Abstract
Objective:To assess whether implementation of age-dependent therapeutic targets for high hemoglobin A1c (HbA1c) changed clinicians’ ordering of diabetes medications for older adults.Background:In 2016, Kaiser Permanente Southern California (KPSC) changed the therapeutic targets for alerting clinicians about high HbA1c results in the electronic health record, KP HealthConnect (KPHC). Previously, all HbA1c results ≥7.0 percent were flagged as high in adult patients with diabetes. Starting in 2016, HbA1c therapeutic targets were relaxed to <7.5 percent for patients age 65 to 75, and to <8.0 percent for patients over age 75 to reduce treatment intensity and adverse events.Methods:This retrospective analysis used logistic regression models to calculate the change in odds of a medication change following an HbA1c result after age-dependent HbA1c flags were introduced.Results:The odds of medication change decreased among patients whose HbA1c targets were relaxed: Odds Ratio (OR) 0.72 (95 percent CI 0.67–0.76) for patients age 65–75 and HbA1c 7.0 percent–7.5 percent; OR 0.72 (95 percent CI 0.65–0.80) for patients over age 75 and HbA1c 7.0 percent–7.5 percent; and OR 0.67 (95 percent CI 0.61–0.75) for patients over age 75 and HbA1c 7.5 percent–8.0 percent. In the age and HbA1c ranges for which the alerts did not change, the odds of medication change generally increased or stayed the same. There was little evidence of medication de-intensification in any group.Conclusions:These findings suggest that the change in therapeutic targets was associated with a reduction in medication intensification among older adults with diabetes.
Highlights
In the past decade, largely in response to the regulations and financial incentives put in place by the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, adoption of electronic health record (EHR) technology has increased dramatically in the United States
We address the question: are age-dependent therapeutic hemoglobin A1c (HbA1c) targets associated with less intensive glucose management among persons age 65 and older who have diabetes, compared to targets that do not differentiate based on age?
Note that the patient counts in the age groups do not sum to the count of all unique patients because approximately 6 percent of patients contributed to multiple age groups during the analysis
Summary
Largely in response to the regulations and financial incentives put in place by the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, adoption of electronic health record (EHR) technology has increased dramatically in the United States. The mechanism by which alert fatigue leads to alert overrides is not w ell-understood: alerts may be overridden because they interrupt clinicians’ workflows (i.e., they must be routinely bypassed to access more pertinent sections of the patient’s medical record), but multiple (and possibly competing) alerts encountered frequently may lead to cognitive overload, in which considerable effort is required to identify the most important alerts. Another possible mechanism involves desensitization, in which repeated exposure
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