Factors Associated with Clinical Information Overload and Its Management Strategies: A Mixed-Methods Study in Isfahan University of Medical Sciences

Document Type : Original Article

Authors
1 Assistant Professor Medical Library and Information Science, Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
2 Associate Professor, Knowledge and Information Science, Department of Knowledge and Information Science; University of Isfahan; Isfahan, Iran
3 Professor, faculty of Nursing and Midwifery, Isfahan University of medical sciences, Isfahan,
4 Professor, Department of Knowledge and Information Science, University of Isfahan, Isfahan, Iran
Abstract
Introduction: Clinical information overload affects the quality of decision-making and patient safety. This study aimed to identify the associated factors and management strategies for this phenomenon from the perspective of specialists at Isfahan University of Medical Sciences in 2024.
Methods: This study employed a sequential exploratory mixed-methods design conducted in two qualitative and quantitative phases. In the qualitative phase, semi-structured interviews were conducted with 19 Clinical Practitioners, and the data were analyzed using inductive content analysis in MAXQDA software. In the quantitative phase, a 26-item questionnaire with a Likert scale was designed, and its validity and reliability were confirmed (Cronbach's alpha = 0.895) and distributed among 100 Clinical Practitioners. Data from 77 completed questionnaires were analyzed using SPSS. The conceptual model was designed based on the Tushman and Nadler framework.
Results: Data analysis led to the identification of 100 initial codes and 7 main categories including managerial-organizational (mean = 4.269), educational (3.823), informational (3.714), technological (3.801), documentation (3.792), individual (3.510), and task-related (3.389) factors. Overall, 107 strategies were proposed in 7 domains, with the key strategies including utilization of health information professionals, implementation of an integrated electronic health record system, and design of user-friendly systems.
Conclusion: Effective management of clinical information overload requires a systematic and integrated approach. The conceptual model based on the balance between information processing capacity and needs can serve as a framework for policymaking and information system design, although its practical validation requires future studies.
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1.      Sweller J, Van Merrienboer JJ, Paas FG. Cognitive architecture and instructional design. Educational psychology review. 1998;10(3):251-96.
2.      Schmid FN. Prospective effects of information overload on psychophysical stress reactions among clinical staff 2022.
3.      Siegel MG, Rossi MJ, Lubowitz JH. Artificial Intelligence and Machine Learning May Resolve Health Care Information Overload. The Journal of Arthroscopic & Related Surgery. 2024;40(6):1721-3.
4.      Yamamoto Y. Healthcare and the roles of the medical profession in the big data era. J Japan Medical Association Journal: JMAJ. 2016;59(2-3):125.
5.      Nijor S, Rallis G, Lad N, Gokcen E. Patient safety issues from information overload in electronic medical records. Journal of Patient Safety. 2022;18(6):e999-e1003.
6.      Klerings I, Weinhandl AS, Thaler KJ. Information overload in healthcare: too much of a good thing? Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen. 2015;109(4-5):285-90.
7.      Walter-tscharf F. Intelligent Clinical Information Platform for Assisting Heart Disease Care Pathway using Machine Learning. 2024.
8.      Jackson TW, Farzaneh P. Theory-based model of factors affecting information overload. International Journal of Information Management. 2012;32(6):523-32.
9.      Al-Kumaim NH, Alhazmi AK, Mohammed F, Gazem NA, Shabbir MS, Fazea Y. Exploring the impact of the COVID-19 pandemic on university students’ learning life: An integrated conceptual motivational model for sustainable and healthy online learning. Sustainability. 2021;13(5):2546.
10.    Sbaffi L, Walton J, Blenkinsopp J, Walton G. Information overload in emergency medicine physicians: a multisite case study exploring the causes, impact, and solutions in four North England National Health Service Trusts. Journal of Medical Internet Research. 2020;22(7):e19126.
11.    Zhang X, LI Z. A Review of Doctor-Patient Communication Studies. Canadian Social Science. 2020;16(4):51-6.
12.    Eliyana A, Ajija SR, Sridadi AR, Setyawati A, Emur AP. Information overload and communication overload on social media exhaustion and job performance. Systematic Reviews in Pharmacy. 2020;11(8):334-51.
13.    Schmitt JB, Debbelt CA, Schneider FM. Too much information? Predictors of information overload in the context of online news exposure. Information, Communication & Society. 2018;21(8):1151-67.
14.    DeLaine TP. Physician information overload and the role of the medical librarian or informaticist. Philadelphia, PA: Drexel University. 2004.
15.    Laker LF, Froehle CM, Windeler JB, Lindsell CJ. Quality and efficiency of the clinical decision‐making process: Information overload and emphasis framing. Production operations management 2018;27(12):2213-25.
16.    Eppler MJ, Mengis J. The concept of information overload-a review of literature from organization science, accounting, marketing, mis, and related disciplines (2004). The Information Society. 2004;20(5):325-44.
17.   Tushman ML, Nadler DA. Information processing as an integrating concept in organizational design. Academy of management review. 1978;3(3):613-24.
18.   Kim, Lustria MLA, Burke D, Kwon N. Predictors of cancer information overload: Findings from a national survey. Information Research. 2007;12(4).
19.   Al-Kumaim NH, Hassan SH, Shabbir MS, Almazroi AA, Al-Rejal HMA. Exploring the Inescapable Suffering Among Postgraduate Researchers: Information Overload Perceptions and Implications for Future Research. International Journal of Information Communication Technology Education 2021;17(1):19-41.
20.    Heggelund MO, Hussain SS, Farshchian BA, editors. Information overload–A case study of using an integrated electronic health record system in the emergency room. Norsk IKT-konferanse for forskning og utdanning; 2024.
21.    Hashemzadeh M, Adibi P, Rahimi A. The Presence of a Clinical Informationist on Ward Rounds: An Action Research Study. Journal of Hospital Librarianship. 2021;21(3):245-56.
22.   Sweller J. Cognitive load theory and educational technology. Educational technology research and development. 2020;68(1):1-16.
23.   Mabaso MZP. The impact of information overload on employees at Vodacom uMhlanga Regional Office. South Africa: University of KwaZulu-Natal; 2015.
24.   Arjmand-Kermani R. Survey of the relation between organizational structure and informational overload in case study: Payame Noor University. Research Journal of Recent Sciences 2013;2(6):52-7.
25.    Mansourian Y, Ford N. Search persistence and failure on the web: a “bounded rationality” and “satisficing” analysis. Journal of Documentation. 2007.
26.    Virkus S, Mandre S, Pals E. Information Overload in a Disciplinary Context. 2018. p. 615-24.
27.    Graf B, Antoni CH. Drowning in the flood of information: a meta-analysis on the relation between information overload, behaviour, experience, and health and moderating factors. European Journal of Work and Organizational Psychology. 2023;32(2):173-98.
28.   Keszthelyi D, Gaudet-Blavignac C, Bjelogrlic M, Lovis C. Patient information summarization in clinical settings: scoping review. JMIR Medical Informatics. 2023;11(1):e44639.
29.   Hashemzadeh M, Rahimi A, Allahbakhsh M, Adibi P, Beigi-Harchegani H. Information Capsule: A New Approach for Summarizing Medical Information. International Journal of Preventive Medicine. 2024;15:52.