I. Prescription Drug Monitoring Program dataset (PDMP/CURES)
CURES (Controlled Substance Utilization Review and Evaluation System) is California’s statewide prescription drug monitoring program (PDMP) and is maintained by the Department of Justice. CURES is a database of all scheduled II, III and IV controlled substances prescribed by California prescribers. The database includes records of opioid prescriptions by provider, date, location, and patient. As of 2017 prescribers in California are required by law to check CURES every 4 months for their patients receiving opioid prescriptions. PDMPs have been scaled up in an effort to monitor potentially hazardous opioid prescribing, flag patients with potential opioid use disorder, and reduce prescription opioid
Strong research question: the effects of a provider-level academic detailing intervention on opioid stewardship efforts. This study targets a randomized list of high opioid prescribers in the top 10 overdosing counties in California with one-on-one academic detailing educational trainings. Our hypothesis is that a tailored academic detailing intervention on opioid stewardship will change providers’ prescribing practices in the following ways: decrease the number of opioid prescriptions and increase the number of buprenorphine prescriptions. The CURES database is well suited to answer this question because it is an up-to-date, comprehensive data source of all opioid prescriptions written in California. All prescriptions in the database are recorded with date and linked to providers. Exposures will be measured based on our own tracking of who has received academic detailing training from a list of MediCal prescribing providers. We will give DOJ the list of providers with the date on which they were detailed. DOJ will return to us a de-identified list of those providers with the number of opioids and buprenorphine prescriptions written 6 months before and after the educational intervention so we can conduct a pre/post analysis. We will include a comparison group of providers in each county that are also high opioid prescribers but who did not receive the academic detailing intervention.
Weak research question: CURES only has the ability to answer questions related to provider-level activity – it is therefore not useful in drawing any patient-level inferences because it does not record information at the patient-level and is not currently linked to other datasets that would allow for that type of analysis. Questions this dataset cannot answer include: do changes in opioid prescribing at the provider-level reduce opioid-related ED visits for patients with long-term pain? Do mandatory PDMP checks by providers improve patient pain-related outcomes? Or, does switching from a full agonist opioid to a partial agonist like buprenorphine decrease pain and increase function among chronic pain patients? While this is useful, CURES data needs to be merged with additional datasets (like ED records or medical examiner databases) in order to fully understand the utility at the patient-level of interventions aimed at changing opioid prescribing practices.
II. United Nationals Office on Drugs and Crime (UNODC) database
The UNODC Drugs and Crime database collects data on drug use, trafficking, retail/black market opioid prices, production and diversion. The data are derived from results of annual UNODC national surveys: the Annual Report Questionnaire, the Individual Drug Seizure report, and the UN Survey on Crime Trends and Operations of Criminal Justice Systems. The UNODC maintains the database to increase cross-national data comparability and to produce regional and global estimates on drug trends.
Strong research question: This database can be useful to look at changes in country’s opioid consumption across time related to changes in national legislation. A within-country comparison manages the problems with the data mentioned below as long as countries employs consistent data reporting processes over time (E.g. uses the same operational definition for “illicit opioid use”, and the same mechanisms of collecting and reporting data). A strong research question would be related to what effects new legislation could have on opioid consumption and distribution at the national level. For example, we can compare national opioid consumption pre and post a law enforcement policy related to interdiction, or pre and post the establishment of nation-wide harm reduction programs such as the legality of opioid substitution therapy to assess the effect of the new policy. This data is aggregated at the national level so we will still not be able to assess changes at the individual level (opioid consumption is based off of national retail consumption rates from supply requests). Even with this limitation, from a policy perspective it is still useful to assess changes in opioid at the national level.
Weak research question: The opioid consumption data recorded by the UNODC does not actually represent the quantity of opioids used at an individual level, or distributed at the provider/clinic/hospital level, nor does it give insight into geographic dispersion of opioid dissemination e.g. rural vs urban opioid consumption. Additionally, data is not highly standardized across countries (e.g. different countries have different definitions of “illicit opioid use” and different mechanisms for collecting and reporting data) which makes it difficult to draw cross-national comparisons. Research questions related to comparing opioid consumption trends between countries is going to be flawed or infeasible with this datasets. Therefore, we cannot answer questions such as: Are opioid consumption rates by country associated with national statistics such as GDP, open versus closed democracy, criminalization of drug use, life expectancy, etc)?
III. Death certificate data
Death certificate data from the coroners’ reports record all pertinent death information for individual decedents (e.g. primary and secondary causes of deaths, age, race, gender, address/location, medical comorbidities etc). The difference between a strong and weak study design here could be based merely on the degree of specificity we’re looking for in our results. Using data from coroners’ reports is useful in determining broad categories death (e.g. drug poisoning) but it is not necessary useful at specificities within each category (causal opioid involved in opioid overdose).
Strong research question: Assessing changes in opioid overdose rates based on geographic and demographic criteria like gender, race, age, and resident and death location. Based on the geographic information provided, we could answer questions such as: is there an association between opioid overdose fatalities and proximity to syringe exchange programs?
Weak research question: Death certificate date is not always useful for determining specific causes (e.g. opioid type) of overdose, preventing us from accurately answering questions related to changes in the prevalence of different opioid types in overdose events. Different drug toxicology screens test for different opioids therefore if medical examiners change their drug screens it can make it appear as though causal opioids are changing when it may only be a result of measurement bias not actual changes in opioid type in overdose. One current problem with this dataset is that the SF medical examiners’ toxicology screens only recently started to test for buprenorphine. Therefore, buprenorphine will only now begin showing up as a causal agent in opioid overdoses. At the same time, we are working to encourage providers to prescribe more buprenorphine to manage patients’ pain and OUD. This will coincide with the new toxicology report that now tests for buprenorphine and could lead researchers to draw biased conclusions about the association between prescribing buprenorphine and rates of buprenorphine-involved overdoses. If the death data is taken out of context it may look like increases in buprenorphine prescribing lead to increases in buprenorphine deaths which would draw a potential causal inference where there is not one.