How to Gain Access to Retrospective Chart Review

OVERVIEW

• Retrospective studies are designed to analyse pre-existing data, and are subject to numerous biases as a result
• Retrospective studies may be based on nautical chart reviews (information collection from the medical records of patients)
• Types of retrospective studies include:
  • example series
  • retrospective cohort studies (current or historical cohorts)
  • case-control studies

STATISTICAL ANALYSIS USED IN RETROSPECTIVE STUDIES

• Unadjusted, univariate, 'simple' or 'raw' assay
  • Compare outcomes between treatment and command group
  • Used if treatment and control group are selected by a run a risk mechanism
• Stratified analysis
  • Divide all patients into subgroups co-ordinate to a risk factor, and so perform comparison within these subgroups
  • Used if only one key confounding variable exists
• Matched pair assay
  • Find pairs of patients that take specific characteristics in mutual, simply received different treatments; compares effect simply in these pairs
  • Used if only a few confounders exist and if the size of one of the comparison groups is much larger than the other
• Multivariate assay
  • More than 1 confounder is controlled simultaneously, if a larger number of confounders needs to be adapted for computer software and statistical advice is necessary
  • Used if sample size is big
• No statistical analysis
  • Simple description of data
  • Used if sample size is low and other options failed

ADVANTAGES OF RETROSPECTIVE STUDIES

• quicker, cheaper and easier than prospective cohort studies
• tin address rare diseases and identify potential adventure factors (e.k. case-control studies)
• non prone to loss of follow upwardly
• may be used as the initial study generating hypotheses to be studied further by larger, more than expensive prospective studies

DISADVANTAGES OF RETROSPECTIVE STUDIES

• inferior level of bear witness compared with prospective studies
• controls are often recruited by convenience sampling, and are thus non representative of the general population and prone to selection bias
• prone to retrieve bias or misclassification bias
• subject to misreckoning (other take chances factors may be present that were not measured)
• cannot determine causation, only association
• some fundamental statistics cannot exist measured
• temporal relationships are frequently difficult to assess
• retrospective cohort studies need large sample sizes if outcomes are rare

SOURCES OF Error IN Chart REVIEWS AND THEIR SOLUTIONS

From Kaji et al (2014) and Gilbert et al (1996):

• Chart review inappropriate for report question
  • establish whether necessary information is available in the charts
  • establish if there are sufficient charts to perform the analysis with adequate precision
  • perform a sample size calculation
• Investigator conflict of involvement or bias
  • Declare whatever conflict of involvement
    Provide evidence of institutional review board approval
  • Submit the data collection form, every bit well as the coding rules and definitions, every bit an online appendix
• Patient sample is non-representative
  • Instance selection or exclusion using explicit protocols and well described the criteria
  • Ensure all bachelor charts have an equal chance of pick
  • Provide a menstruum diagram showing how the written report sample was derive from the source population
• Needed variables are non in the records
  • define the predictor and outcome variables to be nerveless a priori
  • Develop a coding transmission and publish as an online appendix
• Chart abstraction is non systematic (misclassification bias)
  • Use standardized abstraction forms to guide data collection
  • Provide precise definitions of variables
  • Pilot examination the abstraction form
• Presence of missing or alien data
  • Ensure uniform handling of data that is conflicting, ambiguous, missing, or unknown
  • Perform a sensitivity analysis if needed
• Abstractors biased or not blinded
  • Blind nautical chart reviewers to the etiologic relation being studied or the hypotheses being tested. If groups of patients are to be compared, the abstractor should exist blinded to the patient'due south grouping consignment
  • Describe how blinding was maintained in the article
• Abstractors not sufficiently trained
  • Railroad train chart abstractors to perform their jobs.
  • Describe the qualifications and training of the nautical chart abstracters.
  • Ideally, railroad train abstractors earlier the study starts, using a set up of "practice" medical records.
  • Ensure uniform training, peculiarly in multi-eye studies
• Abstractors not sufficiently monitored
  • Monitor the functioning of the chart abstractors
  • Hold periodic meetings with nautical chart abstractors and report coordinators to resolve disputes and review coding rules.
• Chart abstraction unreliable
  • A 2d reviewer should re-abstract a sample of charts, blinded to the information obtained by the first correlation reviewer.
  • Written report a kappa-statistic, intraclass coefficient, or other mensurate of agreement to assess inter-rater reliability of the data
  • Provide justification for the criteria for each variable

SOURCES OF Mistake FROM THE USE OF ELECTRONIC MEDICAL RECORDS

Potential biases introduced from:

• use of boilerplates (a unit of writing that can be reused over and over without change)
• items copied and pasted
• default tick boxes
• delays in time stamps relative to actual intendance

References and Links

LITFL

• CCC — Case-command studies

Journal articles

• Gilbert EH, Lowenstein SR, Koziol-McLain J, Barta DC, Steiner J. Chart reviews in emergency medicine inquiry: Where are the methods? Ann Emerg Med. 1996 Mar;27(iii):305-8. PMID: 8599488.
• Kaji AH, Schriger D, Light-green S. Looking through the retrospectoscope: reducing bias in emergency medicine nautical chart review studies. Ann Emerg Med. 2014 Sep;64(3):292-viii. PMID: 24746846.
• Sauerland Due south, Lefering R, Neugebauer EA. Retrospective clinical studies in surgery: potentials and pitfalls. J Manus Surg Br. 2002 Apr;27(ii):117-21. PMID: 12027483.
• Worster A, Bledsoe RD, Cleve P, Fernandes CM, Upadhye S, Eva K. Reassessing the methods of medical record review studies in emergency medicine research. Ann Emerg Med. 2005 Apr;45(4):448-51. PMID: 15795729.

Chris Nickson

Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also the Innovation Atomic number 82 for the Australian Heart for Health Innovation at Alfred Wellness and Clinical Adjunct Acquaintance Professor at Monash University. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator program. He is on the Lath of Directors for the Intensive Care Foundation and is a First Part Examiner for the Higher of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians larn and for improving the clinical performance of individuals and collectives.

Afterwards finishing his medical degree at the Academy of Auckland, he continued mail-graduate training in New Zealand also every bit Commonwealth of australia'due south Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, likewise every bit post-graduate preparation in biochemistry, clinical toxicology, clinical epidemiology, and wellness professional education.

He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU'south educational activity and simulation programmes and runs the unit's education website, INTENSIVE.  He created the 'Critically Ill Airway' course and teaches on numerous courses around the earth. He is ane of the founders of the FOAM movement (Free Open-Admission Medical educational activity) and is co-creator of litfl.com, the RAGE podcast, the Resuscitology course, and the SMACC briefing.

His one dandy achievement is existence the father of two amazing children.

On Twitter, he is @precordialthump.

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Source: https://litfl.com/retrospective-studies-and-chart-reviews/

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