Recent Research Areas and Grand Challenges in Electronic Medical Record: A Literature Survey Approach

Najaftorkaman, Mohammadreza; Ghapanchi, Amir Hossein; Talaei-Khoei, Amir; Ray, Pradeep

doi:10.2991/itmr.2013.3.1.2

Cited by 23 publications

(12 citation statements)

References 26 publications

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“…To conduct this literature survey, we followed the guidelines used by previous literature (Najaftorkaman et al, 2013), including three main discrete activities: (i) searching the initial list of papers; (ii) appraising relevant papers; (iii) extracting and analysing data.…”

Section: Methodsmentioning

confidence: 99%

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Data Completeness in Healthcare: A Literature Survey

Liu

Talaei-Khoei

Zowghi

et al. 2017

PAJAIS

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As the adoption of eHealth has made it easier to access and aggregate healthcare data, there has been growing application for clinical decisions, health services planning, and public health monitoring with daily collected data in clinical care. Reliable data quality is a precursor of the aforementioned tasks. There is a body of research on data quality in healthcare, however, a clear picture of data completeness in this field is missing. This research aims to identify and classify current research themes related to data completeness in healthcare. In addition, the paper presents problems with data completeness in the reviewed literature and identifies methods that have been adopted to address those problems. This study has reviewed 24 papers (January 2011-April 2016) published in information and computing sciences, biomedical engineering, and medicine and health sciences journals. The paper uncovers three main research themes, including design and development, evaluation, and determinants. In conclusion, this paper improves our understanding of the current state of the art of data completeness in healthcare records and indicates future research directions.

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Section: Methodsmentioning

confidence: 99%

“…We identified initial search resources informed through prior work (Najaftorkaman et al, 2013). We considered that the relevant papers might distribute in the areas of research in Information and Computing Sciences, Biomedical Engineering, and Medicine and Health Sciences.…”

Section: Initial Searchmentioning

confidence: 99%

Data Completeness in Healthcare: A Literature Survey

Liu

Talaei-Khoei

Zowghi

et al. 2017

PAJAIS

Self Cite

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“…A study from Afghanistan, conducted in hospitals in two different regions, found that readiness differed significantly between the hospitals included in the study due to the extent of usage of the technologies by providers [25]. A number of studies stressed the importance of assessing healthcare provider readiness for the implementation of ICTs in healthcare institutions [26, 27]. In Pakistan, stakeholders agreed that assessing readiness was essential to successful implementation [26].…”

Section: Introductionmentioning

confidence: 99%

Readiness of healthcare providers for eHealth: the case from primary healthcare centers in Lebanon

Saleh

Khodor

Alameddine

et al. 2016

BMC Health Serv Res

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BackgroundeHealth can positively impact the efficiency and quality of healthcare services. Its potential benefits extend to the patient, healthcare provider, and organization. Primary healthcare (PHC) settings may particularly benefit from eHealth. In these settings, healthcare provider readiness is key to successful eHealth implementation. Accordingly, it is necessary to explore the potential readiness of providers to use eHealth tools. Therefore, the purpose of this study was to assess the readiness of healthcare providers working in PHC centers in Lebanon to use eHealth tools.MethodsA self-administered questionnaire was used to assess participants’ socio-demographics, computer use, literacy, and access, and participants’ readiness for eHealth implementation (appropriateness, management support, change efficacy, personal beneficence). The study included primary healthcare providers (physicians, nurses, other providers) working in 22 PHC centers distributed across Lebanon. Descriptive and bivariate analyses (ANOVA, independent t-test, Kruskal Wallis, Tamhane’s T2) were used to compare participant characteristics to the level of readiness for the implementation of eHealth.ResultsOf the 541 questionnaires, 213 were completed (response rate: 39.4 %). The majority of participants were physicians (46.9 %), and nurses (26.8 %). Most physicians (54.0 %), nurses (61.4 %), and other providers (50.9 %) felt comfortable using computers, and had access to computers at their PHC center (physicians: 77.0 %, nurses: 87.7 %, others: 92.5 %). Frequency of computer use varied. The study found a significant difference for personal beneficence, management support, and change efficacy among different healthcare providers, and relative to participants’ level of comfort using computers. There was a significant difference by level of comfort using computers and appropriateness. A significant difference was also found between those with access to computers in relation to personal beneficence and change efficacy; and between frequency of computer use and change efficacy.ConclusionThe implementation of eHealth cannot be achieved without the readiness of healthcare providers. This study demonstrates that the majority of healthcare providers at PHC centers across Lebanon are ready for eHealth implementation. The findings of this study can be considered by decision makers to enhance and scale-up the use of eHealth in PHC centers nationally. Efforts should be directed towards capacity building for healthcare providers.

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“…According to the Department of Trade and Industry (DTI) in the UK, Condition Based Maintenance (CBM) in wind turbine rotating elements has contributed to a saving of up to £1.3 billion per year [1]. Hence, Condition Monitoring (CM) of bearings has become a popular approach to increase performance and reduce costs [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Application of anomaly technique in wind turbine bearing fault detection

Purarjomandlangrudi

Nourbakhsh

Ghaemmaghami

et al. 2014

IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

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Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

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Recent Research Areas and Grand Challenges in Electronic Medical Record: A Literature Survey Approach

Cited by 23 publications

References 26 publications

Data Completeness in Healthcare: A Literature Survey

Data Completeness in Healthcare: A Literature Survey

Readiness of healthcare providers for eHealth: the case from primary healthcare centers in Lebanon

Application of anomaly technique in wind turbine bearing fault detection

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