A Pragmatic Cluster Randomized Trial of an Electronic Clinical Decision Support System to Improve Chronic Kidney Disease Management in Primary Care: Design, Rationale, and Implementation Experience

Assessing trends and variability in outpatient dual testing for chronic kidney disease with urine albumin and serum creatinine, 2009-2018: a retrospective cohort study in the Veterans Health Administration System

BACKGROUND

Simultaneous urine testing for albumin (UAlb) and serum creatinine (SCr), that is, 'dual testing,' is an accepted quality measure in the management of diabetes. As chronic kidney disease (CKD) is defined by both UAlb and SCr testing, this approach could be more widely adopted in kidney care.

OBJECTIVE

We assessed time trends and facility-level variation in the performance of outpatient dual testing in the integrated Veterans Health Administration (VHA) system.

DESIGN, SUBJECTS AND MAIN MEASURES

This retrospective cohort study included patients with any inpatient or outpatient visit to the VHA system during the period 2009-2018. Dual testing was defined as UAlb and SCr testing in the outpatient setting within a calendar year. We assessed time trends in dual testing by demographics, comorbidities, high-risk (eg, diabetes) specialty care and facilities. A generalised linear mixed-effects model was applied to explore individual and facility-level predictors of receiving dual testing.

KEY RESULTS

We analysed data from approximately 6.9 million veterans per year. Dual testing increased, on average, from 17.4% to 21.2%, but varied substantially among VHA centres (0.3%-43.7% in 2018). Dual testing was strongly associated with diabetes (OR 10.4, 95% CI 10.3 to 10.5, p<0.0001) and not associated with VHA centre complexity level. However, among patients with high-risk conditions including diabetes, <50% received dual testing in any given year. As compared with white veterans, black veterans were less likely to be tested after adjusting for other individual and facility characteristics (OR 0.93, 95% CI 0.92 to 0.93, p<0.0001).

CONCLUSIONS

Dual testing for CKD in high-risk specialties is increasing but remains low. This appears primarily due to low rates of testing for albuminuria. Promoting dual testing in high-risk patients will help to improve disease management and patient outcomes.

Improving the identification and management of diabetic nephropathy in patients with diabetes in primary care

BACKGROUND

Diabetic nephropathy is the leading cause of renal failure in the United States. Screening for albuminuria in individuals with diabetes is critical to identify the early stages of DKD. Prompt identification and management of DKD improves patient outcomes, increases life expectancy, and decreases health care costs.

LOCAL PROBLEM

The DKD screening rate for patients ≥18 years of age with diabetes at the project site was 29%, below the national benchmark of 90%. Patients diagnosed with DKD were not receiving appropriate management. This quality-improvement project used a standardized protocol consisting of a checklist and educational initiatives to improve DKD identification and management.

METHODS

The Knowledge-to-Action Framework was used for this project at a primary care practice in the southeastern United States. Data collection included demographic data, DKD screening with urine albumin-to-creatine ratio, diagnosis rates, DKD treatment with angiotensin-converting enzyme inhibitor (ACEi) or angiotensin II receptor blocker (ARB), and a sodium-glucose cotransporter-2 inhibitor (SGLT2i) reviewed 6 months before and after intervention.

INTERVENTIONS

Evidence-based interventions included a DKD educational in-service for clinical staff, creation of a standardized protocol through a checklist for screening and appropriate management of DKD, and implementation of patient educational handouts.

RESULTS

Diabetic kidney disease screening rates increased by 100%, patients diagnosed with DKD decreased by 8%, patients with DKD on ACEi/ARB increased by 39%, and patients with DKD on SGLT2i increased by 15%.

CONCLUSION

Implementation of a standardized protocol through a checklist and providing patient education on DKD can improve DKD identification/management.

Expectation of clinical decision support systems: a survey study among nephrologist end-users

BACKGROUND

Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce.

PURPOSE

Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting.

METHODS

The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted.

RESULTS

The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse.

CONCLUSION

This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.

Complex Interventions Across Primary and Secondary Care to Optimize Population Kidney Health: A Systematic Review and Realist Synthesis to Understand Contexts, Mechanisms, and Outcomes

BACKGROUND

CKD affects 850 million people worldwide and is associated with high risk of kidney failure and death. Existing, evidence-based treatments are not implemented in at least a third of eligible patients, and there is socioeconomic inequity in access to care. While interventions aiming to improve delivery of evidence-based care exist, these are often complex, with intervention mechanisms acting and interacting in specific contexts to achieve desired outcomes.

METHODS

We undertook realist synthesis to develop a model of these context-mechanism-outcome interactions. We included references from two existing systematic reviews and from database searches. Six reviewers produced a long list of study context-mechanism-outcome configurations based on review of individual studies. During group sessions, these were synthesized to produce an integrated model of intervention mechanisms, how they act and interact to deliver desired outcomes, and in which contexts these mechanisms work.

RESULTS

Searches identified 3371 relevant studies, of which 60 were included, most from North America and Europe. Key intervention components included automated detection of higher-risk cases in primary care with management advice to general practitioners, educational support, and non-patient-facing nephrologist review. Where successful, these components promote clinician learning during the process of managing patients with CKD, promote clinician motivation to take steps toward evidence-based CKD management, and integrate dynamically with existing workflows. These mechanisms have the potential to result in improved population kidney disease outcomes and cardiovascular outcomes in supportive contexts (organizational buy-in, compatibility of interventions, geographical considerations). However, patient perspectives were unavailable and therefore did not contribute to our findings.

CONCLUSIONS

This systematic review and realist synthesis describes how complex interventions work to improve delivery of CKD care, providing a framework within which future interventions can be developed. Included studies provided insight into the functioning of these interventions, but patient perspectives were lacking in available literature.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_05_08_CJN0000000000000136.mp3.

Optimal Early Diagnosis and Monitoring of Diabetic Kidney Disease in Type 2 Diabetes Mellitus: Addressing the Barriers to Albuminuria Testing

Chronic kidney disease (CKD) in patients with type 2 diabetes (T2D) is associated with increased risk of end-stage renal disease (ESRD) and cardiovascular disease (CVD). Urine albumin-to-creatinine ratio (UACR) is a sensitive and early indicator of kidney damage, which should be used routinely to accurately assess CKD stage and monitor kidney health. However, this test currently is performed in only a minority of patients with T2D. Here, we review the importance of albuminuria testing and current barriers that hinder patient access to UACR testing and describe solutions to such testing in a community clinical setting.

Electronic Decision Support for Management of CKD in Primary Care: A Pragmatic Randomized Trial

RATIONALE & OBJECTIVE

Most adults with chronic kidney disease (CKD) in the United States are cared for by primary care providers (PCPs). We evaluated the feasibility and preliminary effectiveness of an electronic clinical decision support system (eCDSS) within the electronic health record with or without pharmacist follow-up to improve the management of CKD in primary care.

STUDY DESIGN

Pragmatic cluster-randomized trial.

SETTING & PARTICIPANTS

524 adults with confirmed creatinine-based estimated glomerular filtration rates of 30 to 59mL/min/1.73m2 cared for by 80 PCPs at the University of California San Francisco. Electronic health record data were used for patient identification, intervention deployment, and outcomes ascertainment.

INTERVENTIONS

Each PCP's eligible patients were randomly assigned as a group into 1 of 3 treatment arms: (1) usual care; (2) eCDSS: testing of creatinine, cystatin C, and urinary albumin-creatinine ratio with individually tailored guidance for PCPs on blood pressure, potassium, and proteinuria management, cardiovascular risk reduction, and patient education; or (3) eCDSS plus pharmacist counseling (eCDSS-PLUS).

OUTCOMES

The primary clinical outcome was change in blood pressure over 12 months. Secondary outcomes were PCP awareness of CKD and use of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker and statin therapy.

RESULTS

All 80 eligible PCPs participated. Mean patient age was 70 years, 47% were nonwhite, and mean estimated glomerular filtration rate was 56±0.6mL/min/1.73m2. Among patients receiving eCDSS with or without pharmacist counseling (n=336), 178 (53%) completed laboratory measurements and 138 (41%) had laboratory measurements followed by a PCP visit with eCDSS deployment. eCDSS was opened by the PCP for 102 (74%) patients, with at least 1 suggested order signed for 83 of these 102 (81%). Changes in systolic blood pressure were-2.1±1.5mm Hg with usual care, -2.8±1.8mm Hg with eCDSS, and -1.1±1.1 with eCDSS-PLUS (P=0.7). PCP awareness of CKD was 16% with usual care, 26% with eCDSS, and 32% for eCDSS-PLUS (P=0.09). In as-treated analyses, PCP awareness of CKD was significantly greater with eCDSS and eCDSS-PLUS (73% and 69%) versus usual care (47%; P=0.002).

LIMITATIONS

Recruitment of smaller than intended sample size and limited uptake of the testing component of the intervention.

CONCLUSIONS

Although we were unable to demonstrate the effectiveness of eCDSS to lower blood pressure and uptake of the eCDSS was limited by low testing rates, eCDSS use was high when laboratory measurements were available and was associated with higher PCP awareness of CKD.

FUNDING

Grants from government (National Institutes of Health) and not-for-profit (American Heart Association) entities.

TRIAL REGISTRATION

Registered at ClinicalTrials.gov with study number NCT02925962.

Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review

Predictive analytics using electronic health record (EHR) data have rapidly advanced over the last decade. While model performance metrics have improved considerably, best practices for implementing predictive models into clinical settings for point-of-care risk stratification are still evolving. Here, we conducted a systematic review of articles describing predictive models integrated into EHR systems and implemented in clinical practice. We conducted an exhaustive database search and extracted data encompassing multiple facets of implementation. We assessed study quality and level of evidence. We obtained an initial 3393 articles for screening, from which a final set of 44 articles was included for data extraction and analysis. The most common clinical domains of implemented predictive models were related to thrombotic disorders/anticoagulation (25%) and sepsis (16%). The majority of studies were conducted in inpatient academic settings. Implementation challenges included alert fatigue, lack of training, and increased work burden on the care team. Of 32 studies that reported effects on clinical outcomes, 22 (69%) demonstrated improvement after model implementation. Overall, EHR-based predictive models offer promising results for improving clinical outcomes, although several gaps in the literature remain, and most study designs were observational. Future studies using randomized controlled trials may help improve the generalizability of findings.

Integrating risk prediction models into chronic kidney disease care

PURPOSE OF REVIEW

Although the concept of risk prediction in chronic kidney disease (CKD) is not new, how to integrate risk prediction models into CKD care remains largely unknown, particularly in the prevention and early management of CKD. The present review presents a timely overview of recent CKD risk prediction models and conceptualizes how these may be integrated into the care of patients with CKD.

RECENT FINDINGS

In recent literature, prediction of time-to-ESKD has been thoroughly validated in multiple international cohorts, new models focused on CKD incidence, morbidity, and mortality have been developed, and ongoing work will determine the impact of integrating risk prediction models into CKD care on patients, nephrologists, and health systems.

SUMMARY

With the availability of new models focused on CKD incidence, the United States Preventive Task Force should reconsider its determination of insufficient evidence for primary screening of CKD, which was due in part to the absence of validated risk models to guide CKD screening. Models predicting CKD morbidity and mortality present a new opportunity to standardize the intensity and frequency of care across nephrology practices.

A Virtual Multidisciplinary Care Program for Management of Advanced Chronic Kidney Disease: Matched Cohort Study

Background

It is not well established whether a virtual multidisciplinary care program for persons with advanced chronic kidney disease (CKD) can improve their knowledge about their disease, increase their interest in home dialysis therapies, and result in more planned outpatient (versus inpatient) dialysis starts.

Objective

We aimed to evaluate the feasibility and preliminary associations of program participation with disease knowledge, home dialysis modality preference, and outpatient dialysis initiation among persons with advanced CKD in a community-based nephrology practice.

Methods

In a matched prospective cohort, we enrolled adults aged 18 to 85 years with at least two estimated glomerular filtration rates (eGFRs) of less than 30 mL/min/1.73 m2 into the Cricket Health program and compared them with controls receiving care at the same clinic, matched on age, gender, eGFR, and presence of heart failure and diabetes. The intervention included online education materials, a virtual multidisciplinary team (nurse, pharmacist, social worker, dietician), and patient mentors. Prespecified follow-up time was nine months with extended follow-up to allow adequate time to determine the dialysis start setting. CKD knowledge and dialysis modality choice were evaluated in a pre-post survey among intervention participants.

Results

Thirty-seven participants were matched to 61 controls by age (mean 67.2, SD 10.4 versus mean 68.8, SD 9.5), prevalence of diabetes (54%, 20/37 versus 57%, 35/61), congestive heart failure (22%, 8/37 versus 25%, 15/61), and baseline eGFR (mean 19, SD 6 versus mean 21, SD 5 mL/min/1.73 m2), respectively. At nine-month follow-up, five patients in each group started dialysis (P=.62). Among program participants, 80% (4/5) started dialysis as an outpatient compared with 20% (1/5) of controls (OR 6.28, 95% CI 0.69-57.22). In extended follow-up (median 15.7, range 11.7 to 18.1 months), 19 of 98 patients started dialysis; 80% (8/10) of the intervention group patients started dialysis in the outpatient setting versus 22% (2/9) of control patients (hazard ratio 6.89, 95% CI 1.46-32.66). Compared to before participation, patients who completed the program had higher disease knowledge levels (mean 52%, SD 29% versus mean 94%, SD 14% of questions correct on knowledge-based survey, P<.001) and were more likely to choose a home modality as their first dialysis choice (36%, 7/22 versus 68%, 15/22, P=.047) after program completion.

Conclusions

The Cricket Health program can improve patient knowledge about CKD and increase interest in home dialysis modalities, and may increase the proportion of dialysis starts in the outpatient setting.