Health Professional Morale Lisa S. Meredith, Ph.D. Benjamin - - PowerPoint PPT Presentation

Long-Term Impact of Evidence-Based Quality Improvement for Facilitating Medical Home Implementation on Primary Care Health Professional Morale

Lisa S. Meredith, Ph.D. Benjamin Batorsky, M.A. Doctoral Fellow Matthew Cefalu, Ph.D. Jill Darling, M.S.H.S. Susan Stockdale, Ph.D. Elizabeth M. Yano, Ph.D., M.S.P.H. Lisa V. Rubenstein, M.D., M.S.P.H. AcademyHealth June 26, 2017

• New patient-centered primary care models can

potentially improve primary care provider (PCP) and staff morale – Patient-Centered Medical Home (PCMH) – Including the VA’s Patient Aligned Care Team (PACT) initiative (launched in 2010)

• They also may improve efficiency by reducing

unnecessary utilization and costs, and ultimately improve patient care

• And can be associated with positive experiences

New models of care hold promise

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• May increase PCP/staff burnout due to high levels of

transformational change required

• Large literature on prevalence/causes of burnout but

little on how healthcare organizations can work to reduce it.

• Use of evidence-based quality improvement (EBQI)*

to facilitate change is promising – Multi-level strategy to promote regional and local primary care practice engagement in innovation – Ease potential PCP/staff burnout during system- wide transformation to PCMH

But implementation is challenging

*Rubenstein et al., 2010; 2014

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• 1 of 5 diverse VHA PACT Demonstration

Laboratories funded by the VHA Office of Patient Care Services* in 2010

• To develop and implement systematic methods for

supporting and evaluating the VHA’s transition to the PCMH model (PACT)

• Used EBQI as in improvement intervention in one

regions to engage practices in innovations and easy potential burnout

Veterans Assessment Improvement Laboratory (VAIL) for Patient-Centered Care

4 *to Drs. Rubenstein, Yano, and Altman.

• Promotes cross-discipline, data-driven problem

solving in local primary care practices

• Aligns local practices with organizational

priorities to sustain successful QI innovations

• ver time and spread them across teams/clinics
• Focuses on engaging and empowering front-line

primary care teams with multi-level, interdisciplinary stakeholders in structured EBQI

EBQI Intervention

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• Solicited brief innovation proposals (n=71) submitted through

– The EBQI practice’s quality council (supported by a quality council coordinator) OR – An across-EBQI site VAIL workgroup

• Additional support for approved projects

– Limited release time for leaders (per prior MoU) – Priority setting by regional leaders (administrators, quality, medical care, information technology, patient advocacy, & pharmacy experts) who reviewed/rated proposals – Annual collaborative learning sessions for EBQI practices – Local primary care site audit and feedback (practice level data on patients, providers/staff) for quality councils

EBQI Proposal Review and Approval Process

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• Received additional support:

– Rapid innovation evidence review – Budget of $12,000 – QI facilitation for project management and measures

• Successful projects generated toolkits (n=12) if the

innovation spread to at least 1 other site

• There were 6 approved and completed projects plus

6 additional volunteer projects completed during the reported time period that addressed burnout

Approved EBQI Projects (n=26)

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• Quasi-experiment to assess change over time in

attitudes/experiences with PACT implementation across 42 months

• Cohort of 356 PCPs/staff
• Compared the impact of PACT transformation alone

to PACT + EBQI on burnout (emotional exhaustion) – 3 Early EBQI intervention clinics (August 2010) – 3 Late EBQI intervention clinics (May 2012) – 17 Comparison clinics

Study Design and Intervention Evaluation

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Wave 1

(11/30/11 – 3/13/12)

Wave 2

(8/1/13 – 10/11/13)

Wave 3

(9/10/15 – 1/8/16)

Data: 3 Waves of Surveys

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Survey Response Rates by Staff Type and Wave

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Survey Response Rates for EBQI and Comparison Practices by Wave

11 59 49 38 59 48 55

10 20 30 40 50 60 70 Wave 1 Wave 2 Wave 3 % Complete EBQI Comparison

Demographic Characteristics

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Characteristic EBQI (n=181) Comparison (n=175) All (n=356) Female, n (%) 124 (67) 121 (70) 245 (69) Latino, n (%) 20 (11) 15 (9) 35 (10) Non-white Non-Latino, n (%) 87 (47) 71 (41) 158 (44) Age, mean years (SD) 47.4 (10) 47.6(11) 46.8 (10.9) Years in clinic, mean (SD) 8.0 (8.1) 5.2 (7.1) 7.0 (7.7)*

*p<01, where EBQI and comparison employees differ significantly for these variables.

Professional Characteristics

13 Characteristic EBQI (n=181) Comparison (n=175) All (n=356) Physician* _ 75 (21) Gen Practice/Family Med 3 (2) 7 (4) 10 (3) Internal Medicine 39 (22) 20 (11) 59 (17) Other Specialty 3 (2) 3 (2) 6 (2) Nurse Practitioner 12 (7) 16 (9) 28 (8) Physician Assistant 2 (1) 2 (1) 4 (1) Registered Nurse 48 (27) 49 (28) 97 (27) Licensed Practical/Voc.Nurse 37 (20) 41 (23) 78 (22) Mental Health Professional 5 (3) 9 (5) 14 (4) Dietician or Nutritionist 5 (3) 3 (2) 8 (2) Pharmacist 11 (6) 12 (7) 23 (6) MedicalTech/Assistant/Clerk 16 (8) 13 (7) 28 (8)

*Other specialty includes rheumatology, geriatrics, and infectious disease. Data are missing for 32 physicians.

PCPs Staff

15 20 25 30 Wave 1 Wave 2 Wave 3 15 20 25 30 Wave 1 Wave 2 Wave 3

Change in Burnout Scores (Emotional Exhaustion) Across Wave by Intervention Group for PCPs and Staff

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PCPs Staff

3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4 Wave 1 Wave 2 Wave 3 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4 4.1 Wave 1 Wave 2 Wave 3

Change in Job Satisfaction Across Wave by Intervention Group for Primary Care Providers

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• EBQI was effective in reducing burnout for PCPs

(but not staff) relative to PACT alone – Effect sizes of 0.40-0.50 of a standard deviation

• n the 0-54 point EE dimension of burnout
• EBQI to support PCMH transformation may alleviate

burnout and reduce variation in implementation

• utcomes across clinics during early implementation
• EBQI approach is consistent with recommendations

from West et al. (2016) review or interventions to reduce burnout

– Used both individual and organizational strategies to engage providers and leadership

Summary of Findings and Implications

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lisa_meredith@rand.org

Questions?

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Results from Regression Models for Change in Burnout

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Effect PCPs EE Change (CI) Staff EE Change (CI) Difference in Differences (Wave 3 – Wave 1) Early EBQI-PACT Intervention vs. Comparison Group

• 1.42 (-8.74, 5.90)
• 1.44 (-7.02, 4.15)

Late EBQI-PACT Intervention vs. Comparison Group

• 6.82 (-13.29, -0.35)*
• 1.30 (-6.72, 4.11)

Change within Group (Wave 3 – Wave 1) Comparison Group 4.96 (0.66, 9.25)* 0.84 (-2.28, 3.96) Early EBQI-PACT Intervention 3.54 (-2.53, 9.60)

• 0.60 (-5.28, 4.08)

Late EBQI-PACT Intervention

• 1.86 (-6.84, 3.11)
• 0.46 (-4.98, 4.06)

Change from Wave 1 (Comparison Group) Wave 1 (Reference group) Wave 2 1.75 (-2.18, 5.69) 0.03 (-2.77, 2.83) Wave 3 4.96 (0.66, 9.25)* 0.84 (-2.28, 3.96) Difference between Comparison Group and Early EBQI Wave 1

• 1.66 (-8.69, 5.36)

0.41 (-4.80, 5.63) Wave 2 0.52 (-6.07, 7.11)

• 0.12 (-4.58, 4.33)

Wave 3

• 3.08 (-10.28, 4.12)
• 1.02 (-5.88, 3.84)

Difference between Comparison Group and Late EBQI Wave 1 0.59 (-5.38, 6.56) 0.10 (-4.29, 4.48) Wave 2

• 0.64 (-6.88, 5.60)

0.06 (-4.18, 4.30) Wave 3

• 6.23 (-13.04, 0.59)
• 1.21 (-6.39, 3.98)

*p<.05; **p<.01.