Reducing delays to diagnosis in ambulatory care settings: A macrocognition perspective.

We aim to use a macrocognition theoretical perspective to characterize contributors to diagnostic delays by physicians that can be mitigated by work system redesign. As experienced with other complex, sociotechnical domains, system redesign is anticipated to be more effective at improving safety than training-based solutions. In the outpatient care setting, complex tasks, conducted by a primary care provider, are provided for five macrocognition functions: sensemaking, re-planning, detecting problems, deciding, and coordinating. Redesigning systems could reduce delays to diagnosis by helping users to avoid missed symptoms, forgotten follow-up activities, and delayed actions. Health information technology could support resilience strategies by offloading documentation burdens, recording working diagnoses, displaying planned follow-up activities at the correct time interval, and supporting recognition of patterns in patient care. These insights suggest a path forward for future research on system design innovations to reduce diagnostic delays, and ultimately, reduce patient harm.

[1]  Melinda D. Sawyer,et al.  Defining the critical role of nurses in diagnostic error prevention: a conceptual framework and a call to action , 2017, Diagnosis.

[2]  Mary K Goldstein,et al.  Accuracy of computerized outpatient diagnoses in a Veterans Affairs general medicine clinic. , 2002, The American journal of managed care.

[3]  Philippe N. Tobler,et al.  Cognitive biases associated with medical decisions: a systematic review , 2016, BMC Medical Informatics and Decision Making.

[4]  J. Lave,et al.  Retail clinics, primary care physicians, and emergency departments: a comparison of patients' visits. , 2008, Health affairs.

[5]  Nick Summerton,et al.  The medical history as a diagnostic technology. , 2008, The British journal of general practice : the journal of the Royal College of General Practitioners.

[6]  Jason J Saleem,et al.  Ambulatory Clinic Exam Room Design with respect to Computing Devices: A Laboratory Simulation Study , 2018, IISE transactions on occupational ergonomics and human factors.

[7]  Carol A. Keohane,et al.  Randomized Trial of Reducing Ambulatory Malpractice and Safety Risk: Results of the Massachusetts PROMISES Project , 2017, Medical care.

[8]  B. Karsh,et al.  Interruptions and Distractions in Healthcare: Review and Reappraisal Method Inclusion and Exclusion Criteria Nih Public Access , 2022 .

[9]  K. Peltekian,et al.  Patterns of paging medical interns during night calls at two teaching hospitals. , 1994, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[10]  Daniel M Kaplan.  Clear writing, clear thinking and the disappearing art of the problem list. , 2007, Journal of hospital medicine.

[11]  Robert F Bunting,et al.  From To Err Is Human to Improving Diagnosis in Health Care: The risk management perspective. , 2016, Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management.

[12]  Christopher A. Harle,et al.  Understanding how primary care clinicians make sense of chronic pain , 2018, Cognition, Technology & Work.

[13]  Emily S. Patterson,et al.  Workarounds to Intended Use of Health Information Technology: A Narrative Review of the Human Factors Engineering Literature , 2018, Hum. Factors.

[14]  Robert R. Hoffman,et al.  Visualization framework of macrocognition functions , 2011, Cognition, Technology & Work.

[15]  Erik Hollnagel,et al.  Safety-I and Safety-II: The Past and Future of Safety Management , 2014 .

[16]  Pat Croskerry,et al.  Cognitive debiasing 2: impediments to and strategies for change , 2013, BMJ quality & safety.

[17]  Laura G Militello,et al.  Characterizing a Naturalistic Decision-Making Phenomenon , 2016, Journal of cognitive engineering and decision making.

[18]  Nancy F. Lenfestey,et al.  Cognitive interventions to reduce diagnostic error: a narrative review , 2012, BMJ quality & safety.

[19]  J. Hampton,et al.  Relative contributions of history-taking, physical examination, and laboratory investigation to diagnosis and management of medical outpatients. , 1975, British medical journal.

[20]  P. Carayon,et al.  Work system design for patient safety: the SEIPS model , 2006, Quality and Safety in Health Care.

[21]  Jenny W. Rudolph,et al.  The Dynamics of Action-Oriented Problem Solving: Linking Interpretation and Choice , 2009 .

[22]  Marianna Diomidous,et al.  Nurse staffing and education and hospital mortality in nine European countries: a retrospective observational study , 2014, The Lancet.

[23]  U. Sarkar,et al.  Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients , 2017, Implementation Science.

[24]  A. Thapar,et al.  Interruptions during general practice consultations--the patients' view. , 1996, Family practice.

[25]  Peter Griffiths,et al.  Registered nurse, healthcare support worker, medical staffing levels and mortality in English hospital trusts: a cross-sectional study , 2016, BMJ Open.

[26]  Jonathan Grudin,et al.  Discretionary Adoption of Group Support Software: Lessons from Calendar Applications , 2003, Implementing Collaboration Technologies in Industry.

[27]  B. Karsh,et al.  A human factors engineering paradigm for patient safety: designing to support the performance of the healthcare professional , 2006, Quality and Safety in Health Care.

[28]  M. Graber.  The incidence of diagnostic error in medicine , 2013, BMJ quality & safety.

[29]  Pat Croskerry,et al.  Cognitive forcing strategies in clinical decisionmaking. , 2003, Annals of emergency medicine.

[30]  B. Miller,et al.  Improving Diagnosis in Health Care , 2015 .

[31]  Emily S. Patterson,et al.  Collaborative cross-checking to enhance resilience , 2005, Cognition, Technology & Work.

[32]  E. Patterson,et al.  Macrocognition in the Healthcare Built Environment (mHCBE): A Focused Ethnographic Study of “Neighborhoods” in a Pediatric Intensive Care Unit , 2018, HERD.

[33]  Thomas Bodenheimer,et al.  In Search of Joy in Practice: A Report of 23 High-Functioning Primary Care Practices , 2013, The Annals of Family Medicine.

[34]  Z. Bursac,et al.  Racial disparities in survival outcomes by breast tumor subtype among African American women in Memphis, Tennessee , 2017, Cancer medicine.

[35]  E. Patterson,et al.  Towards computer-assisted coding: A case study of ‘charge by documentation’ software at an endoscopy clinic , 2014 .

[36]  Pierre Dragicevic,et al.  A Task-Based Taxonomy of Cognitive Biases for Information Visualization , 2020, IEEE Transactions on Visualization and Computer Graphics.

[37]  A. Guerguerian,et al.  Technology-mediated macrocognition: Investigating how physicians, nurses, and respiratory therapists make critical decisions. , 2019, Journal of critical care.

[38]  Richard A. Stephans.  System Safety for the 21st Century: The Updated and Revised Edition of System Safety 2000 , 2004 .

[39]  G. Klein.  Macrocognitive Measures for Evaluating Cognitive Work , 2018, Macrocognition Metrics and Scenarios.

[40]  Erik Hollnagel,et al.  Joint Cognitive Systems: Patterns in Cognitive Systems Engineering , 2006 .

[41]  Michael Weiner,et al.  Hidden complexities in information flow between primary and specialty care clinics , 2018, Cognition, Technology & Work.

[42]  Patricia C. Dykes,et al.  Care coordination gaps due to lack of interoperability in the United States: a qualitative study and literature review , 2016, BMC Health Services Research.

[43]  T. Brennan,et al.  Missed and Delayed Diagnoses in the Ambulatory Setting: A Study of Closed Malpractice Claims , 2006, Annals of Internal Medicine.