Nilsen, Elizabeth A
(2024)
The Relationship Between Postoperative Prescriber Networks and Opioid Prescribing Discoordination.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Introduction
Postoperative opioid prescribing is common in the United States and poor coordination of prescriptions may lead to higher opioid doses and increased risk for overdose. Our study aimed to use social network analysis to evaluate the impact of prescriber connections on postoperative high-risk opioid prescriptions, including subgroups with chronic opioid use (COU), serious mental illness (SMI), and substance use disorder (SUD).
Methods
Using administrative claims, we sampled patients who underwent surgery in 2018. We created patient-prescriber networks utilizing prescription claims and prescriber-prescriber ties via medical claims with shared patients. Network measures included density (proportion of existing ties to possible ties, scale 0-1) and mean prescriber and opioid prescriber tie strength (number of shared patients, scale 0-3). Measures were categorized into 4 levels for values of 0 and terciles (Levels 0-3). High-risk prescribing was defined as high-dose prescribing (cumulative opioid doses >90 MME daily) and concurrent prescribing (>30 days of concurrent opioid and benzodiazepine prescriptions). We evaluated associations between prescription drug monitoring program (PDMP) legislation and high-risk prescribing across varying levels of network measures. We used mixed effects logistic regression models and generalized estimating equations models to evaluate associations between high-risk prescribing and network measures.
Results
Our final study cohort included 53,273 patients (COU n=4,170; SMI n=9,673; SUD n=1,948; SMI & SUD n=1,783). The majority of the sample was white (70.24%), female (67.90%) with a mean age of 54.36 years. Overall, network density and mean prescriber and opioid prescriber tie strength was low (density 0.5, prescriber tie weight 0.10, opioid prescriber tie weight 0.11). Compared to patients in Level 0, those in Level 1 were more likely, and those in Level 3 were less likely, to have high-risk prescribing. Exact relationships varied by network measure, patient subgroup and outcome. In disconnected networks, having prescribers in a strong PDMP state (compared to weak) reduced the odds of high-risk prescribing by 10% (OR 0.90, 95% CI 0.87, 0.93).
Discussion
Having more and stronger connections between prescribers reduced high-risk prescribing in the year after surgery. Our findings suggest that healthcare networks and policies that enhance communication between prescribers may improve opioid prescribing outcomes.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
9 August 2024 |
| Date Type: |
Publication |
| Defense Date: |
4 June 2024 |
| Approval Date: |
9 August 2024 |
| Submission Date: |
8 August 2024 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
138 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Nursing > Nursing |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Postoperative opioid prescribing, social network analysis, health services research, high-risk prescribing |
| Date Deposited: |
09 Aug 2024 19:45 |
| Last Modified: |
09 Aug 2024 19:45 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/46804 |
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