Merging statewide data in a public/university collaboration to address opioid use disorder and overdose.

OBJECTIVE: Describe methods to compile a unified database from disparate state agency datasets linking person-level data on controlled substance prescribing, overdose, and treatment for opioid use disorder in Connecticut. METHODS: A multidisciplinary team of university, state and federal agency experts planned steps to build the data analytic system: stakeholder engagement, articulation of metrics, funding to establish the system, determination of needed data, accessing data and merging, and matching patient-level data. RESULTS: Stakeholder meetings occurred over a 6-month period driving selection of metrics and funding was obtained through a grant from the Food and Drug Administration. Through multi-stakeholder collaborations and memoranda of understanding, we identified relevant data sources, merged them and matched individuals across the merged dataset. The dataset contains information on sociodemographics, treatments and outcomes. Step-by-step processes are presented for dissemination. CONCLUSIONS: Creation of a unified database linking multiple sources in a timely and ongoing fashion may assist other states to monitor the public health impact of controlled substances, identify and implement interventions, and assess their effectiveness.

Hyperkalemia and Acute Kidney Injury with Spironolactone Use Among Patients with Heart Failure.

OBJECTIVE: To quantify the risk of hyperkalemia and acute kidney injury (AKI) when spironolactone use is added on to loop diuretic use among patients with heart failure, and to evaluate whether the risk is modified by level of kidney function. METHODS: We identified 17,110 patients with heart failure treated with loop diuretics between January 1, 2004, and December 31, 2016 within the Geisinger Health System. We estimated the incidence of hyperkalemia and AKI associated with spironolactone initiation, and used target trial emulation methods to minimize confounding by indication. RESULTS: During a mean follow-up of 134 mo, 3229 of 17,110 patients (18.9%) initiated spironolactone. Incidence rates of hyperkalemia and AKI in patients using spironolactone with a loop diuretic were 2.9 and 10.1 events per 1000 person-months, respectively. In propensity score-matched analyses, spironolactone initiation was associated with higher hyperkalemia and AKI risk compared with loop alone (hazard ratio, 1.69; 95% CI, 1.35 to 2.10; P<.001, and hazard ratio, 1.12; 95% CI, 1.00 to 1.26; P=.04, respectively). There were no differences in the relative risk of either outcome associated with spironolactone by level of kidney function. CONCLUSION: The addition of spironolactone to loop diuretics in patients with heart failure was associated with higher risk of hyperkalemia and AKI; these risks must be weighed against the potential benefits of spironolactone.

Measures to quantify the abuse of prescription opioids: a review of data sources and metrics.

PURPOSE: The abuse and nonmedical use of prescription opioids and its subsequent consequences are an important public health concern. This phenomenon has paralleled the increase in the therapeutic use of opioids for pain management. There is thus a need to measure prescription opioid abuse to understand trends over time and to compare abuse of one product to another. The purpose of this review is to provide an overview of the strengths and weaknesses of frequently used numerators and denominators in "abuse ratios" (ARs). METHODS: For this review, we critically evaluated the various measures to quantify drug availability and the available data sources to measure prescription opioid abuse. RESULTS: There are currently no commonly adopted metrics for measuring either the prevalence of opioid abuse, or abuse relative to drug availability. Because the settings, manifestations, and severity of abuse can vary from one person to the next, no one measure of abuse, abuse-related outcome, or drug exposure is ideal. Each measure of abuse captures a specific facet of abuse, but not the whole spectrum. Reliable estimation of population-adjusted or utilization-adjusted rates of abuse can be accomplished with a prescription opioid AR. This metric estimates the prevalence of abuse in a given population or abuse relative to how much drug is available, and, in certain cases, can be used to compare abuse among various opioid drugs. AR measurements in the literature vary in the inclusion of specific measures of abuse and availability, and there is little consensus in the field regarding which measures allow for the most appropriate approximation of the extent of abuse, and for comparisons among opioids. Crude numbers of outcomes related to abuse (e.g., emergency department visits, treatment admissions, and overdoses) cannot be properly understood without context as these may overestimate or underestimate the true scope and severity of prescription opioid abuse. They can, however, serve as numerators in properly constructed ARs. The denominator of the AR provides the necessary context by accounting for populations at risk or drug availability (e.g., prescriptions or tablets dispensed, unique recipients of dispensed drug, total patient days of therapy, or kilograms sold), and each comes with its own set of assumptions to consider. CONCLUSIONS: Moving forward, it is important that there be a common understanding in the scientific community regarding how to select appropriate measures to serve as numerators and denominators in AR calculations, and how to interpret the resultant findings. There is no single best measure of abuse for use as a numerator in an AR, and each must be chosen and interpreted in the context of what it measures. For public health considerations, one must always look at both absolute numbers and adjusted numbers. When conducting multiple analyses using different measures of exposure as denominators, differences in ARs are not unexpected, but one should explore why there are differences and assess the appropriateness of each of the denominators.

A comparison of psychosocial and cognitive functioning between depressed and non-depressed patients with cannabis dependence.

Cannabis use and depressive disorders are thought to impair cognitive performance and psychosocial functioning. Both disorders co-occurring may compound the negative effects of these diagnoses. In this study, the authors used the California Computerized Assessment Package as the cognitive performance measure and the Addiction Severity Index as the psychosocial functioning measure to compare individuals who were cannabis dependent and either depressed or not depressed (N= 108: 54 cannabis dependent only, 54 cannabis dependent and depressed or dysthymic). As predicted, cannabis dependent individuals with comorbid depression showed more psychosocial impairment than individuals with cannabis dependence alone. However, contrary to the authors' hypothesis, individuals who were cannabis dependent with comorbid depression showed less cognitive impairment in some California Computerized Assessment Package modules than individuals with cannabis dependence alone. Based on the authors' results, they concluded that the additive effects of cannabis dependency and depression may only be limited to psychosocial domains and may not extend to cognitive functioning.