Utilizing electronic medical records alert to improve documentation of neonatal acute kidney injury.

Background: Neonatal acute kidney injury (AKI) is a common yet underdiagnosed condition in neonates with significant implications for long-term kidney health. Lack of timely recognition and documentation of AKI contributes to missed opportunities for nephrology consultation and follow-up, potentiall...

Descripción completa

Detalles Bibliográficos
Publicado en:Pediatric Nephrology Vol. 39; no. 8; pp. 2505 - 2515
Autores principales: Nada, Arwa, Bagwell, Amy
Formato: pictorial research tables/charts Journal Article
Publicado: Springer Nature Aug2024
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=178064754&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 178064754
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        0931041X
        EF1
      jtl: Pediatric Nephrology
      issn: 0931041X
      maglogo: N
    pubinfo:
      dt: Aug2024
      vid: 39
      iid: 8
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        178064754
        176172475
        178064754
        178064754
        10.1007/s00467-024-06352-2
        178064754
      ppf: 2505
      ppct: 10
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Utilizing electronic medical records alert to improve documentation of neonatal acute kidney injury.
      aug:
        au:
          Nada, Arwa
          Bagwell, Amy
        affil: https://ror.org/0011qv509 Department of Pediatrics, Division of Pediatric Nephrology, The University of Tennessee Health Science Center (UTHSC), 50 N Dunlap St., 38105, Memphis, TN, USA
      sug:
        subj:
          Electronic Health Records Utilization
          Decision Support Systems, Clinical
          Quality Improvement
          Documentation
          Kidney Failure, Acute Diagnosis
          Nephrology
          Referral and Consultation
          Creatinine Blood
          Human
          Funding Source
          Physicians Psychosocial Factors
          Intensive Care Units, Neonatal
          Hospitals, Pediatric Tennessee
          Tennessee
          Automation
          Physician Engagement
          Workflow
          Infant, Newborn
          Infant, Newborn: birth-1 month
      ab: Background: Neonatal acute kidney injury (AKI) is a common yet underdiagnosed condition in neonates with significant implications for long-term kidney health. Lack of timely recognition and documentation of AKI contributes to missed opportunities for nephrology consultation and follow-up, potentially leading to adverse outcomes. Methods: We conducted a quality improvement (QI) project to address this by incorporating an automated real-time electronic medical record (EMR)-AKI alert system in the Neonatal Intensive Care Unit (NICU) at Le Bonheur Children's Hospital. Our primary objective was to improve documentation of neonatal AKI (defined as serum creatinine (SCr) > 1.5 mg/dL) by 25% compared to baseline levels. The secondary goal was to increase nephrology consultations and referrals to the neonatal nephrology clinic. We designed an EMR-AKI alert system to trigger for neonates with SCr > 1.5 mg/dL, automatically adding AKI diagnosis to the problem list. This prompted physicians to consult nephrology, refer neonates to the nephrology clinic, and consider medication adjustments. Results: Our results demonstrated a significant improvement in AKI documentation after implementing the EMR-AKI alert, reaching 100% compared with 7% at baseline (p < 0.001) for neonates with SCr > 1.5 mg/dL. Although the increase in nephrology consultations was not statistically significant (p = 0.5), there was a significant increase in referrals to neonatal nephrology clinics (p = 0.005). Conclusions: Integration of an EMR alert system with automated documentation offers an efficient and economical solution for improving neonatal AKI diagnosis and documentation. This approach enhances healthcare provider engagement, streamlines workflows, and supports QI. Widespread adoption of similar approaches can lead to improved patient outcomes and documentation accuracy in neonatal AKI care.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N