Diagnostic accuracy of undernutrition codes in hospital administrative discharge database: improvements needed.

OBJECTIVES: Hospital administrative databases are widely used for disease monitoring. Undernutrition is highly prevalent among hospitalized patients but the diagnostic accuracy of undernutrition coding in administrative data is poorly known. This study examined the diagnostic accuracy of undernutrition coding in administrative hospital discharge databases.

METHODS: A retrospective cross-sectional study was conducted using 2013 and 2014 administrative data of the Internal Medicine Unit of the Lausanne University Hospital (n = 2509). Two reference diagnoses were defined: Confirmed undernutrition (2002 nutrition risk screening [NRS-2002] score ≥3 plus body mass index [BMI] < 18.5 kg/m2) and probable undernutrition (NRS-2002 ≥ 3 plus any prescribed nutritional management plus BMI ≥18.5 and <20 kg/m2 if age <70 y [ < 22 kg/m2 if age ≥70 y]). Missing BMI values were imputed.

RESULTS: Of the 2509 eligible patients, 262 (10.4%) were classified as confirmed and 631 (25.2%) as probable undernutrition. The sensitivity, specificity, and negative and positive predictive values (and corresponding 95% confidence intervals) for undernutrition codes using confirmed undernutrition were 43.0 (37.0-49.3), 87.2 (85.8-88.6), 92.9 (91.7-94.0), and 28.2 (23.8-32.8), respectively. The corresponding values using both confirmed and probable undernutrition were 30.0 (27.2-32.9), 93.4 (92.0-94.6), 66.7 (64.7-68.7), and 75.1 (70.6-79.3), respectively. Similar findings were obtained after stratifying for sex or age groups or restricting the analysis to patients with non-missing BMI data.

CONCLUSIONS: The undernutrition codes in hospital discharge data have good specificity but the sensitivity and positive predictive values are low.