Impact of a Primary Care CKD Registry in a US Public Safety-Net Health Care Delivery System: A Pragmatic Randomized Trial

Abstract

Background: Many individuals with chronic kidney disease (CKD) do not receive guideline-concordant care. We examined the impact of a team-based primary care CKD registry on clinical measures and processes of care among patients with CKD cared for in a public safety-net health care delivery system.

Study design: Pragmatic trial of a CKD registry versus a usual-care registry for 1 year.

Setting & participants: Primary care providers (PCPs) and their patients with CKD in a safety-net primary care setting in San Francisco.

Intervention: The CKD registry identified at point of care all patients with CKD, those with blood pressure (BP)>140/90mmHg, those without angiotensin-converting enzyme (ACE) inhibitor/angiotensin receptor blocker (ARB) prescription, and those without albuminuria quantification in the past year. It also provided quarterly feedback pertinent to these metrics to promote "outreach" to patients with CKD. The usual-care registry provided point-of-care cancer screening and immunization data.

Outcomes: Changes in systolic BP at 12 months (primary outcome), proportion of patients with BP control, prescription of ACE inhibitors/ARBs, quantification of albuminuria, severity of albuminuria, and estimated glomerular filtration rate.

Results: The patient population (n=746) had a mean age of 56.7±12.1 (standard deviation) years, was 53% women, and was diverse (8% non-Hispanic white, 35.7% black, 24.5% Hispanic, and 24.4% Asian). Randomization to the CKD registry (30 PCPs, 285 patients) versus the usual-care registry (49 PCPs, 461 patients) was associated with 2-fold greater odds of ACE inhibitor/ARB prescription (adjusted OR, 2.25; 95% CI, 1.45-3.49) and albuminuria quantification (adjusted OR, 2.44; 95% CI, 1.38-4.29) during the 1-year study period. Randomization to the CKD registry was not associated with changes in systolic BP, proportion of patients with uncontrolled BP, or degree of albuminuria or estimated glomerular filtration rate.

Limitations: Potential misclassification of CKD; missing baseline medication data; limited to study of a public safety-net health care system.

Conclusions: A team-based safety-net primary care CKD registry did not improve BP parameters, but led to greater albuminuria quantification and more ACE inhibitor/ARB prescriptions after 1 year. Adoption of team-based CKD registries may represent an important step in translating evidence into practice for CKD management.

Keywords: CKD management; CKD registry; Chronic kidney disease (CKD); albuminuria; angiotensin converting enzyme inhibitors (ACEi); angiotensin receptor blockers (ARB); best practices; blood pressure control; disease progression; evidence-based care; guideline implementation; hypertension; pragmatic trial; process of care.

Figure 1. Marginal estimates and 95% confidence intervals of systolic BP over time, by registry arm

(A) all CKD patients (n=575;1230 observations; average 3.7 observations per patient), (B) patients with CKD stage 3 & 4 (n=397; 1534 observations; average 3.9 observations per patient), (C) patients with uncontrolled BP at baseline (n=207; 750 observations; average 3.6 observations per patient). Estimates are adjusted for age, gender, race/ethnicity, clinic, and participation in a health coaching study, as well as primary care team, primary care provider and patient clustering.

Figure 2. Marginal estimates and 95% confidence intervals of proportion of patients with BP < 140/90 mmHg over time by registry arm

(A) all CKD patients (n=575; 1230 observations; average 3.7 observations per patient), (B) patients with CKD stage 3 & 4 (n=403; 1544 observations; average 3.8 observations per patient), (C) patients with uncontrolled BP at baseline (n=207; 630 observations; average 3.0 observations per patient). Estimates are adjusted for age, gender, race/ethnicity, clinic, and participation in a health coaching study, as well as primary care team, primary care provider and patient clustering.

Figure 3. Marginal estimates and 95% confidence intervals of change in albuminuria over time by registry arm

(A) all CKD patients (n=487; 1736 observations; average 3.6 observations per patient), (B) patients with CKD stage 3 & 4 (n=347; 1272 observations; average 3.7 observations per patient), (C) patients with uncontrolled BP at baseline (n=175; 622 observations; average 3.6 observations per patient). Estimates are adjusted for age, gender, race/ethnicity, clinic, and participation in a health coaching study, as well as primary care team, primary care provider and patient clustering.

Figure 4. Adjusted odds and 95% confidence intervals of ACEi/ARB prescription and albuminuria quantification among patients randomized to the CKD registry vs. usual care registry

(A) ACEi/ARB prescription; (B) albuminuria quantification. Results are displayed for three patient groups: all patients with CKD (n=575), patients with CKD stage 3 & 4 (n=403), and patients with uncontrolled BP at baseline (n=207). Models are adjusted for age, gender, race/ethnicity, clinic, participation in a health coaching study, as well as primary care team, primary care provider and patient clustering. *denominator is 715