Leveraging Clinical Informatics in the Conduct of Clinical Trials

eResearch in acute kidney injury: a primer for electronic health record research

Acute kidney injury (AKI) has a significant impact on patient morbidity and mortality as well as overall health care costs. eResearch, which integrates information technology and information management to optimize research strategies, provides a perfect platform for necessary ongoing AKI research. With the recent adoption of a widely accepted definition of AKI and near-universal use of electronic health records, eResearch is becoming an important tool in AKI research. Conducting eResearch in AKI should ideally be based on a relatively uniform methodology. This article is the first of its kind to describe a methodology for pursuing eResearch specific to AKI and includes an illustrative database example for critically ill patients. We discuss strategies for using serum creatinine and urine output in large databases to identify and stage AKI and ways to interpolate missing values and validate data. Issues specific to the pediatric population include variation in serum creatinine with growth, varied severity of illness scoring systems and medication dosage based on weight. Many of these same strategies used to optimize AKI eResearch can be applicable to real-time AKI alerts with potential integration of additional clinical variables.

Balanced Crystalloids versus Saline in the Intensive Care Unit. The SALT Randomized Trial

RATIONALE

Saline is the intravenous fluid most commonly administered to critically ill adults, but it may be associated with acute kidney injury and death. Whether use of balanced crystalloids rather than saline affects patient outcomes remains unknown.

OBJECTIVES

To pilot a cluster-randomized, multiple-crossover trial using software tools within the electronic health record to compare saline to balanced crystalloids.

METHODS

This was a cluster-randomized, multiple-crossover trial among 974 adults admitted to a tertiary medical intensive care unit from February 3, 2015 to May 31, 2015. The intravenous crystalloid used in the unit alternated monthly between saline (0.9% sodium chloride) and balanced crystalloids (lactated Ringer's solution or Plasma-Lyte A). Enrollment, fluid delivery, and data collection were performed using software tools within the electronic health record. The primary outcome was the difference between study groups in the proportion of isotonic crystalloid administered that was saline. The secondary outcome was major adverse kidney events within 30 days (MAKE30), a composite of death, dialysis, or persistent renal dysfunction.

MEASUREMENTS AND MAIN RESULTS

Patients assigned to saline (n = 454) and balanced crystalloids (n = 520) were similar at baseline and received similar volumes of crystalloid by 30 days (median [interquartile range]: 1,424 ml [500-3,377] vs. 1,617 ml [500-3,628]; P = 0.40). Saline made up a larger proportion of the isotonic crystalloid given in the saline group than in the balanced crystalloid group (91% vs. 21%; P < 0.001). MAKE30 did not differ between groups (24.7% vs. 24.6%; P = 0.98).

CONCLUSIONS

An electronic health record-embedded, cluster-randomized, multiple-crossover trial comparing saline with balanced crystalloids can produce well-balanced study groups and separation in crystalloid receipt. Clinical trial registered with www.clinicaltrials.gov (NCT 02345486).

Identification of Major Adverse Kidney Events Within the Electronic Health Record

Acute kidney injury is common among critically ill adults and is associated with increased mortality and morbidity. The Major Adverse Kidney Events by 30 days (MAKE30) composite of death, new renal replacement therapy, or persistent renal dysfunction is recommended as a patient-centered outcome for pragmatic trials involving acute kidney injury. Accurate electronic detection of the MAKE30 endpoint using data within the electronic health record (EHR) could facilitate the use of the EHR in large-scale kidney injury research. In an observational study using prospectively collected data from 200 admissions to a single medical intensive care unit, we tested the performance of electronically-extracted data in identifying the MAKE30 composite compared to the reference standard of two-physician manual chart review. The incidence of MAKE30 on manual-review was 16 %, which included 8.5 % for in-hospital mortality, 3.5 % for new renal replacement therapy, and 8.5 % for persistent renal dysfunction. There was strong agreement between the electronic and manual assessment of MAKE30 (98.5 % agreement [95 % CI 96.5-100.0 %]; kappa 0.95 [95 % CI 0.87-1.00]; P < 0.001), with only three patients misclassified by electronic assessment. Performance of the electronic MAKE30 assessment was similar among patients with and without CKD and with and without a measured serum creatinine in the 12 months prior to hospital admission. In summary, accurately identifying the MAKE30 composite outcome using EHR data collected as a part of routine care appears feasible.