Development of an electronic health record-based chronic kidney disease registry to promote population health management

An Electronic Health Record-Integrated Application for Standardizing Care and Monitoring Patients With Autosomal Dominant Polycystic Kidney Disease Enrolled in a Tolvaptan Clinic: Design and Implementation Study

Background

Tolvaptan is the only US Food and Drug Administration-approved drug to slow the progression of autosomal dominant polycystic kidney disease (ADPKD), but it requires strict clinical monitoring due to potential serious adverse events.

Objective

We aimed to share our experience in developing and implementing an electronic health record (EHR)-based application to monitor patients with ADPKD who were initiated on tolvaptan.

Methods

The application was developed in collaboration with clinical informatics professionals based on our clinical protocol with frequent laboratory test monitoring to detect early drug-related toxicity. The application streamlined the clinical workflow and enabled our nursing team to take appropriate actions in real time to prevent drug-related serious adverse events. We retrospectively analyzed the characteristics of the enrolled patients.

Results

As of September 2022, a total of 214 patients were enrolled in the tolvaptan program across all Mayo Clinic sites. Of these, 126 were enrolled in the Tolvaptan Monitoring Registry application and 88 in the Past Tolvaptan Patients application. The mean age at enrollment was 43.1 (SD 9.9) years. A total of 20 (9.3%) patients developed liver toxicity, but only 5 (2.3%) had to discontinue the drug. The 2 EHR-based applications allowed consolidation of all necessary patient information and real-time data management at the individual or population level. This approach facilitated efficient staff workflow, monitoring of drug-related adverse events, and timely prescription renewal.

Conclusions

Our study highlights the feasibility of integrating digital applications into the EHR workflow to facilitate efficient and safe care delivery for patients enrolled in a tolvaptan program. This workflow needs further validation but could be extended to other health care systems managing chronic diseases requiring drug monitoring.

Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review

BACKGROUND

Approximately 37 million individuals in the United States (US) have chronic kidney disease (CKD). Patients with CKD have a substantial morbidity and mortality, which contributes to a huge economic burden to the healthcare system. A limited number of clinical pathways or defined workflows exist for CKD care delivery in the US, primarily due to a lower prioritization of CKD care within health systems compared with other areas (e.g., cardiovascular disease [CVD], cancer screening). CKD is a public health crisis and by the year 2040, CKD will become the fifth leading cause of years of life lost. It is therefore critical to address these challenges to improve outcomes in patients with CKD.

METHODS

The CKD Leaders Network conducted a virtual, 3 h, multidisciplinary roundtable discussion with eight subject-matter experts to better understand key factors impacting CKD care delivery and barriers across the US. A premeeting survey identified topics for discussion covering the screening, diagnosis, risk stratification, and management of CKD across the care continuum. Findings from this roundtable are summarized and presented herein.

RESULTS

Universal challenges exist across health systems, including a lack of awareness amongst providers and patients, constrained care team bandwidth, inadequate financial incentives for early CKD identification, non-standardized diagnostic classification and triage processes, and non-centralized patient information. Proposed solutions include highlighting immediate and long-term financial implications linked with failure to identify and address at-risk individuals, identifying and managing early-stage CKD, enhancing efforts to support guideline-based education for providers and patients, and capitalizing on next-generation solutions.

CONCLUSIONS

Payers and other industry stakeholders have opportunities to contribute to optimal CKD care delivery. Beyond addressing the inadequacies that currently exist, actionable tactics can be implemented into clinical practice to improve clinical outcomes in patients at risk for or diagnosed with CKD in the US.

Implementation of chronic kidney disease guidelines for sodium-glucose co-transporter-2 inhibitor use in primary care in the UK: a cross-sectional study

Background

The cardiovascular and kidney benefits of sodium-glucose co-transporter-2 (SGLT2) inhibitors in people with chronic kidney disease (CKD) are well established. The implementation of updated SGLT2 inhibitor guidelines and prescribing in the real-world CKD population remains largely unknown.

Methods

A cross-sectional study of adults with CKD registered with UK primary care practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre network on the 31st December 2022 was undertaken. Pseudonymised data from electronic health records held securely within the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) were extracted. An update to a previously described ontological approach was used to identify the study population, using a combination of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) indicating a diagnosis of CKD and laboratory confirmed CKD based on Kidney Disease: Improving Global Outcomes (KDIGO) diagnostic criteria. We examined the extent to which SGLT2 inhibitor guidelines apply to and are then implemented in adults with CKD. A logistic regression model was used to identify factors associated with SGLT2 inhibitor prescribing, reported as odds ratios (ORs) with 95% confidence intervals (CI). The four guidelines under investigation were the United Kingdom Kidney Association (UKKA) Clinical Practice Guideline SGLT2 Inhibition in Adults with Kidney Disease (October 2021), American Diabetes Association (ADA) and KDIGO Consensus Report on Diabetes Management in CKD (October 2022), National Institute for Health and Care Excellence (NICE) Guideline Type 2 Diabetes in Adults: Management (June 2022), and NICE Technology Appraisal Dapagliflozin for Treating CKD (March 2022).

Findings

Of 6,670,829 adults, we identified 516,491 (7.7%) with CKD, including 32.8% (n = 169,443) who had co-existing type 2 diabetes (T2D). 26.8% (n = 138,183) of the overall CKD population had a guideline directed indication for SGLT2 inhibitor treatment. A higher proportion of people with CKD and co-existing T2D were indicated for treatment, compared to those without T2D (62.8% [n = 106,468] vs. 9.1% [n = 31,715]). SGLT2 inhibitors were prescribed to 17.0% (n = 23,466) of those with an indication for treatment, and prescriptions were predominantly in those with co-existing T2D; 22.0% (n = 23,464) in those with T2D, and <0.1% (n = 2) in those without T2D. In adjusted multivariable analysis of people with CKD and T2D, females (OR 0.69, 95% CI 0.67-0.72, p <0.0001), individuals of Black ethnicity (OR 0.84, 95% CI 0.77-0.91, p <0.0001) and those of lower socio-economic status (OR 0.72, 95% CI 0.68-0.76, p <0.0001) were less likely to be prescribed an SGLT2 inhibitor. Those with an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 had a lower likelihood of receiving an SGLT2 inhibitor, compared to those with an eGFR ≥60 mL/min/1.73 m2 (eGFR 45-60 mL/min/1.73 m2 OR 0.65, 95% CI 0.62-0.68, p <0.0001, eGFR 30-45 mL/min/1.73 m2 OR 0.73, 95% CI 0.69-0.78, p <0.0001, eGFR 15-30 mL/min/1.73 m2 OR 0.52, 95% CI 0.46-0.60, p <0.0001, eGFR <15 mL/min/1.73 m2 OR 0.03, 95% CI 0.00-0.23, p = 0.0037, respectively). Those with albuminuria (urine albumin-to-creatinine ratio 3-30 mg/mmol) were less likely to be prescribed an SGLT2 inhibitor, compared to those without albuminuria (OR 0.78, 95% CI 0.75-0.82, p <0.0001).

Interpretation

SGLT2 inhibitor guidelines in CKD have not yet been successfully implemented into clinical practice, most notably in those without co-existing T2D. Individuals at higher risk of adverse outcomes are paradoxically less likely to receive SGLT2 inhibitor treatment. The timeframe between the publication of guidelines and data extraction may have been too short to observe changes in clinical practice. Enhanced efforts to embed SGLT2 inhibitors equitably into routine care for people with CKD are urgently needed, particularly in those at highest risk of adverse outcomes and in the absence of T2D.

Funding

None.

Factors Associated With Receipt of Diabetes Self-Management Education and Support for Type 2 Diabetes: Potential for a Population Health Management Approach

BACKGROUND

Population health management approaches can help target diabetes resources like Diabetes Self-Management Education and Support (DSMES) to individuals at the highest risk of complications and poor outcomes. Little is known about patient characteristics associated with DSMES receipt since widespread uptake of telemedicine for diabetes care in 2020.

METHODS

In this retrospective cohort study, we used electronic medical record (EMR) data to assess patterns of DSMES delivery from May 2020 to May 2022 among adults who used telemedicine for type 2 diabetes (T2D) endocrinology care in a large integrated health system. Multilevel regression models were used to evaluate the association of key patient characteristics with DSMES receipt.

RESULTS

Of 3530 patients in the overall cohort, 401 patients (11%) received DSMES. In adjusted multivariable logistic regression, higher baseline HbA1c (odds ratios [OR] 3.10 [95% confidence interval 2.22-4.33] for HbA1c ≥9% vs <7%), insulin regimen complexity (OR 3.53 [2.59-4.80] for multiple daily injections vs no insulin), and number of noninsulin medications (OR 1.17 [1.05-1.30] per 1 additional medication) were significantly associated with receipt of DSMES, whereas rurality and area-level deprivation of patient residence were not.

CONCLUSIONS

Diabetes Self-Management Education and Support remains underutilized in this cohort of adults using telemedicine to access endocrinology care for T2D. Factors contributing to clinical complexity increased the odds of receiving DSMES. These results support a potential population health management approach using EMR data, which could target DSMES resources to those at higher risk of poor outcomes. This risk-stratified approach may be even more effective now that more people can access DSMES via telemedicine in addition to in-person care.

Electronic Phenotype for Advanced Chronic Kidney Disease in a Veteran Health Care System Clinical Database: Systems-Based Strategy for Model Development and Evaluation

BACKGROUND

Identifying advanced (stages 4 and 5) chronic kidney disease (CKD) cohorts in clinical databases is complicated and often unreliable. Accurately identifying these patients can allow targeting this population for their specialized clinical and research needs.

OBJECTIVE

This study was conducted as a system-based strategy to identify all prevalent Veterans with advanced CKD for subsequent enrollment in a clinical trial. We aimed to examine the prevalence and accuracy of conventionally used diagnosis codes and estimated glomerular filtration rate (eGFR)-based phenotypes for advanced CKD in an electronic health record (EHR) database. We sought to develop a pragmatic EHR phenotype capable of improving the real-time identification of advanced CKD cohorts in a regional Veterans health care system.

METHODS

Using the Veterans Affairs Informatics and Computing Infrastructure services, we extracted the source cohort of Veterans with advanced CKD based on a combination of the latest eGFR value ≤30 ml·min-1·1.73 m-2 or existing International Classification of Diseases (ICD)-10 diagnosis codes for advanced CKD (N18.4 and N18.5) in the last 12 months. We estimated the prevalence of advanced CKD using various prior published EHR phenotypes (ie, advanced CKD diagnosis codes, using the latest single eGFR <30 ml·min-1·1.73 m-2, utilizing two eGFR values) and our operational EHR phenotypes of a high-, intermediate-, and low-risk advanced CKD cohort. We evaluated the accuracy of these phenotypes by examining the likelihood of a sustained reduction of eGFR <30 ml·min-1·1.73 m-2 over a 6-month follow-up period.

RESULTS

Of the 133,756 active Veteran enrollees at North Florida/South Georgia Veterans Health System (NF/SG VHS), we identified a source cohort of 1759 Veterans with advanced nondialysis CKD. Among these, 1102 (62.9%) Veterans had diagnosis codes for advanced CKD; 1391(79.1%) had the index eGFR <30 ml·min-1·1.73 m-2; and 928 (52.7%), 480 (27.2%), and 315 (17.9%) Veterans had high-, intermediate-, and low-risk advanced CKD, respectively. The prevalence of advanced CKD among Veterans at NF/SG VHS varied between 1% and 1.5% depending on the EHR phenotype. At the 6-month follow-up, the probability of Veterans remaining in the advanced CKD stage was 65.3% in the group defined by the ICD-10 codes and 90% in the groups defined by eGFR values. Based on our phenotype, 94.2% of high-risk, 71% of intermediate-risk, and 16.1% of low-risk groups remained in the advanced CKD category.

CONCLUSIONS

While the prevalence of advanced CKD has limited variation between different EHR phenotypes, the accuracy can be improved by utilizing two eGFR values in a stratified manner. We report the development of a pragmatic EHR-based model to identify advanced CKD within a regional Veterans health care system in real time with a tiered approach that allows targeting the needs of the groups at risk of progression to end-stage kidney disease.

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.

Assessing the Contribution of Scanned Outside Documents to the Completeness of Real-World Data Abstraction

PURPOSE

Electronic health record (EHR) data are widely used in precision medicine, quality improvement, disease surveillance, and population health management. However, a significant amount of EHR data are stored in unstructured formats including scanned documents external to the treatment facility presenting an informatics challenge for secondary use. Studies are needed to characterize the clinical information uniquely available in scanned outside documents (SODs) to understand to what extent the availability of such information affects the use of these real-world data for cancer research.

MATERIALS AND METHODS

Two independent EHR data abstractions capturing 30 variables commonly used in oncology research were conducted for 125 patients treated for advanced non-small-cell lung cancer at a comprehensive cancer center, with and without consideration of SODs. Completeness and concordance were compared between the two abstractions, overall, and by patient groups and variable types.

RESULTS

The overall completeness of the data with SODs was 77.6% as compared with 54.3% for the abstraction without SODs. The differences in completeness were driven by data related to biomarker tests, which were more likely to be uniquely available in SODs. Such data were prone to missingness among patients who were diagnosed externally.

CONCLUSION

There were no major differences in completeness between the two abstractions by demographics, diagnosis, disease progression, performance status, or oral therapy use. However, biomarker data were more likely to be uniquely contained in the SODs. Our findings may help cancer centers prioritize the types of SOD data being abstracted for research or other secondary purposes.

A National Registry for People With All Stages of Kidney Disease: The National Kidney Foundation (NKF) Patient Network

RATIONALE & OBJECTIVE

The National Kidney Foundation (NKF) launched the first national US kidney disease patient registry, the NKF Patient Network, that is open to patients throughout the continuum of chronic kidney disease (CKD). The Network provides individualized education and will facilitate patient-centered research, clinical care, and health policy decisions. Here, we present the overall design and the results of a feasibility study that was conducted July through December 2020.

STUDY DESIGN

Longitudinal observational cohort study of patient-entered data with or without electronic health care record (EHR) linkage in collaboration with health systems.

SETTING & PARTICIPANTS

People with CKD, age≥18 years, are invited through their provider, NKF communications, or national outreach campaign. People self-enroll and share their data through a secure portal that offers individualized education and support. The first health system partner is Geisinger.

EXPOSURE

Any cause and stage of CKD, including dialysis and kidney transplant recipients.

OUTCOME

Feasibility of the EHR data transfer, participants' characteristics, and their perspectives on usability and content.

ANALYTICAL APPROACH

Data were collected and analyzed through the registry portal powered by the Pulse Infoframe healthie 2.0 platform.

RESULTS

During the feasibility study, 80 participants completed their profile, and 42 completed a satisfaction survey. Mean age was 57.5 years, 51% were women, 83% were White, and 89% were non-Hispanic or Latino. Of the participants, 60% were not aware of their level of estimated glomerular filtration rate and 91% of their urinary albumin-creatinine ratio.

LIMITATIONS

Challenges for the Network are lack of awareness of kidney disease for many with CKD, difficulty in recruiting vulnerable populations or those with low digital readiness, and loss to follow-up, all leading to selection bias.

CONCLUSIONS

The Network is positioned to become a national and international platform for real-world data that can inform the development of patient-centered research, care, and treatments.

Defining measures of kidney function in observational studies using routine health care data: methodological and reporting considerations

The availability of electronic health records and access to a large number of routine measurements of serum creatinine and urinary albumin enhance the possibilities for epidemiologic research in kidney disease. However, the frequency of health care use and laboratory testing is determined by health status and indication, imposing certain challenges when identifying patients with kidney injury or disease, when using markers of kidney function as covariates, or when evaluating kidney outcomes. Depending on the specific research question, this may influence the interpretation, generalizability, and/or validity of study results. This review illustrates the heterogeneity of working definitions of kidney disease in the scientific literature and discusses advantages and limitations of the most commonly used approaches using 3 examples. We summarize ways to identify and overcome possible biases and conclude by proposing a framework for reporting definitions of exposures and outcomes in studies of kidney disease using routinely collected health care data.

Unlocking Potential within Health Systems Using Privacy-Preserving Record Linkage: Exploring Chronic Kidney Disease Outcomes through Linked Data Modelling

BACKGROUND

 Chronic kidney disease (CKD) is a major global health problem that affects approximately one in 10 adults. Up to 90% of individuals with CKD go undetected until its progression to advanced stages, invariably leading to death in the absence of treatment. The project aims to fill information gaps around the burden of CKD in the Western Australian (WA) population, including incidence, prevalence, rate of progression, and economic cost to the health system.

METHODS

 Given the sensitivity of the information involved, the project employed a privacy preserving record linkage methodology to link data from four major pathology providers in WA to hospital records, to establish a CKD registry with continuous medical record for individuals with biochemical specification for CKD. This method uses encrypted personal identifying information in a probability-based linkage framework (Bloom filters) to help mitigate risk while maximizing linkage quality.

RESULTS

 The project developed interoperable technology to create a transparent CKD data catalogue which is linkable to other datasets. This technology has been designed to support the aspirations of the research program to provide linked de-identified pathology, morbidity, and mortality data that can be used to derive insights to enable better CKD patient outcomes. The cohort includes over 1 million individuals with creatinine results over the period 2002 to 2021.

CONCLUSION

 Using linked data from across the care continuum, researchers are able to evaluate the effectiveness of service delivery and provide evidence for policy and program development. The CKD registry will enable an innovative review of the epidemiology of CKD in WA. Linking pathology records can identify cases of CKD that are missed in the early stages due to disaggregation of results, enabling identification of at-risk populations that represent targets for early intervention and management.

Development and implementation of an automated electronic health record-linked registry for emergency general surgery

INTRODUCTION

Despite adoption of the emergency general surgery (EGS) service by hospitals nationally, quality improvement (QI) and research for this patient population are challenging because of the lack of population-specific registries. Past efforts have been limited by difficulties in identifying EGS patients within institutions and labor-intensive approaches to data capture. Thus, we created an automated electronic health record (EHR)-linked registry for EGS.

METHODS

We built a registry within the Epic EHR at University of California San Diego for the EGS service. Existing EHR labels that identified patients seen by the EGS team were used to create our automated inclusion rules. Registry validation was performed using a retrospective cohort of EGS patients in a 30-month period and a 1-month prospective cohort. We created quality metrics that are updated and reported back to clinical teams in real time and obtained aggregate data to identify QI and research opportunities. A key metric tracked is clinic schedule rate, as we care that discontinuity postdischarge for the EGS population remains a challenge.

RESULTS

Our registry captured 1,992 patient encounters with 1,717 unique patients in the 30-month period. It had a false-positive EGS detection rate of 1.8%. In our 1-month prospective cohort, it had a false-positive EGS detection rate of 0% and sensitivity of 85%. For quality metrics analysis, we found that EGS patients who were seen as consults had significantly lower clinic schedule rates on discharge compared with those who were admitted to the EGS service (85% vs. 60.7%, p < 0.001).

CONCLUSION

An EHR-linked EGS registry can reliably conduct capture data automatically and support QI and research.

LEVEL OF EVIDENCE

Prognostic and epidemiological, level III.

Prediction models used in the progression of chronic kidney disease: A scoping review

Objective

To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD).

Design

Scoping review.

Data sources

Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022.

Study selection

All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression.

Data extraction

Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications.

Results

From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models.

Conclusions

Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.

Improving Care for Patients with Chronic Hepatitis B via Establishment of a Disease Registry

In the United States, there is poor clinician adherence to the American Association for the Study of Liver Disease and other guidelines for chronic hepatitis B virus (CHB) management. This prospective cohort study evaluated whether a CHB registry improves CHB management. We included patients with CHB aged ≥ 18 years and who had a clinical encounter during September 1, 2016–August 31, 2019. We divided patients into three groups based on care received before September 1, 2019: 1) CIH: primary care clinician at HealthPartners Center for International Health, 2) GI: not CIH and seen by gastroenterology within previous 18 months, and 3) primary care (PC): not CIH and not seen by gastroenterology within previous 18 months. We created and implemented a CHB registry at CIH that allowed staff to identify and perform outreach to patients overdue for CHB management. Patients with laboratory testing (i.e., alanine transaminase and hepatitis B virus DNA) and hepatocellular carcinoma screening in the previous 12 months were considered up to date (UTD). We compared UTD rates between groups at baseline (September 1, 2019) and pilot CHB registry end (February 28, 2020). We evaluated 4,872 patients, 52% of whom were female: 213 CIH, 656 GI, and 4,003 PC. At baseline, GI patients were most UTD (69%) followed by CIH (51%) and PC (11%). At pilot end the percent of UTD patients at CIH increased by 11%, GI decreased by 10%, and PC was unchanged. CHB registry use standardized care and increased the percent of CHB patients with recent laboratory testing and HCC screening.

Prescribing Patterns of Sodium-Glucose Cotransporter-2 Inhibitors in Patients with CKD: A Cross-Sectional Registry Analysis

Background

Sodium-glucose cotransporter-2 inhibitors (SGLT-2i) reduce kidney disease progression and mortality in patients with chronic kidney disease (CKD), regardless of diabetes status. However, the prescribing patterns of these novel therapeutics in the CKD population in real-world settings remain largely unknown.

Methods

This cross-sectional study included adults with stages 3-5 CKD included in the Mass General Brigham (MGB) CKD registry in March 2021. We described the adoption of SGLT-2i therapy and evaluated factors associated with SGLT-2i prescription using multivariable logistic regression models in the CKD population, with and without diabetes.

Results

A total of 72,240 patients with CKD met the inclusion criteria, 31,688 (44%) of whom were men and 61,265 (85%) White. A total of 22,653 (31%) patients were in the diabetic cohort, and 49,587 (69%) were in the nondiabetic cohort. SGLT-2i prescription was 6% in the diabetic cohort and 0.3% in the nondiabetic cohort. In multivariable analyses, younger Black men with a history of heart failure, use of cardiovascular medications, and at least one cardiologist visit in the previous year were associated with higher odds of SGLT-2i prescription in both diabetic and nondiabetic cohorts. Among patients with diabetes, advanced CKD stages were associated with lower odds of SGLT-2i prescription, whereas urine dipstick test and at least one subspecialist visit in the previous year were associated with higher odds of SGLT-2i prescription. In the nondiabetic cohort, CKD stage, urine dipstick test, and at least one nephrologist visit in the previous year were not significantly associated with SGLT-2i prescription.

Conclusions

In this registry study, prescription of SGLT-2i was low in the CKD population, particularly among patients without diabetes.

Value-Based Care and Kidney Disease: Emergence and Future Opportunities

The United States health care system has increasingly embraced value-based programs that reward improved outcomes and lower costs. Health care value, defined as quality per unit cost, was a major goal of the 2010 Patient Protection and Affordable Care Act amid high and rising US health care expenditures. Many early value-based programs were specifically designed for patients with end-stage renal disease (ESRD) and targeted toward dialysis facilities, including the ESRD Prospective Payment System, ESRD Quality Incentive Program, and ESRD Seamless Care Organizations. While a great deal of attention has been paid to these ESRD-focused programs, other value-based programs targeted toward hospitals and health systems may also affect the quality and costs of care for a broader population of patients with kidney disease. Value-based care for kidney disease is increasingly relevant in light of the Advancing American Kidney Health initiative, which introduces new value-based payment models: the mandatory ESRD Treatment Choices Model in 2021 and voluntary Kidney Care Choices Model in 2022. In this review article, we summarize the emergence and impact of value-based programs on the quality and costs of kidney care, with a focus on federal programs. Key opportunities in value-based kidney care include shifting the focus toward chronic kidney disease, enhancing population health management capabilities, improving quality measurement, and leveraging programs to advance health equity.

The Kidney Failure Risk Equation Score and CKD Care Delivery Measures: A Cross-sectional Study

RATIONALE & OBJECTIVE

The 4-variable kidney failure risk equation (KFRE) allows for the prediction of chronic kidney disease (CKD) progression using age, sex, estimated glomerular filtration rate, and urine albumin/creatinine ratio. Electronic health records enable KFRE auto-calculation, and registries allow population-level application. We assessed whether 2-year KFRE score categories are associated with CKD care metrics.

STUDY DESIGN

Cross-sectional cohort.

SETTING & PARTICIPANTS

This study included individuals with CKD in March 2020 who were receiving care within the Partners HealthCare system in Massachusetts.

OUTCOMES

The presence of sufficient data to calculate the KFRE and, among those with a KFRE score, performance on CKD clinical care metrics, including (1) prescription of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker; (2) blood pressure at goal (<140/90 mm Hg) based on clinic measurements; (3) composite metric of hepatitis B virus immunity; (4) composite metric of referral, evaluation, or waitlist status for kidney transplantation; (5) advance directive documentation; (6) yearly influenza vaccination; and (7) pneumonia vaccination.

ANALYTICAL APPROACH

Multivariable logistic regression analysis was used to analyze the association of KFRE score category with CKD care metrics.

RESULTS

Of 61,546 patients, 18,272 (30%) had auto-calculated 2-year KFRE scores; the remaining patients lacked KFRE scores because of absent albuminuria assessment. Individuals with a KFRE score were more likely to have a primary care provider or nephrologist. Among patients with 2-year KFRE scores, high-risk patients had increased odds of completing advance directives (OR, 1.52; 95% CI, 1.07-2.17), while low-risk patients had decreased odds of influenza vaccination (OR, 0.85; 95% CI, 0.75-0.97). Patients with moderate- and high-risk KFRE scores had lower odds of having blood pressure at goal (OR, 0.77; 95% CI, 0.61-0.96 and OR, 0.63; 95% CI, 0.44-0.88, respectively).

LIMITATIONS

Albuminuria data may have been assessed outside of the Partners system.

CONCLUSIONS

A higher-risk KFRE score is associated with the delivery of some but not all CKD care measures. An opportunity exists to improve albuminuria measurement.

Factors associated with the absence of pharmacological treatment for common modifiable complications in children with chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is associated with many comorbidities requiring complex management. We described treatment patterns for common modifiable CKD complications (high blood pressure, anemia, hyperphosphatemia, and acidosis) according to severity of CKD and examined factors associated with the absence of drug therapy, among participants with a persistent comorbidity, for 1 year in children enrolled in the CKiD study.

METHODS

A total of 703 CKiD participants contributed 2849 person-visits over a median 3.5 years of follow-up. Using pairs of annual visits, we examined whether participants with abnormal biomarker levels at the first (index) visit persisted in the abnormal levels 1 year later according to CKD risk stage. Multivariate analyses identified demographic and clinical factors associated with the absence of drug therapy among those with persistent comorbid conditions for 1 year.

RESULTS

The overall proportions of person-visits prescribing therapy at 1-year follow-up for treating anemia, acidosis, hyperphosphatemia, and high blood pressure were 54%, 45%, 29%, and 81%, respectively. The frequency of therapy increased with advanced CKD risk stage for all comorbidities; however, 19-23% of participants with acidosis, 24-27% with anemia, and 30-39% with hyperphosphatemia at high-risk stages (E and F) were not prescribed appropriate therapy despite the persistence of abnormal levels of these biomarkers for at least 1 year. The resolution of comorbidities at advanced CKD stages without treatment was unlikely.

CONCLUSIONS

Many children with CKD in the CKiD cohort did not receive pharmacological treatment for common and persistent modifiable comorbidities, even in severe CKD risk stages.

Big Data in Nephrology

A huge array of data in nephrology is collected through patient registries, large epidemiological studies, electronic health records, administrative claims, clinical trial repositories, mobile health devices and molecular databases. Application of these big data, particularly using machine-learning algorithms, provides a unique opportunity to obtain novel insights into kidney diseases, facilitate personalized medicine and improve patient care. Efforts to make large volumes of data freely accessible to the scientific community, increased awareness of the importance of data sharing and the availability of advanced computing algorithms will facilitate the use of big data in nephrology. However, challenges exist in accessing, harmonizing and integrating datasets in different formats from disparate sources, improving data quality and ensuring that data are secure and the rights and privacy of patients and research participants are protected. In addition, the optimism for data-driven breakthroughs in medicine is tempered by scepticism about the accuracy of calibration and prediction from in silico techniques. Machine-learning algorithms designed to study kidney health and diseases must be able to handle the nuances of this specialty, must adapt as medical practice continually evolves, and must have global and prospective applicability for external and future datasets.

Examining the Potential Impact of Race Multiplier Utilization in Estimated Glomerular Filtration Rate Calculation on African-American Care Outcomes

BACKGROUND

Advancing health equity entails reducing disparities in care. African-American patients with chronic kidney disease (CKD) have poorer outcomes, including dialysis access placement and transplantation. Estimated glomerular filtration rate (eGFR) equations, which assign higher eGFR values to African-American patients, may be a mechanism for inequitable outcomes. Electronic health record-based registries enable population-based examination of care across racial groups.

OBJECTIVE

To examine the impact of the race multiplier for African-Americans in the CKD-EPI eGFR equation on CKD classification and care delivery.

DESIGN

Cross-sectional study SETTING: Two large academic medical centers and affiliated community primary care and specialty practices.

PARTICIPANTS

A total of 56,845 patients in the Partners HealthCare System CKD registry in June 2019, among whom 2225 (3.9%) were African-American.

MEASUREMENTS

Exposures included race, age, sex, comorbidities, and eGFR. Outcomes were transplant referral and dialysis access placement.

RESULTS

Of 2225 African-American patients, 743 (33.4%) would hypothetically be reclassified to a more severe CKD stage if the race multiplier were removed from the CKD-EPI equation. Similarly, 167 of 687 (24.3%) would be reclassified from stage 3B to stage 4. Finally, 64 of 2069 patients (3.1%) would be reassigned from eGFR > 20 ml/min/1.73 m2 to eGFR ≤ 20 ml/min/1.73 m2, meeting the criterion for accumulating kidney transplant priority. Zero of 64 African-American patients with an eGFR ≤ 20 ml/min/1.73 m2 after the race multiplier was removed were referred, evaluated, or waitlisted for kidney transplant, compared to 19.2% of African-American patients with eGFR ≤ 20 ml/min/1.73 m2 with the default CKD-EPI equation.

LIMITATIONS

Single healthcare system in the Northeastern United States and relatively small African-American patient cohort may limit generalizability.

CONCLUSIONS

Our study reveals a meaningful impact of race-adjusted eGFR on the care provided to the African-American CKD patient population.

Improving hepatitis B vaccination rates for advanced chronic kidney disease patients: a quality improvement initiative

Introduction

Chronic kidney disease (CKD) patients are vulnerable to hepatitis B, and immunization prior to end stage kidney disease is recommended to optimize seroconversion. Our institution undertook a process improvement approach to increase hepatitis B vaccination in stage 4 and 5 CKD patients.

Methods

Four strategies were utilized such as: (1) Electronic health record (EHR)-based CKD registry to identify patients, (2) EHR-based physician/nurse reminders, (3) a co-located nurse appointment for vaccine administration, and (4) information sharing and provider awareness effort. The CKD registry was utilized to identify patients with stage 4 or 5 CKD, with at least two clinic visits in the prior 2 years, who had not received the hepatitis B vaccine or did not have serologic evidence of immunity. Target monthly vaccination rate was set at 75%, based on clinic leadership, nephrologist, and nurse consensus.

Results

A total of 239 patients were included in the study period, from November 2018 to January 2019 (observation period) and from February 2019 to September 2019 (intervention period). Monthly vaccination rate improved from 48% in November 2018 to the target rate of 75% by the end of the intervention (August and September 2019). There was a statistically significant increase from the rate of vaccination at a unique patient level in the first month of the baseline period, compared to the last month of the intervention period (51 vs. 75% p = 0.03).

Conclusions

Utilizing a nurse-led approach to hepatitis B vaccination, coupled with EHR-based tools, along with continuous monitoring of performance, helped to improve hepatitis B vaccination among CKD stage 4 and 5 patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10157-020-02013-4.

Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019

Objective

To describe the design, implementation, and utilization of electronic health record (EHR)-based digital health surveillance strategies used to manage the coronavirus disease 2019 (COVID-19) pandemic and to ensure delivery of high-quality clinical care, such as case identification, remote monitoring, telemedicine services, and recruitment to clinical trials at Mayo Clinic.

Methods

The design and implementation work described in this report was performed at Mayo Clinic, a large multistate integrated health care system with more than 1.5 million annual patient visits that uses the Epic EHR system. Rule-based live registries were designed in the EHR system to classify patients who currently test positive for COVID-19, patients who test positive but have recovered from COVID-19, patients who are thought to have COVID-19 but do not yet meet clinical diagnostic criteria, patients who test negative for COVID-19, and patients who exceed a risk score for serious complications from COVID-19.

Results

By use of registries, custom dashboards and operational reports were developed to provide a daily high-level summary for clinical practice use and up-to-date information to manage individual patients affected by COVID-19, including support of case identification, contact isolation, and other care management tasks.

Conclusion

We developed and implemented a systematic approach to the use of EHR patient registries to manage the COVID-19 pandemic that proved feasible and useful in a large multistate group clinical practice. The key to harnessing the potential of digital surveillance tools to promote patient-centered care during the COVID-19 pandemic was to use the registry data, reports, and dashboards as informatics tools to inform decision-making.

Burden and Cost of Caring for US Veterans With CKD: Initial Findings From the VA Renal Information System (VA-REINS)

Kidney disease is a common, complex, costly, and life-limiting condition. Most kidney disease registries or information systems have been limited to single institutions or regions. A national US Department of Veterans Affairs (VA) Renal Information System (VA-REINS) was recently developed. We describe its creation and present key initial findings related to chronic kidney disease (CKD) without kidney replacement therapy (KRT). Data from the VA's Corporate Data Warehouse were processed and linked with national Medicare data for patients with CKD receiving KRT. Operational definitions for VA user, CKD, acute kidney injury, and kidney failure were developed. Among 7 million VA users in fiscal year 2014, CKD was identified using either a strict or liberal operational definition in 1.1 million (16.4%) and 2.5 million (36.3%) veterans, respectively. Most were identified using an estimated glomerular filtration rate laboratory phenotype, some through proteinuria assessment, and very few through International Classification of Diseases, Ninth Revision coding. The VA spent ∼$18 billion for the care of patients with CKD without KRT, most of which was for CKD stage 3, with higher per-patient costs by CKD stage. VA-REINS can be leveraged for disease surveillance, population health management, and improving the quality and value of care, thereby enhancing VA's capacity as a patient-centered learning health system for US veterans.

J-CKD-DB: a nationwide multicentre electronic health record-based chronic kidney disease database in Japan

The Japan Chronic Kidney Disease (CKD) Database (J-CKD-DB) is a large-scale, nation-wide registry based on electronic health record (EHR) data from participating university hospitals. Using a standardized exchangeable information storage, the J-CKD-DB succeeded to efficiently collect clinical data of CKD patients across hospitals despite their different EHR systems. CKD was defined as dipstick proteinuria ≥1+ and/or estimated glomerular filtration rate <60 mL/min/1.73 m² base on both out- and inpatient laboratory data. As an initial analysis, we analyzed 39,121 CKD outpatients (median age was 71 years, 54.7% were men, median eGFR was 51.3 mL/min/1.73 m²) and observed that the number of patients with a CKD stage G1, G2, G3a, G3b, G4 and G5 were 1,001 (2.6%), 2,612 (6.7%), 23,333 (59.6%), 8,357 (21.4%), 2,710 (6.9%) and 1,108 (2.8%), respectively. According to the KDIGO risk classification, there were 30.1% and 25.5% of male and female patients with CKD at very high-risk, respectively. As the information from every clinical encounter from those participating hospitals will be continuously updated with an anonymized patient ID, the J-CKD-DB will be a dynamic registry of Japanese CKD patients by expanding and linking with other existing databases and a platform for a number of cross-sectional and prospective analyses to answer important clinical questions in CKD care.

Expanding the Population Health Workforce: Strategic Priorities of Hospital Organizations in the United States

The role of hospital contributions to population health is a topic increasingly worthy of attention in the years since the Affordable Care Act. To explore how hospitals themselves consider their role as population health leaders, the authors analyzed data from the 2015 American Hospital Association Annual Population Health Survey, which asks organizations about which strategic priorities should be expanded in order to strengthen their organization's population health workforce. Descriptive statistics for the study sample of 1418 hospitals show that physicians were the most commonly ranked priority, followed by behavioral health professionals. Using multivariate analysis, the professional roles identified were grouped into 5 categories: behavioral health, clinical, data collection, business functions, and social supports and services. Doing so revealed that different types of hospitals were more likely to identify different types of roles as more important. Larger hospitals were more likely than others to identify behavioral health and clinical roles. For-profit hospitals were less likely to prioritize data collection and social determinants than their nonprofit peers. These findings provide important insight for public health professionals regarding the staffing priorities of hospitals within their communities. Many population health programs may not be moving beyond traditional clinical expertise to engage the upstream determinants of health in their communities.

Advancing Pharmacist Collaborative Care within Academic Health Systems

Introduction: The scope of pharmacy practice has evolved over the last few decades to focus on the optimization of medication therapy. Despite this positive impact, the lack of reimbursement remains a significant barrier to the implementation of innovative pharmacist practice models. Summary: We describe the successful development, implementation and outcomes of three types of pharmacist collaborative care models: (1) a pharmacist with physician oversight, (2) pharmacist–interprofessional teams and (3) physician–pharmacist teams. The outcome measurement of these pharmacist care models varied from the design phase to patient volume measurement and to comprehensive quality dashboards. All of these practice models have been successfully funded by affiliated health systems or grants. Conclusions: The expansion of pharmacist services delivered by clinical faculty has several benefits to affiliated health systems: (1) significant improvements in patient care quality, (2) access to experts in specialty areas, and (3) the dissemination of outcomes with national and international recognition, increasing the visibility of the health system.