A call to action: Engage in big data science

Clancy, Thomas R.; Bowles, Kathryn H.; Gelinas, Lillee; Androwich, Ida M.; Delaney, Connie W; Matney, Susan; Sensmeier, Joyce; Warren, Judith J.; Welton, John; Westra, Bonnie L.

doi:10.1016/j.outlook.2013.12.006

Cited by 28 publications

(19 citation statements)

References 2 publications

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“…A large proportion of Google searches on these keywords returns results that are irrelevant to their intrinsic semantics and scope, or simply repeat familiar arguments about the needs of data science and existing phenomena. In many such findings [5], [54], [17], [29], [2], [25], [50], [39], [40], [18], [55], [45], [49], [23], [36], [41], [48], [34], [35], [43], [21], [15], [53], [31], [33], big data is described as being simple, data science has nothing to do with the science of data, and advanced analytics is the same as classic data analysis and information processing. There is a lack of deep thinking and exploration of why, what and how these new terms should be defined, developed and applied.…”

Section: A About Data Science Conceptsmentioning

confidence: 99%

Data Science: Nature and Pitfalls

Cao

2016

IEEE Intell. Syst.

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Section: A About Data Science Conceptsmentioning

confidence: 99%

Data Science: Nature and Pitfalls

Cao

2016

IEEE Intell. Syst.

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“…Not understanding the necessity of balancing the technology-practice platform polarity is a major barrier to appreciating and adopting standardization of practice standards and data. Several national calls for action for "sharable and comparable" data to support practice and translational research have also been identified which would include data related to the SBDH (Big Data Proceedings Report, 2013; Clancy et al, 2014;Nursing Knowledge Proceedings Report, 2014;Westra. et al, 2015).…”

Section: Lack Of Commitment To Standardization Of Clinical Practice mentioning

confidence: 99%

Putting “health” in the electronic health record: A call for collective action

2015

Nursing Outlook

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The American Academy of Nursing (Academy) endorses the capturing of social and behavioral determinants of health in the electronic health record (EHR). For this to happen, action must be taken to identify specific social and behavioral determinants of health (SBHD) to be included in a parsimonious panel to foster standardization and promote interoperability. Despite rapid technological advancements in the U.S. health system, care remains fragmented, uncoordinated, costly, and yields poor population health outcomes. Clinical care currently accounts for only 20 percent of health outcomes. To improve care and population health outcomes, healthcare providers must address other factors, including social determinants of health. To do this, we must first focus on addressing the variability in capturing and documenting social determinants in order to use this health data to benefit patients. Timing for action is now to leverage the recommendations within the Institute of Medicine (IOM) 2014 report Capturing Social and Behavioral Domains and Measures in Electronic Health Records (Phase 1 and Phase 2) (IOM, 2014a, 2014b) and to inform the regulations for the third stage of meaningful use incentive program. Meaningful Use Stage 3 is in development, and implementation for this stage is expected to start in 2017. This Policy Brief provides the Academy's recommendations for "collective action" required of multiple stakeholders to include social and behavioral determinants of health to really put "health" in electronic health records to improve care and health outcomes. Multiple stakeholders include, but are not limited to, patients, families, population aggregates, providers, healthcare organizations, professional organizations, and industry partners. Lack of Consistency and Ease of Use of Clinical Workflow within EHR Technology Usability and clinical application design of EHR technology has long been a concern for nurses at the point

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“…(1) Advocate for the adoption of Systematized Nomenclature of Medicine -Clinical Terminology (SNOMED-CT) and Logical Observation Identifiers Names and Codes (LOINC) as national standards for clinical data, and link them with nursing terminologies through mappings; (2) Develop a strategy/campaign for educating front line nurses, students, and faculty on informatics competencies and the value of standardized nursing data; (3) Convene a consensus conference with leaders of the major nursing organizations and inter-professional stakeholders to educate them, hear their views, and ultimately speak in one voice; (4) Refresh and activate the American Nurses Association's Nursing Information & Data Set Evaluation Center (NIDSEC) criteria to advance systems that represent and value nursing data; and (5) Continue bold participation in standards and EHR standards development to ensure a nursing voice. (Clancy et al, 2014) These recommendations have several strengths including supporting the need for nursing terminology and database standards. In addition, there is a laudable call for greater participation by the profession in the development of standards and EHRs that will impact nursing.…”

Section: Introductionmentioning

confidence: 99%

A Shovel‐Ready Solution to Fill the Nursing Data Gap in the Interdisciplinary Clinical Picture

Keenan

Lopez

Sousa

et al. 2017

Int J of Nursing Knowl

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PURPOSE To critically evaluate 2014 American Academy of Nursing (AAN) call‐to‐action plan for generating interoperable nursing data. DATA SOURCES Healthcare literature. DATA SYNTHESIS AAN's plan will not generate the nursing data needed to participate in big data science initiatives in the short term because Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine – Clinical Terms are not yet ripe for generating interoperable data. Well‐tested viable alternatives exist. CONCLUSIONS Authors present recommendations for revisions to AAN's plan and an evidence‐based alternative to generating interoperable nursing data in the near term. These revisions can ultimately lead to the proposed terminology goals of the AAN's plan in the long term.

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A call to action: Engage in big data science

Cited by 28 publications

References 2 publications

Data Science: Nature and Pitfalls

Data Science: Nature and Pitfalls

Putting “health” in the electronic health record: A call for collective action

A Shovel‐Ready Solution to Fill the Nursing Data Gap in the Interdisciplinary Clinical Picture

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