DOCSLIB.ORG

Diagnostic Downshift’: Clinical and System Consequences of Extrapolating Secondary Care Testing Tactics to Primary Care

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Diagnostic Downshift’: Clinical and System Consequences of Extrapolating Secondary Care Testing Tactics to Primary Care EBM analysis BMJ EBM: first published as 10.1136/bmjebm-2020-111629 on 7 June 2021. Downloaded from ‘Diagnostic downshift’: clinical and system consequences of extrapolating secondary care testing tactics to primary care Imran Mohammed Sajid ,1,2 Kathleen Frost,3 Ash K Paul4 10.1136/bmjebm-2020-111629 ABSTRACT Several drivers push specialist diagnostic Numerous drivers push specialist diagnostic approaches down to the broader primary care layer of a health system, which we describe as ‘diag- 1NHS West London Clinical approaches down to primary care (‘diagnostic Commissioning Group, downshift’), intuitively welcomed by clinicians nostic downshift’. Aspirations for earlier disease London, UK and patients. However, primary care’s different detection or capacity pressures in specialist and 2University of Global Health population and processes result in under- cancer pathways underlie shifting of tests from Equity, Kigali, Rwanda recognised, unintended consequences. Testing high- cost hospital settings to primary care. Such 3 NHS Central London Clinical performs poorer in primary care, with indication assumptions have led to procurement and growth Commissioning Group, creep due to earlier, more undifferentiated of GP diagnostics, with unfettered direct access to London, UK presentation and reduced accuracy due to physiology tests, endoscopy, ultrasound, MRI, CT, 4NHS South West London spectrum bias and the ‘false-positive paradox’. and biochemical and immunological tests, often Health and Care Partnership only evaluated in secondary care. It is increasingly STP, London, UK In low- prevalence settings, tests without near- 100% specificity have their useful yield eclipsed expected, sometimes mandated, for GPs to perform by greater incidental or false- positive findings. secondary care- based testing strategies prior to Correspondence to: Ensuing cascades and multiplier effects can referral. Earlier diagnostics are presumed to accel- Dr Imran Mohammed Sajid, generate clinician workload, patient anxiety, erate patient journeys (eg, decision-making at NHS West London Clinical further low- value tests, referrals, treatments and first outpatient appointment) or reduce referrals (NHS). Protected by copyright. Commissioning Group, a potentially nocebic population ‘disease’ burden by empowering GPs. However, diagnostic growth, London, London, UK; 1 of unclear benefit. Increased diagnostics earlier in heavily cited for low- value overuse, has unin- imransajid@ nhs. net pathways can burden patients and stretch general tended consequences. In the COVID-19 pandemic practice (GP) workloads, inducing downstream context, reduced hospital access and increasing service utilisation and unintended ‘market virtual consultations may proliferate community failure’ effects. Evidence is tenuous for reducing testing. http://ebm.bmj.com/ secondary care referrals, providing patient Clinicians intuitively welcome tests, bolstering reassurance or meaningfully improving clinical autonomy and professional confidence, while outcomes. Subsequently, inflated investment in playing into patients’ biases. Medical risks should per capita testing, at a lower level in a healthcare be discussed, yet test inaccuracy and cascades system, may deliver diminishing or even negative go unrecognised,2 while clinicians poorly inter- economic returns. Test cost poorly represents pret results.3 4 Tests can guide management, but ‘value’, neglecting under- recognised downstream also generate anxiety, low- value disease labels, on June 14, 2021 at GPs and Practice Staff in London, Kent & Surrey consequences, which must be balanced against fear avoidance behaviours, further investigations, therapeutic yield. With lower positive predictive referrals and treatment cascades of little benefit.5–7 values, more tests are required per true diagnosis Consider vitamin D, recommended only in select and cost- effectiveness is rarely robust. With patients, now ubiquitously screened, with almost fixed secondary care capacity, novel primary 100- fold increases, reflecting massive costs, time care testing is an added cost pressure, rarely and prescribing of spurious value.8 reducing hospital activity. GP testing strategies require real-world evaluation, in primary care populations, of all downstream consequences. Testing in primary care is different from Test formularies should be scrutinised in view of secondary care the setting of care, with interventions to focus Tests are integral to primary care, with overlapping rational testing towards those with higher pretest symptoms between benign and serious conditions © Author(s) (or their probabilities, while improving interpretation and and uncertainty in up to 40% of consultations.9 employer(s)) 2021. No communication of results. However, secondary care has different populations, commercial re- use. See workflows and expertise; thus, diagnostic tactics rights and permissions. should not be blindly extrapolated. General prac- Published by BMJ. tice performs a technical but also wider psycho- To cite: Sajid IM, Frost K, social role for non-specific presentations, with a Paul AK. BMJ Evidence- Introduction more person- orientated, than pathophysiology- Based Medicine Epub ahead Are more tests, earlier in pathways, within primary orientated focus.10 While uncertainty management of print: [please include Day care helpful? While welcomed by clinicians, depends on psychological factors,11 12 there tends Month Year]. doi:10.1136/ patients and policymakers, we explore under- to be diminishing decision- making value from bmjebm-2020-111629 recognised consequences. additional tests.13 BMJ Evidence- Based Medicine Month 2021 | volume 0 | number 0 | 1 EBM analysis BMJ EBM: first published as 10.1136/bmjebm-2020-111629 on 7 June 2021. Downloaded from Diagnostic downshift’s pretest considerations (table 1) include patients.17–19 Systematic review shows little to no high- quality inflated (inappropriate) tests per capita, test indication creep and evidence of clinical or cost benefits to support increasing tests in inadvertent screening. Suspicion to trigger a test will typically be primary or community settings, with only low-quality evidence of lower than that for a referral. Thus, more patients are tested than reducing referrals, suggesting such diagnostic strategies may be otherwise referred. Post- test dynamics (table 2) include altered more politically motivated.20 performance (false- positive paradox and spectrum bias) with lower positive predictive values, greater false- positive rates, a burden of Earlier testing does not necessarily improve cancer incidental findings, misinterpretation problems (particularly for outcomes serial testing), limited reassurance and ‘multiplier effects’ of low- Rhetoric around cancer detection system delays often drives diag- value cascades. nostic expansion.21 22 However, there is a paucity of evidence that Diagnostic sensitivity trades off against specificity. Compared advanced GP testing improves outcomes (survival rate statistics with secondary care encounters, GPs do not require imme- are misleading due to lead time, length bias or overdiagnosis of diate high- sensitivity testing tactics, as patients can be referred indolent disease). Impact of ‘delayed diagnosis’ is mixed, including onwards for evaluation, as well as readily reattend for persisting the so-called ‘waiting- time- paradox’ (‘delay’ associated with or worsening symptoms. Test specificity is more critical to manage improved outcome for some cancers).23–25 Diagnostic strategy, referral appropriateness. In low-prevalence settings, without near- particularly for low- but- not- no- risk presentations, is complex. 100% specificity, benefit (diagnostic yield) is eclipsed by greater Systematic review of GP direct access testing suggests, although false- positives or incidental findings (see table 2). With pretest time- to- test may improve, there is no change in time- to- diagnosis probability <10% (common for primary care), even with 90% or outcomes.26 Novel pathway triage may enable prehospital specificity, Bayesian analysis shows greater false- positives than diagnostics, although it has its own drawbacks; in ‘straight-to- true- positives, with positive predictive value no better than a coin test’ pathways, alternate diagnostics may have been preferred toss. For example, carotid artery ultrasound screening, with 92% by specialists.27 Furthermore, pre- referral laboratory cancer tests specificity, across 100 000 patients, generates 7920 false- positives are broadly unreliable, including many biomarkers.28 Without versus only 940 true- positives.14 evidence, novel technologies should be cautioned, considering High-quality studies rarely demonstrate benefit from already pressured workloads. (NHS). Protected by copyright. advanced testing in primary care Outside of low- income countries, there is little evidence to suggest increased diagnostic direct access resolves the problem of Despite disseminated use in different populations, for wider indica- misdiagnosis in primary care, which is due to a myriad of factors, tions, traditionally specialist tests are rarely robustly evaluated in including cognitive reasoning errors.29 30 primary care, reliant on haphazard postmarket surveillance, such as audits. Referral reduction is often based on self- report without capturing downstream utilisation and typically lacks usual care Expansive testing in primary care creates a population comparator analysis. The few randomised controlled trials, such ‘disease’ burden of unclear
Load more

Recommended publications
  • Prior Belief Innuences on Reasoning and Judgment: a Multivariate Investigation of Individual Differences in Belief Bias
    Prior Belief Innuences on Reasoning and Judgment: A Multivariate Investigation of Individual Differences in Belief Bias Walter Cabral Sa A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Education University of Toronto O Copyright by Walter C.Si5 1999 National Library Bibliothèque nationaIe of Canada du Canada Acquisitions and Acquisitions et Bibliographic Services services bibliographiques 395 Wellington Street 395, rue WePington Ottawa ON K1A ON4 Ottawa ON KtA ON4 Canada Canada Your file Votre rëfërence Our fi& Notre réterence The author has granted a non- L'auteur a accordé une licence non exclusive Licence allowing the exclusive permettant à la National Libraq of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microforni, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/film, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor subçtantial extracts fi-om it Ni la thèse ni des extraits substantiels may be printed or otherwise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. Prior Belief Influences on Reasoning and Judgment: A Multivariate Investigation of Individual Differences in Belief Bias Doctor of Philosophy, 1999 Walter Cabral Sa Graduate Department of Education University of Toronto Belief bias occurs when reasoning or judgments are found to be overly infiuenced by prior belief at the expense of a normatively prescribed accommodation of dl the relevant data.
    [Show full text]
  • Thinking and Reasoning
    Thinking and Reasoning Thinking and Reasoning ■ An introduction to the psychology of reason, judgment and decision making Ken Manktelow First published 2012 British Library Cataloguing in Publication by Psychology Press Data 27 Church Road, Hove, East Sussex BN3 2FA A catalogue record for this book is available from the British Library Simultaneously published in the USA and Canada Library of Congress Cataloging in Publication by Psychology Press Data 711 Third Avenue, New York, NY 10017 Manktelow, K. I., 1952– Thinking and reasoning : an introduction [www.psypress.com] to the psychology of reason, Psychology Press is an imprint of the Taylor & judgment and decision making / Ken Francis Group, an informa business Manktelow. p. cm. © 2012 Psychology Press Includes bibliographical references and Typeset in Century Old Style and Futura by index. Refi neCatch Ltd, Bungay, Suffolk 1. Reasoning (Psychology) Cover design by Andrew Ward 2. Thought and thinking. 3. Cognition. 4. Decision making. All rights reserved. No part of this book may I. Title. be reprinted or reproduced or utilised in any BF442.M354 2012 form or by any electronic, mechanical, or 153.4'2--dc23 other means, now known or hereafter invented, including photocopying and 2011031284 recording, or in any information storage or retrieval system, without permission in writing ISBN: 978-1-84169-740-6 (hbk) from the publishers. ISBN: 978-1-84169-741-3 (pbk) Trademark notice : Product or corporate ISBN: 978-0-203-11546-6 (ebk) names may be trademarks or registered trademarks, and are used
    [Show full text]
  • Fixing Biases: Principles of Cognitive De-Biasing
    Fixing biases: Principles of cognitive de-biasing Pat Croskerry MD, PhD Clinical Reasoning in Medical Education National Science Learning Centre, University of York Workshop, November 26, 2019 Case q A 65 year old female presents to the ED with a complaint of shoulder sprain. She said she was gardening this morning and injured her shoulder pushing her lawn mower. q At triage she has normal vital signs and in no distress. The triage nurse notes her complaint and triages her to the fast track area. q She is seen by an emergency physician who notes her complaint and examines her shoulder. He orders an X-ray. q The shoulder X ray shows narrowing of the joint and signs of osteoarthrtritis q He discharges her with a sling and Rx for Arthrotec q She is brought to the ED 4 hours later following an episode of syncope, sweating, and weakness. She is diagnosed with an inferior MI. Biases q A 65 year old female presents to the ED with a complaint of ‘shoulder sprain’. She said she was gardening this morning and sprained her shoulder pushing her lawn mower (Framing). q At triage she has normal vital signs and in no distress. The triage nurse notes her complaint and triages her to the fast track area (Triage cueing). q She is seen by an emergency physician who notes her complaint and examines her shoulder. He orders an X-ray (Ascertainment bias). q The shoulder X ray shows narrowing of the joint and signs of osteoarthrtritis. He explains to the patient the cause of her pain (Confirmation bias).
    [Show full text]
  • Bias Miguel Delgado-Rodrı´Guez, Javier Llorca
    635 J Epidemiol Community Health: first published as 10.1136/jech.2003.008466 on 13 July 2004. Downloaded from GLOSSARY Bias Miguel Delgado-Rodrı´guez, Javier Llorca ............................................................................................................................... J Epidemiol Community Health 2004;58:635–641. doi: 10.1136/jech.2003.008466 The concept of bias is the lack of internal validity or Ahlbom keep confounding apart from biases in the statistical analysis as it typically occurs when incorrect assessment of the association between an the actual study base differs from the ‘‘ideal’’ exposure and an effect in the target population in which the study base, in which there is no association statistic estimated has an expectation that does not equal between different determinants of an effect. The same idea can be found in Maclure and the true value. Biases can be classified by the research Schneeweiss.5 stage in which they occur or by the direction of change in a In this glossary definitions of the most com- estimate. The most important biases are those produced in mon biases (we have not been exhaustive in defining all the existing biases) are given within the definition and selection of the study population, data the simple classification by Kleinbaum et al.2 We collection, and the association between different have added a point for biases produced in a trial determinants of an effect in the population. A definition of in the execution of the intervention. Biases in data interpretation, writing, and citing will not the most common biases occurring in these stages is given. be discussed (see for a description of them by ..........................................................................
    [Show full text]
  • Systematic Reviews of Diagnostic Test Accuracy
    Systematic reviews of diagnostic test accuracy Karen R Steingart, MD, MPH July 10, 2014 [email protected] Conflicts of interest • Editor Cochrane Infectious Diseases Group • Editor Cochrane Diagnostic Test Accuracy Working Group • Member GRADE Working Group • No financial interests to declare Overview • Describe key steps in a systematic review of diagnostic test accuracy • Describe standard methods for meta-analysis of diagnostic test accuracy • Describe resources for those who consider doing a systematic review of diagnostic test accuracy Overview of reviews A systematic review starts with a clearly formulated question and uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyse data from the studies that are included in the review Egg slide adapted from Madhu Pai Why systematic reviews? • Scientific summary of all available evidence • Transparent and reproducible • Minimize bias • Studies can be formally compared to establish generalizability and consistency • Heterogeneity can be identified and investigated • Meta-analyses may increase the precision of the overall results J Reitsma, Cochrane DTA Workshop, Amsterdam, Sept 2011 Why systematic reviews? Standards for systematic reviews - 21 standards (~ 80 elements of performance) US Institute of Medicine - 80 standards for conducting - 108 standards for reporting The Cochrane Collaboration Selected Elements, Protocols and Reviews of Diagnostic Test Accuracy, Chapter 4, Handbook Systematic review author Diagnostic
    [Show full text]
  • Can Psychology Become a Science?
    Personality and Individual Differences 49 (2010) 281–288 Contents lists available at ScienceDirect Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid Can psychology become a science? Scott O. Lilienfeld Department of Psychology, Emory University, Room 473, 36 Eagle Row, Atlanta 30322, Georgia article info abstract Article history: I am profoundly grateful to Tom Bouchard for helping me learn to think scientifically. Scientific thinking, Received 3 December 2009 which is characterized by a set of safeguards against confirmation bias, does not come naturally to the Received in revised form 16 January 2010 human species, as the relatively recent appearance of science in history attests. Even today, scientific Accepted 25 January 2010 thinking is in woefully short supply in many domains of psychology, including clinical psychology and Available online 23 February 2010 cognate disciplines. I survey five key threats to scientific psychology – (a) political correctness, (b) radical environmentalism, (c) the resurrection of ‘‘common sense” and intuition as arbiters of scientific truth, Keywords: (d) postmodernism, and (e) pseudoscience – and conclude that these threats must be confronted directly Psychology by psychological science. I propose a set of educational and institutional reforms that should place Science Pseudoscience psychology on firmer scientific footing. Postmodernism Ó 2010 Elsevier Ltd. All rights reserved. Psychotherapy 1. Can psychology become a science? groups, they would need to possess above zero validity for at least one subgroup. When I entered graduate school in psychology at the University Of course, a naïve graduate student can perhaps be forgiven for of Minnesota in the Fall of 1982, I was a bright-eyed, bushy-tailed such logical errors, especially one embarking on his training nearly 21 year-old eager to learn about the mysteries of the mind.
    [Show full text]
  • Preregistration: a Pragmatic Tool to Reduce Bias and Calibrate Confidence in Scientific Research
    PERSPECTIVE Preregistration: A pragmatic tool to reduce bias and calibrate confidence in scientific research Tom E. Hardwicke* & Eric-Jan Wagenmakers# Department of Psychology, University of Amsterdam Scientific research is performed by fallible humans. Degrees of freedom in the construction and selection of evidence and hypotheses grant scientists considerable latitude to obtain study outcomes that align more with their preferences than is warranted. This creates a risk of bias and can lead to scientists fooling themselves and fooling others. Preregistration involves archiving study information (e.g., hypotheses, methods, and analyses) in a public registry before data are inspected. This offers two potential benefits: (1) reduce bias by ensuring that research decisions are made independently of study outcomes; and (2) calibrate confidence in research by transparently communicating information about a study’s risk of bias. In this article, we briefly review the historical evolution of preregistration in medicine, psychology, and other domains, clarify its pragmatic functions, discuss relevant meta-research, and provide recommendations for scientists and journal editors. * [email protected] ORCID: 0000-0001-9485-4952 # [email protected] ORCID: 0000-0003-1596-1034 “The mind lingers with pleasure upon the facts that fall happily into the embrace of the theory...There springs up...an unconscious pressing of the theory to make it fit the facts, and a pressing of the facts to make them fit the theory.” — Chamberlin (1890/1965)1 “We are human after all.” — Daft Punk (2005)2 1. Introduction Science is a human endeavour and humans are fallible. Scientists’ cognitive limitations and self-interested motivations can infuse bias into the research process, undermining the production of reliable knowledge (Box 1)3–6.
    [Show full text]
  • Episode 62 – Diagnostic Decision Making Part 1: EBM, Risk Tolerance
    Chris Hicks and Doug Sinclair), teamwork failure, systems or process failure, and wider community issues such as access to care. Five Strategies to master evidence-based Episode 62 – Diagnostic Decision Making diagnostic decision making Part 1: EBM, Risk Tolerance, Over-testing 1. Evidence Based Medicine incorporates & Shared Decision Making patient values and clinical expertise - not only the evidence With Dr. David Dushenski, Dr. Chris Hicks & Dr. Walter Himmel Prepared by Dr. Anton Helman, April 2015 Are doctors effective diagnosticians? Diagnostic errors accounted for 17% of preventable errors in medical practice in the Harvard Medical Practice Study and a systematic review of autopsy studies conducted over four decades found that nearly 1 in 10 patients suffered a major ante-mortem diagnostic error; a figure that has fallen by only approximately 5% For an explanation of the interaction of the 3 spheres of EBM see despite all of todays’ advanced imaging technology and increased Episode 49: Walter Himmel on Evidence Based Medicine from the testing utilization. NYGH EMU Conference 2014 The factors that contribute to diagnostic error (adapted from the http://emergencymedicinecases.com/episode-47-walter-himmel- Ottawa M&M model) include patient factors such as a language evidence-based-medicine-nygh-emu-conference-2014/ barrier, clinician factors such as knowledge base, fatigue or emotional distress; cognitive biases (reviewed in Episode 11 with The intent of EBM is to… 7. Was the reference standard appropriate? • Make the ethical care of the patient its top priority 8. Was there good follow up? • Demand individualised evidence in a format that clinicians and patients can understand 9.
    [Show full text]
  • Differential Diagnosis Diagnostic Process?
    8/23/2010 What We’ll Cover Today • 1. (Part 1) Differential Diagnosis (defined) The Best Tests for Diagnosis: And Why – The decision making process it's Important – Costs associated with errors in decision making • 3. (Part 2) Diagnostic Accuracy – The language of diagnosis Chad Cook PT, PhD, MBA, OCS, FAAOMPT – Bias (studying diagnosis) Professor and Chair Walsh University • 4. (Part 3) Best tests for diagnosis (Part 1) Differential Diagnosis My Objectives • Differential diagnosis is a systematic 1. Differential Diagnosis is Extremely Important process used to identify the proper (in the early phases of the examination but diagnosis from a competing set of possible less so in the later phases of the examination) diagnoses. 2. Recognizing Bias in Diagnosis is Half the Battle • Diagnosis is one of many necessary 3. It is Critical to Know which tests are best used components during the clinical decision early or late in the examination making process Diagnostic Process? Who Performs Diagnoses? • The Diagnostic process involves identifying or • Anyone who treats determining the etiology of a disease or patients condition through evaluation of patient • Certainly, physical history, physical examination, and review of therapists laboratory data or diagnostic imaging; and the subsequent descriptive title of that finding Whiting et al. J Health Serv Res 2008 1 8/23/2010 PT’s and Diagnosis 1988 Why it’s Important • “Physical Therapists thus must establish • Failure to correctly identify an appropriate diagnostic categories that direct their diagnosis can lead to: treatment prescriptions and that provide a – Negative outcomes (Trowbridge 2008). means of communication both within the – Delays in appropriate treatment (Whiting et al.
    [Show full text]
  • A Systematic Review and Quantitative Meta-Analysis of the Accuracy Of
    A SYSTEMATIC REVIEW AND QUANTITATIVE META-ANALYSIS OF THE ACCURACY OF VISUAL INSPECTION FOR CERVICAL CANCER SCREENING: DOES PROVIDER TYPE OR TRAINING MATTER? by Susan D. Driscoll A Dissertation Submitted to the Faculty of the Christine E. Lynn College of Nursing In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Florida Atlantic University Boca Raton, FL December 2016 Copyright 2016 by Susan D. Driscoll ii ACKNOWLEDGEMENTS My dear friend and fellow PhD student referred to her doctoral dissertation as an “excrementitious” process and I couldn’t agree more. I would like to acknowledge a few of the many people who helped me navigate through the winding road of life, career, and academia. Dr. Tappen always had faith in my abilities and her easy going nature made the climb a little easier than expected. Dr. Goodman’s undying commitment to nursing and education is contagious and inspired me to continue the long hard slog. Dr. David Newman can always make me laugh and guided me through complicated statistics. Dr. Drowos’ medical perspectives were welcomed and needed. My sincerest thanks to all the wonderful teachers and mentors in my academic and professional career. Dr. Moore gave me the best career advice ever, “don’t get into medicine unless you can’t see yourself doing anything else”…so I didn’t. Teri Richards gave me my first glimpse at nursing. Dick Keyser introduced me to the business of healthcare, Dr. Grinspoon and Dr. Dolan-Looby sparked my interest in clinical research, Dr. Andrist and Dr. Steele sharpened my clinical skills, Dr.
    [Show full text]
  • Evidence to Inform the Development of QUADAS-2
    Updating QUADAS: Evidence to inform the development of QUADAS-2 Penny Whiting, Anne Rutjes, Marie Westwood, Susan Mallett, Mariska Leeflang, Hans Reitsma, Jon Deeks, Jonathan Sterne, Patrick Bossuyt 1 QUADAS Steering Group members: Penny Whiting, Department of Social Medicine, University of Bristol Anne Rutjes, Departments of Social and Preventive Medicine and Rheumatology, University of Berne Jonathan Sterne, Department of Social Medicine, University of Bristol Jon Deeks, Unit of Public Health, Epidemiology & Biostatistics, University of Birmingham Mariska Leeflang, Department of Clinical Epidemiology, Biostatistics and Informatics, AMC, University of Amsterdam Patrick Bossuyt, Department of Clinical Epidemiology, Biostatistics and Informatics, AMC, University of Amsterdam Hans Reitsma, Department of Clinical Epidemiology, Biostatistics and Informatics, AMC, University of Amsterdam Marie Westwood, Kleijnen Systematic Reviews, York Susan Mallett, Centre for Statistics in Medicine, University of Oxford 2 Contents Chapter 1: Background .......................................................................................................................... 5 Items in italics are those removed from the Cochrane version of QUADAS.Chapter 2: Approach and Scope of QUADAS-2 ............................................................................................................................... 6 Chapter 2: Approach and Scope of QUADAS-2 ...................................................................................... 7 2.1 Rationale
    [Show full text]
  • Bias and Confounding
    Bias and Confounding [email protected] Objectives By the end of this session you should: – Understand the concept of bias – Be able to give examples of differing types of bias that may be introduced into a study – Understand the concept of confounding – Be able to give examples of confounding within studies – Understand how bias and confounding may affect study results – Be able to identify ways to control for confounding Good research All epidemiological studies should: − Obtain a sample population that is as representative of the true population of interest as possible − Aim to acquire the best information possible on parameters of interest amongst their sample population Causality • Causality is the central concern of epidemiology Obesity CHD OR, RR, IRR Bias “Systematic, non-random deviation of results and inferences from the truth, or processes leading to such deviation.” (Dictionary of Epidemiology, 3rd ed.) Bias (including confounding) must be avoided or reduced as much as is possible – Help to produce accurate, precise, valid and reliable measurements – Ensure inferences made are true and generalisable Selection bias Systematic differences exist between comparison groups in a sample population Or, when the sample population does not represent the target population Examples of selection bias Respondent bias those who agree to be in a study are in some way different from those who refuse so the sample population is not truly representative of the target population Healthy worker effect employed population have lower mortality and less disease when compared with the general population Ascertainment bias the cases gathered are not representative of cases in the target population e.g.
    [Show full text]