Anticipated Impacts on Veteran's Healthcare: This project will demonstrate the use of spatiotemporal (ST) analysis as a method for use in monitoring specific prescribing patterns and in the identification of clusters or hot spots of prescribing associated with safety issues or inappropriate practices. For this surveillance demonstration we propose to employ the Opioid Safety Initiative (OSI) as a demonstration of how ST methods can provide valuable information about progress with a high-priority VA initiative. We will evaluate increases and decreases in specific patterns of opioid prescribing using space-time statistics and software. In addition to guiding OSI implementation, our work also will have broader implications. Developing capability to contribute real-time surveillance regarding the uptake of medications will interest QUERI and PBM. Moving the analysis upstream is preferable to reacting to prescribing patterns after they occur. In addition, enhanced capability to analyze ST trends of medication prescribing will be instrumental in insights on why differences arise. That is, by identifying ST trends, we will have newfound capability to examine why some sites change practice more rapidly than others. Project Background/Rationale: ST analysis has great potential to provide meaningful information about rapidly developing prescribing patterns, and patterns of reductions in prescribing, in real time. The OSI provides an ideal proof of concept QI venue to test how these methods can be used to assess changes in prescribing patterns through surveillance in real time. The OSI grew out of an accumulating body of evidence that some opioid use is unsafe and may be contributing to harm for our Veteran patients. OSI represents the VA application of this evidence through an organized initiative. Major goals of OSI include: 1) Limiting the use of high-dose opioids; 2) Limiting the co-prescription of opioids and benzodiazepines; and 3) Developing toolkits and other implementation strategies for providing safer alternatives for treating chronic pain. Project Objectives: (1) We will identify Veterans prescribed 200 mg morphine equivalents (high-dose opioids) and calculate counts by VAMC. We will reconcile these counts with other data sources, including QUERI SUD measures and the OSI Dashboard and toolkit implementation from FY2014 into FY2016; (2) We will apply ST methods to describe changes in high-dose opioid prescribing quarter by quarter, starting with FY2014 and continuing through the four quarters of FY2015 and first half of FY2016; (3) We will expand the ST analysis to track other OSI-relevant metrics, such as 100 mg morphine equivalents and both incident prescribing (new starts) and cessation (de-prescribing) of co-prescription of opioids and benzodiazepines. Supplementary analysis will test for differences in chronic non-cancer pain syndromes. Project Methods: The findings of this pilot will serve as a springboard for further HSR&D research proposals to identify hot spots of change in real time using ST methods and what incrementally can be learned over more traditional tracking methods. The results of this project also will support future research to understand how these hot spots occur through more detailed investigations, such as social network analyses among patients and providers and through key informant interviews. The present proposal will open the door to monitoring and understanding phenomena previously invisible to us, simply because we lacked the means to identify them.
Using spatiotemporal methods, we will assess prescribing patterns, both to identify ?hot spots? of growth, as well as ?cold spots? where prescribing is decreasing for high-dose opioids, defined as more than 200 mg/day of morphine or the equivalent. These have been linked to an elevated risk of accidental death by overdose in VA patients. Through the present pilot study, we will establish a methodological proof-of-concept, namely that spatiotemporal methods can be applied to track changes in prescribing, and other changes in VA care, through real time surveillance, and can provide policy details not available otherwise. This framework will be essential to future proposals to use such methods to track changes in prescribing of other medications in real time.
