Improving Quality Improvement Capacity and Clinical Performance in Small Primary Care Practices

Katie F. Coleman; Chloe Krakauer; Melissa Anderson; LeAnn Michaels; David A. Dorr; Lyle J. Fagnan; Clarissa Hsu; Michael L. Parchman

doi:10.1370/afm.2733

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Figure 1.
Timing of QICAs relative to CQM lookback periods 1 and 2.
CQM = clinical quality measure ( appropriate aspirin prescribing, blood pressure control, cholesterol control, and tobacco screening and cessation counseling [ABCS]) ; Jan = January; QICA = Quality Improvement Capacity Assessment.
Note: Figure shows the timing of QICA completions relative to the period of time included in 2015 (lookback period 1) and 2017 (lookback period 2) CQM summary measures. The vertical lines denote the first and last observed dates of QICA 1 and QICA 2 completion. The CQMs assess outcomes over an entire calendar year; lookback period 1 covered 2015, while lookback period 2 covered 2017.
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Figure 2.
Flowchart of practice inclusion in various analyses.
BP = blood pressure; CQM = Clinical Quality Measure; QICA = Quality Improvement Capacity Assessment.

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Table 1.

Changes in QICA Score and Clinical Quality Measures Between Baseline and Follow-up

Measure	Baseline, Mean (SD)	Follow-Up, Mean (SD)	Change, Mean (95% CI)	P Value^{^a}
QICA score^{^b}
Total score	6.45 (1.39)	7.88 (1.4)	1.44 (1.20-1.68)	<.001
HLC subscore				<.001
1. Embed clinical evidence	6.95 (2.29)	8.32 (1.74)	1.37 (1.01-1.73)	<.001
2. Utilize data to improve Performance	4.98 (2.43)	6.97 (2.40)	1.98 (1.58-2.39)	<.001
3. Establish regular QI processes	5.14 (2.20)	7.39 (2.16)	2.25 (1.85-2.65)	<.001
4. Identify at-risk patients	5.46 (1.86)	7.06 (1.85)	1.60 (1.27-1.93)	<.001
5. Define roles and responsibilities	6.96 (1.80)	8.15 (1.80)	1.20 (0.90-1-.51)	<.001
6. Improve patient self-management	7.44 (1.82)	8.51 (1.78)	1.08 (0.78-1.39)	<.001
7. Link patients to outside resources	8.20 (1.64)	8.99 (1.40)	0.79 (0.52-1.07)	<.001
Clinical Quality Measure^{^c}
Aspirin use, %	66.81 (16.61)	70.79 (13.20)	3.98 (1.17-6.79)	.006
Blood pressure control, %	61.48 (12.00)	64.84 (11.48)	3.36 (1.44-5.27)	.001
Smoking screening/cessation counseling, %	73.78 (22.88)	81.27 (21.26)	7.49 (4.21-10.77)	<.001

HLC = high-leverage change; QI = quality improvement; QICA = Quality Improvement Capacity Assessment.
↵^aFrom a t test that tested for differences of the mean change from zero.
↵^bLimited to clinics that completed both QICA surveys (N = 165). Possible range of total score and of each HLC subscore is 1 to 12 points; higher scores denote greater QI capacity.
↵^cPercent of the eligible patient population achieving the measure. Limited to clinics that completed both QICA surveys and reported clinical quality measures in both 2015 and 2017 (N = 130 for aspirin use, N = 161 for blood pressure control, and N = 130 for smoking screening/cessation counseling).

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Table 2.

Mean Change in Clinical Quality Measure With Each 1-Point Increase in QICA Score

Clinical Quality Measure	Unadjusted Mean Change (95% CI)	Adjusted^{^a} Mean Change (95% CI) [P Value^{^b]}
Aspirin use (N = 130)	‒0.58 (‒3.44 to 2.28)	‒0.20 (‒2.61 to 2.21) [.87]
Blood pressure control (N = 161)	1.74 (0.74 to 2.74)	1.25 (0.41 to 2.09) [.003]
Smoking screening/cessation counseling (N = 130)	0.16 (‒1.88 to 2.20)	0.52 (‒1.20 to 2.24) [.55]

QICA = Quality Improvement Capacity Assessment.
↵^aAdjusted for baseline Clinical Quality Measure.
↵^bFrom Wald test for difference of coefficient from 0; see Methods for assumptions made to estimate the standard error.

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Table 3.

Likelihood of 2017 Clinical Quality Measure Being Greater Than 70% With Each 1-Point Increase in QICA Score

Clinical Quality Measure	Unadjusted RR (95% CI)	Adjusted^{^a} RR (95% CI) [P Value^{^b}]
Aspirin use (N = 130)	1.05 (0.87-1.26)	1.03 (0.87-1.24) [.72]
Blood pressure control (N = 161)	1.21 (1.04-1.41)	1.24 (1.09-1.40) [<.001]
Smoking screening/cessation counseling (N = 130	1.00 (0.95-1.05)	1.01 (0.96-1.06) [.78]

QICA = Quality Improvement Capacity Assessment; RR = relative risk.
↵^aAdjusted for Clinical Quality Measure value at baseline.
↵^bWald test for difference of RR from 1; see Methods for assumptions made to estimate the standard error.

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Supplemental appendix; supplemental table
In Brief

Improving Quality Improvement Capacity and Clinical Performance in Small Primary Care Practices

Katie F. Coleman

Background A team of family medicine researchers conducted an assessment to determine if the implementation of policies and workflows designed to improve quality of care in smaller primary care practices was associated with improved health outcomes for patients with cardiovascular disease. The study also examined whether enhancements in quality improvement capacity are associated with a change in clinic performance.

During the15-month intervention, study participants received training on how to extract clinical quality measures from patient data and implement QI innovations using plan-do-study-act cycles of improvement. Performance on three cardiovascular quality measures —appropriate aspirin use, blood pressure (BP) control, and tobacco screening/cessation counseling—were reported by clinics at baseline and follow-up.

What This Study Found Within 15 months of the intervention, practices were able to make improvements in all areas, with most improvements occurring in the domains related to QI where facilitators focused their efforts. Additionally, the researchers observed that for each one-point increase in the QICA score, practices were 24% more likely to reach the Million Hearts campaign goal of 70% of patients with well-controlled blood pressure.

Implications

With these findings, the authors suggest that relatively light QI support provided by an external facilitator can support important QI changes within small primary care practices.