How Do Clinical Information Systems Affect the Cognitive Demands of General Practitioners?: Usability Study with a Focus on Cognitive Workload

Ferran Ariza, Dipak Kalra, Henry WW Potts


Background Clinical information systems in the National Health Service do not need to conform to any explicit usability requirements. Poor usability can increase the mental workload experienced by clinicians and cause fatigue, increase error rates and impact the overall patient safety. Mental workload can be used as a measure of usability.

Objective To assess the subjective cognitive workload experienced by general practitioners (GPs) with their systems. To raise awareness of the importance of usability in system design among users, designers, developers and policymakers.

Methods We used a modified version of the NASA Task Load Index, adapted for web. We developed a set of common clinical scenarios and computer tasks on an online survey. We emailed the study link to 199 clinical commissioning groups and 1,646 GP practices in England. 

Results Sixty-seven responders completed the survey. The respondents had spent an average of 17 years in general practice, had experience of using a mean of 1.5 GP computer systems and had used their current system for a mean time of 6.7 years. The mental workload score was not different among systems. There were significant differences among the task scores, but these differences were not specific to particular systems. The overall score and task scores were related to the length of experience with their present system. 

Conclusion Four tasks imposed a higher mental workload on GPs: ‘repeat prescribing’, ‘find episode’, ‘drug management’ and ‘overview records’. Further usability studies on GP systems should focus on these tasks. Users, policymakers, designers and developers should remain aware of the importance of usability in system design.

What does this study add?

• Current GP systems in England do not need to conform to explicit usability requirements. Poor usability can increase the mental workload of clinicians and lead to errors.

• Some clinical computer tasks incur more cognitive workload than others and should be considered carefully during the design of a system.

• GPs did not report overall very high levels of subjective cognitive workload when undertaking common clinical tasks with their systems.

• Further usability studies on GP systems should focus on the tasks incurring higher cognitive workload.

• Users, policymakers, and designers and developers should remain aware of the importance of usability in system design.



cognitive science, computerized medical record systems, general practice, human engineering, medical informatics, primary health care, user–computer interface.

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Goetz Goldberg D, Kuzel AJ, Feng LB, DeShazo JP and Love LE. EHRs in primary care practices: benefits, challenges, and successful strategies. American Journal of Managed Care 2012;18(2):e48–54. PMid:22435884.

Schade CP, Sullivan FM, de Lusignan S and Madeley J. e-Prescribing, efficiency, quality: lessons from the computerization of UK family practice. Journal of the American Medical Informatics Association 2006;13(5):470–5. PMid:16799129; PMCid:PMC1561797.

HIMSS EHR Usability Task Force. Defining and testing EMR usability: principles and proposed methods of EMR usability evaluation and rating. Healthcare Information and Management Systems Society, 2009.

Horsky J, Zhang J and Patel VL. To err is not entirely human: complex technology and user cognition. Journal of Biomedical Informatics 2005;38(4):264–6. PMid:15967732.

Peute LWP, De Keizer NF, Van Der Zwan EPA and Jaspers MWM. Reducing clinicians’ cognitive workload by system redesign; a pre-post think aloud usability study. Studies in Health Technology and Informatics 2011;169:925–9. PMid:21893881.

Jha AK, Doolan D, Grandt D, Scott T and Bates DW. The use of health information technology in seven nations. International Journal of Medical Informatics 2008;77(12):848–54. PMid:18657471.

Shachak A, Hadas-Dayagi M, Ziv A and Reis S. Primary care physicians’ use of an electronic medical record system: a cognitive task analysis. Journal of General Internal Medicine 2009;24(3):341–8. PMid:19130148; PMCid:PMC2642564.

Microsoft Health Common User Interface [Internet], 2010. Available from:

Patel VL and Kushniruk AW. Interface design for health care environments: the role of cognitive science. Proceedings of the AMIA Symposium 1998;29–37. PMid:9929179; PMCid:PMC2232103.

Alexander G and Staggers N. A Systematic review on the designs of clinical technology: findings and recommendations for future research. ANS. Advances in Nursing Science 2009;32(3):252–79. PMid:19707093; PMCid:PMC3018768.

Sittig DF, Kuperman GJ and Fiskio J. Evaluating physician satisfaction regarding user interactions with an electronic medical record system. Proceedings of the AMIA Symposium 1999;400–4. PMid:10566389; PMCid:PMC2232602.

Nielsen J. Usability 101: Introduction to Usability [Internet]. Nielsen Norman Group, 2012. Available from:

Levinson W, Lesser CS and Epstein RM. Developing physician communication skills for patient-centered care. Health Affairs (Millwood) 2010;29(7):1310–18. PMid:20606179.

Pelaccia T, Tardif J, Triby E and Charlin B. An analysis of clinical reasoning through a recent and comprehensive approach: the dual-process theory. Medical Education Online 2011 [cited 2013 Jul 11];16. Available from:

O’Riordan M, Dahinden A, Aktürk Z, Ortiz JMB, Dağdeviren N, Elwyn G et al. Dealing with uncertainty in general practice: an essential skill for the general practitioner. Quality in Primary Care 2011;19(3):175–81. PMid:21781433.

Starfield B. Primary care. The Journal of Ambulatory Care Management 1993;16(4):27–37. PMid:10128415.

Smith PC, Araya-Guerra R, Bublitz C, Parnes B, Dickinson LM, Van Vorst R et al. Missing clinical information during primary care visits. Journal of the American Medical Association 2005;293(5):565–71. PMid:15687311.

Beasley JW, Wetterneck TB, Temte J, Lapin JA, Smith P, Rivera-Rodriguez AJ et al. Information chaos in primary care: implications for physician performance and patient safety. The Journal of the American Board of Family Medicine 2011;24(6):745–51. PMid:22086819; PMCid:PMC3286113.

Byrne AJ, Oliver M, Bodger O, Barnett WA, Williams D, Jones H et al. Novel method of measuring the mental workload of anaesthetists during clinical practice. British Journal of Anaesthesia 2010;105(6):767–71. PMid:20846966.

Kirsh D. A few thoughts on cognitive overload. Intellectica 2000;30:19–51.

Clarke MA, Steege LM, Moore JL, Belden JL, Koopman RJ and Kim MS. Addressing Human Computer Interaction Issues of Electronic Health Record in Clinical Encounters. Marcus A (Ed). Design, user experience, and usability health, learning, playing, cultural, and cross-cultural user experience [Internet]. Heidelberg: Springer, 2013 [cited 2013 Jul 10], pp. 381–90. Available from: PMid:23444324.

Ahmed A, Chandra S, Herasevich V, Gajic O and Pickering BW. The effect of two different electronic health record user interfaces on intensive care provider task load, errors of cognition, and performance. Critical Care Medicine 2011;39(7):1626–34. PMid:21478739.

Longo L and Kane B. A novel methodology for evaluating user interfaces in health care. 24th International Symposium on Computer-Based Medical Systems (CBMS), 2011, pp. 1–6.

Bouamrane MM and Mair FS. A study of general practitioners’ perspectives on electronic medical records systems in NHSScotland. BMC Medical Informatics and Decision Making 2013;13(1):58. PMid:23688255; PMCid:PMC3704757.

Viitanen J, Hyppönen H, Lääveri T, Vänskä J, Reponen J and Winblad I. National questionnaire study on clinical ICT systems proofs: physicians suffer from poor usability. International Journal of Medical Informatics 2011;80(10):708–25. PMid:21784701.

Viitanen J, Kuusisto A and Nykänen P. Usability of electronic nursing record systems: definition and results from an evaluation study in Finland. Studies in Health Technology and Informatics 2011;164:333–8. PMid:21335733.

Militello L, Patterson ES, Tripp-Reimer T, Asch SM, Fung CH, Glassman P et al. Clinical reminders: why don’t they use them? Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2004;48(15):1651–5.

Garrard CS. Human-computer interactions: can computers improve the way doctors work? Schweizerische medizinische Wochenschrift 2000;130(42):1557–63. PMid:11092058.

Saitwal H, Feng X, Walji M, Patel V and Zhang J. Assessing performance of an Electronic Health Record (EHR) using cognitive task analysis. International Journal of Medical Informatics 2010;79(7):501–6. PMid:20452274.

Zhang J. Human-centered computing in health information systems. Part 1: analysis and design. Journal of Biomedical Informatics 2005;38(1):1–3. PMid:15694880.

Khajouei R, de Jongh D and Jaspers MWM. Usability evaluation of a computerized physician order entry for medication ordering. Studies in Health Technology and Informatics 2009;150:532–6. PMid:19745368.

Koppel R, Metlay JP, Cohen A, Abaluck B, Localio AR, Kimmel SE et al. Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors. Journal of the American Medical Association 2005;293(10):1197–203. PMid:15755942.

Middleton B, Bloomrosen M, Dente MA, Hashmat B, Koppel R, Overhage JM et al. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. Journal of the American Medical Association 2013;20(e1):e2–8. PMid:23355463; PMCid:PMC3715367.

Cousins DH and Baker M. The work of the National Patient Safety Agency to improve medication safety. British Journal of General Practice 2004;54(502):331–3. PMid:15113513; PMCid:PMC1266164.

Protti D. Lessons to be learned from England about the potential of GP computer systems to improve patient safety. Healthcare Quarterly2004;7(3):76–80. PMid:15230172.

Johnson C, Johnson D and Crowly P. EHR Usability Toolkit: a background report on usability and electronic health records (prepared by Westat under Contract No. HHSA 290-2009-00023I). Rockville, Maryland: Agency for Healthcare Research and Quality, 2011. Report No.: 11-0084-EF.

Rubio S, Díaz E, Martín J and Puente JM. Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology 2004;53(1): 61–86.

Hart SG. Nasa-Task Load Index (NASA-TLX); 20 years later. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2006;50(9):904–8.

Hoonakker P, Carayon P, Gurses AP, Brown R, Khunlertkit A, McGuire K et al. Measuring workload of ICU nurses with a questionnaire survey: the NASA Task Load Index (TLX). IIE Transactions on Healthcare Systems Engineering 2011;1(2):131–43. PMid:22773941 PMCid:PMC3388621.

Carswell CM, Lio CH, Grant R, Klein MI, Clarke D, Seales WB et al. Hands-free administration of subjective workload scales: acceptability in a surgical training environment. Applied Ergonomics 2010;42(1):138–45. PMid:20630495.

Zheng B, Jiang X, Tien G, Meneghetti A, Panton ONM and Atkins MS. Workload assessment of surgeons: correlation between NASA TLX and blinks. Surgical Endoscopy 2012;26(10):2746–50. PMid:22527300.

France DJ, Levin S, Hemphill R, Chen K, Rickard D, Makowski R et al. Emergency physicians’ behaviors and workload in the presence of an electronic whiteboard. International Journal of Medical Informatics 2005;74(10):827–37. PMid:16043391.

Hart SG and Staveland LE. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research [Internet], 1988 [cited 2013 Jul 25]. Available from:

National Aeronautics and Space Administration. NASA TLX: Task Load Index [Internet]. NASA TLX: Task Load Index, no date. Available from: groups/TLX/index.html.

Laerum H and Faxvaag A. Task-oriented evaluation of electronic medical records systems: development and validation of a questionnaire for physicians. BMC Medical Informatics and Decision Making 2004;4:1.,

ISD Scotland. Practice Team Information Annual Update (2009/10) [Internet]. ISD Scotland, 2011. Available from:

The Health and Social Care Information Centre – Workforce Directorate. General and Personal Medical Services, England, 2001 - 2011, as at 30 September [Internet]. The Health and Social Care Information Centre, 2012 [cited 2012 Dec 15]. Available from:

Davis E. English GP Systems Market [Internet]. Woodcode Consulting, 2011 [cited 2012 Dec 7]. Available from:

Todd R. CSC to withdraw from primary care. EHI eHealth Insider [Internet]. UK; 2012 Sep 17. Available from:

SystmOne. TPP to become second biggest GP supplier [Internet]. TTP SystmOne Latests News Stories, 2011 [cited 2012 Dec 7]. Available from:

Anders S, Albert R, Miller A, Weinger MB, Doig AK, Behrens M et al. Evaluation of an integrated graphical display to promote acute change detection in ICU patients. International Journal of Medical Informatics 2012;81(12):842–51. PMid:22534099; PMCid:PMC3414670.

Avery A, Barber N, Maisoon G, Franklin BD, Armstrong S and Crowe S. Investigating the prevalence and causes of prescribing errors in general practice: the PRACtICe study [Internet]. GMC, 2012 May [cited 2013 Jul 21]. Available from:

Haworth LA, Bivens CC and Shively RJ. An investigation of single-piloted advanced cockpit and control configurations for Nap-of-the-Earth Helicopter Combat Mission Tasks. Proceedings of the 1986 Meeting of the American Helicopter Society (Washington, District of Columbia), 1986, pp. 672–5.

Colligan L, Potts HWW, Finn CT and Sinkin RA. Cognitive workload changes for nurses transitioning from a legacy system with paper documentation to a commercial electronic health record. International Journal of Medical Informatics 2015;84(7):469–76. PMid:25868807.

Kumarapeli P and de Lusignan S. Using the computer in the clinical consultation; setting the stage, reviewing, recording, and taking actions: multi-channel video study. Journal of the American Medical Informatics Association [Internet] 2012 [cited 2013 Jan 17]. Available from:

De Lusignan S, Pearce C, Kumarapeli P, Stavropoulou C, Kushniruk A, Sheikh A et al. Reporting observational studies of the use of information technology in the clinical consultation. A position statement from the IMIA Primary Health Care Informatics Working Group (IMIA PCI WG). Yearbook of Medical Informatics 2011;6(1):39–47. PMid:21938323.

Moroney WF, Biers DW and Eggemeier FT. Some measurement and methodological considerations in the application of subjective workload measurement techniques. The International Journal of Aviation Psychology 1995;5(1):87–106.

Bethlehem J. Selection bias in web surveys. International Statistical Review 2010;78(2):161–88.

VanGeest JB, Johnson TP and Welch VL. Methodologies for improving response rates in surveys of physicians: a systematic review. Evaluation and the Health Professions 2007;30(4):303–21. PMid:17986667.

Nicholls K, Chapman K, Shaw T, Perkins A, Sullivan MM, Crutchfield S et al. Enhancing response rates in physician surveys: the limited utility of electronic options. Health Services Research 2011;46(5):1675–82. PMid:21492157; PMCid:PMC3207199.



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