BackgroundSelective reporting bias (SRB), the incomplete publication of outcomes measured or of analyses performed in a study, may lead to the over- or underestimation of treatment effects or harms. Cochrane systematic reviews of interventions are required to assess the risk of SRB, achieved in part by applying the Cochrane risk of bias tool to each included randomised trial. The Cochrane Handbook outlines strategies for a comprehensive risk of bias assessment, but the extent to which these are followed by Cochrane review groups (CRGs) has not been assessed to date. The objective of this study was to determine the methods which CRGs require of their authors to address SRB within systematic reviews, and how SRB risk assessments are verified.MethodsA cross-sectional survey was developed and distributed electronically to the 52 CRGs involved in intervention reviews.ResultsResponses from 42 CRGs show that the majority refer their authors to the Cochrane Handbook for specific instruction regarding assessments of SRB. The handbook strategies remain variably enforced, with 57 % (24/42) of CRGs not requiring review authors to search for included trial protocols and 31 % (13/42) not requiring that contact with individual study authors be attempted. Only half (48 %, 20/42) of the groups consistently verify review authors’ assessments of the risk of SRB to ensure completeness.ConclusionsA range of practices are used by CRGs for addressing SRB, with many steps outlined in the Cochrane Handbook being encouraged but not required. The majority of CRGs do not consider their review authors to be sufficiently competent to assess for SRB, yet risk of bias assessments are not always verified by editors before publication. The implications of SRB may not be fully appreciated by all CRGs, and resolving the identified issues may require an approach targeting several steps in the systematic review process.Electronic supplementary materialThe online version of this article (doi:10.1186/s13643-015-0070-y) contains supplementary material, which is available to authorized users.
Objective In preference-sensitive conditions such as back pain, there can be high levels of variability in the trajectory of patient care. We sought to develop a methodology that extracts a realistic and comprehensive understanding of the patient journey using medical and pharmaceutical insurance claims data. Materials and Methods We processed a sample of 10 000 patient episodes (comprised of 113 215 back pain–related claims) into strings of characters, where each letter corresponds to a distinct encounter with the healthcare system. We customized the Levenshtein edit distance algorithm to evaluate the level of similarity between each pair of episodes based on both their content (types of events) and ordering (sequence of events). We then used clustering to extract the main variations of the patient journey. Results The algorithm resulted in 12 comprehensive and clinically distinct patterns (clusters) of patient journeys that represent the main ways patients are diagnosed and treated for back pain. We further characterized demographic and utilization metrics for each cluster and observed clear differentiation between the clusters in terms of both clinical content and patient characteristics. Discussion Despite being a complex and often noisy data source, administrative claims provide a unique longitudinal overview of patient care across multiple service providers and locations. This methodology leverages claims to capture a data-driven understanding of how patients traverse the healthcare system. Conclusions When tailored to various conditions and patient settings, this methodology can provide accurate overviews of patient journeys and facilitate a shift toward high-quality practice patterns.
Many journals seemed to lack a method with which to detect ORB and its estimated prevalence was much lower than that reported in literature suggesting inadequate detection. There exists a potential for overestimation of treatment effects of interventions and unclear risks. Fortunately, there are journals within this sample which appear to utilize comprehensive methods for detection of ORB, but overall, the data suggest improvements at the biomedical journal level for detecting and minimizing the effect of this bias are needed.
Although medical research has addressed the clinical management of chronic opioid users, little is known about how operational interventions shortly after opioid initiation can impact a patient’s likelihood of long-term opioid use. Using a nationwide U.S. database of medical and pharmaceutical claims, we investigate the care delivery process at the most common entry point to opioid use: the primary care setting. For patients who return to primary care for a follow-up appointment within 30 days of opioid initiation, we ask who should revisit and potentially revise the opioid-based treatment plan: the initial prescriber (provider concordance) or an alternate clinician (provider discordance)? First, using a fully controlled logistic model, we find that provider discordance reduces the likelihood of long-term opioid use 12 months after opioid initiation by 31% (95% Confidence Interval: [18%, 43%]). Both the instrumental variable analysis technique and propensity-score matching (utilizing the minimum-bias estimator approach) account for omitted variable bias and indicate that this is a conservative estimate of the true causal effect. Second, looking at patient activities immediately after the follow-up appointment, we find that this long-term reduction is at least partially explained by an immediate reduction in opioids prescribed after the follow-up appointment. Third, the data suggest that the benefit associated with provider discordance remains significant regardless of whether the patient’s initial prescriber was their regular primary care provider or another clinician. Overall, our analysis indicates that systematic, operational changes in the early stages of managing new opioid patients may offer a promising, and hitherto overlooked, opportunity to curb the opioid epidemic. This paper was accepted by David Simchi-Levi, healthcare management.
BackgroundDiscrepancies in outcome reporting (DOR) between protocol and published studies include inclusions of new outcomes, omission of prespecified outcomes, upgrade and downgrade of secondary and primary outcomes, and changes in definitions of prespecified outcomes. DOR can result in outcome reporting bias (ORB) when changes in outcomes occur after knowledge of results. This has potential to overestimate treatment effects and underestimate harms. This can also occur at the level of systematic reviews when changes in outcomes occur after knowledge of results of included studies. The prevalence of DOR and ORB in systematic reviews is unknown in systematic reviews published post-2007.ObjectiveTo estimate the prevalence of DOR and risk of ORB in all Cochrane reviews between the years 2007 and 2014.MethodsA stratified random sampling approach was applied to collect a representative sample of Cochrane systematic reviews from each Cochrane review group. DOR was assessed by matching outcomes in each systematic review with their respective protocol. When DOR occurred, reviews were further assessed if there was a risk of ORB (unclear, low or high risk). We classified DOR as a high risk for ORB if the discrepancy occurred after knowledge of results in the systematic review.Results150 of 350 (43%) review and protocol pairings contained DOR. When reviews were further scrutinised, 23% (35 of 150) of reviews with DOR contained a high risk of ORB, with changes being made after knowledge of results from individual trials.ConclusionsIn our study, we identified just under a half of Cochrane reviews with at least one DOR. Of these, a fifth were at high risk of ORB. The presence of DOR and ORB in Cochrane reviews is of great concern; however, a solution is relatively simple. Authors are encouraged to be transparent where outcomes change and to describe the legitimacy of changing outcomes in order to prevent suspicion of bias.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.