34
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE)

      other

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In pharmacoepidemiology, routinely collected data from electronic health records (including primary care databases, registries, and administrative healthcare claims) are a resource for research evaluating the real world effectiveness and safety of medicines. Currently available guidelines for the reporting of research using non-randomised, routinely collected data—specifically the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) and the Strengthening the Reporting of OBservational studies in Epidemiology (STROBE) statements—do not capture the complexity of pharmacoepidemiological research. We have therefore extended the RECORD statement to include reporting guidelines specific to pharmacoepidemiological research (RECORD-PE). This article includes the RECORD-PE checklist (also available on www.record-statement.org) and explains each checklist item with examples of good reporting. We anticipate that increasing use of the RECORD-PE guidelines by researchers and endorsement and adherence by journal editors will improve the standards of reporting of pharmacoepidemiological research undertaken using routinely collected data. This improved transparency will benefit the research community, patient care, and ultimately improve public health.

          Related collections

          Most cited references56

          • Record: found
          • Abstract: found
          • Article: not found

          High-dimensional propensity score adjustment in studies of treatment effects using health care claims data.

          Adjusting for large numbers of covariates ascertained from patients' health care claims data may improve control of confounding, as these variables may collectively be proxies for unobserved factors. Here, we develop and test an algorithm that empirically identifies candidate covariates, prioritizes covariates, and integrates them into a propensity-score-based confounder adjustment model. We developed a multistep algorithm to implement high-dimensional proxy adjustment in claims data. Steps include (1) identifying data dimensions, eg, diagnoses, procedures, and medications; (2) empirically identifying candidate covariates; (3) assessing recurrence of codes; (4) prioritizing covariates; (5) selecting covariates for adjustment; (6) estimating the exposure propensity score; and (7) estimating an outcome model. This algorithm was tested in Medicare claims data, including a study on the effect of Cox-2 inhibitors on reduced gastric toxicity compared with nonselective nonsteroidal anti-inflammatory drugs (NSAIDs). In a population of 49,653 new users of Cox-2 inhibitors or nonselective NSAIDs, a crude relative risk (RR) for upper GI toxicity (RR = 1.09 [95% confidence interval = 0.91-1.30]) was initially observed. Adjusting for 15 predefined covariates resulted in a possible gastroprotective effect (0.94 [0.78-1.12]). A gastroprotective effect became stronger when adjusting for an additional 500 algorithm-derived covariates (0.88 [0.73-1.06]). Results of a study on the effect of statin on reduced mortality were similar. Using the algorithm adjustment confirmed a null finding between influenza vaccination and hip fracture (1.02 [0.85-1.21]). In typical pharmacoepidemiologic studies, the proposed high-dimensional propensity score resulted in improved effect estimates compared with adjustment limited to predefined covariates, when benchmarked against results expected from randomized trials.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Increasing value and reducing waste in biomedical research: who's listening?

            The biomedical research complex has been estimated to consume almost a quarter of a trillion US dollars every year. Unfortunately, evidence suggests that a high proportion of this sum is avoidably wasted. In 2014, The Lancet published a series of five reviews showing how dividends from the investment in research might be increased from the relevance and priorities of the questions being asked, to how the research is designed, conducted, and reported. 17 recommendations were addressed to five main stakeholders-funders, regulators, journals, academic institutions, and researchers. This Review provides some initial observations on the possible effects of the Series, which seems to have provoked several important discussions and is on the agendas of several key players. Some examples of individual initiatives show ways to reduce waste and increase value in biomedical research. This momentum will probably move strongly across stakeholder groups, if collaborative relationships evolve between key players; further important work is needed to increase research value. A forthcoming meeting in Edinburgh, UK, will provide an initial forum within which to foster the collaboration needed.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Stroke, Bleeding, and Mortality Risks in Elderly Medicare Beneficiaries Treated With Dabigatran or Rivaroxaban for Nonvalvular Atrial Fibrillation.

              Dabigatran and rivaroxaban are non-vitamin K oral anticoagulants approved for stroke prevention in patients with nonvalvular atrial fibrillation (AF). There are no randomized head-to-head comparisons of these drugs for stroke, bleeding, or mortality outcomes.
                Bookmark

                Author and article information

                Contributors
                Role: associate professor
                Role: registrar
                Role: assistant professor
                Role: professor
                Role: postdoctoral fellow
                Role: assistant professor
                Role: professor
                Role: professor
                Role: professor
                Role: professor
                Role: senior scientist
                Role: associate professor
                Role: senior scientist
                Role: professor
                Role: professor
                Role: professor
                Role: associate professor
                Role: codirector
                Role: assistant professor
                Role: associate professor and senior scientist
                Journal
                BMJ
                BMJ
                BMJ-UK
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2018
                14 November 2018
                : 363
                : k3532
                Affiliations
                [1 ]Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
                [2 ]Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark
                [3 ]Ottawa Hospital Research Institute, Ottawa, ON, Canada;
                [4 ]School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
                [5 ]Departments of Medicine and of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada
                [6 ]Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
                [7 ]Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands
                [8 ]Department of Primary Care and Population Health, University College London, London, UK
                [9 ]Arthritis Research UK Centre for Epidemiology, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
                [10 ]Institute for Clinical Evaluative Sciences, Toronto, ON, Canada
                [11 ]Hospital for Sick Children, Department of Paediatrics, University of Toronto, Toronto, ON, Canada
                [12 ]ICH Population, Policy, and Practice Programme, University College London, Great Ormond Street Institute of Child Health, London, UK
                [13 ]Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
                [14 ]Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
                [15 ]Julius Global Health, University Medical Center Utrecht, Utrecht, Netherlands
                [16 ]Cochrane Switzerland, Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland
                [17 ]Department of Pediatrics and School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
                [18 ]Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
                Author notes
                Correspondence to: S M Langan sinead.langan@ 123456lshtm.ac.uk
                Article
                lans044971
                10.1136/bmj.k3532
                6234471
                30429167
                bc153e97-6bff-46da-b179-4c4c7549cefe
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 July 2018
                Categories
                Research Methods & Reporting

                Medicine
                Medicine

                Comments

                Comment on this article

                scite_

                Similar content332

                Cited by168

                Most referenced authors1,416