Automated Electronic Alert for the Care and Outcomes of Adults With Acute Kidney Injury: A Randomized Clinical Trial.

Importance: Despite the expansion of published electronic alerts for acute kidney injury (AKI), there are still concerns regarding their effect on the clinical outcomes of patients. Objective: To evaluate the effect of the AKI alert combined with a care bundle on the care and clinical outcomes of patients with hospital-acquired AKI. Design, Setting, and Participants: This single-center, double-blind, parallel-group randomized clinical trial was conducted in a tertiary teaching hospital in Nanjing, China, from August 1, 2019, to December 31, 2021. The inclusion criteria were inpatient adults aged 18 years or older with AKI, which was defined using the Kidney Disease: Improving Global Outcomes creatinine criteria. Participants were randomized 1:1 to either the alert group or the usual care group, which were stratified by medical vs surgical ward and by intensive care unit (ICU) vs non-ICU setting. Analyses were conducted on the modified intention-to-treat population. Interventions: A programmatic AKI alert system generated randomization automatically and sent messages to the mobile telephones of clinicians (alert group) or did not send messages (usual care group). A care bundle accompanied the AKI alert and consisted of general, nonindividualized, and nonmandatory AKI management measures. Main Outcomes and Measures: The primary outcome was maximum change in estimated glomerular filtration rate (eGFR) within 7 days after randomization. Secondary patient-centered outcomes included death, dialysis, AKI progression, and AKI recovery. Care-centered outcomes included diagnostic and therapeutic interventions for AKI. Results: A total of 2208 patients (median [IQR] age, 65 [54-72] years; 1560 males [70.7%]) were randomized to the alert group (n = 1123) or the usual care group (n = 1085) and analyzed. Within 7 days of randomization, median (IQR) maximum absolute changes in eGFR were 3.7 (-6.4 to 19.3) mL/min/1.73 m2 in the alert group and 2.9 (-9.2 to 16.9) mL/min/1.73 m2 in the usual care group (P = .24). This result was robust in all subgroups in an exploratory analysis. For care-centered outcomes, patients in the alert group had more intravenous fluids (927 [82.6%] vs 670 [61.8%]; P < .001), less exposure to nonsteroidal anti-inflammatory drugs (56 [5.0%] vs 119 [11.0%]; P < .001), and more AKI documentation at discharge (560 [49.9%] vs 296 [27.3%]; P < .001) than patients in the usual care group. No differences were observed in patient-centered secondary outcomes between the 2 groups. Conclusions and Relevance: Results of this randomized clinical trial showed that the electronic AKI alert did not improve kidney function or other patient-centered outcomes but changed patient care behaviors. The findings warrant the use of a combination of high-quality interventions and AKI alert in future clinical practice. Trial Registration: ClinicalTrials.gov Identifier: NCT03736304.

The efficiency analysis and spatial implications of health information technology: A regional exploratory study in China.

The new adoption of healthcare information technology is costly, and effects on healthcare performance can be questionable. This nationwide study in China investigated the efficient performance of healthcare information technology and examined its spatial correlation. Panel data were extracted from the Annual Investigation Report on Hospital Information in China and the China Health Statistics Yearbook for 2007 through 2015 (279 observations). Stochastic frontier analysis was employed to estimate the technical efficiency of healthcare information technology performance and related factors at the regional level. Healthcare information technology performance was positively associated with electronic medical records, total input, and cost of inpatient stay, while picture archiving and communication systems and net assets were negatively related. Local Indicators of Spatial Association showed that there existed significant spatial autocorrelation. Governmental policies would best make distinctions among different forms of healthcare information technology, especially between electronic medical records and picture archiving and communication systems. Policies should be formulated to improve healthcare information technology adoption and reduce regional differences.