Factors Affecting Compliance with Diabetes Hypertension Guidelines

1
Factors Affecting Compliance with Diabetes
Hypertension Guidelines

• Julie C. Lowery, PhD, MHSA
• Sarah L. Krein, PhD, RN
• Lee A Green, MD, MPH
• Leon Wyszewianski, PhD
• Hyungjin Myra Kim, ScD
• Christine P. Kowalski, MPH
• VA HSRD Center of Excellence
• University of Michigan Departments of Health
  Management Policy, Family Medicine
• Ann Arbor, MI

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Introduction

• Question How to get clinicians to change their
  practices and adopt practice guidelines for
  treating hypertension in patients with diabetes?

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Introduction

• Educational strategies are most common, but
  seldom result in lasting practice changes.
• Other strategies work some of the time, but none
  works all of the time.

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Introduction

• New perspective by Wyszewianski and Green
  provides a guide for selecting the most effective
  change strategies for a given group of
  physicians
• Wyszewianski L, Green LA. Strategies for
  changing clinicians practice patterns A new
  perspective. J Fam Pract 200049461-4.

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Introduction

• Clinicians are classified into four categories
  based on their usual responses to new research
  findings about the effectiveness of clinical
  practices seeker, receptive, traditionalist,
  pragmatist.
• Classification is based on scores from 3
  subscales evidence, practicality, conformity.

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Introduction

• A valid physician classification instrument could
  be used by clinicians and managers, both within
  and outside VHA, to tailor the design of their
  research translation or guideline implementation
  efforts to the types of physicians in their
  organizations, thereby improving the
  effectiveness of their efforts.

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Objective

• To evaluate the construct validity and
  reliability of the physician classification
  instrument.

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Primary Hypothesis

• Compliance with medication guidelines for
  diabetes patients with hypertension varies by
  physician category and guideline implementation
  strategy.

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Methods

• Cross-sectional, observational design.
• Primary and secondary data collection.

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Analysis

• Logistic regression, clustering within provider.
• DV Adherence to medication guidelines (yes/no).
• IVs Site implementation strategies, physician
  category (defined two different ways).

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Data Collection Phase I

• IV Site implementation strategies.
• Semi-structured telephone interviews were
  conducted with 2 clinical representatives at 43
  participating VA medical centers to determine
  what strategies were implemented for meeting
  diabetes hypertension guidelines in the time
  period from 1999-2001.

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Data Collection Phase II

• IV Physician categories.
• All primary care physicians (PCPs) in the
  participating VAMCs were sent a one-page
  questionnaire (the physician classification
  instrument) regarding their responses to research
  findings about the efficacy of specific clinical
  practices. Instrument.

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Data Collection Phase III

• DV Adherence to medication guidelines (yes/no).
• Defined as of each participating
  physicians patients with diabetes and HTN who
  were on HTN meds at time of elevated BP reading,
  or who had ? in dosage or ? in med class in 6
  months following reading.

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Data Collection Phase III

• Diabetes (1) had filled a prescription for
  diabetes medications or blood glucose monitoring
  supplies or, (2) had 1 inpatient or 2 outpatient
  encounters with a diabetes related ICD-9 code
  (250.x, 357.2, 362.0-362.1, 366.41) in fiscal
  year (FY) 1999.
• HTN BP gt 140/90 mmHg.
• HTN meds ace inhibitors, beta blockers, calcium
  channel blockers, alpha blockers, angiotensin II
  inhibitors, diuretics.
• Data sources VA secondary data sets with data
  on vitals, medications, diagnoses.
• Time frame October 1998 March 2000.

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Data Collection Phase III

• Data sources VA secondary data sets with data
  on vitals, medications, diagnoses.
• Time frame October 1998 March 2000.
• Patient data were matched to each participating
  PCP.

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Results Phase I

• All sites used some type of educational approach
  to implement the guidelines (written,
  presentation, or conference).
• Over 90 of sites also provided group or
  individual feedback on physician performance on
  the guidelines, and over 75 implemented some
  type of reminder system.
• Minority of sites used monetary incentives,
  penalties, or barrier reduction.

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Results Phase II

• Of 745 questionnaires distributed to primary care
  physicians, 307 were returned (response rate of
  41.2).
• Of 307 questionnaires returned, 16 had missing
  data, leaving a total of 291 useable
  surveys/PCPs.
• Factor analysis confirmed the 3-factor
  psychometric scaling used previously (2 questions
  dropped).

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Results Phase III

• 174 pragmatists (59.8)
• 80 receptives (27.5).
• 36 seekers (12.4).
• 1 traditionalist (0.3).

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Results Phase III

• The total number of diabetes patients in the 42
  participating sites was 208,653 in 1999.
• Patients in the diabetes cohort were assigned to
  participating PCPs if more than 50 of a
  patients outpatient medical clinic visits were
  to a participating PCP.
• Final dataset 1174 diabetes patients had BP
  data, had HTN, and could be matched to 163 of our
  participating PCPs.

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Results Phase III

• 1st method of measuring interaction between
  intervention strategy and physician category
  (concordance scores) ? no association with
  guideline adherence.

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Results Phase III

• 2nd method of measuring interaction between
  intervention strategy and physician category
• Interventions were coded as the number of
  educational interventions, barrier removal
  interventions, and motivational interventions (3
  variables).
• Physician characteristics coded as scale scores
  (3 variables).

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Results Phase III

• Testing without interactions
• Only conformity scale was significantly
  associated with guideline concordant-care. Lower
  conformity was associated with better decisions.
• No association between guideline interventions
  and guideline concordant care.

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Results Phase III

• Testing full model with all 2-way interactions
  between interventions and physician scale scores
• The only interaction that approached significance
  was conformity with barrier removal (p 0.07).
  Barrier reduction was associated with improved
  guideline concordance for the least conforming
  physicians, but not for the conforming
  physicians. Figure
• Significant positive association of barrier
  removal with guideline concordance (p 0.03).

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Results Reliability

• One-year test-retest results. Of the 291
  participating providers with useable surveys, 263
  (90) completed follow-up surveys one year later.
  The correlations for the three subscales were as
  follows
• Evidence .75
• Practicality .68
• Non-comformity .75
• These findings suggest that physician scores on
  the three subscales remain relatively stable over
  time, indicating that the concept of physician
  response to new information is more of a trait
  than a state.

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Discussion

• Main conclusions
• Non-conformity is associated with better
  guideline adherence.
• Barrier reduction is associated with better
  guideline adherence.
• As conformity increases, the impact of barrier
  reduction decreases.
• Guideline implementation strategies that were
  designed to reduce, or at least not increase,
  physician time demands and task complexity were
  the only ones that improved guideline
  adherenceparticularly for physicians low on the
  conformity scale. In other words, the more
  physicians were willing to practice differently
  from the local norm, the more they took advantage
  of system changes to change their own practices.

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Discussion

• Education may have been necessary, but it was
  clearly not sufficient all sites included
  education in their mix of strategies, but those
  doing a great deal of it saw no more effect than
  those doing the minimum.
• Incentives had no discernible effect.

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Discussion

• Primary hypothesis was not validno association
  between physician type/intervention interaction
  (measured by concordance scores) and guideline
  adherence.
• Possible explanation time constraints of
  current delivery environment?
• Is an instrument for measuring physician type
  useful?
• Limitation Small sample size.

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Discussion

• Focus of interventions should be at the system or
  organizational level, rather than the provider.
• Results consistent with other studies ? quality
  improvement efforts should focus on addressing
  facility-level performance variations, because of
  the small amount of variation in performance
  found at the provider level.