Inclusion of quasi-experimental studies in systematic reviews of health systems research. Digital Education in Health Professions: The Need for Overarching Evidence Synthesis An international registry of systematic-review protocols Reports of clinical trials should begin and end with up-to-date systematic reviews of other relevant evidence: a status report. Clinical research in implant dentistry: study design, reporting and outcome measurements: consensus report of Working Group 2 of the VIII European Workshop on Periodontology. Interventions to reduce dependency in personal activities of daily living in community-dwelling adults who use homecare services: protocol for a systematic review Interventions aimed at increasing research use in nursing: a systematic review Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review The use of systematic reviews in the planning, design and conduct of randomised trials: a retrospective cohort of NIHR HTA funded trials Evidence-based behavioral medicine: What is it and how do we achieve it? Getting to grips with Archie Cochrane's agenda. Systematic review of effectiveness of universal self-regulation-based interventions and their effects on distal health and social outcomes in children and adolescents: review protocol Comparative Effectiveness Research: A Report From the Institute of Medicine Protocol for an overview of systematic reviews of interventions to reduce unscheduled hospital admissions among adults Measures for assessing practice change in medical practitioners Strategies to Promote Physical Activity During Pregnancy Systematic reviews in public health: old chestnuts and new challenges. A systematic review and development of a classification framework for factors associated with missing patient-reported outcome data PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies Driving up the Quality and Relevance of Research Through the Use of Agreed Core Outcomes Towards systematic reviews that inform health care management and policy-making Methods of Randomized Controlled Clinical Trials in Health Services Research To RCT or not to RCT: deciding when ‘more evidence is needed’ for public health policy and practice
Systematic review s of health systems research commonly limit studies for evidence synthesis to r and omized controlled trials . However , well-conducted quasi-experimental studies can provide strong evidence for causal inference . With this article , we aim to stimulate and inform discussion s on including quasi-experiments in systematic review s of health systems research . We define quasi-experimental studies as those that estimate causal effect sizes using exogenous variation in the exposure of interest that is not directly controlled by the research er . We incorporate this definition into a non-hierarchical three-class taxonomy of study design s - experiments , quasi-experiments , and non-experiments . Based on a review of practice in three disciplines related to health systems research ( epidemiology , economics , and political science ) , we discuss five commonly used study design s that fit our definition of quasi-experiments : natural experiments , instrumental variable analyses , regression discontinuity analyses , interrupted times series studies , and difference studies including controlled before- and -after design s , difference-in-difference design s and fixed effects analyses of panel data . We further review current practice s regarding quasi-experimental studies in three non-health fields that utilize systematic review s ( education , development , and environment studies ) to inform the design of approaches for synthesizing quasi-experimental evidence in health systems research . Ultimately , the aim of any review is practical : to provide useful information for policymakers , practitioners , and research ers . Future work should focus on building a consensus among users and producers of systematic review s regarding the inclusion of quasi-experiments Synthesizing evidence from r and omized controlled trials of  digital health education  poses some challenges . These include a lack of clear categorization of digital health education in the literature ; constantly evolving concepts , pedagogies , or theories ; and a multitude of methods , features , technologies , or delivery setting s. The Digital Health Education Collaboration was established to evaluate the evidence on digital education in health professions ; inform policymakers , educators , and students ; and ultimately , change the way in which these professionals learn and are taught . The aim of this paper is to present the overarching methodology that we use to synthesize evidence across our digital health education review s and to discuss challenges related to the process . For our research , we followed Cochrane recommendations for the conduct of systematic review s ; all review s are reported according to the PRISMA ( Preferred Reporting Items for Systematic Review s and Meta-Analyses ) guidance . This included assembling experts in various digital health education fields ; identifying gaps in the evidence base ; formulating focused research questions , aims , and outcome measures ; choosing appropriate search terms and data bases ; defining inclusion and exclusion criteria ; running the search es jointly with librarians and information specialists ; managing abstract s ; retrieving full-text versions of papers ; extracting and storing large data sets , critically appraising the quality of studies ; analyzing data ; discussing findings ; drawing meaningful conclusions ; and drafting research papers . The approach used for synthesizing evidence from digital health education trials is commonly regarded as the most rigorous benchmark for conducting systematic review s. Although we acknowledge the presence of certain biases ingrained in the process , we have clearly highlighted and minimized those biases by strictly adhering to scientific rigor , method ological integrity , and st and ard operating procedures . This paper will be a valuable asset for research ers and method ologists undertaking systematic review s in digital health education Support for prospect i ve registration of protocol s for systematic review s has been gathering momentum . The PRISMA statement , a guideline for reporting systematic review s and meta-analyses of studies that evaluate health-care interventions , advocates registration . Well-conducted systematic review s are accepted as the best- quality evidence to inform policy and practice , and the dramatic upward trend in the number of systematic review s published annually ( fi gure ) is set to continue . However , there is currently no single facility for identifying this type of research in advance of the appearance of the results of the review . There is concern about and evidence of publication and selective outcome -reporting biases associated with systematic review s. An open registry of review s captured at the protocol stage would facilitate good practice in systematic review s by providing transparency of the review process and outcomes . Discrepancies between the methods of the published review and those planned in the registered protocol could be more readily identifi ed . Registration might also encourage full publication of the review ’s fi ndings and transparency in changes to methods that could bias fi ndings . In both the prevention and revelation of potential bias , registration should improve quality and increase confi dence that policy or practice informed by the fi ndings of systematic review s are indeed drawing on best- quality evidence . A registry of protocol s of systematic review s could assist those planning new review s and updating existing ones . Easy access to information about ongoing review s should help to optimise the use of fi nite re sources by enabling funding and commissioning agencies to avoid unnecessary duplication and encourage collaboration . A comprehensive registry could also create opportunities for method ological and other research , both within and across disciplines . Existing access to systematic - review protocol s is limited to the outputs of individual organisations , such as the Cochrane and Campbell Collaborations and the Joanna Briggs Institute . The National Public Health Service for Wales is piloting an All Wales Systematic Review s Register , but , up to now , there has been no central ised comprehensive registry of systematic - review protocol s. We are developing an international facility to register the details of ongoing systematic review s in health and social care . Our registry is being established with the existing platform and infrastructure that supports the Data base of Abstract s of Review s of Eff ects ( DARE ) , the NHS Economic Evaluations Data base ( NHS EED ) and the Health Technology Assessment ( HTA ) data base produced by the Centre for Review s and Dissemination . The initial scope of the registry will be limited to systematic review s of the eff ectiveness of health interventions . However , the longterm aim is for the registry to include details of all ongoing systematic review s with a health-related outcome in the broadest sense . Ultimately , inclusion will encompass systematic review s of health-care interventions , and review s of the social determinants of health , of service delivery , and of risk factors and genetic associations . Our web-based registry will off er free public access , be electronically search able , and open to all prospect i ve registrants . Registration will require the provision of a minimum data set , the completeness of which will be checked automatically before registration . After acceptance , the registry ’s entry and protocol for the review , if available , will be loaded on the data base as a permanent entry and a unique identifi cation number issued . An audit trail for any amendments to the information will be available within the record . Links to result ing publications will be added . These provisions ensure that the registry will match the relevant criteria required of clinical trials registries OBJECTIVE Scientific and ethical justification for new clinical trials requires them to have been design ed in the light of scientifically defensible assessment s of relevant previous research . Reliable interpretation of the results of new clinical trials entails setting them in the context of up date s of the review s upon which they were deemed scientifically and ethically justifiable . We have shown previously that most reports of r and omized trials published in five general medical journals in May 1997 and in May 2001 failed to set their results in the context of the findings from similar research . In the current study , we assess whether there had been progress in this respect in 2005 and also investigate the extent to which reports begin by referring to systematic review s providing the justification for the new research reported . DESIGN Assessment of the Introduction and Discussion sections in all reports of r and omized trials published during May 2005 in five general medical journals . SETTING Reports of r and omized trials in five general medical journals . PARTICIPANTS Annals of Internal Medicine , BMJ , JAMA , Lancet and New Engl and Journal of Medicine . INTERVENTIONS None . MAIN OUTCOME MEASURES The inclusion or mention of one or more systematic review s in the Introduction or Discussion section of each report assessed . RESULTS We found 18 reports of r and omized trials . The Introduction sections referred to systematic review s in five ( 27 % ) of these reports . None of the discussion sections of the 15 reports of trials that were not the first published trials to address the question studied placed the results of the new trial in the context of an up date d systematic review of other research . Although reference was made to relevant systematic review s in five of these 15 reports , there was no integration - quantitative or qualitative - of the results of the new trials in an up date of these review s. In the remaining ten reports there was no evidence that any systematic attempt had been made to set the new results in the context of previous trials . CONCLUSIONS There is no evidence of progress between 1997 and 2005 in the proportion of reports of trials published in general medical journals which discussed new results within the context of up-to- date systematic review s of relevant evidence from other controlled trials . Although the proportion of trials referring to systematic review s in Discussion sections has increased , the majority of reports continued to fail even to do this . Similarly , most research ers appear not to have considered a systematic review when design ing their trial . Research ers and journal editors do a disservice to the interests of the public and others involved in healthcare decision-making by acquiescing in this situation AIMS The objective of this working group was to assess and make specific recommendations to improve the quality of reporting of clinical research in implant dentistry and discuss ways to reach a consensus on choice of outcomes . MATERIAL AND METHODS Discussion s were informed by three systematic review s on quality of reporting of observational studies ( case series , case-control and cohort ) and experimental research ( r and omized clinical trials ) . An additional systematic review provided information on choice of outcomes and analytical methods . In addition , an open survey among all workshop participants was utilized to capture a consensus view on the limits of currently used survival and success-based outcomes as well as to identify domains that need to be captured by future outcome systems . RESULTS The Workshop attempted to clarify the characteristics and the value in dental implant research of different study design s. In most areas , measurable quality improvements over time were identified . The Workshop recognized important aspects that require continued attention by clinical research ers , funding agencies and peer review ers to decrease potential bias . With regard to choice of outcomes , the limitations of currently used systems were recognized . Three broad outcome domains that need to be captured by future research were identified : ( i ) patient reported outcome measures , ( ii ) peri-implant tissue health and ( iii ) performance of implant supported restorations . Peri-implant tissue health can be measured by marginal bone level changes and soft tissue inflammation and can be incorporated in time to event analyses . CONCLUSIONS The Workshop recommended that collaboration between clinicians and epidemiologists/ clinical trials specialists should be encouraged . Aspects of design aim ed at limitation of potential bias should receive attention by clinical research ers , funding agencies and journal editors . Adherence to appropriate reporting guidelines such as STROBE and CONSORT are necessary st and ards . Research on outcome measure domains is an area of top priority and should urgently inform a proper process leading to a consensus on outcome measures in dental implant research Background There is a growing dem and for services whereby individuals receive assistance from care workers for personal care within the home . This has led to the development of re-ablement or restorative homecare services that provide time-limited input aim ed at reducing dependency in personal activities of daily living , and preventing or delaying the need for further homecare support . However , little is currently known about how such interventions are configured , or how they may affect individuals ’ ability to carry out personal care independently . Methods / Design We will seek to identify studies that compare an intervention design ed to reduce dependency in personal activities of daily living with routine input or usual care as the control . We will include r and omised controlled trials , nonr and omised controlled trials , and controlled before and after studies . We will also include interrupted time series studies .We shall search electronic data bases in addition to search ing for ongoing and unpublished studies , and where appropriate will contact key authors . Two review ers will independently screen articles for inclusion ; will assess risk of bias using quality assessment tools ; and will carry out data extraction using pre-prepared forms . Any disagreements , at any stage , will be resolved by discussion and the involvement of a third review er if needed . We will produce a narrative summary of the results . A meta- analysis will be conducted if sufficient data are available of appropriate quality and comparability . Discussion The findings from this review will inform future practice within homecare re-ablement services ; will inform policy decisions about the structure , organisation and content of such services ; and will identify areas where further research is warranted . Systematic review registration This review protocol has been registered on the PROSPERO data base ( CRD42013004163 ) Background There has been considerable interest recently in developing and evaluating interventions to increase research use by clinicians . However , most work has focused on medical practice s ; and nursing is not well represented in existing systematic review s. The purpose of this article is to report findings from a systematic review of interventions aim ed at increasing research use in nursing . Objective To assess the evidence on interventions aim ed at increasing research use in nursing . Methods A systematic review of research use in nursing was conducted using data bases ( Medline , CINAHL , Healthstar , ERIC , Cochrane Central Register of Controlled Trials , and Psychinfo ) , grey literature , ancestry search ing ( Cochrane Data base of Systematic Review s ) , key informants , and manual search ing of journals . R and omized controlled trials and controlled before- and after- studies were included if they included nurses , if the intervention was explicitly aim ed at increasing research use or evidence -based practice , and if there was an explicit outcome to research use . Method ological quality was assessed using pre-existing tools . Data on interventions and outcomes were extracted and categorized using a pre-established taxonomy . Results Over 8,000 titles were screened . Three r and omized controlled trials and one controlled before- and after- study met the inclusion criteria . The method ological quality of included studies was generally low . Three investigators evaluated single interventions . The most common intervention was education . Investigators measured research use using a combination of surveys ( three studies ) and compliance with guidelines ( one study ) . Research er-led educational meetings were ineffective in two studies . Educational meetings led by a local opinion leader ( one study ) and the formation of multidisciplinary committees ( one study ) were both effective at increasing research use . Conclusion Little is known about how to increase research use in nursing , and the evidence to support or refute specific interventions is inconclusive . To advance the field , we recommend that investigators : ( 1 ) use theoretically informed interventions to increase research use , ( 2 ) measure research use longitudinally using theoretically informed and psychometrically sound measures of research use , as well as , measuring patient outcomes relevant to the intervention , and ( 3 ) use more robust and method ologically sound study design s to evaluate interventions . If investigators aim to establish a link between using research and improved patient outcomes they must first identify those interventions that are effective at increasing research use Background Computerized clinical decision support systems are information technology-based systems design ed to improve clinical decision-making . As with any healthcare intervention with cl aims to improve process of care or patient outcomes , decision support systems should be rigorously evaluated before widespread dissemination into clinical practice . Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake . The objective of this research was to form a partnership of healthcare providers , managers , and research ers to review r and omized controlled trials assessing the effects of computerized decision support for six clinical application areas : primary preventive care , therapeutic drug monitoring and dosing , drug prescribing , chronic disease management , diagnostic test ordering and interpretation , and acute care management ; and to identify study characteristics that predict benefit . Methods The review was undertaken by the Health Information Research Unit , McMaster University , in partnership with Hamilton Health Sciences , the Hamilton , Niagara , Haldim and , and Brant Local Health Integration Network , and pertinent healthcare service teams . Following agreement on information needs and interests with decision-makers , our earlier systematic review was up date d by search ing Medline , EMBASE , EBM Review data bases , and Inspec , and review ing reference lists through 6 January 2010 . Data extraction items were exp and ed according to input from decision-makers . Authors of primary studies were contacted to confirm data and to provide additional information . Eligible trials were organized according to clinical area of application . We included r and omized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a  computerized clinical decision support system compared with patient care without such a system . Results Data will be summarized using descriptive summary measures , including proportions for categorical variables and means for continuous variables . Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates . When reporting results from individual studies , we will cite the measures of association and p-values reported in the studies . If appropriate for groups of studies with similar features , we will conduct meta-analyses . Conclusion A decision-maker- research er partnership provides a model for systematic review s that may foster knowledge translation and uptake Background A systematic review , with or without a meta- analysis , should be undertaken to determine if the research question of interest has already been answered before a new trial begins . There has been limited research on how systematic review s are used within the design of new trials , the aims of this study were to investigate how systematic review s of earlier trials are used in the planning and design of new r and omised trials . Methods Documentation from the application process for all r and omised trials funded by the National Institute for Health Research Health Technology Assessment ( NIHR HTA ) between 2006 and 2008 were obtained . This included the : commissioning brief ( if appropriate ) , outline application , minutes of the Board meeting in which the outline application was discussed , full application , detailed project description , referee comments , investigator response to referee comments , Board minutes on the full application and the trial protocol . Data were extracted on references to systematic review s and how any such review s had been used in the planning and design of the trial . Results 50 r and omised trials were funded by NIHR HTA during this period and documentation was available for 48 of these . The cohort was predominately individually r and omised parallel trials aim ing to detect superiority between two treatments for a single primary outcome . 37 trials ( 77.1 % ) referenced a systematic review within the application and 20 of these ( i.e. 41.7 % of the total ) used information contained in the systematic review in the design or planning of the new trial . The main areas in which systematic review s were used were in the selection or definition of an outcome to be measured in the trial ( 7 of 37 , 18.9 % ) , the sample size calculation ( 7 , 18.9 % ) , the duration of follow up ( 8 , 21.6 % ) and the approach to describing adverse events ( 9 , 24.3 % ) . Boards did not comment on the presence/absence or use of systematic review s in any application . Conclusions Systematic review s were referenced in most funded applications but just over half of these used the review to inform the design . There is an expectation from funders that applicants will use a systematic review to justify the need for a new trial but no expectation regarding further use of a systematic review to aid planning and design of the trial . Guidelines for applicants and funders should be developed to promote the use of systematic review s in the design and planning of r and omised trials , to optimise delivery of new studies informed by the most up-to- date evidence base and to minimise waste in research The goal of evidence -based medicine is ultimately to improve patient outcomes and quality of care .  Systematic review s of the available published evidence are required to identify interventions that lead to improvements in behavior , health , and well-being . Authoritative literature review s depend on the quality of published research and research reports . The Consoli date d St and ards for Reporting Trials ( CONSORT ) Statement ( www.consort-statement.org ) was developed to improve the design and reporting of interventions involving r and omized clinical trials ( RCTs ) in medical journals . We describe the 22 CONSORT guidelines and explain their application to behavioral medicine research and to evidence -based practice . Additional behavioral medicine-specific guidelines ( e.g. , treatment adherence ) are also presented . Use of these guidelines by clinicians , educators , policymakers , and research ers who design , report , and evaluate or review RCTs will strengthen the research itself and accelerate efforts to apply behavioral medicine research to improve the processes and outcomes of behavioral medicine practice s is likely to be particularly useful . 8 The problem of unpublished or incompletely published trials remains difficult . A prerequisite for any solution is that the widespread practice of underreporting the results of well conducted trials should be seen for what it is-namely , scientific misconduct.'9 Clearly , the resolution of the problem ofunderreporting lies mainly in the h and s ofinvestigators and those who fund and enable their research . 12 - 14 20 If research ers , funding bodies , and research ethics committees are to take properly informed decisions about proposals for new research they need both the results of systematic review s and information about trials that are currently recruiting patients . In this way , inadvertent and unnecessary duplication of research ( as distinct from planned and appropriate replication ) can be reduced . Reasonably complete ascertainment of all trials seems likely only through some form of m and atory registration of studies at the time they are started.2'22 Although several registries exist,2425 most remain incomplete because they depend on voluntary notification . Funding agencies and ethics committees should require the registration and publication of trials that they have supported and approved . Encouraging signs exist in several countries ofan interest in establishing systems for registering r and omised controlled trials at their inception , and there is certainly scope for collaboration.25 Within Britain the information systems strategy being developed by the NHS 's research and development programme , the registration of cancer trials fostered by the United Kingdom Coordinating Committee for Cancer Research , and the Medical Research Council 's inventory of controlled trials together provide a useful basis for developing systems to ensure that information about current r and omised controlled trials is assembled more efficiently . As Archie Cochrane pointed out many years ago , failing to conduct systematic , up to date review s of controlled trials of health care may result in substantial adverse consequencesfor patients , practitioners , the health services , research ers , and research funding bodies . Reliable and informative review s depend on identifying as many relevant studies as possible . Achieving this should be possible by registering trials at their inception , minimising underreporting of trials , improving descriptions of research methods in reports of trials , and better indexing in data bases of completed and current research . IAIN Background Growing evidence suggests that childhood and adolescence self-regulation contributes to multiple health , educational and social outcomes . Considering the potential impact of self-regulation skills on improved life chances in conjunction with evidence suggesting that self-regulation can be modified by interventions , there is a need to identify interventions which are most effective in improving childhood and adolescence self-regulation . The present systematic review was design ed to determine the effectiveness of universal interventions focused on enhancing the  self-regulation of children and adolescents . As secondary outcomes , we will also examine the effectiveness of such interventions on distal health and social outcomes . Methods Eligible studies include r and omised controlled trials ( including cluster r and omised trials ) reporting on universal interventions design ed to improve self-regulation in childhood and adolescence ( age 0–19 years ) . The following data bases will be search ed for peer- review ed publications using an iterative search strategy : Medline , PsycINFO , EMBASE , ERIC , CINAHL Plus , British Education Index , Child Development & Adolescent Studies and CENTRAL without applying language or date filters . Additionally , reference lists and citations of included studies will be search ed for eligible studies . A 10 % proportion of the total titles and abstract s will be r and omly selected and screened independently by two review ers ( AP and DH ) . Results will be compared to ensure less than 5 % discrepancy , followed by screening of all results by one review er ( AP ) . Full-text review and data collection will be independently performed by two review ers . Any discrepancies will be solved by mutual discussion , and if unresolved , a third review er ( RV ) will be consulted . Meta- analysis will be conducted to quantify trial effects , if the data is sufficiently homogenous to allow quantitative synthesis . Otherwise , results will be described narratively . Discussion The evidence derived from the systematic review will strengthen the evidence base to inform planning of effective interventions targeting self-regulation skills in childhood and adolescence . This will benefit policy makers , academicians , research ers , health professionals , and also , young people who will benefit from policy and interventions informed by this review . Systematic review registration CRD42016047661 Join the dialogue on health care reform . Comment on the perspectives published in Annals and offer ideas of your own . All thoughtful voices should be heard . On 30 June 2009 , another milestone was achieved in progress toward a national system to promote medical research that focuses on decision making by physicians and patients . The first steps occurred in late 2007 and early 2008 with a seminal article ( 1 ) and an Institute of Medicine ( IOM ) report that called for a national initiative of research that would support better decision making about interventions in health care ( 2 ) . One of us was a coeditor of the IOM report . A third milestone was reached when both presidential c and i date s endorsed this concept . A fourth milestone came when the president signed into law the American Recovery and Reinvestment Act of 2009 ( ARRA ) ; this act allotted $ 1.1 billion to support this form of research , which had become known as comparative effectiveness research ( CER ) . The legislation created a federal council on CER and asked the IOM to elicit input from a broad array of stakeholders on which research topics should have the highest-priority for funding through the ARRA and to then develop a list of the highest-priority topics for the Secretary of Health and Human Services to consider . By law , the Federal Coordinating Council and the IOM committee to set priorities for comparative effectiveness research reported to the Secretary on 30 June 2009 . This issue contains both this article , which is a commentary on the IOM committee report ( 3 ) by the committee 's cochairs , and a perspective on better research methods for CER ( 4 ) . Definition of CER The IOM committee quickly settled on a working definition of CER , which consisted of the elements of earlier definitions reduced to 2 sentences : CER is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent , diagnose , treat and monitor a clinical condition , or to improve the delivery of care . The purpose of CER is to assist consumers , clinicians , purchasers , and policy makers to make informed decisions that will improve health care at both the individual and population levels . Two key elements that are embedded in this definition are the direct comparison of effective interventions and their study in patients who are typical of day-to-day clinical care . These features would ensure that the research would provide information that decision makers need to know , as would a third feature , research design ed to identify the clinical characteristics that predict which intervention would be most successful in an individual patient . The same research design would also help policymakers by identifying sub population s of patients that are more likely to benefit from one intervention than the other . High-Priority Research Topics The IOM committee sought advice from a broad range of stakeholders and received it in 3 forms : approximately 90 letters ; 54 oral presentations at a day-long hearing in Washington , DC ; and a Web-based nomination form . Overall , the committee received more than 2606 nominations from 1758 individual responders within 3 weeks . In a 3-step voting process , the committee identified 100 high-priority topics , which it ranked in quartiles . At each stage , the committee sought to have a balanced portfolio of topics . Table 5 - 1 in the report ( available at www.iom.edu/cerpriorities ) lists the 100 highest-ranked topics . Establishing a Sustainable National Program of CER The U.S. Congress is currently debating legislation that would guarantee health insurance to more Americans while reforming the U.S. health system . A key aim of the legislation is to moderate the rate at which the cost of health care increases while improving the quality of care . Many leaders believe that reaching this goal will require a sustained effort to produce better evidence to inform decision making . Government officials have characterized the $ 1.1 billion allocated to CER as a down payment on a national program of CER . As of this writing , the House of Representatives bill proposes a national program of CER , and the Senate Finance Committee white paper does likewise . Accordingly , the IOM committee made several recommendations aim ed at a sustainable , trustworthy national CER initiative . The Appendix provides the full text of these recommendations . Governance The 2008 IOM committee recommended establishing a national program with authority , overarching responsibility , sustained re sources , and adequate capacity to ensure production of credible , unbiased information about what is known and what is not known about clinical effectiveness ( 2 ) . The current committee exp and ed this recommendation by calling upon the secretary of the Department of Health and Human Services to establish a mechanismsuch as a coordinating advisory bodywith the authority to strategize , organize , monitor , evaluate , and report on the implementation and impact of the CER Program . The committee recognized that many agencies of the federal government are engaged in research that fits some or all of the key elements of CER . To make the best use of the funds allocated for CER , these agencies should be jointly accountable for spending CER funds on research that reflects the same conceptualization of CER . Therefore , these disparate efforts should use a single definition of CER and the same definitions of outcomes and measures of function and illness . This form of cross-agency coordination is compatible with each agency focusing on the form of research with which it has the greatest experience . Active Involvement of Consumers in CER The 2009 ARRA created a means for coordinating federal CER efforts : the Federal Coordinating Council . Seeking to complement the functions of the Council , the IOM committee focused on the potential contribution of consumers of health care to CER and recommended involving them at all levels of the national CER initiative . The recommendation is as follows : The CER Program should fully involve consumers , patients and their caregivers in key aspects of CER , including strategic planning , priority setting , research proposal development , peer review , and dissemination . The concept that animates this recommendation is a radical but logical departure from past practice : When a principal aim of research is to inform decision makers , listen to the decision makers . Meaningful participation will require consumers to learn more about research , just as they will teach research ers about how to frame their investigations to satisfy the needs of consumers who are also decision makers . This approach has precedent . For example , the National Institute for Health and Clinical Effectiveness in the United Kingdom teaches decision making to consumers who participate in the institute 's program . Methodology of CER Remembering that the purpose of CER is to inform decision making , consider the principal forms of clinical research . Systematic review s of the literature summarize a body of evidence . Over the past 2 decades , they have become indispensable to expert panels that formulate practice guidelines or policymakers who make insurance coverage decisions . These macro decision makers are starting to use decision models for the same purpose s ( 5 ) . Two broad categories of research are the starting point for systematic review s : observational research and r and omized trials . Large established data bases provide an opportunity to link current health care practice s to the outcome of care . These data bases are representative of critical groups often omitted from r and omized trials , but they contain limited data ; of note , they seldom specify the rationale for medical decisions . These observational research methods have many advantagesspeed , real-world decisions , large numbers of decisions and outcomes , and low costbut they can not escape a key limitation : Characteristics of the patient that drive real-life clinical decisions may also influence clinical outcomes , leading to uncertainty about whether they or the intervention itself causes the outcomes . Overcoming the limitations of observational research is the most important frontier of research on study methods . To overcome these limitations , research ers often r and omly assign patients to different interventions . This simple action eliminates much of the uncertainty that plagues the interpretation of observational research . However , we have too often used the conceptual elegance of r and omization to answer the wrong questions . We ask , Does this work ? when our readers want to know , Is this better than that ? Thus , too often , r and omized trials are so-called efficacy studies : They are design ed to create near-ideal circumstances to see whether the intervention can possibly work . To this end , research ers exclude many types of patients from efficacy trials and often compare the intervention with a placebo . In these respects , efficacy trials are unlike the conditions that physicians and patients face in daily practice . Another article in this issue ( 4 ) describes several exciting new methods for making r and omized trials more suitable for CER . The examples of observational research and new r and omized trial methods are the basis for the IOM committee 's strong recommendation that a national CER program should support research in the methods of clinical research . The Infrastructure for Observational Research The committee believes that very large collection s of the electronic records of patients can be a valuable re source for CER . Using these data sets , it is possible to compare the outcomes of using several effective interventions in a population that is representative of daily care , 2 features that are aligned with the goals of CER . The great numbers of patients in these data sets also makes it possible to study subgroups with precision and perhaps identify key predictors of response to an intervention , both of which would facilitate decision making at the individual and population Introduction Unscheduled hospital admissions are an increasing burden on health systems worldwide . To date , initiatives to reduce admissions have had limited success as it is unclear which strategies effectively reduce admissions and are supported by a strong evidence -base . Therefore , we will conduct an overview to find , assess and summarise all published peer- review ed systematic review s of r and omised controlled trials that examine the effect of an intervention on  unplanned admissions among adults . Methods and analysis This is a protocol for a systematic overview of review s. We will search four data bases : Ovid MEDLINE , PubMed , Cochrane Data base of Systematic Review s and the Cochrane Data base of Abstract s of Review s of Effects . We will consider systematic review s and meta-analyses of r and omised controlled trials in adults ( ≥16 years old ) evaluating the effect of any intervention on unscheduled hospital admissions including those to treat , monitor , diagnose or prevent a health problem . We will only include review s that identified unscheduled hospitalisations as a prespecified outcome . Two authors will independently screen articles for inclusion using a priori criteria . We will assess the quality of included review s and extract ratings of the quality of evidence from within each review . We will create a hierarchical list of interventions based on estimates of absolute admission reductions and the quality of the evidence . Presentation of results will align with guidelines in the Cochrane H and book of Systematic Review s of Interventions and the Preferred Reporting Items for Systematic Review s and Meta- Analysis statement . Ethics and dissemination Ethics approval is not required . We will su bmi t the results of this study for peer- review publication . The results will inform future research and could be used by healthcare managers , administrators and policymakers to guide re source allocation decisions and inform local implementation and optimisation of interventions to reduce unscheduled hospital admissions Background There are increasing numbers of r and omised trials and systematic review s examining the efficacy of interventions design ed to bring about a change in clinical practice . The findings of this research are being used to guide strategies to increase the uptake of evidence into clinical practice . Knowledge of the outcomes measured by these trials is vital not only for the interpretation and application of the work done to date , but also to inform future research in this exp and ing area of endeavour and to assist in collation of results in systematic review s and meta-analyses . Methods The objective of this review was to identify methods used to measure change in the clinical practice s of health professionals following an intervention aim ed at increasing the uptake of evidence into practice . All published trials included in a recent , comprehensive Health Technology Assessment of interventions to implement clinical practice guidelines and change clinical practice ( n = 228 ) formed the sample for this study . Using a st and ardised data extraction form , one review er ( SH ) , extracted the relevant information from the methods and /or results sections of the trials . Results Measures of a change of health practitioner behaviour were the most common , with 88.8 % of trials using these as outcome measures . Measures that assessed change at a patient level , either actual measures of change or surrogate measures of change , were used in 28.8 % and 36.7 % of studies ( respectively ) . Health practitioners ' knowledge and attitudes were assessed in 22.8 % of the studies and changes at an organisational level were assessed in 17.6 % . Conclusion Most trials of interventions aim ed at changing clinical practice measured the effect of the intervention at the level of the practitioner , i.e. did the practitioner change what they do , or has their knowledge of and /or attitude toward that practice changed ? Less than one-third of the trials measured , whether or not any change in practice , result ed in a change in the ultimate end-point of patient health status Physical activity during pregnancy has been associated with significant health benefits ; however , most women in the United States do not meet the current guidelines . This systematic review evaluates evidence for interventions to improve physical activity during pregnancy in order to identify best practice s and inform future research . Electronic data bases ( PubMed , CINAHL , SportD ISCUS , Embase , ERIC , Psych Info , and ISI Web of Science ) were search ed in July 2011 for peer- review ed journal articles . Studies were included if they were English- language r and omized control trials that measured the efficacy of an intervention targeted at pregnant women and were design ed to change physical activity as a primary or secondary outcome . Out of 777 studies identified through the systematic search , 9 interventions were selected for inclusion by multiple review ers . Data were abstract ed using an abstract ion form modeled after the “ Guide to Community Preventive Services . ” Of the 9 interventions included in the review , 3 reported statistically significant positive results for physical activity . Although the interventions included a variety of strategies and techniques , none were uniquely associated with positive outcomes . Overall , this review suggests that little is known about the efficacy of interventions for physical activity during pregnancy . This study provides several recommendations for future research and intervention design The Bulletin ’s editorial team has decided to encourage systematic review s. This is an important decision and is to be welcomed . However it is possible that it will not be received positively by all . Some may feel that systematic review s are not suitable for answering wider public health questions , and that the new section will simply result in the publication of systematic review s addressing narrowly focused , clinical questions with a focus on r and omized controlled trials alone.1 There is no reason why this should be so , and there are far too many examples of systematic review s of non- clinical interventions ( including government policies ) , which include non-r and omized studies , to list.2 Systematic review s of qualitative research are also becoming more common.3 Nonetheless misconceptions about the scope and flexibility of systematic review s still surface occasionally and it never fails to surprise me when I stumble across one of these hoary old chestnuts . If it really were true that systematic review s were only for simple , individual-level interventions , systematic review ers working in public health would be very concerned . After all , public health problems require us to draw on complex sets of qualitative as well as quantitative evidence ; and some policy interventions have never been subjected to r and omized controlled trials ( RCTs ) but have been evaluated using other approaches ; everything from controlled and uncontrolled before- and -after studies , to time series analyses , to qualitative methods . In such cases , systematic review s that focused on RCTs alone would have little to say and we would end up producing many “ empty review s ” , which contain no studies at all . These would be undoubtedly quicker to do and quicker to read than the typical systematic review , but would be of limited use for making policy . However this is not the case . In public health we already have a wealth of review s that prioritize RCTs where they are available , but which draw upon a range of other evidence where they are appropriate to answering the review question .2 Take , as an example , transport policies , an important social determinant of health.4 Public health decision-makers have been interested in the effects on health of building new roads for decades , but there has never been a r and omized controlled trial , for obvious reasons . Yet it would make no sense to cl aim that there is no evidence to be review ed ; rather , there have been many controlled and uncontrolled studies that have examined the effects of new roads on respiratory symptoms , injuries , community severance , disturbance and a variety of other outcomes of public health importance . These studies have in fact been systematic ally review ed.5 Many other examples of review s of complex interventions that impact on public health could be given , which appear on the Cochrane Data base and elsewhere,6,7 and such review s are the main focus of the recently-established Cochrane Public Health Review Group . It is also worth noting that both the Cochrane and Campbell Collaboration include increasing numbers of review s that are relevant to low- and middle- income countries,8 though there is a particular need for more systematic review s that consider the effects on equity of the interventions that they include.9 Currently systematic review s have a “ utilitarian bias ” – they tend to be concerned more with the effects on population s and average effects than with distributional effects and impacts in disadvantaged subgroups . It is to be hoped that systematic review s su bmi tted to the Bulletin will routinely consider the effects of interventions on health inequities . The Cochrane Health Equity Field ( http://equity.cochrane.org/en/index.html ) was set up explicitly to further this agenda , to encourage systematic review authors to explicitly assess the effects of interventions not only on the whole population , but on the disadvantaged . So where does this leave non- systematic review s ? Should every review be a systematic review ? This is a difficult question to answer in a short editorial . My own view is that not all review s need to be systematic review s ; there is still a place for review papers that provide a broad overview , and that discuss a range of evidence and make a contribution to wider debates about what might work in particular setting s. However , while such discussion s help place evidence in context and suggest how it may be used , they should not be confused with the evidence -based conclusions of a transparent , scientific review , which systematic ally attempts to find all the relevant evidence , appraises its strengths and limitations in a transparent fashion , and draws that evidence together in such a way that the more robust studies are given greater weight . Finally , the challenges are many . Evidence on interventions to improve public health is in short supply , particularly evidence on social determinants . Systematic review ers therefore face a real challenge in making best use of the sometimes poor , often sparse and usually heterogeneous evidence available to them . It is easy to set narrow inclusion criteria for a review and then sift through the evidence before concluding that there is n’t enough – and what there is , is n’t very good anyway . Such “ evidential nihilism ” is probably not helpful to decision-makers , and public health systematic review ers need to continue to develop new methods and better frameworks within which different types of research evidence can be integrated to inform decision-making . Publishing systematic review s in the Bulletin should give an added impetus to this ongoing work . Background / aims : Missing patient-reported outcome data can lead to biased results , to loss of power to detect between-treatment differences , and to research waste . Awareness of factors may help research ers reduce missing patient-reported outcome data through study design and trial processes . The aim was to construct a Classification Framework of factors associated with missing patient-reported outcome data in the context of comparative studies . The first step in this process was informed by a systematic review . Methods : Two data bases ( MEDLINE and CINAHL ) were search ed from inception to March 2015 for English articles . Inclusion criteria were ( a ) relevant to patient-reported outcomes , ( b ) discussed missing data or compliance in prospect i ve medical studies , and ( c ) examined predictors or causes of missing data , including reasons identified in actual trial data sets and reported on cover sheets . Two review ers independently screened titles and abstract s. Discrepancies were discussed with the research team prior to finalizing the list of eligible papers . In completing the systematic review , four particular challenges to synthesizing the extracted information were identified . To address these challenges , operational principles were established by consensus to guide the development of the Classification Framework . Results : A total of 6027 records were screened . In all , 100 papers were eligible and included in the review . Of these , 57 % focused on cancer , 23 % did not specify disease , and 20 % reported for patients with a variety of non-cancer conditions . In total , 40 % of the papers offered a descriptive analysis of possible factors associated with missing data , but some papers used other methods . In total , 663 excerpts of text ( units ) , each describing a factor associated with missing patient-reported outcome data , were extracted verbatim . Redundant units were identified and sequestered . Similar units were grouped , and an iterative process of consensus among the investigators was used to reduce these units to a list of factors that met the guiding principles . The list was organized on a framework , using an iterative consensus-based process . The result ant Classification Framework is a summary of the factors associated with missing patient-reported outcome data described in the literature . It consists of 5 components ( instrument , participant , centre , staff , and study ) and 46 categories , each with one or more sub-categories or examples . Conclusion : A systematic review of the literature revealed 46 unique categories of factors associated with missing patient-reported outcome data , organized into 5 main component groups . The Classification Framework may assist research ers to improve the design of new r and omized clinical trials and to implement procedures to reduce missing patient-reported outcome data . Further research using the Classification Framework to inform quantitative analyses of missing patient-reported outcome data in existing clinical trials and to inform qualitative inquiry of research staff is planned Prediction relates to estimating the probability of something currently unknown . In the context of medical research , prediction typically concerns either diagnosis ( probability of a certain condition being present but not yet detected ) or prognosis ( probability of an outcome developing in the future ) ( 13 ) . Prognosis applies not only to sick persons or those with an established diagnosis but also to , for example , pregnant women at risk for diabetes ( 4 ) . Prediction research includes predictor finding studies , prediction model studies ( development , validation , and extending or updating ) , and prediction model impact studies ( 1 ) . Predictor finding studies ( also known as risk factor or prognostic factor studies ) aim to identify which predictors ( such as age , disease stage , or biomarkers ) independently contribute to the prediction of a diagnostic or prognostic outcome ( 1 , 5 ) . Prediction model studies aim to develop , vali date , or up date ( for example , extend ) a multivariable prediction model . A prediction model uses multiple predictors in combination to estimate probabilities to inform and often guide individual care ( 2 , 6 , 7 ) . These models can predict an individual 's probability of either currently having a particular outcome or disease ( diagnostic prediction model ) or having a particular outcome in the future ( prognostic prediction model ) . Both types of model are widely used in various medical domains and setting s ( 810 ) , as evidence d by the large number of models developed in cancer ( 11 , 12 ) , neurology ( 13 , 14 ) , and cardiovascular disease ( 15 ) . Prediction models are sometimes described as  risk prediction models , predictive models , prediction indices or rules , or risk scores ( 2 , 7 ) . An example is QRISK2 for predicting cardiovascular risk ( 16 ) . Prediction model impact studies evaluate the effect of using a model to guide patient care compared with not using such a model . They use a comparative design , such as a r and omized trial , to study the model 's effect on clinical decision making , patient outcomes , or costs of care ( 1 ) . Systematic review s have a key role in evidence -based medicine and the development of clinical guidelines ( 1719 ) . They are considered to provide the most reliable form of evidence for the effects of an intervention or diagnostic test ( 20 , 21 ) . Systematic review s of prediction models are a relatively new and evolving area but are increasingly undertaken to systematic ally identify , appraise , and summarize evidence on the performance of prediction models ( 1 , 6 , 22 ) . Assessing the quality of included studies is a crucial step in any systematic review ( 20 , 21 ) . The QUIPS ( Quality In Prognosis Studies ) tool has been developed to assess risk of bias ( ROB ) in predictor finding ( prognostic factor ) studies ( 23 ) . Research ers can use the revised Cochrane ROB Tool ( ROB 2.0 ) ( 24 ) to investigate the method ological quality of prediction model impact studies that use a r and omized comparative design , or ROBINS-I ( Risk Of Bias In Nonr and omized Studies of Interventions ) for those that use a nonr and omized comparative design ( 25 ) . As more prediction model studies and systematic review s of such studies are used as evidence for clinical guidance , a tool facilitating quality assessment for individual prediction model studies is urgently needed . We present PROBAST ( Prediction model Risk Of Bias ASsessment Tool ) , a tool to assess the ROB and concerns regarding the applicability of diagnostic and prognostic prediction model studies . PROBAST can be used to assess studies of model development and model validation , including those updating a prediction model ( Box 1 [ 26 ] ) . We refer to the accompanying explanation and elaboration document ( 27 ) , for detailed explanations of how to use PROBAST and how to judge ROB and applicability . Box 1 . Types of diagnostic and prognostic modeling studies or reports addressed by PROBAST . Adopted from the TRIPOD ( Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis ) and CHARMS ( CHecklist for critical Appraisal and data extraction for systematic Review s of prediction Modelling Studies ) guidance ( 7 , 26 ) . PROBAST = Prediction model Risk Of Bias ASsessment Tool . Methods : Development of PROBAST Development of PROBAST was based on a 4-stage approach for developing health research reporting guidelines : define the scope , review the evidence base , use a Web-based Delphi procedure , and refine the tool through piloting ( 28 ) . Guidelines explicitly aim ed at the development of quality assessment tools were not available at the time ( 29 ) . Development Stage 1 : Scope and Definitions A steering group of 9 experts in prediction model studies and development of quality assessment tools agreed on key features of the desired scope of PROBAST . A panel of 38 experts with different background s further refined the scope during the Web-based Delphi procedure . PROBAST was design ed mainly to assess primary studies included in a systematic review . The group agreed that PROBAST would assess both risk of bias and concerns regarding applicability of a study evaluating a multivariable prediction model to be used for individualized diagnosis or prognosis . A domain-based structure was adopted , similar to that used in other ROB tools , such as ROB 2.0 ( 24 ) , ROBINS-I ( 25 ) , QUADAS-2 ( Quality Assessment of Diagnostic Accuracy Studies 2 ) ( 30 ) , and ROBIS ( 31 ) . We agreed that PROBAST should cover primary studies that develop , vali date , or up date multivariable prediction models aim ing to make individualized predictions of a diagnostic or prognostic outcome ( Box 1 ) . Studies that use multivariable modeling techniques to identify predictors ( such as risk or prognostic factors ) associated with an outcome but do not attempt to develop , vali date , or up date a model for making individualized predictions are not covered by PROBAST ( 5 ) . Therefore , PROBAST is not intended for predictor finding studies or prediction model impact studies . Studies of diagnostic and prognostic models often use different terms for predictors and outcomes ( Box 2 ) . A multivariable prediction model is defined as any combination or equation of 2 or more predictors for estimating probability or risk for an individual ( 6 , 7 , 3234 ) . Box 2 . Differences between diagnostic and prognostic prediction model studies . PROBAST = Prediction model Risk Of Bias ASsessment Tool . Development Stage 2 : Review of Evidence We used the following 3 approaches to build an evidence base to inform the development of PROBAST : identifying relevant method ological review s in the area of prediction model research ( November 2012 to January 2013 ) , asking members of the steering group to identify relevant method ological studies ( January 2013 to March 2013 ) , and using the Delphi procedure to ask members of the wider group to identify additional evidence ( February 2012 to July 2014 ) . Identified literature was used to guide the scope and produce an initial list of signaling questions to consider for inclusion in PROBAST ( 1 , 2 , 57 , 26 , 3340 ) . We grouped signaling questions into common themes to identify possible domains . Additional literature provided as part of the Web-based surveys informed development of the explanation and elaboration document . Development Stage 3 : Web-Based Delphi Procedure We used a modified Delphi process to gain feedback and agreement on the scope , structure , and content of PROBAST . Web-based surveys were developed to gather structured feedback for each round . The 38-member Delphi group comprised method ological experts in prediction model research and development of quality assessment tools , experienced systematic review ers , commissioners , and representatives of reimbursement agencies . We included various stakeholders to ensure that the views of end users , method ological experts , and decision makers were represented . The Delphi process consisted of 7 rounds . Round 1 asked about the scope of the tool , and participants agreed to focus on prediction model studies and follow a domain-based structure . Round 2 aim ed to identify relevant domains and agree on which to include . The signaling questions for domains were refined in rounds 3 to 5 . Respondents used a 1-to-5 Likert scale to rate each proposed signaling question for inclusion . They could also suggest rephrasing , provide supporting evidence ( such as references to relevant studies ) , and suggest missing signaling questions . Round 6 refined the domains and introduced further optional guidance for using PROBAST . In the last round , participants received the agreed draft version of PROBAST and had the opportunity to provide any final feedback . Development Stage 4 : Piloting and Refining the Tool We held 6 workshops on PROBAST at consecutive annual Cochrane Colloquia ( Quebec , Canada , 2013 ; Hyderabad , India , 2014 ; Vienna , Austria , 2015 ; Seoul , South Korea , 2016 ; Cape Town , South Africa , 2017 ; and Edinburgh , United Kingdom , 2018 ) . We also held numerous consecutive workshops with MSc and PhD students ( for example , the master 's program in epidemiology at Utrecht University [ Utrecht , the Netherl and s ] and the Evidence -Based Health Care program at Oxford University [ Oxford , United Kingdom ] ) . In these workshops , we piloted the then-current version of PROBAST to gather feedback on practical issues associated with using the tool so that we could further refine and subsequently vali date it . Finally , more than 50 review groups have already piloted PROBAST versions , including the final version , in their review s. Topics included cancer , cardiology , endocrinology , pulmonology , and orthopedics . All feedback received from these initiatives was used to further inform the content and structure of PROBAST , wording of the signaling questions , and content of the guidance documents ( 27 ) . Results : The PROBAST Tool What Does PROBAST Assess ? PROBAST assesses both risk of bias and concerns regarding applicability of primary studies that developed or vali date d multivariable prediction models for diagnosis or prognosis ( Boxes 1 and 2 ) There is a growing recognition that insufficient attention has been paid to the selection of the outcomes to measure in clinical trials and clinical audit . Outcomes need to be relevant to patients , clinicians , purchasers and policy-makers if the findings of research are to influence practice and future research . In addition , st and ardization of outcomes is needed to combine data from different studies to allow evidence synthesis and to compare data sets . Inconsistent choice of outcome measures means that many meta-analyses are unable to include data from all the relevant studies . For example , the five most accessed Cochrane review s in 2009 , together with the top cited review in that year , all described inconsistencies in the outcomes reported in eligible trials . A call for the st and ardization of outcomes is a regular conclusion of systematic review s. Furthermore , outcome reporting bias , defined as the bias arising from selecting outcomes for publication based on the results , affects many r and omized trials and ‘ is an under-recognized problem that affects the conclusions in a substantial proportion of Cochrane review s ’ . That bias is likely to affect systematic review s more widely as well as affecting individual studies when considered on their own . Similar problems occur with clinical audit , highlighting the importance of establishing national audits that use and report the same outcomes for all participants . All these issues could be addressed with the development and application of agreed st and ardized sets of outcomes that have been termed ‘ core outcome sets ’ . These should be measured and reported , as a minimum , in all relevant clinical trials and national clinical audits for a specific condition . Adopting a core outcome set does not imply that a particular study , review or audit should be restricted to only those outcomes . Rather , the expectation is that , as a minimum , core outcomes will always be collected and reported to allow the results of trials to be compared , contrasted and combined as appropriate . The adoption of core outcomes would have implication s across all areas of research in health and health care , reduce heterogeneity between trials , and lead to research that is more likely to have measured relevant outcomes . Importantly , they would enhance the value of evidence synthesis by reducing the risk of outcome reporting bias and ensuring that all trials contribute usable information . In addition , they will increase the efficiency and value of research . An important rationale for core outcome sets is that outcomes currently reported for trials do not consistently reflect endpoints that are meaningful for patients . Examples exist where trials failed to include all outcomes important to patients and where involvement of patients has identified an outcome that might not have been considered by practitioners on their own . Despite increasing recognition of the importance of incorporating patients ’ opinions , their involvement has been limited . Recent regulatory guidance in the USA requires documented evidence of patient input during the development of instruments to measure  patient reported outcomes ( PROs ) . However , measurement of PROs in clinical trials is hampered by the multiplicity and heterogeneity of tools currently available . Many generic , disease and domain-specific instruments have been developed and vali date d , each containing multiple scales and items . As a result , synthesis of PRO data from trials is difficult and review s aim ing to summarize treatment effect according to PROs may fail . There is synergy between the development of core outcome sets for trials and work to select up to seven outcomes that are important to patients for inclusion in Summary of Findings tables in systematic review s. Developed by the GRADE group ( http://www . grade workinggroup.org ) , Cochrane review s have featured such tables since 2008 , and they play a key role in presenting research in guidelines , such as those produced by the World Health Organization ( WHO ) . The development of core outcome sets needs to be accelerated and undertaken in ways that maximize efficiency . The COMET ( Core Outcome Measures in Effectiveness Trials , http://www.comet-initiative.org ) Initiative in the UK brings together research ers interested in the development and application of core outcome sets . These include key participants in a collaboration of research ers in rheumatology who have done the most notable work to date in this area . The COMET Initiative was launched in January 2010 , with a second meeting in July 2011 . Attendees included trialists , systematic review ers , patients , clinicians , journal editors , research funders , policy-makers , people responsible for trials registries and regulators . Data on individual studies , both published and ongoing , are being included in a free , publically available internet-based re source . This will be up date d periodically , to minimize the risk of duplication . Seventy-eight published or ongoing studies have already been entered into the repository . In addition , published review s of outcomes used in clinical trials or studies examining patients ’ views , will be entered Objectives To identify ways to improve the usefulness of systematic review s for health care managers and policy-makers that could then be evaluated prospect ively . Methods We systematic ally review ed studies of decision-making by health care managers and policy-makers , conducted interviews with a purposive sample of them in Canada and the United Kingdom ( n=29 ) , and review ed the websites of research funders , producers/purveyors of research , and journals that include them among their target audiences ( n=45 ) . Results Our systematic review identified that factors such as interactions between research ers and health care policy-makers and timing/timeliness appear to increase the prospect s for research use among policy-makers . Our interviews with health care managers and policy-makers suggest that they would benefit from having information that is relevant for decisions highlighted for them ( e.g. context ual factors that affect a review 's local applicability and information about the benefits , harms/risks and costs of interventions ) and having review s presented in a way that allows for rapid scanning for relevance and then grade d entry ( such as one page of take-home messages , a three-page executive summary and a 25-page report ) . Managers and policy-makers have mixed views about the helpfulness of recommendations . Our analysis of websites found that context ual factors were rarely highlighted , recommendations were often provided and grade d entry formats were rarely used . Conclusions Research ers could help to ensure that the future flow of systematic review s will better inform health care management and policy-making by involving health care managers and policy-makers in their production and better highlighting information that is relevant for decisions . Research funders could help to ensure that the global stock of systematic review s will better inform health care management and policy-making by supporting and evaluating local adaptation processes such as developing and making available online more user-friendly ‘ front ends ’ for potentially relevant systematic review The r and omized controlled clinical trial is an increasingly used method in health services research . Analysis of methodology is needed to accelerate practical implementation of trial results , select trials for meta- analysis , and improve trial quality in health services research . The objectives of this study are to explore the methodology of health services research  trials , create and vali date a streamlined quality evaluation tool , and identify frequent quality defects and confounding effects on quality . The authors developed a quality question naire that contained 20 evaluation criteria for health services research trials . One hundred one trials from the Columbia Registry of Controlled Clinical Trials were evaluated using the new quality tool . The overall agreement between independent review ers , Cohen 's kappa , was 0.94 ( ±0.01 ) . Of a possible score of 100 , the trials received an average score of 54.8 ( ±12.5 ) . Five evaluation criteria indicated significant quality deficiencies ( sample size , description of case selection , data on possible adverse effects , analysis of secondary effect variables , and retrospective analysis ) . The quality of study characteristics was significantly weaker than the quality of reporting characteristics ( P < 0.001 ) . The total average scores of Medline -indexed journals were better than the non- Medline -indexed journals ( P < 0.001 ) . There was a positive correlation between the overall quality and year of publication ( R = 0.21 , P < 0.05 ) . The authors conclude that the new quality evaluation tool leads to replicable results and there is an urgent need to improve several study characteristics of clinical trials . In comparison to drug trials , site selection , r and omization , and blinding often require different approaches in health services research Background Amid the calls for ‘ more public health evidence ’ , we also need simple underst and able methods of determining when more research really is needed . This paper describes a simple decision aid to help policymakers , research ers and other decision makers assess the potential ‘ information value ’ of a new public health r and omised controlled trial . Methods The authors developed a flow chart to help make explicit ( 1 ) the user 's information needs , ( 2 ) the intended use of the new information that the study will produce , ( 3 ) the added value of the evidence to be derived from the new study and ( 4 ) the levels of precision , bias and generalisability required by the user . Results The flow chart is briefly illustrated , first in generic form and then in a worked example , showing how it may be used in deciding whether a new study should be commissioned to evaluate the health impact of allowing motorcycles to use bus lanes in London . Conclusions In this paper , the authors have presented a flow chart for enacting an informal ‘ Value-of-Information’-like approach to deciding when a new public health evaluation is needed . The authors do not suggest that the flow chart approach is technically the equivalent of Value-of-Information methods . Nonetheless , it represents a valuable perspective and process to adopt , and this structured approach will be more revealing than an unstructured thought experiment as the basis for decisions about a new study . To aid in its development as an effective tool , we invite users from a variety of perspectives and context s to review it , to use it in practice and to send us their comments
No single vali date d outcome measure encompassed all potential patient benefits from using a CGS .
A variety of different domains were identified , including anxiety and depression , coping , decision-making , distress , family environment , health status , knowledge , mood , perception of risk , perceived personal control , psychological impact , quality of life , satisfaction and expectations , self-esteem , spiritual well-being , and worry .
Some important aspects of patient benefit from CGS are not covered by existing outcome measures .
OBJECTIVE This systematic review aim ed to inform research ers and policymakers about what vali date d outcome measures are available to evaluate clinical genetics services ( CGS ) and the need for new measures .