Wisdom within: unlocking the potential of big data for nursing regulators

Blumer, Lawrence S.; Giblin, Cathy; Lemermeyer, Gillian; Kwan, Jennifer

doi:10.1111/inr.12315

Cited by 10 publications

(15 citation statements)

References 2 publications

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“…Extracting knowledge from big data and process mining has been examined and promoted in recent years to inform the execution of workflow processes, check conformance with guidelines, and find improvement opportunities in healthcare and nursing. [17][18][19][20][21] This study focused on an electronic nursing admission assessment form which is one of the most common forms for communicating nursing care in Australia. This is important particularly because more Australian hospitals are moving towards fully adopting eMR-based technologies to manage patient care processes and multidisciplinary communication.…”

Section: Introductionmentioning

confidence: 99%

Completion of electronic nursing documentation of inpatient admission assessment: insights from Australian metropolitan hospitals

Shala

Jones

Fairbrother

et al. 2021

Preprint

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INTRODUCTION: Electronic nursing documentation is an essential aspect of inpatient care and multidisciplinary communication. Analysing data in electronic medical record (eMR) systems can assist in understanding clinical workflows, improving care quality, and promoting efficiency in the healthcare system. This study aims to assess timeliness of completion of an electronic nursing admission assessment form and identify patient and facility factors associated with form completion in three metropolitan hospitals. MATERIALS AND METHODS: Records of 37,512 adult inpatient admissions (November 2018-November 2019) were extracted from the hospitals eMR system. A dichotomous variable descriptive of completion of the nursing assessment form (Yes/No) was created. Timeliness of form completion was calculated as the interval between date and time of admission and form completion. Univariate and multivariate multilevel logistic regression were used to identify factors associated with form completion. RESULTS: An admission assessment form was completed for 78.4% (n=29,421) of inpatient admissions. Of those, 78% (n=22,953) were completed within the first 24 hours of admission, 13.3% (n=3,910) between 24-72 hours from admission, and 8.7% (n=2558) beyond 72 hours from admission. Patient length of hospital stay, admission time, and admitting units nursing hours per patient day were associated with form completion. Patient gender, age, and admitting unit type were not associated with form completion. DISCUSSION: Form completion rate was high, though more emphasis needs to be placed on the importance of timely completion to allow for adequate patient care planning. Staff education, qualitative understanding of delayed form completion, and streamlined guidelines on nursing admission and eMR use are recommended.

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Section: Introductionmentioning

confidence: 99%

Completion of electronic nursing documentation of inpatient admission assessment: insights from Australian metropolitan hospitals

Shala

Jones

Fairbrother

et al. 2021

Preprint

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“…Working with data in active administrative databases poses quality control challenges (Blumer et al. ; Statistics Canada ). In addition, CARNA transitioned to a new client management database in May 2013, which required significant alignment of data codes.…”

Section: Discussionmentioning

confidence: 99%

The evaluation of evidence‐informed changes to an internationally educated nurse registration process

Kwan

Wang

Cummings

et al. 2019

International Nursing Review

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Aim To evaluate effectiveness of specific policy and practice changes to the process of registration for internationally educated nurses. Background Little research exists to inform registration policy for internationally educated health professionals. Introduction Internationally educated nurse employment can help address nursing shortages. Regulators assess competencies for equivalency to Canadian‐educated nurses, but differences in health systems, education and practice create challenges. Methods The study setting was a Canadian province. We used a mixed methods approach, with a pre–post‐quasi‐experimental design and a qualitative evaluation. Previous analysis of relationships between applicant variables, registration outcomes and timelines informed changes to our registration process. Implementation of these changes composes the intervention. Comparisons between pre‐ and post‐implementation exemplar subgroups and timeline analyses were conducted using descriptive statistics, univariate analysis and non‐parametric tests. Data were collected from complete application files before (n = 426) and after (n = 287) implementation of the intervention. Interviews, focus groups and consultations were completed with various stakeholders. Findings The time between steps in the process was significantly reduced following implementation. Stakeholders reported an increase in perceived efficiency, transparency and use of evidence. Discussion Results indicated that initial impacts of the policy changes streamlined the process for applicants and staff. Conclusion Maintaining a consistent and systematic review of an organization's data coupled with implementation of findings to effect policy and practice change may have an important impact on regulatory policy. Implications for Nursing Policy These findings represent the beginning of an international policy conversation. Policy changes based on organizational data can underlie major process improvement initiatives. Ongoing nursing shortages across the globe and increasing mobility of nurses make it important to have efficient and transparent regulatory policy informed by evidence.

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“…Incorporating significant amounts of data into the decision‐making and healthcare policy development process results in evidence‐informed policies that are more easily analysed, reviewed, revised and updated (Blumer et al. ). Aggregated data will allow provision of information that will serve as the basis of health policies in the region.…”

Section: Implications For Nursing and Health Policymentioning

confidence: 99%

Construction and usability of community health nursing database in rural north‐eastern Thailand

Arakawa

Ota

Piyabanditkul

et al. 2018

International Nursing Review

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515-523Introductions: Digitization could be incorporated in rural areas of resource-poor countries because information gathered by nurses working on-site could be better used. Background: For effective management of community health information, the usage and maintenance of digital records are important. Digitization of information provides essential information for informing health policy. Aim: To develop a sustainable database to effectively collect and manage community health information and nursing practice. Methods: This study used a mixed method design. Phase 1 involved the development of a database system through repeated systematic focus group discussions with community health nurses. Phase 2 involved a practical trial examination of the developed system with both objective and subjective evaluations. Results: A nursing database system was developed with templates designed for the major health problems of communities. The templates were composed of multiple-choice items and a free-text field that allowed records to be more detailed than handwritten records and maintained in standardized formats. This enables accumulation of data that were less likely to be influenced by the variance of ability in each nurse. Discussion and conclusion: A multifaceted evaluation of the database system suggested that it could improve the efficiency of information management and contribute to the improvement of nursing care quality through standardization of the recording pattern. Implications for nursing and health policy: The nursing database will enable high-quality information storage that will potentially better inform health and healthcare policies as well as enable visualization of data concerning nursing care challenges and activities within the relevant communities. This information is Correspondence address: Naoko Arakawa, Department of Nursing, College of Life and Health Sciences, Chubu University, 1200 Matsumoto, Kasugai, Aichi 487-8501, Japan; Tel: 81-568-51-1111; Fax: 81-568-51-5370; E-mail: n-maruyama@isc.chubu.ac.jp. FundingThis study was carried out upon receiving a JSPS KAKENHI Grant-in-Aid for Young Scientists (B)15K20819 as well as a research grant from the Mitsubishi Foundation. Conflict of interestNo conflict of interest has been declared by the authors. © 2018 International Council of NursesThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Original Article essential for policy development and implementation in areas of human and fiscal resource allocations and meeting training/education needs.Keywords: Chronic Diseases, Community Health Nursing, Database System, Electronic Health Records, Information Technology, Resource-Poor Countries, Rural Areas, System Usability, Thailand IntroductionInformation and communication technology (ICT) is an effective tool to promote health care in resource-poor countr...

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Wisdom within: unlocking the potential of big data for nursing regulators

Abstract: Understanding and using big data is a critical part of developing relevant, sound and credible policy. Rigorous collection and analysis of big data supports the integrity of the evidence used by nurse regulators in developing nursing and health policy.

Cited by 10 publications

References 2 publications

Completion of electronic nursing documentation of inpatient admission assessment: insights from Australian metropolitan hospitals

Completion of electronic nursing documentation of inpatient admission assessment: insights from Australian metropolitan hospitals

The evaluation of evidence‐informed changes to an internationally educated nurse registration process

Construction and usability of community health nursing database in rural north‐eastern Thailand

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