Project Details - Ongoing
- Grant Number:R21 HS025238
- Funding Mechanism:
- AHRQ Funded Amount:$294,956
- Principal Investigator:
- Project Dates:4/1/2017 to 3/31/2020
- Care Setting:
- Medical Condition:
- Type of Care:
- Health Care Theme:
Sepsis is a life-threatening blood stream infection that affects 8 percent of infants in the pediatric intensive care unit (PICU) and is responsible for 25 percent of PICU mortality. Blood cultures are the only way to diagnose sepsis; however, overuse of blood cultures may result in unnecessary laboratory tests, unnecessary antibiotic use, prolonged hospitalization, and increased health care costs. Existing clinical decision support (CDS) tools for optimizing blood culture utilization rely on analytic approaches to determine the pretest probability of bloodstream infections and fail to address the naturalistic and intuitive nature of clinical decisionmaking, resulting in low adoption by providers.
This project will develop an electronic health record (EHR)-embedded CDS tool that draws upon the strengths of analytical and naturalistic decisionmaking. The team will apply a sociotechnical systems approach and a user-centered design method to guide the development of the CDS tool. The tool will be implemented in the PICU at the Johns Hopkins Hospital (JHH), and an interrupted time series study design will be used to evaluate its impact on blood culture utilization and patient outcomes.
The specific aims of this project are as follows:
- Examine individual and team cognitive work associated with obtaining a blood culture.
- Develop an EHR-embedded CDS tool to facilitate data-driven naturalistic decisionmaking for blood culture utilization.
- Implement the CDS tool in the PICU at JHH and assess its use and impacts on blood culture utilization and patient outcomes.
This study has the potential to demonstrate that a CDS tool that relies on analytical and naturalistic decisionmaking can reduce blood culture utilization in the PICU. If successful, the design principles of the tool maybe generalizable to a broader set of health care issues.