Project Details - Ended
- Grant Number:K08 HS023683
- Funding Mechanism:
- AHRQ Funded Amount:$633,436
- Principal Investigator:
- Project Dates:9/30/2014 to 9/29/2018
- Care Setting:
- Medical Condition:
- Type of Care:
- Health Care Theme:
In the United States, patients with heart failure experience 4 million hospitalizations per year. The primary diagnosis for three-quarters of these hospitalizations is not for heart failure. Many of these individuals do not receive heart failure guidelines-based care, putting them at high risk of post-discharge mortality. A clinical decision support (CDS) tool has the potential to enhance clinician compliance with guidelines.
This research evaluated the implementation and effectiveness of a CDS tool designed to prompt providers to prescribe an angiotensin converting enzyme (ACE) inhibitor for hospitalized patients with heart failure who were not on the medication. The tool was refined through usability testing with provider feedback prior to implementation. In order to give context to the alert, the CDS displayed vital signs and relevant labs. Two strategies for implementing the CDS tool were compared: an interruptive alert and a non-interruptive alert. Message content for both versions was identical. The interruptive alert occurred as a pop-up when the end user was in the order section of the electronic health record (EHR). The non-interruptive alert was available to all providers in a daily provider checklist in the EHR and could also be accessed through a ‘best practice alert’ section of the patient’s chart. When processing the alert, providers were given the options to order the ACE inhibitor, list a contraindication, choose to reassess the alert in 6 hours, or dismiss the alert. To identify patients with heart disease, an EHR-based algorithm was developed that utilized structured data and natural language processing of unstructured text.
The specific aims of the research were as follows:
- Develop an EHR-based search method that uses both structured data and natural language processing of unstructured text to identify hospitalized patients with heart failure while they are still in the hospital.
- Develop and test the usability of an EHR-based CDS to support delivery of evidence-based care to hospitalized heart failure patients using human computer interaction methods.
- Assess the effect of an EHR-based CDS on processes of care for heart failure patients who are hospitalized for other causes.
The study had two cohorts: a cohort of patients hospitalized with a primary diagnosis of heart failure, and a cohort not hospitalized for heart failure that triggered the alert. Patients with even medical record numbers were assigned the interruptive alert, while those with odd numbers had the non-interruptive version. The primary outcome assessed was the percentage of patients in the heart failure cohort who were discharged on an ACE inhibitor or angiotensin receptor blocker (ARB), an alternative therapy for heart failure.
Improvements were detected in the utilization of ACE and ARBs at discharge, primarily among those without a primary diagnosis of heart failure. The interruptive alert demonstrated a non-significant increase in use of the medications, as well as significant improvements of in-hospital prescription of these therapies and documentation of contraindications. The gains noted were partly a result of the alert having been triggered an average of over 25 times per hospitalization with medication being ordered less than 2 percent of the time, equivalent to the alert needing to be triggered 358 times in order to have one additional ACE inhibitor prescribed. The clinician burden of 358 alerts per quality outcome was described by the researchers as too high. In the future, the researchers plan to tailor the CDS tool toward patients who may benefit the most, to avoid alert fatigue among providers.