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Quality and Efficiency of the Clinical Decision‐Making Process: Information Overload and Emphasis Framing

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  • Lauren F. Laker
  • Craig M. Froehle
  • Jaime B. Windeler
  • Christopher John Lindsell

Abstract

The healthcare industry has invested heavily in electronic health records and other clinical information systems in order to improve caregivers' access to information and ability to share information with other care providers. It has been shown that these systems can readily induce in their users a state of information overload, where the volume and complexity of information overwhelms the user, leading to lower decision speed and quality. This research introduces and tests a cognitive technique called “emphasis framing” as an operational tactic to help mitigate the effects of information overload, thereby improving the quality and timeliness of clinical decision‐making. Emphasis framing is the highlighting or stressing of some aspect or component of the information being exchanged in order to make it more easily processed, or more likely to be processed, by the recipient. We conducted a controlled laboratory experiment with emergency department physicians experiencing information overload to measure the effect of emphasis framing on two operational performance metrics: (1) the quality of the physician's clinical evaluation, and (2) the efficiency (timeliness) of the physician's clinical decision‐making. Our findings show that the emphasis frame helped mitigate the effects of information overload and increased the quality of clinical decision‐making. Contrary to expectations, however, we found decision‐making took longer with the emphasis frame, reinforcing the need to consider the impacts of quality/speed trade‐offs. Implications for theory and practice are discussed.

Suggested Citation

  • Lauren F. Laker & Craig M. Froehle & Jaime B. Windeler & Christopher John Lindsell, 2018. "Quality and Efficiency of the Clinical Decision‐Making Process: Information Overload and Emphasis Framing," Production and Operations Management, Production and Operations Management Society, vol. 27(12), pages 2213-2225, December.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:12:p:2213-2225
    DOI: 10.1111/poms.12777
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    Cited by:

    1. Uzma Mushtaque & Jennifer A. Pazour, 2022. "Assortment optimization under cardinality effects and novelty for unequal profit margin items," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 106-126, February.
    2. Wei Zhao & Qianqian Ben Liu & Xitong Guo & Tianshi Wu & Subodha Kumar, 2022. "Quid pro quo in online medical consultation? Investigating the effects of small monetary gifts from patients," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1698-1718, April.
    3. Büşra Ergün‐Şahin & Evrim Didem Güneş & Ayşe Kocabıyıkoğlu & Ahmet Keskin, 2022. "How does workload affect test ordering behavior of physicians? An empirical investigation," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2664-2680, June.
    4. Diwas Singh KC & Stefan Scholtes & Christian Terwiesch, 2020. "Empirical Research in Healthcare Operations: Past Research, Present Understanding, and Future Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 73-83, January.
    5. Zaiyan Wei & Mo Xiao & Rong Rong, 2021. "Network Size and Content Generation on Social Media Platforms," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1406-1426, May.
    6. Tinglong Dai & Sridhar Tayur, 2022. "Designing AI‐augmented healthcare delivery systems for physician buy‐in and patient acceptance," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4443-4451, December.
    7. Zlatana Nenova & Jennifer Shang, 2022. "Chronic Disease Progression Prediction: Leveraging Case‐Based Reasoning and Big Data Analytics," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 259-280, January.
    8. Sun, Huan & Wang, Haiyan & Steffensen, Sonja, 2022. "Mechanism design of multi-strategy health insurance plans under asymmetric information," Omega, Elsevier, vol. 107(C).
    9. Goodarzi, Shadi & Masini, Andrea & Aflaki, Sam & Fahimnia, Behnam, 2021. "Right information at the right time: Reevaluating the attitude–behavior gap in environmental technology adoption," International Journal of Production Economics, Elsevier, vol. 242(C).

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