title: The positive predictive value of a hyperkalemia diagnosis in automated health care data.
abstract: OBJECTIVE
  Our objectives were to determine performance of coded hyperkalemia diagnosis at identifying (1) clinically evident hyperkalemia and (2) serum potassium>6 mmol/L.
  
  
  METHODS
  This retrospective observational study included 8722 patients with diabetes within an integrated healthcare system who newly initiated an angiotensin converting enzyme inhibitor, angiotensin receptor blocker, or spironolactone. The primary outcome was first hyperkalemia-associated event (hospitalization, emergency department visit or death within 24 hours of coded diagnosis and/or potassium≥6 mmol/L) during the first year of therapy. Medical records were reviewed.
  
  
  RESULTS
  Among a random sample of 99 patients not coded as having hyperkalemia, none had hyperkalemia upon record review. Among all 64 patients identified as having hyperkalemia, all had hospitalization or emergency department visit associated with coded diagnosis or elevated potassium. Of 55 with coded diagnosis, 42 (PPV 76%) had clinically evident hyperkalemia; 32 (PPV 58%) had potassium≥6. Of 9 identified using only potassium≥6, 7 (PPV 78%) had clinically evident hyperkalemia.
  
  
  CONCLUSIONS
  Nearly one-fourth of patients with coded diagnosis do not have clinically evident hyperkalemia and nearly one-half do not have potassium≥6. Because both false positives and negatives occur with coded diagnoses, medical record validation of hyperkalemia-associated outcomes is necessary.
authors.affiliation: Kaiser Permanente Colorado Institute for Health Research, Denver, CO 80237-8066, USA. marsha.a.raebel@kp.org
authors.forename: Marsha A
authors.initials: MA
authors.lastname: Raebel
authors.forename: Michael L
authors.initials: ML
authors.lastname: Smith
authors.forename: Gwyn
authors.initials: G
authors.lastname: Saylor
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Wright
authors.forename: Craig
authors.initials: C
authors.lastname: Cheetham
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Blanchette
authors.forename: Stanley
authors.initials: S
authors.lastname: Xu
mesh_terms: D000368:Aged; D057911:Angiotensin Receptor Antagonists / Q000009:adverse effects; D000806:Angiotensin-Converting Enzyme Inhibitors / Q000009:adverse effects; D001331:Automation; D019033:Delivery of Health Care, Integrated; D003920:Diabetes Mellitus / Q000453:epidemiology; D005188:False Negative Reactions; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D006947:Hyperkalemia / Q000139:chemically induced / Q000175:diagnosis*; D008297:Male; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D008875:Middle Aged; D000451:Mineralocorticoid Receptor Antagonists / Q000009:adverse effects; D011188:Potassium / Q000097:blood*; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D013148:Spironolactone / Q000009:adverse effects
chemical_list: D057911:Angiotensin Receptor Antagonists; D000806:Angiotensin-Converting Enzyme Inhibitors; D000451:Mineralocorticoid Receptor Antagonists; D013148:Spironolactone; D011188:Potassium