Grant Number:	1R01CA267996-01A1 Interpret this number
Primary Investigator:	Bao, Yuhua
Organization:	Weill Medical Coll Of Cornell Univ
Project Title:	Opioid Treatment of Pain in People with Cancer: Intended and Unintended Consequences of State Policies Addressing Opioid Prescribing
Fiscal Year:	2022

ABSTRACT Chronic cancer-related pain is highly prevalent and international guidelines have long supported the use of opioid therapy for moderate to severe pain related to active disease. The strength of such consensus is strongest for patients experiencing advanced disease and limited life expectancy. For patients experiencing long-term remission, or, stable or indolent disease without the need for ongoing anti-cancer treatment (“long- term survivorship”), there is emerging consensus that opioid therapies should be addressed in a similar manner as for patients with chronic non-cancer pain. There is mounting ambiguity regarding best practices for patients receiving active anti-cancer treatment intended for cure. In the wake of the opioid epidemic, state policies have proliferated in an effort to reduce unsafe opioid prescribing. Prominent recent policies include state mandates for prescriber participation in the Prescription Drug Monitoring Programs (PDMPs) and state legislative limits on duration and/or dosage of opioid prescriptions for acute pain. These policies vary in their intended applicability to subpopulations of cancer patients, and, coupled with the ambiguity regarding clinical best practices, may have inadvertently impacted opioid use and related outcomes among the different subpopulations of people with cancer. We propose a study to evaluate intended and unintended consequences of the two types of state policies for opioid prescriptions and pain- and opioid-related adverse health events among cancer patients with advanced disease, long-term survivors, and patients receiving active cancer treatment. To help elucidate mechanisms underlying changes in response to policies, we will also explore the trajectories of opioids dispensed and clinical encounters within each subpopulation, using an innovative pattern mining approach. We will use the SEER-Medicare linked database and a large national commercial insurance database to achieve study aims. Findings will inform consensus-building, guideline and intervention development, and policy and practice changes by providers, health care organizations, and policymakers in optimizing opioid prescribing and pain management for cancer patients.





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