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DOI 10.1002/pds.2030

Медицинская библиотека · Pharmacoepidemiology and drug safety · 2010

The positive predictive value of a hyperkalemia diagnosis in automated health care data.

Raebel Marsha A, Smith Michael L, Saylor Gwyn, Wright Leslie A, Cheetham Craig, Blanchette Christopher M, Xu Stanley

СтатьяПоддержка NIH: внешняя программаВалидационное исследованиеПеревод в очереди

Аннотация

PURPOSE: 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.

Для цитирования: Raebel Marsha A, Smith Michael L, Saylor Gwyn, Wright Leslie A, Cheetham Craig, Blanchette Christopher M, Xu Stanley. The positive predictive value of a hyperkalemia diagnosis in automated health care data.. Pharmacoepidemiology and drug safety. 2010. DOI: 10.1002/pds.2030.

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