Population-Wide Screening for Chronic Kidney Disease : A Cost-Effectiveness Analysis.

BACKGROUND: Sodium-glucose cotransporter-2 (SGLT2) inhibitors have the potential to alter the natural history of chronic kidney disease (CKD), and they should be included in cost-effectiveness analyses of screening for CKD. OBJECTIVE: To determine the cost-effectiveness of adding population-wide screening for CKD. DESIGN: Markov cohort model. DATA SOURCES: NHANES (National Health and Nutrition Examination Survey), U.S. Centers for Medicare & Medicaid Services data, cohort studies, and randomized clinical trials, including the DAPA-CKD (Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease) trial. TARGET POPULATION: Adults. TIME HORIZON: Lifetime. PERSPECTIVE: Health care sector. INTERVENTION: Screening for albuminuria with and without adding SGLT2 inhibitors to the current standard of care for CKD. OUTCOME MEASURES: Costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs), all discounted at 3% annually. RESULTS OF BASE-CASE ANALYSIS: One-time CKD screening at age 55 years had an ICER of $86 300 per QALY gained by increasing costs from $249 800 to $259 000 and increasing QALYs from 12.61 to 12.72; this was accompanied by a decrease in the incidence of kidney failure requiring dialysis or kidney transplant of 0.29 percentage points and an increase in life expectancy from 17.29 to 17.45 years. Other options were also cost-effective. During ages 35 to 75 years, screening once prevented dialysis or transplant in 398 000 people and screening every 10 years until age 75 years cost less than $100 000 per QALY gained. RESULTS OF SENSITIVITY ANALYSIS: When SGLT2 inhibitors were 30% less effective, screening every 10 years during ages 35 to 75 years cost between $145 400 and $182 600 per QALY gained, and price reductions would be required for screening to be cost-effective. LIMITATION: The efficacy of SGLT2 inhibitors was derived from a single randomized controlled trial. CONCLUSION: Screening adults for albuminuria to identify CKD could be cost-effective in the United States. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality, Veterans Affairs Office of Academic Affiliations, and National Institute of Diabetes and Digestive and Kidney Diseases.

Cost-Effectiveness of Dapagliflozin for Non-diabetic Chronic Kidney Disease.

BACKGROUND: In the USA, chronic kidney disease (CKD) affects 1 in 7 adults and costs $100 billion annually. The DAPA-CKD trial found dapagliflozin, a sodium glucose co-transporter 2 (SGLT2) inhibitor, to be effective in reducing CKD progression and mortality in patients with diabetic and non-diabetic CKD. Currently, SGLT2 inhibitors are not considered standard of care for patients with non-diabetic CKD. OBJECTIVE: Determine the cost-effectiveness of adding dapagliflozin to standard management of patients with non-diabetic CKD. DESIGN: Markov model with lifetime time horizon and US healthcare sector perspective. PATIENTS: Patients with non-diabetic CKD INTERVENTION: Dapagliflozin plus standard care versus standard care only. MAIN MEASURES: Quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs), all discounted at 3% annually; total incidence of kidney failure on kidney replacement therapy; average years on kidney replacement therapy. KEY RESULTS: Adding dapagliflozin to standard care improved life expectancy by 2 years, increased discounted QALYS (from 6.75 to 8.06), and reduced the total incidence of kidney failure on kidney replacement therapy (KRT) (from 17.4 to 11.0%) and average years on KRT (from 0.77 to 0.43) over the lifetime of the cohort. Dapagliflozin plus standard care was more effective than standard care alone while increasing lifetime costs (from $245,900 to $324,8900, or $60,000 per QALY gained). Results were robust to variations in assumptions about dapagliflozin's efficacy over time and by CKD stage, added costs of kidney replacement therapy, and expected population annual CKD progression rates and sensitive to the cost of dapagliflozin. The net 1-year budgetary implication of treating all US patients with non-diabetic CKD could be up to $21 billion. CONCLUSIONS: Dapagliflozin improved life expectancy and reduced progression of CKD, the proportion of patients requiring kidney replacement therapy, and time on kidney replacement therapy in patients with non-diabetic CKD. Use of dapagliflozin meets conventional criteria for cost-effectiveness.

Automated Extraction of Tumor Staging and Diagnosis Information From Surgical Pathology Reports.

PURPOSE: Typically stored as unstructured notes, surgical pathology reports contain data elements valuable to cancer research that require labor-intensive manual extraction. Although studies have described natural language processing (NLP) of surgical pathology reports to automate information extraction, efforts have focused on specific cancer subtypes rather than across multiple oncologic domains. To address this gap, we developed and evaluated an NLP method to extract tumor staging and diagnosis information across multiple cancer subtypes. METHODS: The NLP pipeline was implemented on an open-source framework called Leo. We used a total of 555,681 surgical pathology reports of 329,076 patients to develop the pipeline and evaluated our approach on subsets of reports from patients with breast, prostate, colorectal, and randomly selected cancer subtypes. RESULTS: Averaged across all four cancer subtypes, the NLP pipeline achieved an accuracy of 1.00 for International Classification of Diseases, Tenth Revision codes, 0.89 for T staging, 0.90 for N staging, and 0.97 for M staging. It achieved an F1 score of 1.00 for International Classification of Diseases, Tenth Revision codes, 0.88 for T staging, 0.90 for N staging, and 0.24 for M staging. CONCLUSION: The NLP pipeline was developed to extract tumor staging and diagnosis information across multiple cancer subtypes to support the research enterprise in our institution. Although it was not possible to demonstrate generalizability of our NLP pipeline to other institutions, other institutions may find value in adopting a similar NLP approach-and reusing code available at GitHub-to support the oncology research enterprise with elements extracted from surgical pathology reports.

A Method to Improve Availability and Quality of Patient Race Data in an Electronic Health Record System.

BACKGROUND: Although federal regulations mandate documentation of structured race data according to Office of Management and Budget (OMB) categories in electronic health record (EHR) systems, many institutions have reported gaps in EHR race data that hinder secondary use for population-level research focused on underserved populations. When evaluating race data available for research purposes, we found our institution's enterprise EHR contained structured race data for only 51% (1.6 million) of patients. OBJECTIVES: We seek to improve the availability and quality of structured race data available to researchers by integrating values from multiple local sources. METHODS: To address the deficiency in race data availability, we implemented a method to supplement OMB race values from four local sources-inpatient EHR, inpatient billing, natural language processing, and coded clinical observations. We evaluated this method by measuring race data availability and data quality with respect to completeness, concordance, and plausibility. RESULTS: The supplementation method improved race data availability in the enterprise EHR up to 10% for some minority groups and 4% overall. We identified structured OMB race values for more than 142,000 patients, nearly a third of whom were from racial minority groups. Our data quality evaluation indicated that the supplemented race values improved completeness in the enterprise EHR, originated from sources in agreement with the enterprise EHR, and were unbiased to the enterprise EHR. CONCLUSION: Implementation of this method can successfully increase OMB race data availability, potentially enhancing accrual of patients from underserved populations to research studies.