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Use of Learning Analytics Data in Health Care-Related Educational Disciplines: Systematic Review.

ABSTRACT: BACKGROUND:While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. OBJECTIVE:This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes. METHODS:We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation. RESULTS:A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcome measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis. CONCLUSIONS:The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytics record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies.

SUBMITTER: Chan AK

PROVIDER: S-EPMC6391646 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Use of Learning Analytics Data in Health Care-Related Educational Disciplines: Systematic Review.

Chan Albert Km AK Botelho Michael G MG Lam Otto Lt OL Lam Otto Lt OL

Journal of medical Internet research 20190213 2

<h4>Background</h4>While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies.<h4>Objective</h4>This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes.<h4>Methods</h4>We performed com ...[more]

PMID: 30758291

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Project description:BackgroundThe benefits of data and analytics for health care systems and single providers is an increasingly investigated field in digital health literature. Electronic health records (EHR), for example, can improve quality of care. Emerging analytics tools based on artificial intelligence show the potential to assist physicians in day-to-day workflows. Yet, single health care providers also need information regarding the economic impact when deciding on potential adoption of these tools.ObjectiveThis paper examines the question of whether data and analytics provide economic advantages or disadvantages for health care providers. The goal is to provide a comprehensive overview including a variety of technologies beyond computer-based patient records. Ultimately, findings are also intended to determine whether economic barriers for adoption by providers could exist.MethodsA systematic literature search of the PubMed and Google Scholar online databases was conducted, following the hermeneutic methodology that encourages iterative search and interpretation cycles. After applying inclusion and exclusion criteria to 165 initially identified studies, 50 were included for qualitative synthesis and topic-based clustering.ResultsThe review identified 5 major technology categories, namely EHRs (n=30), computerized clinical decision support (n=8), advanced analytics (n=5), business analytics (n=5), and telemedicine (n=2). Overall, 62% (31/50) of the reviewed studies indicated a positive economic impact for providers either via direct cost or revenue effects or via indirect efficiency or productivity improvements. When differentiating between categories, however, an ambiguous picture emerged for EHR, whereas analytics technologies like computerized clinical decision support and advanced analytics predominantly showed economic benefits.ConclusionsThe research question of whether data and analytics create economic benefits for health care providers cannot be answered uniformly. The results indicate ambiguous effects for EHRs, here representing data, and mainly positive effects for the significantly less studied analytics field. The mixed results regarding EHRs can create an economic barrier for adoption by providers. This barrier can translate into a bottleneck to positive economic effects of analytics technologies relying on EHR data. Ultimately, more research on economic effects of technologies other than EHRs is needed to generate a more reliable evidence base.

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Project description:BACKGROUND:Technology-enhanced learning (TEL) programs are increasingly seen as the way in which education for health care professionals can be transformed, giving access to effective ongoing learning and training even where time or geographical barriers exist. Given the increasing emphasis on this mode of educational support for health care practitioners, it is vital that we can effectively evaluate and measure impact to ensure that TEL programs are effective and fit for purpose. This paper examines the current evidence base for the first time, in relation to the evaluation of TEL programs for health care professionals. OBJECTIVE:We conducted a systematic review of the current literature relating to the evaluation of TEL programs for health care professionals and critically appraised the quality of the studies. METHODS:This review employed specific search criteria to identify research studies that included evaluation of TEL for health care professionals. The databases searched included Medline Ovid, Cumulative Index of Nursing and Allied Health Literature Plus Advanced, Applied Social Sciences Index and Abstracts, ZETOC, Institute of Electrical and Electronics Engineers Explore Digital Library, Allied and Complementary Medicine, and Education Resources Information Center between January 2006 and January 2017. An additional hand search for relevant articles from reference lists was undertaken. Each of the studies identified was critically appraised for quality using the Crowe Critical Appraisal Tool. This approach produced a percentage total score for each study across specified categories. A proportion of the studies were independently assessed by an additional two reviewers. RESULTS:The review identified 21 studies that met the inclusion criteria. The studies included scored totals across eight categories within a range of 37%-95% and an average score of 68%. Studies that measured TEL using learner satisfaction surveys, or combined pretest and posttest knowledge score testing with learner satisfaction surveys, were found to be the most common types of TEL evaluations evident in the literature. The studies reviewed had low scores across reporting on ethical matters, design, and data collection categories. CONCLUSIONS:There continues to be a need to develop effective and standard TEL evaluation tools, and good quality studies that describe effective evaluation of TEL education for health care professionals. Studies often fail to provide sufficient detail to support transferability or direct future TEL health care education programs.

Project description:ObjectiveThis study investigated the barriers and facilitators that senior leaders' experience when using knowledge generated from the analysis of administrative health or care records ('analytics') to inform strategic health and care decision-making.SettingOne London-based sustainability and transformation partnership (STP) in England, as it was on the cusp of forming an integrated care system (ICS).Participants20 senior leaders, including health and social care commissioners, public health leads and health providers. Participants were eligible for inclusion if they were a senior leader of a constituent organisation of the STP and involved in using analytics to make decisions for their own organisations or health and care systems.DesignSemi-structured interviews conducted between January 2020 and March 2020 and analysed using the framework method to generate common themes.ResultsOrganisational fragmentation hindered use of analytics by creating siloed data systems, barriers to data sharing and different organisational priorities. Where trusted and collaborative relationships existed between leaders and analysts, organisational barriers were circumvented and access to and support for analytics facilitated. Trusted and collaborative relationships between individual leaders of different organisations also aided cross-organisational priority setting, which was a key facilitator of strategic health and care decision-making and use of analytics. Data linked across health and care settings were viewed as an enabler of use of analytics for decision-making, while concerns around data quality often stopped analytics use as a part of decision-making, with participants relying more so on expert opinion or intuition.ConclusionsThe UK Governments' 2021 White Paper set out aspirations for data to transform care. While necessary, policy changes to facilitate data sharing across organisations will be insufficient to realise this aim. Better integration of organisations with aligned priorities could support and sustain cross-organisational relationships between leaders and analysts, and leaders of different organisations, to facilitate use of analytics in decision-making.

Project description:BackgroundDifferences in health care utilization by educational level can contribute to inequalities in health. Understanding health care utilization and health-related quality of life (HRQoL) of educational groups may provide important insights into the presence of these inequalities. Therefore, we assessed characteristics, health care utilization and HRQoL of injury patients by educational level.MethodData for this registry based cohort study were extracted from the Dutch Injury Surveillance System. At 6-month follow-up, a stratified sample of patients (≥25 years) with an unintentional injury reported their health care utilization since discharge and completed the EQ-5-Dimension, 5-Level (EQ-5D-5L) and visual analogue scale (EQ VAS). Logistic regression analyses, adjusting for patient and injury characteristics, were performed to investigate the association between educational level and health care utilization. Descriptive statistics were used to analyse HRQoL scores by educational level, for hospitalized and non-hospitalized patients.ResultsThis study included 2606 patients; 47.9% had a low, 24.4% a middle level, and 27.7% a high level of education. Patients with low education were more often female, were older, had more comorbidities, and lived more often alone compared to patients with high education (p < 0.001). Patients with high education were more likely to visit a general practitioner (OR: 1.38; CI: 1.11-1.72) but less likely to be hospitalized (OR: 0.79; CI: 0.63-1.00) and to have nursing care at home (OR: 0.66; CI: 0.49-0.90) compared to their low educated counterparts. For both hospitalized an non-hospitalized persons, those with low educational level reported lower HRQoL and more problems on all dimensions than those with a higher educational level.ConclusionPost-discharge, level of education was associated with visiting the general practitioner and nursing care at home, but not significantly with use of other health care services in the 6 months post-injury. Additionally, patients with a low educational level had a poorer HRQoL. However, other factors including age and sex may also explain a part of these differences between educational groups. It is important that patients are aware of potential consequences of their trauma and when and why they should consult a specific health care service after ED or hospital discharge.

Dataset Information

Use of Learning Analytics Data in Health Care-Related Educational Disciplines: Systematic Review.

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Use of Learning Analytics Data in Health Care-Related Educational Disciplines: Systematic Review.

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