van den Bogert CA, Souverein PC, Brekelmans CT, Janssen SW, Koeter GH, Leufkens HG, Bouter LM. Discrepancies between protocols and publications of clinical drug trials Results of an inception cohort study. J.Clin.Epidemiol. Epub 2017 May 20. PMID: 28535887.

OBJECTIVE:
To identify the occurrence and determinants of protocol-publication discrepancies in clinical drug trials.
STUDY DESIGN AND SETTING:
All published clinical drug trials reviewed by the Dutch Institutional Review Boards in 2007 were analyzed. Discrepancies between trial protocols and publications were measured among key reporting aspects. We evaluated the association of trial characteristics with discrepancies in primary endpoints by calculating the risk ratio (RR) and 95% confidence interval (CI).
RESULTS:
Of the 334 published trials, 32 (9.6%) had a protocol/publication discrepancy in the primary endpoints. Among the subgroup of randomized controlled trials (RCTs; N=204), 12 (5.9%) had a discrepancy in the primary endpoint. Investigator-initiated trials with and without industry (co-) funding were associated with having discrepancies in the primary endpoints compared to industry-sponsored trials (RR 3.7; 95% CI 1.4-9.9 and RR 4.4; 95% CI 2.0-9.5, respectively). Furthermore, other than phase 1-4 trials (vs. phase 1; RR 4.6; 95% CI 1.1-19.3), multicenter trials also conducted outside the EU (vs. single center; RR 0.2; 95% CI 0.1-0.6), not prospectively registered trials (RR 3.3; 95% CI 1.5-7.5), non-RCTs (vs. superiority RCT; RR 2.4; 95% CI 1.2-4.8) and, among the RCTs, crossover compared to a parallel group design (RR 3.7; 95% CI 1.1-12.3) were significantly associated with having discrepancies in the primary endpoints.
CONCLUSIONS:
Improvement in completeness of reporting is still needed, especially among investigator-initiated trials and non-RCTs. To eliminate undisclosed discrepancies, trial protocols should be available in the public domain at the same time when the trial is published.
Copyright © 2017. Published by Elsevier Inc.

DOI: https://doi.org/10.1016/j.jclinepi.2017.05.012.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28535887.

Tanniou J, van der Tweel I, Teerenstra S, Roes KCB. Estimates of subgroup treatment effects in overall nonsignificant trials: To what extent should we believe in them? Pharm.Stat. Epub 2017 May 15. PMID: 28503861.

In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial. We should, however, be reasonably confident in the observed treatment effect size to be able to use this estimate in a replication trial in the subpopulation of interest. We were therefore interested in evaluating the bias of the estimate of the subgroup treatment effect, after selection based on significance for the subgroup in an overall "failed" trial. Different scenarios, involving continuous as well as dichotomous outcomes, were investigated via simulation studies. It is shown that the bias associated with subgroup findings in overall nonsignificant clinical trials is on average large and varies substantially across plausible scenarios. This renders the subgroup treatment estimate from the original trial of limited value to design the replication trial. An empirical Bayesian shrinkage method is suggested to minimize this overestimation. The proposed estimator appears to offer either a good or a conservative correction to the observed subgroup treatment effect hence provides a more reliable subgroup treatment effect estimate for adequate planning of future studies.

DOI: http://dx.doi.org/10.1002/pst.1810.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28503861.

Hoaglin DC. A Flawed Meta-analysis: Similar Risk of Cardiopulmonary Adverse Events Between Propofol and Traditional Anesthesia for Gastrointestinal Endoscopy. Clin.Gastroenterol.Hepatol. Epub 2017 Mar 29. PMID: 28365487.
DOI: http://dx.doi.org/ 10.1016/j.cgh.2017.03.034.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28365487.

Gore C, Executive Board of the World Hepatitis Alliance. An open letter to the Cochrane Collaboration. Lancet Gastroenterol.Hepatol. Epub 2017 Jun 22. PMID: 28648800.
DOI: http://dx.doi.org/10.1016/S2468-1253(17)30193-0.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28648800.

Stefaniak JD, Lam TCH, Sim NE, Al-Shahi Salman R, Breen DP. Discontinuation and non-publication of neurodegenerative disease trials: a cross-sectional analysis. Eur.J.Neurol. Epub 2017 Jun 21. PMID: 28636179.

BACKGROUND AND PURPOSE:
Trial discontinuation and non-publication represent major sources of research waste in clinical medicine. No previous studies have investigated non-dissemination bias in clinical trials of neurodegenerative diseases.
METHODS:
ClinicalTrials.gov was searched for all randomized, interventional, phase II-IV trials that were registered between 1 January 2000 and 31 December 2009 and included adults with Alzheimer's disease, motor neurone disease, multiple sclerosis or Parkinson's disease. Publications from these trials were identified by extensive online searching and contact with authors, and multiple logistic regression analysis was performed to identify characteristics associated with trial discontinuation and non-publication.
RESULTS:
In all, 362 eligible trials were identified, of which 12% (42/362) were discontinued. 28% (91/320) of completed trials remained unpublished after 5 years. Trial discontinuation was independently associated with number of patients (P = 0.015; more likely in trials with ?100 patients; odds ratio 2.65, 95% confidence interval 1.21-5.78) and phase of trial (P = 0.009; more likely in phase IV than phase III trials; odds ratio 3.90, 95% confidence interval 1.41-10.83). Trial non-publication was independently associated with blinding status (P = 0.005; more likely in single-blind than double-blind trials; odds ratio 5.63, 95% confidence interval 1.70-18.71), number of centres (P = 0.010; more likely in single-centre than multi-centre trials; odds ratio 2.49, 95% confidence interval 1.25-4.99), phase of trial (P = 0.041; more likely in phase II than phase IV trials; odds ratio 2.88, 95% confidence interval 1.04-7.93) and sponsor category (P = 0.001; more likely in industry-sponsored than university-sponsored trials; odds ratio 5.05, 95% confidence interval 1.87-13.63).
CONCLUSIONS:
There is evidence of non-dissemination bias in randomized trials of interventions for neurodegenerative diseases. Associations with trial discontinuation and non-publication were similar to findings in other diseases. These biases may distort the therapeutic information available to inform clinical practice.
© 2017 EAN.

DOI: http://dx.doi.org/10.1111/ene.13336.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28636179.

Mullane K, Williams M. Enhancing Reproducibility: Failures from Reproducibility Initiatives underline core challenges. Biochem.Pharmacol. Epub 2017 Apr 8. PMID: 28396196.

Efforts to address reproducibility concerns in biomedical research include: initiatives to improve journal publication standards and peer review; increased attention to publishing methodological details that enable experiments to be reconstructed; guidelines on standards for study design, implementation, analysis and execution; meta-analyses of multiple studies within a field to synthesize a common conclusion and; the formation of consortia to adopt uniform protocols and internally reproduce data. Another approach to addressing reproducibility are Reproducibility Initiatives (RIs), well-intended, high-profile, systematically peer-vetted initiatives that are intended to replace the traditional process of scientific self-correction. Outcomes from the RIs reported to date have questioned the usefulness of this approach, particularly when the RI outcome differs from other independent self-correction studies that have reproduced the original finding. As a failed RI attempt is a single outcome distinct from the original study, it cannot provide any definitive conclusions necessitating additional studies that the RI approach has neither the ability nor intent of conducting making it a questionable replacement for self-correction. A failed RI attempt also has the potential to damage the reputation of the author of the original finding. Reproduction is frequently confused with replication, an issue that is more than semantic with the former denoting "similarity" and the latter an "exact copy" - an impossible outcome in research because of known and unknown technical, environmental and motivational differences between the original and reproduction studies. To date, the RI framework has negatively impacted efforts to improve reproducibility, confounding attempts to determine whether a research finding is real (250).

DOI: http://dx.doi.org/10.1016/j.bcp.2017.04.008.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28396196.

Foughty Z, Antalis MS, Ringenberg J, Hall AD. Funding sources and financial disclosures, and their relationship to study outcomes and level of evidence in the Journal of Shoulder and Elbow Surgery. J.Shoulder Elbow Surg. 2017 Jun;26(6):e193-7. PMID: 28395946.

HYPOTHESIS/BACKGROUND:
Concern exists regarding the reliability of published manuscripts due to influence of industry funding and author financial conflicts of interest (COI). We aim to determine whether COI affect the outcome of a research study or the level of evidence (LOE).
METHODS:
We reviewed 244 consecutive original articles in Journal of Shoulder and Elbow Surgery from January 2014 to December 2014. Articles included only those available in the printed journal. For LOE, 178 articles from the Shoulder and Elbow section were used (basic science articles were excluded). COI was determined by comparing financial disclosures and stated funding sources to the study content.
RESULTS:
COI were present in 44 of 244 articles (18%); of these, 24 (55%) had positive outcomes. Of the 200 without COI, 128 (64%) had positive outcomes. This difference in proportions was determined to be significant (P = .007). COI were present in 27 shoulder and elbow articles; of these, only 1 was LOE I or II (4%). Of the 151 without COI, 34 (23%) were LOE I or II. This difference in proportions was determined to be significant (P = .023).
CONCLUSION:
We found that Journal of Shoulder and Elbow Surgery articles with COI are neither more likely to have positive outcomes nor higher LOE than those with no COI. Although the ?2 analysis found a statistically significant relationship between COI and study outcomes, the study outcomes were more often positive in articles without COI. This is contrary to previously published analyses that found outcomes to be more positive in articles with COI.
Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

DOI: http://dx.doi.org/10.1016/j.jse.2017.02.016.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28395946.

Hajibandeh S, Hajibandeh S, Antoniou SA, Antoniou GA, Torella F. Industry sponsorship and positive outcome in vascular and endovascular randomised trials. Vasa. 2017 Jan;46(1):67-8. PMID: 27889961.
DOI: http://dx.doi.org/10.1024/0301-1526/a000592.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=27889961.

Hakala AK, Fergusson D, Kimmelman J. Nonpublication of trial results for new neurological drugs: A systematic review. Ann.Neurol. 2017 Jun;81(6):782-9. PMID: 28486773.

OBJECTIVE:
To evaluate nonpublication rates among trials of new successful and unsuccessful neurological drugs.
METHODS:
"Licensed" drugs consisted of all novel agents receiving US Food and Drug Administration (FDA) licensure 2005-2012 inclusive in seven neurological disorders. "Stalled" drugs included all experimental agents tested in the same domains that had at least one completed phase III trial in the same time frame, but failed to receive FDA approval. Trials of these drugs were included in our sample if their primary outcome collection occurred before October 1, 2010. We determined the publication status of eligible trials using searches of clinicaltrials.gov, Google Scholar, PubMed, Embase, sponsor websites, and direct electronic query of trial contacts and sponsors. The primary outcome was time to journal publication (or results reporting in other media) after study completion.
RESULTS:
The adjusted hazard ratio for publication was 1.79 (95% confidence interval, 1.20-2.67) in favor of licensed drugs. Based on the criteria for nonpublication in this report, 14,092 and 33,882 volunteers participated in unpublished trials of licensed and stalled neurological drugs, respectively. Result data were not publicly available in any form for 10% (16 of 163) and 46% (94 of 203) of trials of licensed and stalled drugs, respectively.
INTERPRETATION:
Results of trials for stalled drugs are heavily under-reported. This deprives research and care communities of evidence about pathophysiology, drug class effects, and the value of surrogate endpoints in trials. Ann Neurol 2017;81:782-789.
© 2017 American Neurological Association.

DOI: http://dx.doi.org/10.1002/ana.24952.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28486773.

Harris C, Allen K, Brooke V, Dyer T, Waller C, King R, Ramsey W, Mortimer D. Sustainability in Health care by Allocating Resources Effectively (SHARE) 6: investigating methods to identify, prioritise, implement and evaluate disinvestment projects in a local healthcare setting. BMC Health Serv.Res. 2017 May 25;17(1):370. PMID: 28545430.

BACKGROUND:
This is the sixth in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE program was established to investigate a systematic, integrated, evidence-based approach to disinvestment within a large Australian health service. This paper describes the methods employed in undertaking pilot disinvestment projects. It draws a number of lessons regarding the strengths and weaknesses of these methods; particularly regarding the crucial first step of identifying targets for disinvestment.
METHODS:
Literature reviews, survey, interviews, consultation and workshops were used to capture and process the relevant information. A theoretical framework was adapted for evaluation and explication of disinvestment projects, including a taxonomy for the determinants of effectiveness, process of change and outcome measures. Implementation, evaluation and costing plans were developed.
RESULTS:
Four literature reviews were completed, surveys were received from 15 external experts, 65 interviews were conducted, 18 senior decision-makers attended a data gathering workshop, 22 experts and local informants were consulted, and four decision-making workshops were undertaken. Mechanisms to identify disinvestment targets and criteria for prioritisation and decision-making were investigated. A catalogue containing 184 evidence-based opportunities for disinvestment and an algorithm to identify disinvestment projects were developed. An Expression of Interest process identified two potential disinvestment projects. Seventeen additional projects were proposed through a non-systematic nomination process. Four of the 19 proposals were selected as pilot projects but only one reached the implementation stage. Factors with potential influence on the outcomes of disinvestment projects are discussed and barriers and enablers in the pilot projects are summarised.
CONCLUSION:
This study provides an in-depth insight into the experience of disinvestment in one local healthcare service. To our knowledge, this is the first paper to report the process of disinvestment from identification, through prioritisation and decision-making, to implementation and evaluation, and finally explication of the processes and outcomes.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445482/pdf/12913_2017_Article_2269.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2269-1.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28545430.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445482/.

Harris C, Allen K, King R, Ramsey W, Kelly C, Thiagarajan M. Sustainability in Health care by Allocating Resources Effectively (SHARE) 2: identifying opportunities for disinvestment in a local healthcare setting. BMC Health Serv.Res. 2017 May 5;17(1):328. PMID: 28476159.

BACKGROUND:
This is the second in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Rising healthcare costs, continuing advances in health technologies and recognition of ineffective practices and systematic waste are driving disinvestment of health technologies and clinical practices that offer little or no benefit in order to maximise outcomes from existing resources. However there is little information to guide regional health services or individual facilities in how they might approach disinvestment locally. This paper outlines the investigation of potential settings and methods for decision-making about disinvestment in the context of an Australian health service.
METHODS:
Methods include a literature review on the concepts and terminology relating to disinvestment, a survey of national and international researchers, and interviews and workshops with local informants. A conceptual framework was drafted and refined with stakeholder feedback.
RESULTS:
There is a lack of common terminology regarding definitions and concepts related to disinvestment and no guidance for an organisation-wide systematic approach to disinvestment in a local healthcare service. A summary of issues from the literature and respondents highlight the lack of theoretical knowledge and practical experience and provide a guide to the information required to develop future models or methods for disinvestment in the local context. A conceptual framework was developed. Three mechanisms that provide opportunities to introduce disinvestment decisions into health service systems and processes were identified. Presented in order of complexity, time to achieve outcomes and resources required they include 1) Explicit consideration of potential disinvestment in routine decision-making, 2) Proactive decision-making about disinvestment driven by available evidence from published research and local data, and 3) Specific exercises in priority setting and system redesign.
CONCLUSION:
This framework identifies potential opportunities to initiate disinvestment activities in a systematic integrated approach that can be applied across a whole organisation using transparent, evidence-based methods. Incorporating considerations for disinvestment into existing decision-making systems and processes might be achieved quickly with minimal cost; however establishment of new systems requires research into appropriate methods and provision of appropriate skills and resources to deliver them.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420107/pdf/12913_2017_Article_2211.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2211-6.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28476159.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420107/.

Harris C, Allen K, Waller C, Brooke V. Sustainability in health care by allocating resources effectively (SHARE) 3: examining how resource allocation decisions are made, implemented and evaluated in a local healthcare setting. BMC Health Serv.Res. 2017 May 9;17(1):340. PMID: 28486953.

BACKGROUND:
This is the third in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Leaders in a large Australian health service planned to establish an organisation-wide, systematic, integrated, evidence-based approach to disinvestment. In order to introduce new systems and processes for disinvestment into existing decision-making infrastructure, we aimed to understand where, how and by whom resource allocation decisions were made, implemented and evaluated. We also sought the knowledge and experience of staff regarding previous disinvestment activities.
METHODS:
Structured interviews, workshops and document analysis were used to collect information from multiple sources in an environmental scan of decision-making systems and processes. Findings were synthesised using a theoretical framework.
RESULTS:
Sixty-eight respondents participated in interviews and workshops. Eight components in the process of resource allocation were identified: Governance, Administration, Stakeholder engagement, Resources, Decision-making, Implementation, Evaluation and, where appropriate, Reinvestment of savings. Elements of structure and practice for each component are described and a new framework was developed to capture the relationships between them. A range of decision-makers, decision-making settings, type and scope of decisions, criteria used, and strengths, weaknesses, barriers and enablers are outlined. The term 'disinvestment' was not used in health service decision-making. Previous projects that involved removal, reduction or restriction of current practices were driven by quality and safety issues, evidence-based practice or a need to find resource savings and not by initiatives where the primary aim was to disinvest. Measuring resource savings is difficult, in some situations impossible. Savings are often only theoretical as resources released may be utilised immediately by patients waiting for beds, clinic appointments or surgery. Decision-making systems and processes for resource allocation are more complex than assumed in previous studies.
CONCLUSION:
There is a wide range of decision-makers, settings, scope and type of decisions, and criteria used for allocating resources within a single institution. To our knowledge, this is the first paper to report this level of detail and to introduce eight components of the resource allocation process identified within a local health service.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423420/pdf/12913_2017_Article_2207.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2207-2.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28486953.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423420/.

Harris C, Allen K, Waller C, Dyer T, Brooke V, Garrubba M, Melder A, Voutier C, Gust A, Farjou D. Sustainability in Health care by Allocating Resources Effectively (SHARE) 7: supporting staff in evidence-based decision-making, implementation and evaluation in a local healthcare setting. BMC Health Serv.Res. 2017 Jun 21;17(1):430. PMID: 28637473.

BACKGROUND:
This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately.
METHODS:
Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes.
RESULTS:
Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed.
CONCLUSION:
Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research evidence and local findings. Local factors, some unanticipated and some unavoidable, were the main barriers to successful implementation. All three proposed support services hold promise as facilitators of EBP in the local healthcare setting. The findings from this study will inform further exploration.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480160/pdf/12913_2017_Article_2388.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2388-8.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28637473.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480160/.

Harris C, Allen K, Waller C, Green S, King R, Ramsey W, Kelly C, Thiagarajan M. Sustainability in Health care by Allocating Resources Effectively (SHARE) 5: developing a model for evidence-driven resource allocation in a local healthcare setting. BMC Health Serv.Res. 2017 May 10;17(1):342. PMID: 28486973.

BACKGROUND:
This is the fifth in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. This paper synthesises the findings from Phase One of the SHARE Program and presents a model to be implemented and evaluated in Phase Two. Monash Health, a large healthcare network in Melbourne Australia, sought to establish an organisation-wide systematic evidence-based program for disinvestment. In the absence of guidance from the literature, the Centre for Clinical Effectiveness, an in-house 'Evidence Based Practice Support Unit', was asked to explore concepts and practices related to disinvestment, consider the implications for a local health service and identify potential settings and methods for decision-making.
METHODS:
Mixed methods were used to capture the relevant information. These included literature reviews; online questionnaire, interviews and structured workshops with a range of stakeholders; and consultation with experts in disinvestment, health economics and health program evaluation. Using the principles of evidence-based change, the project team worked with health service staff, consumers and external experts to synthesise the findings from published literature and local research and develop proposals, frameworks and plans.
RESULTS:
Multiple influencing factors were extracted from these findings. The implications were both positive and negative and addressed aspects of the internal and external environments, human factors, empirical decision-making, and practical applications. These factors were considered in establishment of the new program; decisions reached through consultation with stakeholders were used to define four program components, their aims and objectives, relationships between components, principles that underpin the program, implementation and evaluation plans, and preconditions for success and sustainability. The components were Systems and processes, Disinvestment projects, Support services, and Program evaluation and research. A model for a systematic approach to evidence-based resource allocation in a local health service was developed.
CONCLUSION:
A robust evidence-based investigation of the research literature and local knowledge with a range of stakeholders resulted in rich information with strong consistent messages. At the completion of Phase One, synthesis of the findings enabled development of frameworks and plans and all preconditions for exploration of the four main aims in Phase Two were met.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424307/pdf/12913_2017_Article_2208.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2208-1.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28486973.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424307/.

Harris C, Green S, Ramsey W, Allen K, King R. Sustainability in Health care by allocating resources effectively (SHARE) 1: introducing a series of papers reporting an investigation of disinvestment in a local healthcare setting. BMC Health Serv.Res. 2017 May 4;17(1):323. PMID: 28472962.

This is the first in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE). The SHARE Program is an investigation of concepts, opportunities, methods and implications for evidence-based investment and disinvestment in health technologies and clinical practices in a local healthcare setting. The papers in this series are targeted at clinicians, managers, policy makers, health service researchers and implementation scientists working in this context. This paper presents an overview of the organisation-wide, systematic, integrated, evidence-based approach taken by one Australian healthcare network and provides an introduction and guide to the suite of papers reporting the experiences and outcomes.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5418706/pdf/12913_2017_Article_2210.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2210-7.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28472962.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5418706/.

Harris C, Ko H, Waller C, Sloss P, Williams P. Sustainability in health care by allocating resources effectively (SHARE) 4: exploring opportunities and methods for consumer engagement in resource allocation in a local healthcare setting. BMC Health Serv.Res. 2017 May 5;17(1):329. PMID: 28476155.

BACKGROUND:
This is the fourth in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Healthcare decision-makers have sought to improve the effectiveness and efficiency of services through removal or restriction of practices that are unsafe or of little benefit, often referred to as 'disinvestment'. A systematic, integrated, evidence-based program for disinvestment was being established within a large Australian health service network. Consumer engagement was acknowledged as integral to this process. This paper reports the process of developing a model to integrate consumer views and preferences into an organisation-wide approach to resource allocation.
METHODS:
A literature search was conducted and interviews and workshops were undertaken with health service consumers and staff. Findings were drafted into a model for consumer engagement in resource allocation which was workshopped and refined.
RESULTS:
Although consumer engagement is increasingly becoming a requirement of publicly-funded health services and documented in standards and policies, participation in organisational decision-making is not widespread. Several consistent messages for consumer engagement in this context emerged from the literature and consumer responses. Opportunities, settings and activities for consumer engagement through communication, consultation and participation were identified within the resource allocation process. Sources of information regarding consumer values and perspectives in publications and locally-collected data, and methods to use them in health service decision-making, were identified. A model bringing these elements together was developed.
CONCLUSION:
The proposed model presents potential opportunities and activities for consumer engagement in the context of resource allocation.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420096/pdf/12913_2017_Article_2212.pdf
DOI: http://dx.doi.org/10.1186/s12913-017-2212-5.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28476155.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420096/.

Hoffmann T, Glasziou P, Beller E, Goldacre B, Chalmers I. Focus on sharing individual patient data distracts from other ways of improving trial transparency. BMJ. 2017 Jun 22;357:j2782. PMID: 28642275.

[First paragraph]

The debate on sharing clinical trial data has been dominated by individual patient data. Tammy Hoffmann and colleagues argue that, although patient level data are important, a focus on the other simpler elements of trial transparency should be the first priority

DOI: http://dx.doi.org/10.1136/bmj.j2782.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28642275.

Ioannidis JP. Meta-Analyses Can Be Credible and Useful: A New Standard. JAMA Psychiatry. 2017 Apr 1;74(4):311-2. PMID: 28241194.

[First paragraph]

Carefully done meta-analyses constitute a major advance compared with expert opinion and nonsystematic attempts at summarizing, synthesizing, and integrating information. Meta-analyses serve many fields in summarizing an increasing stream of data and, for clinical purposes, streamlining information for decision making. However, there are flaws and caveats that threaten the validity and utility of meta-analyses.


DOI: http://dx.doi.org/10.1001/jamapsychiatry.2017.0035.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28241194.

Leopold SS, Swiontkowski M, Haddad F. Editorial: JBJS, The Bone & Joint Journal, and Clinical Orthopaedics and Related Research Require Prospective Registration of Randomized Clinical Trials-Why Is This Important? Clin.Orthop.Relat.Res. 2017 Jan;475(1):1-3. PMID: 27896675.

[First paragraph]

Randomized clinical trials (RCTs) represent the best study design for minimizing bias when investigating the effectiveness of a form of treatment. RCTs also are the building blocks of systematic reviews and meta-analyses, which allow more generalizable conclusions to be drawn about therapeutic efficacy [1], provided that the trials themselves are well-designed and implemented, and provided that all of the data are available for such analyses.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5174076/pdf/11999_2016_Article_5174.pdf
DOI: http://dx.doi.org/10.1007/s11999-016-5174-8.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27896675.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5174076/.

Petrini C, Alleva E. On transparency in health care guidelines. Editorial. Ann.Ist.Super.Sanita. 2017 Apr-Jun;53(2):91-2. PMID: 28617251.

[First paragraph]

The US Institute of Medicine (IOM) defines clinical practice guidelines as “statements that include recommendations intended to optimize patient care that are informed by a systematic review of evidence and an assessment of the benefits and harms of alternative care options” [1]. Health care guidelines and their appropriate implementation are of interest to health care providers, national health organizations, professional societies, policy-makers, patients and the public.

DOI: http://dx.doi.org/10.4415/ANN_17_02_01.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28617251.

Sheridan S, Schrandt S, Forsythe L, Hilliard TS, Paez KA, Advisory Panel on Patient Engagement (2013 inaugural panel). The PCORI Engagement Rubric: Promising Practices for Partnering in Research. Ann.Fam.Med. 2017 Mar;15(2):165-70. PMID: 28289118.

PURPOSE:
Engaging patients, caregivers, and other health care stakeholders as partners in planning, conducting, and disseminating research is a promising way to improve clinical decision making and outcomes. Many researchers, patients, and other stakeholders, however, lack clarity about when and how to engage as partners within the clinical research process. To address the need for guidance on creating meaningful stakeholder partnerships in patient-centered clinical comparative effectiveness research, the Patient-Centered Outcomes Research Institute (PCORI) developed the PCORI Engagement Rubric (Rubric).
METHODS:
PCORI developed the Rubric drawing from a synthesis of the literature, a qualitative study with patients, a targeted review of engagement plans from PCORI-funded project applications, and a moderated discussion and review with PCORI's Advisory Panel on Patient Engagement.
RESULTS:
The Rubric provides a framework for operationalizing engagement to incorporate patients and other stakeholders in all phases of research. It includes: principles of engagement; definitions of stakeholder types; key considerations for planning, conducting, and disseminating engaged research; potential engagement activities; and examples of promising practices from PCORI-funded projects.
CONCLUSIONS:
PCORI designed the Rubric to illustrate opportunities for engagement to researchers interested in applying for PCORI funding and to patients and other stakeholders interested in greater involvement in research. By encouraging PCORI applicants, awardees, and others to apply the rubric, PCORI hopes to shift the research paradigm from one of conducting research on patients as subjects to a pursuit carried out in collaboration with patients and other stakeholders to better reflect the values, preferences, and outcomes that matter to the patient community.
© 2017 Annals of Family Medicine, Inc.

FREE FULL TEXT: http://www.annfammed.org/content/15/2/165.long
DOI: http://dx.doi.org/10.1370/afm.2042.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/?term=28289118.

Singh KNM, Shetty YC. Data sharing: A viable resource for future. Perspect.Clin.Res. 2017 Apr-Jun;8(2):63-7. PMID: 28447015.

Clinical trials and research studies are being conducted worldwide at a rampant pace leading to generation of large amount of data. However, to reap the benefits of the data generated it is important that this data is shared with the general public without which it can be deemed useless. Despite its importance being known to us, data sharing does not come without its share of problems and it is not as easy to execute as it sounds on-paper. Over the past few years, multiple coveted organizations around the world involved in research activities have come up with their respective guidelines and initiatives to make sure the sharing of research data is smooth and ethical. Developing countries like India have made a few strides in the right direction with some initiatives in-place, but there still seems a long way to go before unanimous data sharing can be a reality. The stakeholders may have to face certain possible repercussions due to data sharing but there is no doubt that if done in the right way, it can lead to universal development.

FREE FULL TEXT: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384401/
DOI: http://dx.doi.org/10.4103/2229-3485.203036.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28447015.
PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384401/.

Song SY, Koo DH, Jung SY, Kang WK, Kim EY. The significance of the trial outcome was associated with publication rate and time to publication. J.Clin.Epidemiol. 2017 Apr;84:78-84. PMID: 28238789.

OBJECTIVES:
This study aims to comprehensively assess the publication of clinical trial results and factors associated with their publication.
STUDY DESIGN AND SETTING:
Phase II and III trials of advanced breast cancer registered on ClinicalTrials.gov between October 1, 2000, and September 30, 2012, were identified. Publications were searched by using PubMed and reviewing those listed on the registry site. The main outcomes were publication rate, public availability of results, and time to publication.
RESULTS:
Of 352 phase II and 74 phase III trials, 12.5% and 31.1% were published, whereas 46.9% and 58.1% had publicly available results, respectively. Compared to those with significant results, studies with nonsignificant results had delays in time to publication (P < 0.001). Even after adjusting for funding source and phase type, the significance of study outcomes was a significant factor that affected time to publication (hazard ratio = 6.02; 95% confidence interval: 3.59, 10.07; P < 0.001), with trials with significant outcomes taking less time to publish than those with nonsignificant outcomes.
CONCLUSION:
Underreporting of results and nonpublication or delays in the publication of negative results were identified in registered trials of advanced breast cancer. Thus, further initiatives appear necessary to urgently address such publication bias.
Copyright © 2017 Elsevier Inc. All rights reserved.

DOI: https://doi.org/10.1016/j.jclinepi.2017.02.009.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28238789.

Swift S, Rizk D, Lose G. Conflict of interest: what is it, and how do journals manage it in the publication process? Int.Urogynecol.J. 2017 Jul;28(7):969-70. PMID: 28547272.

[First paragraph]

Conflict of interest (COI) according to the World Association of Medical Editors (WAME) “…exists when there is a divergence between an individual’s private interests (competing interests) and his or her responsibilities to scientific and publishing activities such that a reasonable observer might wonder if the individual’s behavior or judgment was motivated by considerations of his or her competing interests” [1]. Most individuals think of COI in financial terms, but in fact, it has as much to do with an individual’s loyalty to a research concept, society, or clinical belief system as it does with any financial considerations. The WAME suggests that each journal have its own definition of COI and attempt to maintain a consistent policy in its publication process.

DOI: http://dx.doi.org/10.1007/s00192-017-3366-8.
PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28547272.