IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v174y2022ics0040162521006557.html
   My bibliography  Save this article

Big data analytics for clinical decision-making: Understanding health sector perceptions of policy and practice

Author

Listed:
  • Weerasinghe, Kasuni
  • Scahill, Shane L.
  • Pauleen, David J.
  • Taskin, Nazim

Abstract

The introduction and use of ‘big data and analytics’ is an on-going issue of discussion in health sectors globally. Healthcare systems of developed countries are trying to create more value and better healthcare through data and use of big data technologies. With an increasing number of articles identifying the value creation of big data and analytics for clinical decision-making, this paper examines how big data is applied, or not applied, in clinical practice. Using social representation theory as a theoretical foundation the paper explores people's perceptions of big data across all levels (policy making, planning, funding, and clinical care) of the New Zealand healthcare sector. The findings show that although adoption of big data technologies is planned for population health and health management, the potential of big data for clinical care has yet to be explored in the New Zealand context. The findings also highlight concern over data quality. The paper provides recommendations for policy and practice particularly around the need for engagement and participation of all levels to discuss data quality as well as big-data-based changes such as precision medicine and technology-assisted clinical decision-making tools. Future avenues of research are suggested.

Suggested Citation

  • Weerasinghe, Kasuni & Scahill, Shane L. & Pauleen, David J. & Taskin, Nazim, 2022. "Big data analytics for clinical decision-making: Understanding health sector perceptions of policy and practice," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006557
    DOI: 10.1016/j.techfore.2021.121222
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521006557
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.121222?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Omar Bentahar & Roslyn Cameron, 2015. "Design and Implementation of a Mixed Method Research Study in Project Management," Post-Print hal-01371708, HAL.
    2. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    3. Liu, Bingsheng & Zhou, Qi & Ding, Ru-Xi & Palomares, Iván & Herrera, Francisco, 2019. "Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination," European Journal of Operational Research, Elsevier, vol. 275(2), pages 737-754.
    4. Wang, Yichuan & Kung, LeeAnn & Byrd, Terry Anthony, 2018. "Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 3-13.
    5. Brendan Collins, 2016. "Big Data and Health Economics: Strengths, Weaknesses, Opportunities and Threats," PharmacoEconomics, Springer, vol. 34(2), pages 101-106, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sunny Sun & Lina Zhong & Rob Law & Xiaoya Zhang & Liyu Yang & Meiling Li, 2022. "A Proposed DISE Approach for Tourist Destination Crisis Management," Sustainability, MDPI, vol. 14(17), pages 1-16, September.
    2. Singha, Sumanta & Arha, Himanshu & Kar, Arpan Kumar, 2023. "Healthcare analytics: A techno-functional perspective," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    2. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    3. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    4. Rodgers, Waymond & Degbey, William Y. & Housel, Thomas J. & Arslan, Ahmad, 2020. "Microfoundations of collaborative networks: The impact of social capital formation and learning on investment risk assessment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    5. Wang, Huamao & Yao, Yumei & Salhi, Said, 2020. "Tension in big data using machine learning: Analysis and applications," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    6. Basile, Luigi Jesus & Carbonara, Nunzia & Pellegrino, Roberta & Panniello, Umberto, 2023. "Business intelligence in the healthcare industry: The utilization of a data-driven approach to support clinical decision making," Technovation, Elsevier, vol. 120(C).
    7. Miraç Fatih İLGÜN, 2020. "Industry 4.0 and Transformation in Public Finance: An Assessment by Government Expenditures," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(44).
    8. Nguyen Dang Tuan, Minh & Nguyen Thanh, Nhan & Le Tuan, Loc, 2019. "Applying a mindfulness-based reliability strategy to the Internet of Things in healthcare – A business model in the Vietnamese market," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 54-68.
    9. Han, Chunjia & Yang, Mu & Piterou, Athena, 2021. "Do news media and citizens have the same agenda on COVID-19? an empirical comparison of twitter posts," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    10. Yu, Wantao & Zhao, Gen & Liu, Qi & Song, Yongtao, 2021. "Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    11. Jiang, Syuan-Yi, 2022. "Transition and innovation ecosystem – investigating technologies, focal actors, and institution in eHealth innovations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Yang, Xiaoping & Cao, Dongmei & Andrikopoulos, Panagiotis & Yang, Zonghan & Bass, Tina, 2020. "Online social networks, media supervision and investment efficiency: An empirical examination of Chinese listed firms," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    13. Martínez-Caro, Eva & Cegarra-Navarro, Juan Gabriel & Alfonso-Ruiz, Francisco Javier, 2020. "Digital technologies and firm performance: The role of digital organisational culture," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    14. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
    15. Yingtian Li, 2023. "A Multi-Step Interaction Opinion Dynamics Group Decision-Making Method and Its Application in Art Evaluation," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 12(1), pages 1-14, January.
    16. Tang, Ming & Liao, Huchang, 2021. "From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey," Omega, Elsevier, vol. 100(C).
    17. Piñeiro-Chousa, Juan & López-Cabarcos, M.Ángeles & Ribeiro-Soriano, Domingo, 2020. "Does investor attention influence water companies’ stock returns?," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    18. Fabio Nappo & Alessandra Lardo & Maria Teresa Bianchi & Federico Schimperna, 2023. "The impact of digitalisation on professional football clubs," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2023(2), pages 117-136.
    19. Agrawal, Smita & Patel, Atul, 2021. "SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    20. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006557. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.