telephone follow-up visits had almost 3% worse TTR (P = .10). There was also a hint, although not statistically significant, that sites with fewer than 500 patients under management might have worse control (performance difference, −1.6%).

Sensitivity Analyses

We performed sensitivity analyses by altering the format of the dependent variable. To ensure that our risk-adjustment model was not obscuring relationships between  structure and outcomes, we also examined the same independent variables as predictors of the mean unadjusted TTR by site, with similar results (data not shown). We also tried categorizing site O − E scores into the top quintile, bottom quintile, and all others and repeated our analyses; the results were unchanged (data not shown).

We also performed sensitivity analyses by altering the format of the independent variables. For example, we varied the cutoffs for what constituted a small site of care or for what constituted adequate staffing levels; the results were unchanged. Finally, we created a combination quality score by assigning a point for each putative quality indicator that a site fulfilled, to examine whether these factors predicted performance better in the aggregate than individually. For example, a site might receive 1 point for having a dedicated program to train providers, 1 point for having fewer than 400 patients per provider, and 1 point for using a computerized system for documentation and patient   tracking. We examined several different versions of this combination quality score, including various measures and assigning them variable relative weights, but none of  these combination scores predicted site RA-TTR.

DISCUSSION

We examined site-level organizational factors (structure of care) as potential predictors of outpatient oral anticoagulation control (outcomes of care).17 Although our hypotheses were supported by consensus guidelines,1,7 the site-level characteristics that we studied were not associated with anticoagulation control. Many studies relating structure and processes of care have been performed within the VA among sample sizes similar to that of this study. One such study18 found that organizational culture and commitment to continuous quality improvement were not associated with better processes of care for depression. However, most other studies have found associations between various aspects of organizational culture and processes of care, including rates of cancer screening19-22 and recommended processes of care for heart failure,23 chronic lung disease,24 and diabetes mellitus.25 In the diabetes study, the authors also found associations between organizational culture and intermediate

 
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