title: Implementation of an Automated Primary Care Acute Kidney Injury Warning System: A Quantitative and Qualitative Review of 2 Years of Experience.
abstract: BACKGROUND
  Acute kidney injury (AKI) is often detected late, leading to worse clinical outcomes. In 2012, we pioneered an AKI-alerting system for primary care clinicians (PCCs). We retrospectively analysed the alerts and evaluated PCC satisfaction to assess the feasibility of the system.
  
  
  METHODS
  The study used a 2-pronged approach. AKI alerts, generated by an algorithm designed by University College London Hospital biochemistry department between June 2012 and June 2014, were analysed to reveal the demographics and outcomes of each patient generating an alert. Second, a survey was sent to all PCCs assessing awareness and satisfaction with the service. Simple statistical methods were applied (mean, median, SD and interquartile range).
  
  
  RESULTS
  One hundred forty-two alerts were generated, of which 101 were genuine. Generally, the patient demographics, AKI stratification and aetiology were in keeping with the inpatient AKI population. Forty-eight percent of cases were referred to the hospital with a median length of stay of 9.9 days. Three-month mortality was 12%. Among PCCs, there was good awareness of the system with most finding it valuable. The key complaints around the system were to do with lack of knowledge of its existence.
  
  
  CONCLUSIONS
  Our evaluation has demonstrated that the implementation of AKI alerts in the community is technically feasible, does not result in excessive demand on hospital services, appears to influence PCC behaviour and was perceived overwhelmingly as a useful service by these clinicians. This experience should inform further developments including behavioural interventions (such as clinician alerts) to improve community AKI care.
authors.affiliation: Department of Nephrology and Hypertension, Royal Free London NHS Foundation Trust, London, UK.
authors.forename: Omid Sadeghi
authors.initials: OS
authors.lastname: Alavijeh
authors.forename: Jas
authors.initials: J
authors.lastname: Bansal
authors.forename: Katie
authors.initials: K
authors.lastname: Hadfield
authors.forename: Christopher
authors.initials: C
authors.lastname: Laing
authors.forename: Anne
authors.initials: A
authors.lastname: Dawnay
mesh_terms: D058186:Acute Kidney Injury / Q000175:diagnosis* / Q000401:mortality / Q000628:therapy; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001331:Automation; D003153:Community Health Services; D003404:Creatinine / Q000097:blood; D005260:Female; D006801:Humans; D000071117:Laboratory Critical Values; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care; D012189:Retrospective Studies; D011795:Surveys and Questionnaires; D055815:Young Adult
chemical_list: D003404:Creatinine