- Title Information
- Title
- Analysis of temporal trends in opioid prescribing: Assessing the effectiveness of an opioid prescribing policy using segmented regression, difference in difference versus propensity scoring techniques
- Type of Resource
- text
- Name:
Personal
- Name Part
- Zhai, Wanting
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- Sullivan, Adam
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Beaudoin, Francesca
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Department of Biostatistics
- Role
- Role Term:
Text
- sponsor
- Origin Information
- Copyright Date
- 2017
- Physical Description
- Extent
- vii, 31 p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Sc. M.)--Brown University, 2017
- Genre (aat)
- theses
- Abstract
- Abstract of Analysis of temporal trends in opioid prescribing: Assessing the Effectiveness of an opioid prescribing policy using segmented regression, difference in difference versus propensity scoring techniques, by Wanting Zhai, ScM, Brown University, May 2017
Background: Efforts to address the issue of prescription opioid misuse have been implemented across the United States and Canada.
Study Objectives: To determine whether the opioid prescribing decreases after implementation of the policy and whether changes in opioid prescribing differ at the level of the provider based on their baseline prescribing practices.
Methods: We will present segmented regression, Difference in Difference and propensity scoring techniques.
Setting and Subjects: The dataset is an extraction from the electronic medical records (EMR) at Newport Hospital, The Miriam Hospital and Rhode Island Hospital from November of 2012 to November of 2014. The data contains patients’ characteristics, providers in the emergency department, diagnoses, disposition (ex. admitted or discharged), medications given in the ED, home medications, and prescription received at discharge.
Results: We found that local, departmental based guidelines are associated with a decrease in the number of prescriptions dispensed from the emergency department. Further, based on our results, this effect is more dramatic for those physicians with median baseline prescribing patterns and patients cared for by advanced practice providers (PA/NP)
Conclusions: Future policy work could evaluate interventions intended to normalize prescribing in “high-prescribers” and determine whether or not this impacts patient-relevant outcomes. For methods, we recommend using propensity score matching and then segmented regression. This would then allow for the adjustment of multiple confounders and fix the limitation of segmented regression analysis.
- Subject
- Topic
- causal inference
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20170616
- Identifier:
DOI
- 10.7301/Z0KP80MB
- Access Condition:
rights statement
(href="http://rightsstatements.org/vocab/InC/1.0/")
- In Copyright
- Access Condition:
restriction on access
- Collection is open for research.