4 Big data The use of big data in healthcare continues to generate intense

4 big data the use of big data in healthcare

This preview shows page 10 - 12 out of 16 pages.

4. Big data The use of big data in healthcare continues to generate intense interest. Just how big is healthcare big data? One measure from 2012 equated the data amount at around 500 petabytes or, in paper terms, enough data to fill 10 billion four-drawer file cabinets ( Roski et al., 2014 ). “The emergence of ‘big data’ offers unprecedented opportunities for not only accelerating scientific advances, but also enabling new modes of discovery” ( Honavar, 2014 , p. 329). There is much speculation about the prospects of pairing massive data reservoirs with predictive analytic tools and identifying healthcare crises before they even begin. Data mining and predictive analytics are presented as opportunities to forecast patient demand for service, such as emergency department visits ( Ekstrom et al., 2015 ); to tailor diagnosis and patient interventions ( Krumholz,
Image of page 10
2014; Roski et al., 2014 ); to discover patterns that may have otherwise gone unnoticed in particular patient populations ( Roski et al., 2014 ); or potentially in epidemic situations ( Grossglauser and Saner, 2014 ); and in tracking and providing automated responses to collected patient data to their care providers. Further specialization of predictive analytics can also support medical decision and triage of care, although ethical concerns abound in these applications, with calls for additional research and training in this area ( Cohen et al., 2014 ). Consideration should be given to establishing or expanding dedicated informatics courses in nursing curriculums to manage these specific learning needs. A broad approach to health informatics that includes the critical importance of social justice and patient centered approaches to technological use and development should frame these opportunities. The ever-present issue of patient privacy and data security must also be considered ( Amarasingham et al., 2014; Roski et al., 2014 ). Future demands aside, there are urgent current needs for additional healthcare personnel with specific data management or analytic skills ( Krumholz, 2014 ) as well as further collaborations between informed clinicians and computer science teams ( Honavar, 2014 ). 5. Patient engagement and empowerment The issue of patient engagement, from a technology perspective, has largely been tied to opportunities for patients to access and contribute to their own healthcare data ( Chunchu et al., 2012; Giardina et al., 2014; Goldzweig et al., 2013 ). Patient EHR portals, PHRs, one-note or other shared provider patient data collection, and increased e-visits or other electronic communication with healthcare team members have all been presented as ways to increase sense of ownership for patients with the hopes that improved outcomes will follow. There is considerable research to support patient desire to have improved access to their healthcare data, be it through EHRs or other technology applications( Chunchu et al., 2012; Giardina et al., 2014; Goldzweig et al., 2013 ). Patients will present with great differences in digital literacy and even basic computer skills and nurses should take the lead in either providing the needed patient
Image of page 11
Image of page 12

You've reached the end of your free preview.

Want to read all 16 pages?

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture