Usefulness of prescription monitoring programs for surveillance-analysis of Schedule II opioid prescription data in Massachusetts, 1996-2006

2010 ◽  
Vol 19 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Nathaniel Katz ◽  
Lee Panas ◽  
MeeLee Kim ◽  
Adele D. Audet ◽  
Arnold Bilansky ◽  
...  
2019 ◽  
Vol 3 (22;3) ◽  
pp. 229-240 ◽  
Author(s):  
Yola Moride

Background: Canada and the United States have the highest levels of prescription opioid consumption in the world. In an attempt to curb the opioid epidemic, a variety of interventions have been implemented. Thus far, evidence regarding their effectiveness has not been consolidated. Objectives: The objectives of this study were to: 1) identify interventions that target opioid prescribing; 2) assess and compare the effectiveness of interventions on opioid prescription and related harms; 3) determine the methodological quality of evaluation studies. Study Design: The study involved a systematic review of the literature including bibliographical databases and gray literature sources. Setting: Systematic review including bibliographical databases and gray literature sources. Methods: We searched MEDLINE, Embase, and LILACS databases from January 1, 2005 to September 23, 2016 for any intervention that targeted the prescription of opioids. We also examined websites of relevant organizations and scanned bibliographies of included articles and reviews for additional references. The target population was that of all health care providers (HCPs) or users of opioids with no restriction on indication. Endpoints were those related to process (implementation), outcomes (effectiveness), or impact. Sources were screened independently by 2 reviewers using pre-defined eligibility criteria. Synthesis of findings was qualitative; no pooling of results was conducted. Results: Literature search yielded 12,278 unique sources. Of these, 142 were retained. During full-text review, 75 were further excluded. Searches of the gray literature and bibliographies yielded 49 additional sources. Thus, a total of 95 distinct interventions were identified. Over half consisted of prescription monitoring programs (PMPs) and mainly targeted HCPs. Evaluation studies addressed mainly opioid prescription rate (30.6%), opioid use (19.4%), or doctor shopping or diversion (9.7%). Fewer studies considered overdose death (9.7%), abuse (9.7%), misuse (4.2%), or diversion (5.6%). Study designs consisted of cross-sectional surveys (23.3%), pre-post intervention (26.7%), or time series without a comparison group (13.3%), which limit the robustness of the evidence. Although PMPs and policies have been associated with a reduction in opioid prescription, their impact on appropriateness of use according to clinical guidelines and restriction of access to patients in need is inconsistent. Continuing medical education (CME) and pain management programs were found effective in improving chronic pain management, but studies were conducted in specific settings. The impact of interventions on abuse and overdose-death is conflicting. Limitations: Due to the very large number of publications and programs found, it was difficult to compare interventions owing to the heterogeneity of the programs and to the methodologies of evaluation studies. No assessment of publication bias was done in the review. Conclusions: Evidence of effectiveness of interventions targeting the prescription of opioids is scarce in the literature. Although PMPs have been associated with a reduction in the overall prescription rates of Schedule II opioids, their impact on the appropriateness of use taking into consideration benefits, misuse, legal and illegal use remains elusive. Our review suggests that existing interventions have not addressed all determinants of inappropriate opioid prescribing and usage. A well-described theoretical framework would be the backdrop against which targeted interventions or policies may be developed. Key words: Opioid, prescription, abuse, misuse, diversion, interventions, prescription monitoring programs


Pain Medicine ◽  
2012 ◽  
Vol 13 (3) ◽  
pp. 434-442 ◽  
Author(s):  
Liza M. Reifler ◽  
Danna Droz ◽  
J. Elise Bailey ◽  
Sidney H. Schnoll ◽  
Reginald Fant ◽  
...  

Author(s):  
Jacopo Vanoli ◽  
Consuelo Rubina Nava ◽  
Chiara Airoldi ◽  
Andrealuna Ucciero ◽  
Virginio Salvi ◽  
...  

While state sequence analysis (SSA) has been long used in social sciences, its use in pharmacoepidemiology is still in its infancy. Indeed, this technique is relatively easy to use, and its intrinsic visual nature may help investigators to untangle the latent information within prescription data, facilitating the individuation of specific patterns and possible inappropriate use of medications. In this paper, we provide an educational primer of the most important learning concepts and methods of SSA, including measurement of dissimilarities between sequences, the application of clustering methods to identify sequence patterns, the use of complexity measures for sequence patterns, the graphical visualization of sequences, and the use of SSA in predictive models. As a worked example, we present an application of SSA to opioid prescription patterns in patients with non-cancer pain, using real-world data from Italy. We show how SSA allows the identification of patterns in prescriptions in these data that might not be evident using standard statistical approaches and how these patterns are associated with future discontinuation of opioid therapy.


2021 ◽  
pp. e1-e9
Author(s):  
Elizabeth A. Erdman ◽  
Leonard D. Young ◽  
Dana L. Bernson ◽  
Cici Bauer ◽  
Kenneth Chui ◽  
...  

Objectives. To develop an imputation method to produce estimates for suppressed values within a shared government administrative data set to facilitate accurate data sharing and statistical and spatial analyses. Methods. We developed an imputation approach that incorporated known features of suppressed Massachusetts surveillance data from 2011 to 2017 to predict missing values more precisely. Our methods for 35 de-identified opioid prescription data sets combined modified previous or next substitution followed by mean imputation and a count adjustment to estimate suppressed values before sharing. We modeled 4 methods and compared the results to baseline mean imputation. Results. We assessed performance by comparing root mean squared error (RMSE), mean absolute error (MAE), and proportional variance between imputed and suppressed values. Our method outperformed mean imputation; we retained 46% of the suppressed value’s proportional variance with better precision (22% lower RMSE and 26% lower MAE) than simple mean imputation. Conclusions. Our easy-to-implement imputation technique largely overcomes the adverse effects of low count value suppression with superior results to simple mean imputation. This novel method is generalizable to researchers sharing protected public health surveillance data. (Am J Public Health. Published online ahead of print September 16, 2021: e1–e9. https://doi.org/10.2105/AJPH.2021.306432 )


2020 ◽  
pp. 103-123
Author(s):  
Peng Zhang ◽  
Breck Stodghill ◽  
Cory Pitt ◽  
Cavin Briody ◽  
Douglas C. Schmidt ◽  
...  

This article describes the structure and functionality of OpTrak, a decentralized app implemented using the Ethereum blockchain that targets the opioid epidemic currently plaguing the United States. Over-prescription and distribution of opioids cost the national healthcare system over $78 billion every year. Problems persist in every stage of the process, from doctors prescribing the medication to the pharmacists fulfilling prescriptions. These problems arise from a combination of factors, including lack of accountability, transparency, and reliability in the current prescription drug monitoring programs. This work provides three key contributions to research on a technical approach to mitigate the opioid epidemic. First, the authors pinpoint key problems in the current opioid prescription system. Second, they propose an integrated approach for addressing the problems by leveraging distributed ledgers, focusing on blockchain technology. Third, the authors describe the structure and functionality of OpTrak that allows a consortium of care providers to exchange patient prescription data securely.


CJEM ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 486-493
Author(s):  
Garrick Mok ◽  
Hailey Newton ◽  
Lisa Thurgur ◽  
Marie-Joe Nemnom ◽  
Ian G. Stiell

ABSTRACTBackgroundOpioid related mortality rate has increased 200% over the past decade. Studies show variable emergency department (ED) opioid prescription practices and a correlation with increased long-term use. ED physicians may be contributing to this problem. Our objective was to analyze ED opioid prescription practices for patients with acute fractures.MethodsWe conducted a review of ED patients seen at two campuses of a tertiary care hospital. We evaluated a consecutive sample of patients with acute fractures (January 2016–April 2016) seen by ED physicians. Patients admitted or discharged by consultant services were excluded. The primary outcome was the proportion of patients discharged with an opioid prescription. Data were collected using screening lists, electronic records, and interobserver agreement. We calculated simple descriptive statistics and a multivariable analysis.ResultsWe enrolled 816 patients, including 441 females (54.0%). Most common fracture was wrist/hand (35.2%). 260 patients (31.8%) were discharged with an opioid; hydromorphone (N = 115, range 1–120 mg) was most common. 35 patients (4.3%) had pain related ED visits <1 month after discharge. Fractures of the lumbar spine (OR 10.78 [95% CI: 3.15–36.90]) and rib(s)/sternum/thoracic spine (OR 5.46 [95% CI: 2.88–10.35)] had a significantly higher likelihood of opioid prescriptions.ConclusionsThe majority of patients presenting to the ED with acute fractures were not discharged with an opioid. Hydromorphone was the most common opioid prescribed, with large variations in total dosage. Overall, there were few return to ED visits. We recommend standardization of ED opioid prescribing, with attention to limiting total dosage.


2019 ◽  
Vol 55 (1) ◽  
pp. 1-11
Author(s):  
Jeff Reist ◽  
Joseph Frazier ◽  
Alecia Rottingham ◽  
Mackenzie Welsh ◽  
Brahmendra Reddy Viyyuri ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document