Abstract
Electronic Health Records (EHR) embody a large volume of measured values and records of clinical encounters. Data is produced in healthcare settings at a large rate. Medical researchers find themselves facing massive volumes of data that should be reviewed and analysed before making clinical decisions that affect the lives of patients. The aim of this study is to apply the performance measurement approach used in finance and engineering to the EHR systems and develop a new system that allows clinicians who are not computer experts to analyse and query the EHR for better clinical decisions. Sources of healthcare data are numerous: nurses, doctors, technicians, patients, pharmaceutical companies, and third-party payers. Data is collected and stored from different sources such as computerised patient files, laboratory and diagnostic machinery, wired and wireless monitoring devices attached to patients across the various care-giver encounters, and many other electronic files and databases. Decision-support is critical in management of healthcare organizations. Data is collected for analysis, but requires organization of structure, design of systems to analyse the data, and technical knowledge from the management. This study aims at developing a novel system for the analysis of EHR data through the application of Performance Measurement and Management (PMM). This is achieved through investigation of the current situation and the state-of-the-art in clinical analytics, and then modifying the solutions to take advantage of PMM.
The original version of this chapter was inadvertently published with an incorrect chapter pagination 828–833 and DOI 10.1007/978-3-319-32703-7_161. The page range and the DOI has been re-assigned. The correct page range is 834–839 and the DOI is 10.1007/978-3-319-32703-7_162. The erratum to this chapter is available at DOI: 10.1007/978-3-319-32703-7_260
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-32703-7_260
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References
Akçura et. al. 2014. “Drug prescription behavior and decision support systems”, Decision Support Systems, Volume 57
Fleming et. al. 2014. “Using the theory of planned behavior to examine pharmacists’ intention to utilize a prescription drug monitoring program database”, Research in Social and Administrative Pharmacy, Volume 10
Syed-Abdul et. al. 2014. “A smart medication recommendation model for the electronic prescription”, Computer Methods and Programs in Biomedicine, Volume 117
Fung et. al. 2013. “Comparison of Electronic Pharmacy Prescription Records With Manually Collected Medication Histories in an Emergency Department”, Annals of Emergency Medicine, Volume 62, Number 3
Thanassoulis et. al. 2012. “Estimating the scope for savings in referrals and drug prescription costs in the general Practice units of a UK primary care trust”, European Journal of Operational Research, Volume 221
Warholak et. al. 2014. “Assessing the effect of providing a pharmacist with patient diagnosis on electronic prescription orders: A pilot study”, Research in Social and Administrative Pharmacy, Volume 10
Villamañán et. al. 2011. “The Assisted Electronic Prescription in Patients Hospitalised in a Chest Diseases Ward”, Archivos de Bronconeumologia, Volume 47, Number 3
Natarajan et. al. 2010. “An analysis of clinical queries in an electronic health record search utility”, Journal of Medical Informatics, Volume 79
Chard et. al. 2011. “A Cloud-based Approach to Medical NLP”, Journal of the American Medical Informatics Association, Volume 0
Park et. al. 2010. “Use of an automated clinical management system improves outpatient immunosuppressive care following liver transplantation”, Journal of the American Medical Informatics Association, Volume 17
Sittig et. al. 2010. “The state of the art in clinical knowledge management: An inventory of tools and techniques”, Journal of Medical Informatics, Volume 79
Hayrinen et. al. 2008. “Definition, structure, content, use and impacts of electronic health records. A review of the research literature”, Journal of Medical Informatics, Volume 77
ZHOU et. al. 2009. “The Relationship between Electronic Health Record Use and Quality of Care over Time”, Journal of the American Medical Informatics Association, Volume 16, Number 4
Linmans et. al. 2012. “Using electronic medical records analysis to investigate the effectiveness of lifestyle programs in real-world primary care is challenging - a case study in diabetes mellitus”, Journal of Clinical Epidemiology, Volume 65
Geissbuhler et. al. 2012. “Trustworthy reuse of health data: A transnational perspective”, Journal of Medical Informatics
Himmelstein et. al. 2009. “Hospital Computing and the Costs and Quality of Care: A National Study”, American Journal of Medicine
Robertson et. al. 2010. “Implementation and adoption of nation- wide electronic health records in secondary care in England: qualitative analysis of interim results from a prospective national evaluation”, British Medical Journal, Volume 341
Urowitz et. al. 2008. “Is Canada ready for patient accessible electronic health records? A national scan”, Medical Informatics and Decision Making, Volume 33, Number 8
Kierkegaard et. al. 2011. “Electronic health record: Wiring Europe’s healthcare”, Computer Law & Security Review, Volume 27
Stroetmann et. al. 2012. “United in Diversity: Legal Challenges on the Road Towards Interoperable eHealth Solutions in Europe”, European Journal for Biomedical Informatics, Volume 8, Number 2
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Nammour, F.L., Mansour, N., Danas, K. (2016). Using Performance Measurement in Healthcare Analytics. In: Kyriacou, E., Christofides, S., Pattichis, C. (eds) XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016. IFMBE Proceedings, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-32703-7_162
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DOI: https://doi.org/10.1007/978-3-319-32703-7_162
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