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Methods Inf Med 2016; 55(01): 14-22
DOI: 10.3414/ME15-01-0031
Original Articles
Schattauer GmbH

Clinical Complexity in Medicine: A Measurement Model of Task and Patient Complexity

R. Islam
1   University of Utah, Biomedical Informatics, School of Medicine, Salt Lake City, Utah, USA
,
C. Weir
1   University of Utah, Biomedical Informatics, School of Medicine, Salt Lake City, Utah, USA
,
G. Del Fiol
2   University of Utah, Biomedical Informatics, Salt Lake City, Utah, USA
› Institutsangaben
Weitere Informationen

Publikationsverlauf

Received 01. März 2015

Accepted 25. Juni 2015

Publikationsdatum:
08. Januar 2018 (online)

   Lizenzen und Reprints

Summary

Background: Complexity in medicine needs to be reduced to simple components in a way that is comprehensible to researchers and clinicians. Few studies in the current literature propose a measurement model that addresses both task and patient complexity in medicine. Objective: The objective of this paper is to develop an integrated approach to understand and measure clinical complexity by incorporating both task and patient complexity components focusing on the infectious disease domain. The measurement model was adapted and modified for the healthcare domain. Methods: Three clinical infectious disease teams were observed, audio-recorded and transcribed. Each team included an infectious diseases expert, one infectious diseases fellow, one physician assistant and one pharmacy resident fellow. The transcripts were parsed and the authors independently coded complexity attributes. This baseline measurement model of clinical complexity was modified in an initial set of coding processes and further validated in a consensus-based iterative process that included several meetings and email discussions by three clinical experts from diverse backgrounds from the Department of Biomedical Informatics at the University of Utah. Inter-rater reliability was calculated using Cohen’s kappa. Results: The proposed clinical complexity model consists of two separate components. The first is a clinical task complexity model with 13 clinical complexity-contributing factors and 7 dimensions. The second is the patient complexity model with 11 complexity-contributing factors and 5 dimensions. Conclusion: The measurement model for complexity encompassing both task and patient complexity will be a valuable resource for future researchers and industry to measure and understand complexity in healthcare.

Keywords

Decision Complexity - Decision Support Systems - Clinical/Utilization - Social Medicine/Methods - Humans - Quality Assurance - Health Care/methods - Software Design - Information Technology
 

  • References

  • 1 Bedny GZ, Karwowski W, Bedny IS. Complexity Evaluation of Computer-Based Tasks. International Journal of Human-Computer Interaction 2012; 28 (Suppl. 04) 236-257.
    PubMedGoogle Scholar
  • 2 Braithwaite RS, Concato J. Vector Model of Complexity. J Gen Intern Med 2008; 23 (Suppl. 06) 895.
    CrossrefPubMedGoogle Scholar
  • 3 Jenkins DP. Cognitive Work Analysis: Coping with Complexity. Ashgate Publishing, Ltd.; 2009
    Google Scholar
  • 4 Kannampallil TG, Schauer GF, Cohen T, Patel VL. Considering Complexity in Healthcare Systems. Journal of Biomedical Informatics 2011; 44 (Suppl. 06) 943-947.
    CrossrefPubMedGoogle Scholar
  • 5 Plsek PE, Wilson T. Complexity Science: Complexity, Leadership, and Management in Health-care Organisations. British Medical Journal 2001; 323 7315 746-749.
    PubMedGoogle Scholar
  • 6 Sintchenko V, Coiera E. Decision Complexity Affects the Extent and Type of Decision Support Use. AMIA Annu Symp Proc. 2006: 724-728.
    PubMedGoogle Scholar
  • 7 Wilson T, Holt T. Complexity Science: Complexity and Clinical Care. British Medical Journal 2001; 323 7314 685-688.
    PubMedGoogle Scholar
  • 8 Woods DD. Coping with Complexity: The Psychology of Human Behaviour in Complex Systems. Tasks, Errors and Mental Models 1988; 128-148.
    PubMedGoogle Scholar
  • 9 Moura Jr LA. Complexity and the Will to Transform. Methods Inf Med 2012; 51 (Suppl. 03) 187-188.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 10 Sandoval J, Esteller M. Cancer Epigenomics: Beyond Genomics. Current Opinion in Genetics & Development 2012; 22 (Suppl. 01) 50-55.
    CrossrefPubMedGoogle Scholar
  • 11 Alonso F, Lara JA, Martinez L, PÈrez A, Valente JP. Generating Reference Models for Structurally Complex Data. Application to the Stabilometry Medical Domain. Methods Inf Med 2013; 52 (Suppl. 05) 441-453.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 12 Grant RW, Ashburner JM, Hong CS, Chang Y, Barry MJ, Atlas SJ. Defining Patient Complexity From the Primary Care Physician’s Perspective: A Cohort Study. Annals of Internal Medicine 2011; 155 (Suppl. 12) 797-804.
    CrossrefPubMedGoogle Scholar
  • 13 Shippee ND, Shah ND, May CR, Mair FS, Montori VM. Cumulative Complexity: A Functional, Patient-Centered Model of Patient Complexity Can Improve Research and Practice. J Clin Epidemiol 2012; 65 (Suppl. 10) 1041-1051.
    CrossrefPubMedGoogle Scholar
  • 14 Huntley Jr MS. Task Complexity and Serial Performance Under Steadily Increasing Input Rates. Human Factors 1972; 14 (Suppl. 01) 65-75.
    CrossrefPubMedGoogle Scholar
  • 15 Hartley AA, Anderson JW. Task Complexity and Problem-Solving Performance in Younger and Older Adults. Journals of Gerontology 1983; 38 (Suppl. 01) 72-77.
    PubMedGoogle Scholar
  • 16 Gardner DG. Task Complexity Effects on Non-task-Related Movements: A Test of Activation Theory. Organizational Behavior and Human Decision Processes 1990; 45 (Suppl. 02) 209-231.
    CrossrefPubMedGoogle Scholar
  • 17 Braarud PO. Subjective Task Complexity and Subjective Workload: Criterion Validity for Complex Team Tasks. International Journal of Cognitive Ergonomics 2001; 5 (Suppl. 03) 261-273.
    CrossrefPubMedGoogle Scholar
  • 18 Gill TG, Hicks RC. Task Complexity and Informing Science: A Synthesis. Informing Science 2006; 9: 1-30.
    PubMedGoogle Scholar
  • 19 Gill TG, Murphy WF. Task Complexity and Design Science. In: 9th International Conference on Education and Information Systems. Technologies and Applications (EISTA 2011), Orlando, FL, USA: 2011
    Google Scholar
  • 20 Ham DH, Park J, Jung W. Model-Based Identification and Use of Task Complexity Factors of Human Integrated Systems. Reliability Engineering and System Safety 2012; 100: 33-47.
    CrossrefPubMedGoogle Scholar
  • 21 Liu P, Li Z. Task Complexity: A Review and Conceptualization Framework. International Journal of Industrial Ergonomics 2012; 42 (Suppl. 06) 553-568.
    CrossrefPubMedGoogle Scholar
  • 22 Schaink AK, Kuluski K, Lyons RF, Fortin M, Jadad AR, Upshur R. et al. A Scoping Review and Thematic Classification of Patient Complexity: Offering a Unifying Framework. Journal of Comorbidity 2012; 2 (Suppl. 01) 1-9.
    CrossrefPubMedGoogle Scholar
  • 23 Safford MM, Allison JJ, Kiefe CI. Patient Complexity: More Than Comorbidity. The Vector Model of Complexity. Journal of General Internal Medicine 2007; 22 (Suppl. 03) 382-390.
    PubMedGoogle Scholar
  • 24 Fauci AS, Morens DM. The Perpetual Challenge of Infectious Diseases. N Engl J Med 2012; 366 (Suppl. 05) 454-461.
    CrossrefPubMedGoogle Scholar
  • 25 Fong IW. Challenges in Infectious Diseases. Springer; 2013
    Google Scholar
  • 26 Khabbaz RF, Moseley RR, Steiner RJ, Levitt AM, Bell BP. Challenges of Infectious Diseases in the USA. The Lancet 2014; 384 9937 53-63.
    CrossrefPubMedGoogle Scholar
  • 27 Carroll LN, Au AP, Detwiler LT, Fu T-C, Painter IS, Abernethy NF. Visualization and Analytics Tools for Infectious Disease Epidemiology: A Systematic Review. Journal of Biomedical Informatics 2014; 51 (Suppl. 00) 287-298.
    CrossrefPubMedGoogle Scholar
  • 28 Morens DM, Folkers GK, Fauci AS. The Challenge of Emerging and Re-emerging Infectious Diseases. Nature 2004; 430 6996 242-249.
    CrossrefPubMedGoogle Scholar
  • 29 Tleyjeh IM, Nada H, Baddour LM. VisualDx: Decision-Support Software for the Diagnosis and Management of Dermatologic Disorders. Clinical Infectious Diseases 2006; 43 (Suppl. 09) 1177-1184.
    CrossrefPubMedGoogle Scholar
  • 30 McMullen CK, Ash JS, Sittig DF, Bunce A, Guappone K, Dykstra R. et al. Rapid Assessment of Clinical Information Systems in the Healthcare Setting. An Efficient Method for Time-Pressed Evaluation. Methods Inf Med 2011; 50 (Suppl. 04) 299-307.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 31 Timmermans DR, Gooszen AW, Geelkerken RH, Tollenaar RA, Gooszen HG. Analysis of the Variety in Surgeons’ Decision Strategies for the Management of Left Colonic Emergencies. Medical Care 1997; 35 (Suppl. 07) 701-713.
    CrossrefPubMedGoogle Scholar
  • 32 Timmermans DR, Sprij AJ, de Bel CE. The Discrepancy Between Daily Practice and the Policy of a Decision-Analytic Model: The Management of Fever of Unknown Origin. Medical Decision Making: An International Journal of the Society for Medical Decision Making 1996; 16 (Suppl. 04) 357-366.
    CrossrefPubMedGoogle Scholar
  • 33 Begum S, Ahmed MU, Funk P, Xiong N, Von Schéele B. A Case-Based Decision Support System for Individual Stress Diagnosis Using Fuzzy Similarity Matching. Computational Intelligence 2009; 25 (Suppl. 03) 180-195.
    CrossrefPubMedGoogle Scholar
  • 34 Lynn MR. Determination and Quantification of Content Validity. Nursing Research 1986; 35 (Suppl. 06) 382-386.
    PubMedGoogle Scholar
  • 35 Stemler S. An Overview of Content Analysis. Practical Assessment, Research & Evaluation 2001; 7 (Suppl. 17) 137-146.
    PubMedGoogle Scholar
  • 36 Haney W, Russell M, Gulek C, Fierros E. Drawing on Education: Using Student Drawings to Promote Middle School Improvement. Schools in the Middle 1998; 7 (Suppl. 03) 38-43.
    PubMedGoogle Scholar
  • 37 Clark J. How to Peer Review a Qualitative Manuscript. Peer Review in Health Sciences 2003; 2: 219-235.
    PubMedGoogle Scholar
  • 38 Custer RL, Scarcella JA, Stewart BR. The Modified Delphi Technique-A Rotational Modification. Journal of Vocational and Technical Education. 1999
    PubMedGoogle Scholar
  • 39 Wolff JL, Starfield B, Anderson G. Prevalence, Expenditures, and Complications of Multiple Chronic Conditions in the Elderly. Archives of Internal Medicine 2002; 162 (Suppl. 20) 2269-2276.
    CrossrefPubMedGoogle Scholar
  • 40 Werner RM, Asch DA. Clinical Concerns About Clinical Performance Measurement. The Annals of Family Medicine 2007; 5 (Suppl. 02) 159-163.
    CrossrefPubMedGoogle Scholar
  • 41 Hübner-Bloder G, Ammenwerth E. Key Performance Indicators to Benchmark Hospital Information Systems舘 A Delphi Study. Methods Inf Med 2009; 48 (Suppl. 06) 508-518.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 42 Arnrich B, Mayora O, Bardram J, Tröster G. Pervasive Healthcare. Paving the Way for a Pervasive, User-Centered and Preventive Healthcare Model. Methods Inf Med 2010; 49 (Suppl. 01) 67-73.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 43 Werner RM, Greenfield S, Fung C, Turner BJ. Measuring Quality of Care in Patients With Multiple Clinical Conditions: Summary of a Conference Conducted by the Society of General Internal Medicine. Journal of General Internal Medicine 2007; 22 (Suppl. 08) 1206-1211.
    CrossrefPubMedGoogle Scholar
  • 44 Turner BJ, Cuttler L. The Complexity of Measuring Clinical Complexity. Annals of Internal Medicine 2011; 155 (Suppl. 12) 851-852.
    CrossrefPubMedGoogle Scholar
  • 45 Islam R, Weir C, Fiol GD. editors. Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making. 2014 IEEE International Conference on Healthcare Informatics (ICHI); Sept 15–17, 2014
    PubMedGoogle Scholar
  • 46 Mane KK, Bizon C, Schmitt C, Owen P, Burchett B, Pietrobon R. et al. VisualDecisionLinc: A Visual Analytics Approach for Comparative Effectiveness-Based Clinical Decision Support in Psychiatry. J Biomed Inform 2012; 45 (Suppl. 01) 101-106.
    CrossrefPubMedGoogle Scholar
  • 47 Singh H, Petersen LA, Thomas EJ. Understanding Diagnostic Errors in Medicine: A Lesson from Aviation. Quality and Safety in Health Care 2006; 15 (Suppl. 03) 159-164.
    CrossrefPubMedGoogle Scholar
  • 48 Elstein AS. Thinking About Diagnostic Thinking: A 30-Year Perspective. Advances in Health Sciences Education: Theory and Practice 2009; 14 (Suppl. 01) 7-18.
    CrossrefPubMedGoogle Scholar
  • 49 Schiff GD, Hasan O, Kim S, Abrams R, Cosby K, Lambert BL. et al. Diagnostic Error in Medicine: Analysis of 583 Physician-Reported Errors. Archives of Internal Medicine 2009; 169 (Suppl. 20) 1881-1887.
    CrossrefPubMedGoogle Scholar
  • 50 Graber ML, Kissam S, Payne VL, Meyer AN, Sorensen A, Lenfestey N. et al. Cognitive Interventions to Reduce Diagnostic Error: A Narrative Review. BMJ Quality & Safety 2012; 21 (Suppl. 07) 535-557.
    CrossrefPubMedGoogle Scholar
  • 51 Croskerry P, Petrie DA, Reilly JB, Tait G. Deciding About Fast and Slow Decisions. Academic Medicine: Journal of the Association of American Medical Colleges 2014; 89 (Suppl. 02) 197-200.
    CrossrefPubMedGoogle Scholar
  • 52 Bailey BP, Iqbal ST. Understanding Changes in Mental Workload During Execution of Goal-Directed Tasks and Its Application for Interruption Management. ACM Transactions on Computer-Human Interaction (TOCHI) 2008; 14 (Suppl. 04) 21.
    PubMedGoogle Scholar
  • 53 John BE, Kieras DE. Using GOMS for User Interface Design and Evaluation: Which Technique?. ACM Transactions on Computer-Human Interaction (TOCHI) 1996; 3 (Suppl. 04) 287-319.
    PubMedGoogle Scholar
  • 54 Wagner T, Garvey A, Lesser V. Criteria-Directed Task Scheduling. International Journal of Approximate Reasoning 1998; 19 (Suppl. 01) 91-118.
    CrossrefPubMedGoogle Scholar