Development of a chronic kidney disease patient navigator program.

BACKGROUND: Chronic Kidney Disease (CKD) is a public health problem and there is a scarcity of type 2 CKD translational research that incorporates educational tools. Patient navigators have been shown to be effective at reducing disparities and improving outcomes in the oncology field. We describe the creation of a CKD Patient Navigator program designed to help coordinate care, address system-barriers, and educate/motivate patients. METHODS: The conceptual framework for the CKD Patient Navigator Program is rooted in the Chronic Care Model that has a main goal of high-quality chronic disease management. Our established multidisciplinary CKD research team enlisted new members from information technology and data management to help create the program. It encompassed three phases: hiring, training, and implementation. For hiring, we wanted a non-medical or lay person with a college degree that possessed strong interpersonal skills and experience in a service-orientated field. For training, there were three key areas: general patient navigator training, CKD education, and electronic health record (EHR) training. For implementation, we defined barriers of care and created EHR templates for which pertinent study data could be extracted. RESULTS: We have hired two CKD patient navigators who will be responsible for navigating CKD patients enrolled in a clinical trial. They have undergone training in general patient navigation, specific CKD education through directed readings and clinical shadowing, as well as EHR and other patient related privacy and research training. CONCLUSIONS: The need for novel approaches like our CKD patient navigator program designed to impact CKD care is vital and should utilize team-based care and health information technology given the changing landscape of our health systems.

Chronic kidney disease in an electronic health record problem list: quality of care, ESRD, and mortality.

BACKGROUND: Whether chronic kidney disease (CKD) recognition in an electronic health record (EHR) problem list improves processes of care or clinical outcomes of end-stage renal disease (ESRD) and death is unclear. METHODS: We identified patients who had at least 1 year of follow-up (2005-2009) in our EHR-based CKD registry (n = 25,742). CKD recognition was defined by having ICD-9 codes for CKD, diabetic kidney disease, or hypertensive kidney disease in the problem list. We calculated proportions of patients with and without CKD recognition and examined differences by demographics, clinical factors, and development of ESRD or mortality. We evaluated differences in the proportion of patients with CKD-specific laboratory results checked before and after recognition among cases and propensity-matched controls. RESULTS: Only 11% (n = 2,735) had CKD recognition in the problem list and they were younger (68 vs. 71 years), a higher proportion were male (61 vs. 37%) and African-American (21 vs. 10%) compared to those unrecognized. CKD-specific laboratory results for patients with estimated glomerular filtration rate (eGFR) 30-59 including intact parathyroid hormone (23 vs. 6%), vitamin D (22 vs. 18%), phosphorus (29 vs. 7%), and a urine check for proteinuria (55 vs. 36%) were significantly more likely to be done among those with CKD recognition (all p < 0.05). Similar results were found for eGFR <30 except for proteinuria and in our propensity score-matched control analysis. There was no independent association of CKD recognition with ESRD or mortality. CONCLUSIONS: CKD recognition in the EHR problem list was low, but translated into more CKD-specific processes of care; however ESRD or mortality were not affected.

Implications of the CKD-EPI GFR estimation equation in clinical practice.

BACKGROUND AND OBJECTIVES: Chronic kidney disease (CKD) is a significant public health problem whose diagnosis and staging relies upon GFR-estimating equations, including the new CKD-EPI equation. CKD-EPI demonstrated superior performance compared with the existing MDRD equation but has not been applied to a healthcare system. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We identified 53,759 patients with stages 3 to 5 CKD on the basis of either MDRD or CKD-EPI equations using two eGFR values <60 ml/min per 1.73 m² > 90 days apart from an outpatient setting. We compared patient characteristics, presence of related diagnosis codes, and time CKD classification between equations. RESULTS: The number of patients identified with CKD decreased 10% applying CKD-EPI versus MDRD. Changes varied substantially by patient characteristics including a 35% decrease among patients < 60 years and a 10% increase among patients > 90 years. Women, non-African Americans, nondiabetics, and obese patients were less likely to be classified on the basis of CKD-EPI. Time to CKD classification was significantly longer with CKD-EPI among younger patients. 14% of patients identified with CKD on the basis of either estimating equation also had a related ICD-9 diagnosis, ranging from 19% among patients < 60 years to 7% among patients > 90 years. CONCLUSIONS: Consistent with findings in the general population, CKD-EPI resulted in substantial declines in equation-based CKD diagnoses in a large healthcare system. Further research is needed to determine whether widespread use of CKD-EPI with current guidelines could lead to delayed needed care among younger patients or excessive referrals among older patients.