How prescription drug monitoring programs influence clinical decision-making: A mixed methods systematic review and meta-analysis

Abstract Background In order to address the opioid crisis in North America, many regions have adopted preventative strategies, such as prescription drug monitoring programs (PDMPs). PDMPs aim to increase patient safety by certifying that opioids are prescribed in appropriate quantities. We aimed to synthesize the literature on changes in opioid-related harms and consequences, an important measure of PDMP effectiveness. Methods We completed a systematic review. We conducted a narrative synthesis of opioid-related harms and consequences from PDMP implementation. Outcomes were grouped into categories by theme: opioid dependence, opioid-related care outcomes, opioid-related adverse events, and opioid-related legal and crime outcomes. Results We included a total of 22 studies (49 PDMPs) in our review. Two studies reported on illicit and problematic use but found no significant associations with PDMP status. Eight studies examined the association between PDMP status and opioid-related care outcomes, of which two found that treatment admissions for prescriptions opioids were lower in states with PDMP programs (p < 0.05). Of the thirteen studies that reported on opioid-related adverse events, two found significant (p < 0.001 and p < 0.05) but conflicting results with one finding a decrease in opioid-related overdose deaths after PDMP implementation and the other an increase. Lastly, two studies found no statistically significant association between PDMP status and opioid-related legal and crime outcomes (crime rates, identification of potential dealers, and diversion). Conclusion Our study found limited evidence to support overall associations between PDMPs and reductions in opioid-related consequences. However, this should not detract from the value of PDMPs’ larger role of improving opioid prescribing.

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The Statistical Fragility of Platelet-Rich Plasma in Rotator Cuff Surgery: A Systematic Review and Meta-analysis

The American Journal of Sports Medicine ◽

10.1177/0363546521989976 ◽

2021 ◽

pp. 036354652198997

Author(s):

Robert L. Parisien ◽

Cooper Ehlers ◽

Antonio Cusano ◽

Paul Tornetta ◽

Xinning Li ◽

...

Keyword(s):

Systematic Review ◽

Decision Making ◽

Rotator Cuff ◽

Clinical Decision Making ◽

Platelet Rich Plasma ◽

Meta Analysis ◽

Clinical Decision ◽

Statistical Stability ◽

Lost To Follow Up

Background: The practice of evidence-based medicine relies on objective data to guide clinical decision-making with specific statistical thresholds conveying study significance. Purpose: To determine the utility of applying the fragility index (FI) and the fragility quotient (FQ) analysis to randomized controlled trials (RCTs) evaluating the utilization of platelet-rich plasma (PRP) in rotator cuff repairs (RCRs). Study Design: Systematic review and meta-analysis. Methods: RCTs pertaining to the utilization of PRP in surgical RCRs published in 13 peer-reviewed journals from 2000 to 2020 were evaluated. The FI was determined by manipulating each reported outcome event until a reversal of significance was appreciated. The associated FQ was determined by dividing the FI by the sample size. Results: Of the 9746 studies screened, 19 RCTs were ultimately included for analysis. The overall FI incorporating all 19 RCTs was only 4, suggesting that the reversal of only 4 events is required to change study significance. The associated FQ was determined as 0.092. Of the 43 outcome events reporting lost to follow-up data, 13 (30.2%) represented lost to follow-up >4. Conclusion: Our analysis suggests that RCTs evaluating PRP for surgical RCRs may lack statistical stability with only a few outcome events required to alter trial significance. Therefore, we recommend the reporting of an FI and an FQ in conjunction with P value analysis to carefully interpret the integrity of statistical stability in future comparative trials. Clinical Relevance: Clinical decisions are often informed by statistically significant results. Thus, a true understanding of the robustness of the statistical findings informing clinical decision-making is of critical importance.

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