Opioids are a class of drugs that includes prescription pain medications and also heroin. Addiction to such drugs is a widespread problem that affects countries across the globe. Opioid dependence is a primary, chronic disease which often involves cycles of relapse and remission. There are several medication-assisted treatments currently in use for opioid dependence: buprenorphine, methadone, naloxone, and naltrexone. This study will concentrate on buprenorphine medication-assisted treatment (BMAT), which consists of a doctor prescribing structured doses of buprenorphine that are decreased over time (a process called medically-controlled discontinuation) in an effort to stabilize an opioid-dependent individual.
Patients, providers, and payers are seeking outcomes data that can help to determine appropriate treatment durations that will present the best opportunity for stability. One way that stability in the disease can be measured is by observing the utilization of healthcare resources such as medications, procedures, or hospital visits: unstable patients use more of the healthcare system. The objective of this study is to estimate optimal treatment length of BMAT that leads to stability in opioid-dependent patients by analyzing healthcare resource utilization data in patients who have undergone medically-controlled discontinuation of buprenorphine.
The primary objective is to estimate the duration of BMAT that results in an optimal stable outcome which will be defined by resource utilization after treatment.
The CPRD database will be accessed for specified subgroups meeting the inclusion and exclusion criteria. The overall healthcare resource utilization and associated costs will be calculated using publically-available NHS sources. Each patient will be categorized into either low or high resource utilization using the median for all patients as a threshold. Each patient will then be assigned to one of six time-treated (on BMAT) cohorts based on the duration of BMAT.
The primary objective of estimating BMAT duration for optimal stable outcome will utilize Fisher’s exact test to analyse differences in proportions between the high and low resource utilization groups across the six time-treated cohorts.
Secondary analyses to support the primary objective will involve studying the relationship between length of BMAT and various subgroup characteristics (age, gender, comorbidities, etc.) and will utilize logistic regression for multivariate analysis of categorical sub-group variables.
Inpatient, outpatient and accident & emergency hospital visits and associated costs Number of prescriptions in primary care Number of consultations and referrals
Christopher Tyson - Chief Investigator - Applied Healthcare Resource Management Inc - AHRM
Jane Ruby - Collaborator - Reckitt Benckiser Pharmaceutical, Inc
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient