Nurse Continuity and Hospital-Acquired Pressure Ulcers: A Comparative Analysis Using an Electronic Health Record "Big Data" Set

Standardizing nursing data extracted from electronic health records for integration into a statewide clinical data research network

BACKGROUND

Care plans documented by nurses in electronic health records (EHR) are a rich source of data to generate knowledge and measure the impact of nursing care. Unfortunately, there is a lack of integration of these data in clinical data research networks (CDRN) data trusts, due in large part to nursing care being documented with local vocabulary, resulting in non-standardized data. The absence of high-quality nursing care plan data in data trusts limits the investigation of interdisciplinary care aimed at improving patient outcomes.

OBJECTIVE

To map local nursing care plan terms for patients' problems and goals in the EHR of one large health system to the standardized nursing terminologies (SNTs), NANDA International (NANDA-I), and Nursing Outcomes Classification (NOC).

METHODS

We extracted local problems and goals used by nurses to document care plans from two hospitals. After removing duplicates, the terms were independently mapped to NANDA-I and NOC by five mappers. Four nurses who regularly use the local vocabulary validated the mapping.

RESULTS

83% of local problem terms were mapped to NANDA-I labels and 93% of local goal terms were mapped to NOC labels. The nurses agreed with 95% of the mapping. Local terms not mapped to labels were mapped to the domains or classes of the respective terminologies.

CONCLUSION

Mapping local vocabularies used by nurses in EHRs to SNTs is a foundational step to making interoperable nursing data available for research and other secondary purposes in large data trusts. This study is the first phase of a larger project building, for the first time, a pipeline to standardize, harmonize, and integrate nursing care plan data from multiple Florida hospitals into the statewide CDRN OneFlorida+ Clinical Research Network data trust.

Future advancement of health care through standardized nursing terminologies: reflections from a Friends of the National Library of Medicine workshop honoring Virginia K. Saba

OBJECTIVE

To honor the legacy of nursing informatics pioneer and visionary, Dr. Virginia Saba, the Friends of the National Library of Medicine convened a group of international experts to reflect on Dr. Saba's contributions to nursing standardized nursing terminologies.

PROCESS

Experts led a day-and-a-half virtual update on nursing's sustained and rigorous efforts to develop and use valid, reliable, and computable standardized nursing terminologies over the past 5 decades. Over the course of the workshop, policymakers, industry leaders, and scholars discussed the successful use of standardized nursing terminologies, the potential for expanded use of these vetted tools to advance healthcare, and future needs and opportunities. In this article, we elaborate on this vision and key recommendations for continued and expanded adoption and use of standardized nursing terminologies across settings and systems with the goal of generating new knowledge that improves health.

CONCLUSION

Much of the promise that the original creators of standardized nursing terminologies envisioned has been achieved. Secondary analysis of clinical data using these terminologies has repeatedly demonstrated the value of nursing and nursing's data. With increased and widespread adoption, these achievements can be replicated across settings and systems.

The association between nurse continuity and hypospadias repair patient outcomes: A retrospective study

BACKGROUND

Recently, nurse continuity, the intensity and consistency of a patient's exposure to nurses during hospitalization, has been shown to be associated with patient outcomes. However, little is known about how nurse continuity is related to patients' surgical outcomes.

AIMS

To examine the association between nurse continuity and outcomes of hypospadias repair to clarify the importance of nurse continuity as a nursing practice.

DESIGN

This is a retrospective study.

METHODS

We analysed the data from electronic health records of patients under 1 year who had undergone proximal hypospadias repair between January 2014 and December 2016. Nurse continuity was measured using the Continuity of Care Index. Since approximately half of the patients reportedly needed further operations in the long term, the primary outcome was whether patients with proximal hypospadias repair had two or more additional operations within 3 years of discharge.

RESULTS

The rate of undergoing two or more follow-up operations in 3 years was significantly higher in patients with low nurse continuity-38.6% versus 12.8% for high continuity.

CONCLUSION

This study identified nurse continuity as an important factor related to patients' surgical outcomes. These findings suggest that nurse continuity be considered an important nursing strategy for patient outcomes and further research is needed on this topic.

IMPACT STATEMENT

As empirical evidence regarding the association between nurse continuity and patient outcomes grows, nurse managers and policymakers should view nurse continuity as a critical factor for positive patient outcomes when considering nursing workforce regulations.

NO PATIENT OR PUBLIC CONTRIBUTION

The data for this study were obtained from electronic health records, and the entire process of this study did not involve patient or public participation.

Taking command of continuity-An interview study with agency nurses

AIM

The aim of the study was to describe continuity from the perspective of working as an agency nurse (AN).

DESIGN

Qualitative design was applied using individual semi-structured interviews.

METHOD

Individual interviews with fifteen registered nurses working at agency companies were conducted in 2020. The interviews were analyzed with thematic analysis. The study followed the guidelines addressed in the COREQ (Consolidated Criteria for Reporting Qualitative Research) framework.

RESULTS

Thematic analysis yielded one theme - standing strong and taking command - and four categories: being competent and experienced, being prepared and at ease, ensuring an unbroken chain of care, and belonging on my own terms. The categories illustrated the engagement, professionalism, and natural leadership showed by the ANs to uphold quality and continuity.

Conducting a representative national randomized control trial of tailored clinical decision support for nurses remotely: Methods and implications

Clinical Decision Support (CDS) systems, patient specific evidence delivered to clinicians via the electronic health record (EHR) at the right time and in the right format, has the potential to improve patient outcomes. Unfortunately, outcomes of CDS research are mixed. A potential cause lies in its testing. Many CDS are implemented in practice without sufficient testing, potentially leading to patient harm. When testing is conducted, most research has focused on "what" evidence to provide with little attention to the impact of the CDS display format (e.g., textual, graphical) on the user. In an adequately powered randomized control trial with 220 hospital based registered nurses, we will compare 4 randomly assigned CDS format groups (text, text table, text graphs, tailored to subject's graph literacy score) for effects on decision time and simulated patient outcomes. We recruit using state based professional registries, which allows access to participants from multiple institutions across the nation. We use online survey software (REDCap) for efficient study workflow including screening, informed consent documentation, pre-experiment demographic data collection including a graph literacy questionnaire used in randomization. The CDS prototype is accessed via a web app and the simulation-based experiment is conducted remotely at a subject's local computer using video-conferencing software. Also included are 6 post intervention surveys to assess cognitive workload, usability, numeracy, format preference, CDS utilization rationale, and CDS interpretation. Our methods are replicable and scalable for testing of health information technologies and have the potential to improve the safety and effectiveness of these technologies across disciplines.

Nurse Cognition, Decision Support, and Barcode Medication Administration: A Conceptual Framework for Research, Practice, and Education

This article synthesizes theoretical perspectives related to nurse cognition. We present a conceptual model that can be used by multiple stakeholders to study and contemplate how nurses use clinical decision support systems, and specifically, Barcode-Assisted Medication Administration, to make decisions during the delivery of care. Theoretical perspectives integrated into the model include dual process theory, the Cognitive Continuum Theory, human factors engineering, and the Recognition-Primed Decision model. The resulting framework illustrates the process of nurse cognition during Barcode-Assisted Medication Administration. Additionally, the model includes individual or human and environmental factors that may influence nurse cognition and decision making. It is important to consider the influence of individual, human, and environmental factors on the process of nurse cognition and decision making. Specifically, it is necessary to explore the impact of heuristics and biases on clinician decision making, particularly related to the development of alarm and alert fatigue. Aided by the proposed framework, stakeholders may begin to identify heuristics and cognitive biases that influence the decision of clinicians to accept or override a clinical decision support system alert and whether heuristics and biases are associated with inappropriate alert override.

Secondary use of standardized nursing care data for advancing nursing science and practice: a systematic review

OBJECTIVE

The study sought to present the findings of a systematic review of studies involving secondary analyses of data coded with standardized nursing terminologies (SNTs) retrieved from electronic health records (EHRs).

MATERIALS AND METHODS

We identified studies that performed secondary analysis of SNT-coded nursing EHR data from PubMed, CINAHL, and Google Scholar. We screened 2570 unique records and identified 44 articles of interest. We extracted research questions, nursing terminologies, sample characteristics, variables, and statistical techniques used from these articles. An adapted STROBE (Strengthening The Reporting of OBservational Studies in Epidemiology) Statement checklist for observational studies was used for reproducibility assessment.

RESULTS

Forty-four articles were identified. Their study foci were grouped into 3 categories: (1) potential uses of SNT-coded nursing data or challenges associated with this type of data (feasibility of standardizing nursing data), (2) analysis of SNT-coded nursing data to describe the characteristics of nursing care (characterization of nursing care), and (3) analysis of SNT-coded nursing data to understand the impact or effectiveness of nursing care (impact of nursing care). The analytical techniques varied including bivariate analysis, data mining, and predictive modeling.

DISCUSSION

SNT-coded nursing data extracted from EHRs is useful in characterizing nursing practice and offers the potential for demonstrating its impact on patient outcomes.

CONCLUSIONS

Our study provides evidence of the value of SNT-coded nursing data in EHRs. Future studies are needed to identify additional useful methods of analyzing SNT-coded nursing data and to combine nursing data with other data elements in EHRs to fully characterize the patient's health care experience.

The Byzantine Role of Big Data Application in Nursing Science: A Systematic Review

Big data have the potential to determine enhanced decision-making process and to personalize the approach of delivering care when applied in nursing science. So far, the literature on this topic is still not synthesized for the period between 2014 and 2018. Thus, this systematic review aimed to identify and synthesize the most recent evidence on big data application in nursing research. The systematic search was undertaken for the evidence published from January 2014 to May 2018, and the outputs were formatted using the PRISMA Flow Diagram, whereas the quality appraisal was addressed by recommendations consistent with the Critical Appraisal Skills Program. Twelve studies on big data in nursing were included and divided into two themes: the majority of the studies aimed to determine prediction assessment, while only four studies were related to the impact of big data applications to support clinical practice. This review tracks the recent state of knowledge on big data applications in nursing science, revealing the potential for nursing engagement in big data science, even if currently limited to some fields. Big data applications in nursing might have a tremendous potential impact, but are currently underused in research and clinical practice.

Association between continuity of nursing care and older adults' hospitalization outcomes: A retrospective observational study

AIM

To assess the relationship between continuity in nursing assignment in older adults' acute hospitalization and patient experience and functional decline.

BACKGROUND

In-hospital functional decline affects up to 40% of hospitalized older adults. Nurses are responsible for performing functioning-preserving interventions. Whether continuity of nursing care contributes to patients' functional outcomes is unclear.

METHOD

A retrospective observational study of 609 patients aged ≥70 admitted to internal medicine units. Patients were surveyed on their functional (cognitive and physical) status and satisfaction with the hospital care experience. Dispersion and sequence of nursing assignment were measured by the Continuity of Care Index and Sequential Continuity Index. Multivariate logistic regressions were modelled for each continuity score and outcome.

RESULTS

Achieving 25% of the maximum Continuity of Care Index was associated with lower odds of cognitive decline (OR = 0.64, 95% CI = 0.43-0.94) and higher odds of satisfaction (OR = 1.52, 95% CI = 1.06-2.17). Achieving 25% of the maximum Sequential Continuity Index was associated only with higher odds of satisfaction (OR = 1.43, 95% CI = 1.01-2.02). Continuity scores were not associated with physical functioning decline.

CONCLUSION

Continuity in nursing assignment is related to a positive patient experience and cognitive functioning of hospitalized older adults.

IMPLICATIONS FOR NURSING MANAGEMENT

Continuity should be prioritized in scheduling and assignment algorithms.

Nursing Care for Hospitalized Older Adults With and Without Cognitive Impairment

BACKGROUND

The presence of cognitive impairment (CI) among hospitalized older adults (aged 85 years and older) could interfere with the identification and treatment of other important symptoms experienced by these patients. Little is known, however, about the nursing care provided to this group. Contrasting the nursing care provided to patients with and without CI may reveal important insights about symptom treatment in the CI population.

OBJECTIVE

The aim of this study was to examine the relationship of CI to nursing care provided and length of stay for hospitalized older adults using standardized nursing data retrieved from electronic health records.

METHODS

We conducted a comparative secondary data analysis. A data set of standardized nursing plan of care data retrieved from electronic health record data of nine units at four hospitals was analyzed. The plan of care data for this study were previously transformed into one of eight categories (family, well-being, mental comfort, physical comfort, mental, safety, functional, and physiological care). Fisher exact tests were used to compare the differences in the nursing care for hospitalized older adults with and without CI. Mixed-effects models were used to examine associations of patient's cognitive status and nursing care, and cognitive status and length of stay.

RESULTS

We identified 4,354 unique patients; 746 (17%) had CI. We observed that older adults with CI were less likely to receive physical comfort care than those without CI for seven of nine units. Older adults' cognitive status was associated with the delivery of mental comfort care. In addition, a worsening in cognitive status was associated with an increase in length of stay for older adults with CI.

DISCUSSION

Older adults with CI appeared to be undertreated for symptoms of pain when compared to those without CI across units. There is a need for further research to improve symptom recognition and management for this population. The presence of CI was associated with variation in nursing care provided and length of stay. Future studies that include the analysis of nursing data merged with elements stored in the electronic health record representing the contributions of other health professions are expected to provide additional insights into this gap.

Prevalence of pressure ulcers in hospitalised patients: a cross-sectional study

OBJECTIVE

The main aim of this study was to estimate the prevalence of pressure ulcers (PU) and related risk factors of PU development in hospitalised patients in Italy. Furthermore, the study investigated the association between risk factors for PU present on admission and the development during hospitalisation (hospital-acquired pressure ulcer, HAPU).

METHODS

A cross-sectional study, using two separate designs at two separate timepoints: 2010 and 2015. The methodology used to measure PU prevalence was that recommended by the European Pressure Ulcer Advisory Panel (EPUAP).

RESULTS

The total sample was 7681 hospitalised patients (3011 patients in 2010, 4670 in 2015). Prevalence of PU in hospital was 19.5% in 2010 and 17% in 2015. The number of patients with PU present on admission were 9.60% in 2010 and 9.42% in 2015. Patients with HAPU were 5.08% in 2010 and 5.87% in 2015. Older age and comorbidities, and a total Braden score of ≤16 were positively associated with PU present on admission and HAPU in hospitals (p<0.05). A longer length of stay appeared to correlate positively with a better clinical outcome for PU if there were already present on admission. Heterogeneous results emerged for length of stay of >30 days and being admitted to intensive care unit (ICU).

CONCLUSION

Our results are comparable with other European and Italian studies. Most of the risk factors associated with PU development have been confirmed. However, further studies are needed to examine the effects of context on PU present on arrival and HAPU, especially regarding hospital length of stay.

The pressure injury predictive model: A framework for hospital-acquired pressure injuries

BACKGROUND

Despite decades of research, pressure injuries continue to be a source of significant pain and delayed recovery for patients and substantial quality and cost issues for hospitals. Consideration of the current thinking around pressure injury risk must be evaluated to improve risk assessments and subsequent nursing interventions aimed at reducing hospital-acquired pressure injuries.

DESIGN

This is a discursive paper using Walker and Avant's (2005) theory synthesis framework to examine the relevance of existing pressure injury models as they align with the current literature.

METHODS

PubMed and CINAHL indexes were searched, first for conceptual models and then for pressure injury research conducted on hospitalised patients for the years 2006-2016. A synthesis of the searches culminated into a new pressure injury risk model.

CONCLUSIONS

Gaps in previous models include lack of attention to the environment, contributing episode-of-care factors and the dynamic nature of injury risk for patients. Through theory synthesis, the need for a new model representing the full risk for pressure injury was identified. The Pressure Injury Predictive Model is a representation of the complex and dynamic nature of pressure injury risk that builds on previous models and addresses new patient, contextual and episode-of-care process influences. The Pressure Injury Predictive Model (PIPM) provides a more accurate picture of the complexity of contextual and process factors associated with pressure injury development.

RELEVANCE TO CLINICAL PRACTICE

Using the PIPM to determine risk can result in improved risk identification. This information can be used to implement targeted, evidence-based pressure injury prevention interventions specific to the patient risk profile, thus limiting unwarranted and unnecessary care.

Effect of preventive care interventions on pressure ulcer rates in a national sample of rural and urban nursing units: Longitudinal associations over 4 years

BACKGROUND

Pressure ulcer rates are persistently high despite years of research and practice policies focused on prevention. Prior research found crosssectional associations between care interventions, hospital and nursing unit characteristics and pressure ulcer rates. Whether these associations persist over time is unknown. Finally, comparisons of quality measures across rural and urban location have mixed findings.

OBJECTIVE

Our study examined effects of care interventions on unit-acquired pressure ulcer rates over 4 years controlling for community, hospital, and nursing unit characteristics in rural and urban locations.

DESIGN

Guided by contingency theory a longitudinal study was conducted to examine associations between context, staffing, care interventions, nurse outcomes, and pressure ulcer rates, using unit-level data from the National Database of Nursing Quality Indicators^Ⓡ 2010-2013 (16 quarters) augmented with data on rural classifications and case mix index. Ulcer rates were measured as percentage of patients with a nursing unit-acquired pressure ulcer. The three care interventions were unit-percentage of patients receiving skin assessment on admission, receiving risk assessment on admission, and receiving any risk assessment before the pressure ulcer. Nursing unit characteristics were RN staffing, education, and experience. Nurse outcomes were job satisfaction and intent-to-stay.

PARTICIPANTS

We included 5761 units (332 rural and 5429 urban) in 772 hospitals (89 rural and 683 urban) that reported ulcer rates in two or more quarters during the study period.

METHODS

Rural and urban units were examined separately using multilevel binomial regression in which within-unit changes in pressure ulcer rates were related to the within-unit changes in the explanatory variables, controlling for region, hospital size, unit type, case mix index, and percentage of patients at risk for pressure ulcers.

RESULTS

An increase in the three care interventions, RN skill mix, and the two nurse outcomes were associated with a decrease in unit-acquired pressure ulcers. For example, in rural units a 10% increase in unit-percentage of any risk assessment and in urban units a 10% increase in skin assessment on admission were associated with a 21% and 5% decrease in the odds of developing an ulcer. A 10% increase in RN skill mix was associated with 17-18% and 5-6% decrease in ulcer rates in rural and urban units respectively.

CONCLUSION

Hospitals aiming to improve pressure ulcer prevention should focus on organizational structures that support improved nurses work environments and workflow that will enhance nursing care interventions. Future studies should include both contextual and patient characteristics along with care interventions.

Evidence of Progress in Making Nursing Practice Visible Using Standardized Nursing Data: a Systematic Review

Nursing care documentation in electronic health records (EHRs) with standardized nursing terminologies (SNTs) can facilitate nursing's participation in big data science that involves combining and analyzing multiple sources of data. Before merging SNTs data with other sources, it is important to understand how such data are being used and analyzed to support nursing practice. The main purpose of this systematic review was to identify studies using SNTs data, their aims and analytical methods. A two-phase systematic process resulted in inclusion and review of 35 publications. Aims of the studies ranged from describing most popular nursing diagnoses, outcomes, and interventions on a unit to predicting outcomes using multi-site data. Analytical techniques varied as well and included descriptive statistics, correlations, data mining, and predictive modeling. The review underscored the value of developing a deep understanding of the meaning and potential impact of nursing variables before merging with other sources of data.

Continuity Index Measures in the Acute Care Hospital Setting: An Analytic Review and Tests Using Electronic Health Record Data and Computer Simulation

BACKGROUND AND PURPOSE

Multiple continuity indexes are available; however, their properties are insufficiently understood for examining the influence of nurse staffing patterns on patient outcomes. We conceptually and analytically examined continuity measures to reveal their properties and relationships with each other and identify potential limitations.

METHODS

We examined behavior of continuity indexes as applied to clinical practice data that were collected with the HANDS (Hands-On Automated Nursing Data System) and data from computer simulation.

RESULTS

Studied continuity measures exhibited very different statistical characteristics. Most importantly, many continuity measures contain a length-of-stay dependent term that is uncorrelated with continuity.

CONCLUSION

Findings provide a deep understanding of the conceptual foundations and properties of various continuity measures. Using findings, researchers can select proper measures and better interpret analysis outcomes.

Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress

Objective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research.

Implementation of Electronic Health Records in US Nursing Homes

While electronic health records have emerged as promising tools to help improve quality of care, nursing homes have lagged behind in implementation. This study assessed electronic health records implementation, associated facility characteristics, and potential impact on quality indicators in nursing homes. Using national Centers for Medicare & Medicaid Services and survey data for nursing homes, a cross-sectional analysis was conducted to identify variations between nursing homes that had and had not implemented electronic health records. A difference-in-differences analysis was used to estimate the longitudinal effect of electronic health records on commonly used quality indicators. Data from 927 nursing homes were examined, 49.1% of which had implemented electronic health records. Nursing homes with electronic health records were more likely to be nonprofit/government owned (P = .04) and had a lower percentage of Medicaid residents (P = .02) and higher certified nursing assistant and registered nurse staffing levels (P = .002 and .02, respectively). Difference-in-differences analysis showed greater quality improvements after implementation for five long-stay and two short-stay quality measures (P = .001 and .01, respectively) compared with those who did not implement electronic health records. Implementation rates in nursing homes are low compared with other settings, and better-resourced facilities are more likely to have implemented electronic health records. Consistent with other settings, electronic health records implementation improves quality in nursing homes, but further research is needed to better understand the mechanism for improvement and how it can best be supported.

Patients Negatively Impacted by Discontinuity of Nursing Care During Acute Hospitalization

BACKGROUND

Continuity of nursing care in hospitals remains poor and not prioritized, and we do not know whether discontinuous nursing care is negatively impacting patient outcomes.

OBJECTIVES

This study aims to examine nursing care discontinuity and its effect on patient clinical condition over the course of acute hospitalization.

RESEARCH DESIGN

Retrospective longitudinal analysis of electronic health records (EHR). Average point-in-time discontinuity was estimated from time of admission to discharge and compared with theoretical predictions for optimal continuity and random nurse assignment. Mixed-effects models estimated within-patient change in clinical condition following a discontinuity.

SUBJECTS

A total of 3892 adult medical-surgical inpatients were admitted to a tertiary academic medical center in the Eastern United States during July 1, 2011 and December 31, 2011.

MEASURES

Exposure: discontinuity of nursing care was measured at each nurse assessment entry into a patient's EHR as assignment of the patient to a nurse with no prior assignment to that patient.

OUTCOME

patient's clinical condition score (Rothman Index) continuously tracked in the EHR.

RESULTS

Discontinuity declined from nearly 100% in the first 24 hours to 70% at 36 hours, and to 50% by the 10th postadmission day. Discontinuity was higher than predicted for optimal continuity, but not random. Each instance of discontinuity lead to a 0.12-0.23 point decline in the Rothman Index score, with more pronounced effects for older and high-mortality risk patients.

CONCLUSIONS

Discontinuity in acute care nurse assignments was high and negatively impacted patient clinical condition. Improved continuity of provider-patient assignment should be advocated to improve patient outcomes in acute care.

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

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.

Framework for Mining and Analysis of Standardized Nursing Care Plan Data

Despite an unprecedented amount of health-related data being amassed from various technological innovations, our ability to process this data and extract hidden knowledge has yet to catch up with this explosive growth. Although nursing care plans can be an effective tool to support the achievement of desired patient outcomes, their online collection, storage, and processing is lagging far behind. As a result, the impact of nursing care is not well understood from qualitative as well as quantitative perspectives. In this article, we first outline a complete life cycle of nursing care data, and present a knowledge discovery and analysis framework for such data sets. We also highlight Big Data issues pertaining to the analysis of nursing care data. Using an exemplar data set, we demonstrate the broad applicability of the proposed framework by showing knowledge discovery results for different outcomes related to patients, nursing staff, and administrators.

Big data science: A literature review of nursing research exemplars

BACKGROUND

Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge.

PURPOSE

The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals.

METHODS

A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice.

DISCUSSION

Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods.

CONCLUSION

There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science.

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term "Big Data", which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.