Defining Opioid-related Problems Using a Health Care Safety Net Institution's Inpatient Electronic Health Records:...

Area of Science:

• Health Services Research
• Public Health
• Clinical Informatics

Background:

• Estimating opioid-related health problems (ORHPs) in healthcare systems is difficult due to inconsistent definitions and coding.
• Standardized definitions for ORHPs are crucial for accurate prevalence estimation and evaluating interventions.
• This study aimed to determine the prevalence of opioid use disorder (OUD), opioid misuse, and opioid poisoning among inpatients.

Purpose of the Study:

• To estimate the prevalence of opioid use disorder (OUD), opioid misuse, and opioid poisoning in hospitalized patients.
• To compare the effectiveness of diagnosis-based definitions versus extended definitions using multiple electronic health record (EHR) markers.
• To highlight the need for improved methods for identifying and quantifying ORHPs within healthcare systems.

Main Methods:

• Utilized electronic health records (EHRs) from Denver Health Medical Center between January 1, 2017, and December 31, 2018.
• Developed diagnosis-based and extended definitions for OUD, opioid misuse, and opioid poisoning using various EHR markers.
• Included diagnostic codes, clinical assessments, laboratory results, and free-text clinical documentation to identify patient events.

Main Results:

• Solely using diagnostic codes identified 715 unique patients with ORHPs.
• Extended definitions, incorporating additional EHR markers, identified an additional 973 unique patients, a 136% increase.
• Clinical documentation markers were the most significant contributor (84.0%) to the extended definitions.

Conclusions:

• Relying solely on diagnostic codes underestimates the prevalence of clinically relevant ORHPs.
• More inclusive estimation methods using diverse EHR markers provide a more comprehensive understanding of ORHP prevalence.
• Improved ORHP estimation methods are essential for accurately assessing healthcare system burden and optimizing resource allocation.