Chronic kidney disease (CKD) is a common and serious chronic disease that often leads to end-stage renal disease and major cardiovascular events. Although evidence-based CKD care can slow disease progression and avert complications, less than 10% of CKD patients currently receive major elements of CKD care in a timely fashion. The objective of this project is to develop, implement, and evaluate a technology-driven and team-based intervention to improve quality of care and clinical outcomes for patients with stage 3-4 CKD. The proposed intervention uses a sophisticated Web-based clinical decision support (CDS) system that is seamlessly integrated within the electronic health record (EHR) to: (a) identify adults with CKD at primary care encounters; (b) suggest personalized evidence-based treatment options to increase the appropriate use of renoprotective antihypertensive medications, improve blood pressure control, and improve glycemic management in patients with diabetes; and (c) suggest to patients and providers when collaboration and consultation with nephrologists may be advisable. We rigorously test the impact of the intervention by randomly assigning 30 primary care clinics with approximately 120 primary care physicians and 6100 adults with evidence of stage 3-4 CKD to the CDS intervention versus usual care and assess intervention impact on 5 key evidence-based elements of care for patients with CKD: (i.) recognition and diagnosis of CKD in patients who meet diagnostic criteria; (ii.) adequate blood pressure control; (iii.) optimal angiotensin converting enzyme inhibitor or angiotensin receptor blocker use; (iv.) adequate glucose control; and (v.) nephrology consultation when appropriate. The intervention, referred to as CKD-CDS, provides patient-specific and stage-specific CKD treatment options in high- and low-literacy formats to the primary care provider (PCP) and patients at each primary care encounter to facilitate shared decision making. This CKD-CDS will be implemented using previously successful methods that in previous CDS studies have achieved very high use rates with patients (>75% of targeted patient encounters) for diabetes and high cardiovascular risk. Scalability of this NIH- developed, non-commercialized intervention strategy is supported by its current use (without the CKD identification or specific recommendations) in 4 large medical groups that provide care to 2,000,000 patients in rural and urban areas in 4 Midwestern states, with research contracts to extend use to more than 60 safety net clinics in an additional 14 states in 2018. If the addition of CKD-CDS to this tool is effective, the intervention is immediately scalable and could (a) improve quality of care for large numbers of CKD patients, thereby slowing progression of CKD and improving quality of life, (b) maximize the clinical return on massive public and private investments now being made in sophisticated outpatient EHR systems, and (c) provide a health informatics prototype that rapidly and consistently translates evolving evidence-based CKD clinical guidelines into delivery of personalized and coordinated CKD care within primary care settings.
To prevent serious chronic kidney disease (CKD) complications such as end-stage renal disease and cardiovascular events, better strategies are needed to identify, treat, and refer CKD patients seen in primary care clinics. This project expands an existing and successful non-proprietary Web-based clinical decision support system to include key elements of CKD care and rigorously assesses the impact of this intervention on quality of CKD care for patients seen in primary care settings, including better recognition of CKD, better management of blood pressure and glucose, and more timely referral to nephrologists when appropriate. This low-cost and highly scalable intervention has high potential to improve CKD care and translate massive public and private sector investments in health informatics into tangible health benefits for large numbers of patients with CKD.
