Project Details - Ongoing
- Grant Number:R03 HS026266
- Funding Mechanism:
- AHRQ Funded Amount:$99,155
- Principal Investigator:
- Project Dates:9/1/2019 to 8/31/2021
- Care Setting:
- Medical Condition:
- Type of Care:
- Health Care Theme:
As public health officials and hospitals around the Nation search for interventions and strategies to fight against the opioid epidemic, order sets may be a direct and commonly available clinical decision support (CDS) tool that helps limit the number and dosage of opioid prescriptions. CDS presents healthcare providers with relevant clinical knowledge and patient information to improve healthcare delivery. Within computerized physician order entry (CPOE) systems, an order set is a CDS function that presents multiple orders for a particular clinical purpose as a set for clinicians to select. Since a majority of potential adverse drug events are the result of errors during prescribing, order sets are expected to improve patient safety by reducing prescribing variations and errors, and also facilitate efficient order placement based on best practices and guidelines. The creation of order sets has been considered a requirement for a successful CPOE implementation. However, the association among order sets, their expected benefits, and barriers for their usage, is understudied.
Investigators will identify potential clinical process scenarios where the use of order sets is associated with better outcomes than non-use of order sets by applying advanced data analytics to historical data. Data on order placement are extracted from electronic health records. In parallel, investigators will use interviews and surveys to understand perceptions on order sets, in order to identify barriers to the use of the CDS tool.
The specific aims are as follows:
- Assess the relationship between order set use and care processes.
- Assess the relationships between order set use, their default settings, and opioid prescriptions.
- Assess the relationship between order set use and perceptions among clinicians.
The investigators will examine the trend in order placement from 2012 to 2018 across clinical departments at three sites in a tertiary care center at New York-Presbyterian Hospital. Investigators will study the orders placed by Internal Medicine, Surgery, and Emergency Medicine clinicians; they will collect the number of orders for opioids and their type, dosage, the default setting of the orders if from order sets, patients’ principal diagnoses, and other patient-related factors. Investigators will conduct trend analyses of prescriptions by year across departments and campuses by comparing the number and average dosage of opioids prescribed from order sets and standalone orders. Also, investigators will develop models to examine predictors of opioid prescriptions and their dosages. Predictors include clinician and departmental factors, order set and default settings, patients’ medical history, and patients’ clinical complexity. Investigators will conduct interviews and surveys to elicit clinicians’ level of experience, department, information technology training, trust, and self-efficacy about order sets to understand barriers to order set use.
Ultimately, investigators hope that this study will improve the understanding of how to design and maintain order sets from users’ perspective, such that as a form of CDS, order sets can drive better care processes and outcomes.