Validation of an International Statistical Classification of Diseases and Related Health Problems 10th Revision Coding Algorithm for Hospital Encounters with Hypoglycemia.

OBJECTIVES

To determine the positive predictive value and sensitivity of an International Statistical Classification of Diseases and Related Health Problems, 10th Revision, coding algorithm for hospital encounters concerning hypoglycemia.

METHODS

We carried out 2 retrospective studies in Ontario, Canada. We examined medical records from 2002 through 2014, in which older adults (mean age, 76) were assigned at least 1 code for hypoglycemia (E15, E160, E161, E162, E1063, E1163, E1363, E1463). The positive predictive value of the algorithm was calculated using a gold-standard definition (blood glucose value <4 mmol/L or physician diagnosis of hypoglycemia). To determine the algorithm's sensitivity, we used linked healthcare databases to identify older adults (mean age, 77) with laboratory plasma glucose values <4 mmol/L during a hospital encounter that took place between 2003 and 2011. We assessed how frequently a code for hypoglycemia was present. We also examined the algorithm's performance in differing clinical settings (e.g. inpatient vs. emergency department, by hypoglycemia severity).

RESULTS

The positive predictive value of the algorithm was 94.0% (95% confidence interval 89.3% to 97.0%), and its sensitivity was 12.7% (95% confidence interval 11.9% to 13.5%). It performed better in the emergency department and in cases of more severe hypoglycemia (plasma glucose values <3.5 mmol/L compared with ≥3.5 mmol/L).

CONCLUSIONS

Our hypoglycemia algorithm has a high positive predictive value but is limited in sensitivity. Although we can be confident that older adults who are assigned 1 of these codes truly had a hypoglycemia event, many episodes will not be captured by studies using administrative databases.