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INtegrated Services for Pain: Interventions to Reduce Pain Effectively (INSPIRE) was a pragmatic randomized trial conducted from 2019 to 2023 with adults receiving chronic opioid therapy (COT) of at least 20 morphine milligram equivalents (MME) daily for chronic noncancer pain (CNCP). Participants were recruited from primary care and specialty pain clinics at three academic health centers in North Carolina and Tennessee. The study compared the effectiveness of the two behavioral interventions, 1) shared decision making (SDM) versus 2) motivational interviewing plus cognitive behavioral therapy for chronic pain (MI+CBT), on change in opioid dose, physical function, and pain interference. INSPIRE combined data from electronic health records (EHR) on opioid dose from baseline to 18 months and comorbidities with participant survey data at baseline, 6, and 12 months on the following topics:

• physical function,
• pain interference,
• pain intensity,
• anxiety,
• depression,
• pain severity,
• discontinuation of opioids,
• intent to reduce opioids,
• opioid use relative to baseline,
• adverse events,
• demographics,
• health insurance coverage,
• health literacy,
• patient-centered communication, and
• types of pain treatment used.

The collection includes three analysis datasets:

1. Adverse Events Dataset - one record per subject per adverse event
2. Opioid Prescriptions Dataset (post-processed opioid prescriptions used to derive the study's primary outcome) - one record per subject per opioid prescription
3. Outcomes Dataset (contains all of the study's demographics, primary, secondary, exploratory, and subgroup analysis variables) - one record per subject per timepoint

Comparative effectiveness research compares two or more treatments to see which treatment works better for which patients. Such research may include

• Randomized controlled trials, or RCTs. Researchers assign patients to a treatment by chance. Researchers consider RCTs to be the best way to figure out when changes in patients' health result from the treatment.
• Observational studies. Researchers study what happens when patients and their doctors choose treatments. Patient traits, such as age or health, may affect treatment choices. These traits may also affect patients' responses to treatments. Determining whether a patient's traits, the treatment, or a mix of the two affected how well the treatment worked may be difficult.

In observational studies, researchers use statistical methods to help find out whether changes in patients' health result from treatment or something else. Existing methods work well when studies look at whether treatment affects the risk of a health event, such as a heart attack. In these cases, researchers can compare how often patients had heart attacks before and after patients receive treatment. But existing methods don't work well when studies look at the risk of a one-time event, such as death.

In this study, the research team tested a new statistical method for observational studies called posttreatment event rate ratio, or PTERR, that helps figure out whether a treatment reduces the risk of death.