Review

Human–computer interaction in healthcare: Comprehensive review

  • Received: 17 July 2024 Revised: 05 September 2024 Accepted: 09 September 2024 Published: 09 October 2024
  • Technological advancements have fundamentally transformed healthcare systems and significantly altered the interactions between medical professionals and information interfaces. This study provides a comprehensive review of the role of human–computer interaction (HCI) in healthcare, emphasizing the importance of user-centered design and the integration of emerging technologies. The paper reviews the evolution of healthcare interfaces, exploring key assumptions in foundational HCI principles and theoretical frameworks that guide the design processes. The analysis delves into the application of HCI principles, particularly user-centered approaches, to enhance feedback mechanisms, ensure consistency, and improve visibility within medical settings, all of which contribute to creating practical, usable, and memorable interfaces. The review provides an overview of successful and unsuccessful cases, demonstrating what determines efficacy in healthcare interface design. The discussion extends to cover the role of interactive interfaces in streamlining clinical workflows, facilitating communication and collaboration, and supporting informed decision-making among healthcare providers. This paper focuses on historical views and milestones of interface design, emphasizing the significance of interactive interfaces. The discussion extends to cover the role of interactive interfaces in streamlining clinical workflows, facilitating communication and collaboration, and supporting informed decision-making among healthcare providers. Further, the review concludes with an examination of future trends in HCI for healthcare, particularly focusing on the rapid integration of emerging technologies and their implications for the ongoing evolution of interface design in this critical field.

    Citation: Meher Langote, Saniya Saratkar, Praveen Kumar, Prateek Verma, Chetan Puri, Swapnil Gundewar, Palash Gourshettiwar. Human–computer interaction in healthcare: Comprehensive review[J]. AIMS Bioengineering, 2024, 11(3): 343-390. doi: 10.3934/bioeng.2024018

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  • Technological advancements have fundamentally transformed healthcare systems and significantly altered the interactions between medical professionals and information interfaces. This study provides a comprehensive review of the role of human–computer interaction (HCI) in healthcare, emphasizing the importance of user-centered design and the integration of emerging technologies. The paper reviews the evolution of healthcare interfaces, exploring key assumptions in foundational HCI principles and theoretical frameworks that guide the design processes. The analysis delves into the application of HCI principles, particularly user-centered approaches, to enhance feedback mechanisms, ensure consistency, and improve visibility within medical settings, all of which contribute to creating practical, usable, and memorable interfaces. The review provides an overview of successful and unsuccessful cases, demonstrating what determines efficacy in healthcare interface design. The discussion extends to cover the role of interactive interfaces in streamlining clinical workflows, facilitating communication and collaboration, and supporting informed decision-making among healthcare providers. This paper focuses on historical views and milestones of interface design, emphasizing the significance of interactive interfaces. The discussion extends to cover the role of interactive interfaces in streamlining clinical workflows, facilitating communication and collaboration, and supporting informed decision-making among healthcare providers. Further, the review concludes with an examination of future trends in HCI for healthcare, particularly focusing on the rapid integration of emerging technologies and their implications for the ongoing evolution of interface design in this critical field.



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    Conflict of interest



    The authors declare no conflicts of interest.

    Author contributions



    Meher Langote, Saniya Saratkar, and Praveen Kumar wrote the manuscript and drew figures and tables. Prateek Verma, Chetan Puri, Swapnil Gundewar and Palash Gourshettiwar provided the conceptual idea and revised the manuscript. All authors have read and approved the final manuscript.

    [1] Sawesi S, Rashrash M, Phalakornkule K, et al. (2016) The impact of information technology on patient engagement and health behavior change: A systematic review of the literature. JMIR Med Inf 4: e4514. https://doi.org/10.2196/medinform.4514
    [2] Søgaard Neilsen A, Wilson RL (2019) Combining e-mental health intervention development with human computer interaction (HCI) design to enhance technology-facilitated recovery for people with depression and/or anxiety conditions: An integrative literature review. Int J Ment Health Nu 28: 22-39. https://doi.org/10.1111/inm.12527
    [3] Mishra R, Satpathy R, Pati B (2023) Human computer interaction applications in healthcare: An integrative review. EAI Endorsed T Pervas Health Technol 9. https://doi.org/10.4108/eetpht.9.4186
    [4] Melles M, Albayrak A, Goossens R (2021) Innovating health care: Key characteristics of human-centered design. Int J Qual Health C 33: 37-44. https://doi.org/10.1093/intqhc/mzaa127
    [5] He X, Hong Y, Zheng X, et al. (2023) What are the users' needs? Design of a user-centered explainable artificial intelligence diagnostic system. Int J Hum–Comput Int 39: 1519-1542. https://doi.org/10.1080/10447318.2022.2095093
    [6] Cornelio P, Haggard P, Hornbaek K, et al. (2022) The sense of agency in emerging technologies for human–computer integration: A review. Front Neurosci 16: 949138. https://doi.org/10.3389/fnins.2022.949138
    [7] Sadeghi Milani A, Cecil-Xavier A, Gupta A, et al. (2024) A systematic review of human–computer interaction (HCI) research in medical and other engineering fields. Int J Hum–Comput Int 40: 515-536. https://doi.org/10.1080/10447318.2022.2116530
    [8] Reimer YJ, Douglas SA (2003) Teaching HCI design with the studio approach. Comput Sci Educ 13: 191-205. https://doi.org/10.1076/csed.13.3.191.14945
    [9] Siek KA (2018) Expanding human computer interaction methods to understand user needs in the design process of personal health systems. Yearb Med Inf 27: 74-78. https://doi.org/10.1055/s-0038-1667073
    [10] Jimison HB, Pavel M, Parker A, et al. (2023) Correction to: The role of human computer interaction in consumer health applications: Current state, challenges and the future. Cognitive Informatics for Biomedicine. Health Informatics. Berlin: Springer 259-278. https://doi.org/10.1007/978-3-319-17272-9_15
    [11] Saliba V, Legido-Quigley H, Hallik R, et al. (2012) Telemedicine across borders: A systematic review of factors that hinder or support implementation. Int J Med Inform 81: 793-809. https://doi.org/10.1016/j.ijmedinf.2012.08.003
    [12] Almathami HKY, Win KT, Vlahu-Gjorgievska E (2020) Barriers and facilitators that influence telemedicine-based, real-time, online consultation at patients' homes: Systematic literature review. J Med Internet Res 22: e16407. https://doi.org/10.2196/16407
    [13] Wang D, Yang Q, Abdul A, et al. (2019) Designing theory-driven user-centric explainable AI. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems : 1-15. https://doi.org/10.1145/3290605.3300831
    [14] Dearden A, Finlay J (2006) Pattern languages in HCI: A critical review. Hum–Comput Interact 21: 49-102. https://doi.org/10.1207/s15327051hci2101_3
    [15] Mackay WE, Fayard AL (1997) HCI, natural science and design: A framework for triangulation across disciplines. Proceedings of the 2nd Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques : 223-234. https://doi.org/10.1145/263552.263612
    [16] Gulliksen J, Göransson B, Boivie I, et al. (2003) Key principles for user-centred systems design. Behav Inform Technol 22: 397-409. https://doi.org/10.1080/01449290310001624329
    [17] Pacini Naumovich ER, Mateos Diaz CM, Garcia Garino CG (2015) Balancing throughput and response time in online scientific Clouds via Ant Colony Optimization (SP2013/2013/00006). Adv Eng Softw 84: 31-47. https://doi.org/10.1016/j.advengsoft.2015.01.005
    [18] Frangoudes F, Hadjiaros M, Schiza EC, et al. (2021) An overview of the use of chatbots in medical and healthcare education. International Conference on Human-Computer Interaction : 170-184. https://doi.org/10.1007/978-3-030-77943-6_11
    [19] Pavlovic VI, Sharma R, Huang TS (1997) Visual interpretation of hand gestures for human-computer interaction: A review. IEEE T Pattern Anal 19: 677-695. https://doi.org/10.1109/34.598226
    [20] Spruit M, Lytras M (2018) Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients. Telemat Inform 35: 643-653. https://doi.org/10.1016/j.tele.2018.04.002
    [21] Hegner SM, Beldad AD, Brunswick GJ (2019) In automatic we trust: Investigating the impact of trust, control, personality characteristics, and extrinsic and intrinsic motivations on the acceptance of autonomous vehicles. Int J Hum–Comput Int 35: 1769-1780. https://doi.org/10.1080/10447318.2019.1572353
    [22] Ekstrand MD, Das A, Burke R, et al. (2022) Fairness in information access systems. Found Trends Inf Ret 16: 1-177. https://doi.org/10.1561/1500000079
    [23] Finstad K (2010) The usability metric for user experience. Interact Comput 22: 323-327. https://doi.org/10.1016/j.intcom.2010.04.004
    [24] Ke JXC, George RB, Wozney L, et al. (2021) Application mobile périopératoire destinée aux mères avec un accouchement par césarienne: Une étude de cohorte prospective sur l'intérêt des patientes. Can J Anesth 68: 505-513. https://doi.org/10.1007/s12630-020-01907-x
    [25] Robbins DA, Curro FA, Fox CH (2013) Defining patient-centricity: Opportunities, challenges, and implications for clinical care and research. Ther Innov Regul Sci 47: 349-355. https://doi.org/10.1177/2168479013484159
    [26] Visell Y (2009) Tactile sensory substitution: Models for enaction in HCI. Int Comput 21: 38-53. https://doi.org/10.1016/j.intcom.2008.08.004
    [27] Bukht TFN, Rahman H, Shaheen M, et al. (2024) A review of video-based human activity recognition: Theory, methods and applications. Multimed Tools Appl : 1-47. https://doi.org/10.1007/s11042-024-19711-w
    [28] Holden RJ, Abebe E, Hill JR, et al. (2022) Human factors engineering and human-computer interaction: Supporting user performance and experience. Clinic Inf Stu Guide : 119-132. https://doi.org/10.1007/978-3-030-93765-2_9
    [29] Dino MJS, Davidson PM, Dion KW, et al. (2022) Nursing and human-computer interaction in healthcare robots for older people: An integrative review. Int J Nurs Stu Adv 4: 100072. https://doi.org/10.1016/j.ijnsa.2022.100072
    [30] Luo Y, Li M, Tang J, et al. (2021) Design of a virtual reality interactive training system for public health emergency preparedness for major emerging infectious diseases: Theory and framework. JMIR Serious Games 9: e29956. https://doi.org/10.2196/29956
    [31] Ahmed A, Xi R, Hou M, et al. (2023) Harnessing big data analytics for healthcare: A comprehensive review of frameworks, implications, applications, and impacts. IEEE Access . https://doi.org/10.1109/ACCESS.2023.3323574
    [32] Pierce J, Sengers P, Hirsch T, et al. (2015) Expanding and refining design and criticality in HCI. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems : 2083-2092. https://doi.org/10.1145/2702123.2702438
    [33] Bachmann D, Weichert F, Rinkenauer G (2018) Review of three-dimensional human-computer interaction with focus on the leap motion controller. Sensors 18: 2194. https://doi.org/10.3390/s18072194
    [34] Šumak B, Brdnik S, Pušnik M (2021) Sensors and artificial intelligence methods and algorithms for human–computer intelligent interaction: A systematic mapping study. Sensors 22: 20. https://doi.org/10.3390/s22010020
    [35] Shah SA, Fioranelli F (2019) RF sensing technologies for assisted daily living in healthcare: A comprehensive review. IEEE Aero El Sys Mag 34: 26-44. https://doi.org/10.1109/MAES.2019.2933971
    [36] Omaghomi TT, Elufioye OA, Akomolafe O, et al. (2024) Health apps and patient engagement: A review of effectiveness and user experience. World J Adv Res Rev 21: 432-440. https://doi.org/10.30574/wjarr.2024.21.2.0476
    [37] Oulasvirta A, Hornbæk K (2016) HCI research as problem-solving. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems : 4956-4967. https://doi.org/10.1145/2858036.2858283
    [38] Hekler EB, Klasnja P, Froehlich JE, et al. (2013) Mind the theoretical gap: Interpreting, using, and developing behavioral theory in HCI research. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems : 3307-3316. https://doi.org/10.1145/2470654.2466452
    [39] Su T, Ding Z, Cui L, et al. (2024) System development and evaluation of human–computer interaction approach for assessing functional impairment for people with mild cognitive impairment: A pilot study. Int J Hum–Comput Int 40: 1906-1920. https://doi.org/10.1080/10447318.2023.2228529
    [40] Sin J, Munteanu C (2020) An empirically grounded sociotechnical perspective on designing virtual agents for older adults. Hum–Comput Int 35: 481-510. https://doi.org/10.1080/07370024.2020.1731690
    [41] Mentler T, Berndt H, Herczeg M (2016) Optical head-mounted displays for medical professionals: Cognition-supporting human-computer interaction design. Proceedings of the European Conference on Cognitive Ergonomics : 1-8. https://doi.org/10.1145/2970930.2970957
    [42] Girju R, Girju M (2022) Design considerations for an NLP-driven empathy and emotion interface for clinician training via telemedicine. Proceedings of the Second Workshop on Bridging Human--Computer Interaction and Natural Language Processing : 21-27. https://doi.org/10.18653/v1/2022.hcinlp-1.3
    [43] Dix A (2017) Human–computer interaction, foundations and new paradigms. J Visual Lang Comput 42: 122-134. https://doi.org/10.1016/j.jvlc.2016.04.001
    [44] Prasad S, Smith A, Joshi A, et al. (2005) Report on the first all-India human-computer interaction conference. Interact 12: 67-69. https://doi.org/10.1145/1082369.1082417
    [45] Balcombe L, De Leo D (2022) Human-computer interaction in digital mental health. Informatics 9: 14. https://doi.org/10.3390/informatics9010014
    [46] Chen S, Epps J, Ruiz N, et al. (2011) Eye activity as a measure of human mental effort in HCI. Proceedings of the 16th international conference on Intelligent user interfaces : 315-318. https://doi.org/10.1145/1943403.1943454
    [47] Webster J, Trevino LK, Ryan L (1993) The dimensionality and correlates of flow in human-computer interactions. Comput Hum Behav 9: 411-426. https://doi.org/10.1016/0747-5632(93)90032-N
    [48] Ghani JA, Deshpande SP (1994) Task characteristics and the experience of optimal flow in human—computer interaction. J Psychol 128: 381-391. https://doi.org/10.1080/00223980.1994.9712742
    [49] Middleton B, Bloomrosen M, Dente MA, et al. (2013) Enhancing patient safety and quality of care by improving the usability of electronic health record systems: Recommendations from AMIA. J Am Med Inform Asso 20: e2-e8. https://doi.org/10.1136/amiajnl-2012-001458
    [50] Zheng K, Ratwani RM, Adler-Milstein J (2020) Studying workflow and workarounds in electronic health record–supported work to improve health system performance. Ann Intern Med 172: S116-S122. https://doi.org/10.7326/M19-0871
    [51] Zhang J, Johnson TR, Patel VL, et al. (2003) Using usability heuristics to evaluate patient safety of medical devices. J Biomed Inform 36: 23-30. https://doi.org/10.1016/S1532-0464(03)00060-1
    [52] Bolgova KV, Kovalchuk SV, Balakhontceva MA, et al. (2020) Human computer interaction during clinical decision support with electronic health records improvement. Int J E-Health Med C 11: 93-106. https://doi.org/10.4018/978-1-7998-9023-2.ch062
    [53] Mansur SH, Moran K (2023) Toward automated tools to support ethical GUI design. 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings : 294-298. https://doi.org/10.1109/ICSE-Companion58688.2023.00079
    [54] Aronson AR, Lang FM (2010) An overview of MetaMap: Historical perspective and recent advances. J Am Med Inform Asso 17: 229-236. https://doi.org/10.1136/jamia.2009.002733
    [55] Rossi S, Hallett M, Rossini PM, et al. (2009) Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin Neurophysiol 120: 2008-2039. https://doi.org/10.1016/j.clinph.2009.08.016
    [56] Doebelin N, Kleeberg R (2015) Profex: A graphical user interface for the rietveld refinement program BGMN. J Appl Crystallogr 48: 1573-1580. https://doi.org/10.1107/S1600576715014685
    [57] Kokalj A (2003) Computer graphics and graphical user interfaces as tools in simulations of matter at the atomic scale. Comput Mater Sci 28: 155-168. https://doi.org/10.1016/S0927-0256(03)00104-6
    [58] Xierali IM, Hsiao CJ, Puffer JC, et al. (2013) The rise of electronic health record adoption among family physicians. Annal Fam Med 11: 14-19. https://doi.org/10.1370/afm.1461
    [59] Park A, Wilson M, Robson K, et al. (2023) Interoperability: Our exciting and terrifying Web3 future. Bus Horizons 66: 529-541. https://doi.org/10.1016/j.bushor.2022.10.005
    [60] Keshta I, Odeh A (2021) Security and privacy of electronic health records: Concerns and challenges. Egypt Inform J 22: 177-183. https://doi.org/10.1016/j.eij.2020.07.003
    [61] Nazar M, Alam MM, Yafi E, et al. (2021) A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques. IEEE Access 9: 153316-153348. https://doi.org/10.1109/ACCESS.2021.3127881
    [62] Ledo D, Houben S, Vermeulen J, et al. (2018) Evaluation strategies for HCI toolkit research. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems : 1-17. https://doi.org/10.1145/3173574.3173610
    [63] Barricelli BR, Fogli D (2024) Digital twins in human-computer interaction: A systematic review. Int J Hum–Comput Int 40: 79-97. https://doi.org/10.1080/10447318.2022.2118189
    [64] Blandford A (2019) HCI for health and wellbeing: Challenges and opportunities. Int J Hum-Comput St 131: 41-51. https://doi.org/10.1016/j.ijhcs.2019.06.007
    [65] Hornbæk K (2006) Current practice in measuring usability: Challenges to usability studies and research. Int J Hum-Comput St 64: 79-102. https://doi.org/10.1016/j.ijhcs.2005.06.002
    [66] Lewis JR (1995) IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. Int J Hum–Comput Int 7: 57-78. https://doi.org/10.1080/10447319509526110
    [67] Jaspers MW (2009) A comparison of usability methods for testing interactive health technologies: Methodological aspects and empirical evidence. Int J Med Inform 78: 340-353. https://doi.org/10.1016/j.ijmedinf.2008.10.002
    [68] Sadeghi Milani A, Cecil-Xavier A, Gupta A, et al. (2024) A systematic review of human–computer interaction (HCI) research in medical and other engineering fields. Int J Hum–Comput Int 40: 515-536. https://doi.org/10.1080/10447318.2022.2116530
    [69] Chandra S, Sharma G, Malhotra S, et al. (2015) Eye tracking based human computer interaction: Applications and their uses. 2015 International Conference on Man and Machine Interfacing : 1-5. https://doi.org/10.1109/MAMI.2015.7456615
    [70] Newell AF, Gregor P (1997) Human computer interfaces for people with disabilities. Handbook of Human-Computer Interaction. Holland: North-Holland 813-824. https://doi.org/10.1016/B978-044481862-1.50101-1
    [71] Aggarwal JK, Ryoo MS (2011) Human activity analysis: A review. Acm Comput Surv 43: 1-43. https://doi.org/10.1145/1922649.1922653
    [72] Maes P (1995) Agents that reduce work and information overload. Readings in Human–Computer Interaction. Manhattan: Morgan Kaufmann 811-821. https://doi.org/10.1016/B978-0-08-051574-8.50084-4
    [73] Judd T, Ehinger K, Durand F, et al. (2009) Learning to predict where humans look. 2009 IEEE 12th International Conference on Computer Vision : 2106-2113. https://doi.org/10.1109/ICCV.2009.5459462
    [74] Dalsgaard P, Dindler C (2014) Between theory and practice: Bridging concepts in HCI research. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems : 1635-1644. https://doi.org/10.1145/2556288.2557342
    [75] Stephanidis C, Salvendy G, Antona M, et al. (2019) Seven HCI grand challenges. Int J Hum–Comput Int 35: 1229-1269. https://doi.org/10.1080/10447318.2019.1619259
    [76] Fukizi KY (2023) Collaborative decision-making assistant for healthcare professionals: A human-centered AI prototype powered by azure open AI. Proceedings of the 6th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies : 118-119. https://doi.org/10.1145/3588001.3609370
    [77] Ala A, Simic V, Pamucar D, et al. (2024) Enhancing patient information performance in internet of things-based smart healthcare system: Hybrid artificial intelligence and optimization approaches. Eng Appl Artif Intel 131: 107889. https://doi.org/10.1016/j.engappai.2024.107889
    [78] Han E, DeVeaux C, Miller MR, et al. (2024) Alone together, together alone: The effects of social context on nonverbal behavior in virtual reality. Presence-Virtual Aug 33: 425-451. https://doi.org/10.1162/pres_a_00432
    [79] Greenberg S, Boring S, Vermeulen J, et al. (2014) Dark patterns in proxemic interactions: A critical perspective. Proceedings of the 2014 conference on Designing interactive systems : 523-532. https://doi.org/10.1145/2598510.2598541
    [80] Epstein DA, O'Kane AA, Miller AD (2023) Symposium: Workgroup on interactive systems in healthcare (WISH). Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems : 1-4. https://doi.org/10.1145/3544549.3573804
    [81] Yarmand M, Chen C, Cheng K, et al. (2024) “I'd be watching him contour till 10 o'clock at night”: Understanding tensions between teaching methods and learning needs in healthcare apprenticeship. Proceedings of the CHI Conference on Human Factors in Computing Systems : 1-19. https://doi.org/10.1145/3613904.3642453
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