# Improving Opioid Prescription Safety After Surgery > **NIH NIH K23** · UNIVERSITY OF COLORADO DENVER · 2020 · $36,528 ## Abstract Project Summary Over-prescribed opioids after surgery can create a reservoir of opioids that become available for non-medical use. Effective strategies to maximize non-opioid pain therapy and to limit such a reservoir are lacking. Thus, there is an urgent need to study opioid usage patterns and to individualize post-operative pain therapy. The rationale that underlies the proposed research is that once we better understand post-discharge opioid use patterns, we can improve pain management and significantly decrease unnecessarily prescribed opioids. Our central hypothesis is that pain therapy after surgery can be prescribed in an individualized and safer fashion, as opposed to “one size fits all” or non-data driven methods currently employed. To test our hypothesis, three aims are proposed: Specific aim #1 will examine the relationship between patient and procedural characteristics and long-term opioid prescriptions after surgery. This retrospective cohort study includes 6442 patients and will utilize both clinical and claims-based databases. Specific aim #2 will examine patient and procedural characteristics to assess post-operative pain outcomes and predict use patterns for opioids prescribed after surgery. Using survey methods, we will assess pain intensity and interference and quantify consumption of opioids in 600 patients after surgery. A model to predict high vs. low use of prescribed opioids will be developed. Specific aim #3 will prospectively test a decision support tool integrated into the electronic medical record in 116 surgical patients after hospital discharge. The tool will predict actual need for opioid medications and empower patients to maximize non-opioid analgesics. Limiting excess prescription of opioids and maximizing non-opioid medications has the potential to dramatically reduce the amount of opioids available for non-medical use while improving post-operative pain control. The applicant, an anesthesiologist with subspecialty training in pain medicine, proposes a five-year career development program to compliment the research proposal. This incorporates close mentoring by a well-established investigator with expertise in preventing medical complications of drug use in high-risk populations. A mentoring team composed of key faculty members with expertise in psychiatric perspectives of addiction, biostatistics, and health information technology will support the primary mentor. In addition, the candidate has developed a detailed didactic plan that includes training in specialty knowledge in opioid use disorders, epidemiology, health information technology, and clinical trials. The candidate's long-term goal is to develop into an independent clinical scientist with expertise in drug abuse and emphasis on safe and effective delivery of pain therapy after surgery The proposed research, which serves as the key first step towards the applicant reaching his long-term goal, is significant because it will fill the existin... ## Key facts - **NIH application ID:** 9980324 - **Project number:** 5K23DA040923-05 - **Recipient organization:** UNIVERSITY OF COLORADO DENVER - **Principal Investigator:** Karsten Bartels - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $36,528 - **Award type:** 5 - **Project period:** 2016-08-01 → 2021-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9980324 ## Citation > US National Institutes of Health, RePORTER application 9980324, Improving Opioid Prescription Safety After Surgery (5K23DA040923-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9980324. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*