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_a9781118919408 _q(electronic bk.) |
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| 020 | _z9781118919392 | ||
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| 020 | _z9781118919415 | ||
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_a362.10285 _223 |
| 100 | 1 |
_aYang, Hui, _d1981- _eauthor. |
|
| 245 | 1 | 0 |
_aHealthcare analytics : _bfrom data to knowledge to healthcare improvement / _cHui Yang, Eva K. Lee. |
| 264 | 1 |
_aHoboken, New Jersey : _bJohn Wiley & Sons, _c[2016] |
|
| 300 | _a1 online resource. | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aWiley series in operations research and management science | |
| 504 | _aIncludes bibliographical references and index. | ||
| 533 |
_aElectronic reproduction. _bPalo Alto, Calif. : _cebrary, Inc., _d2016. _nMode of access: Internet. _nSystem requirements: Web browser. _nTitle from title screen (viewed January 5, 2017) _nAccess may be restricted to users at subscribing institutions. |
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| 588 | 0 | _aDescription from print format record. | |
| 520 | _aFeatures of statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting-edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency. Organized into two main sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part II focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician-patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: - Contributions from well-known international experts who shed light on new approaches in this growing area - Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations - Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry - Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvement The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments. HUI YANG, PhD, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor-based modeling and analysis of complex systems for process monitoring/control; system diagnostics/ prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self-organizing behaviors. EVA K. LEE, PhD, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and HealthCare, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health-risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large-scale healthcare/medical decision analysis and quality improvement; clinical translational. | ||
| 650 | 0 |
_aMedical care _xData processing. |
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| 650 | 0 |
_aMedical care _xInformation services. |
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| 650 | 7 |
_aMedical care _xData processing. _2fast _0(OCoLC)fst01013786 |
|
| 650 | 7 |
_aMedical care _xInformation services. _2fast _0(OCoLC)fst01013815 |
|
| 650 | 7 |
_aPOLITICAL SCIENCE / Public Policy / Social Security _2bisacsh |
|
| 650 | 7 |
_aPOLITICAL SCIENCE / Public Policy / Social Services & Welfare _2bisacsh |
|
| 650 | 2 | _aMedical Informatics Applications. | |
| 655 | 0 | _aElectronic books. | |
| 700 | 1 |
_aLee, Eva K., _eauthor. |
|
| 710 | 2 | _aebrary, Inc. | |
| 776 | 0 | 8 |
_iPrint version: _aYang, Hui, 1981- _tHealthcare analytics. _dHoboken, New Jersey : John Wiley & Sons, 2016 _z9781118919392 _w(DLC) 2015047966 _w(OCoLC)907148412 |
| 830 | 0 | _aWiley series in operations research and management science. | |
| 856 | 4 | 0 |
_uhttps://eresourcesptsl.ukm.remotexs.co/user/login?url=https://doi.org/10.1002/9781118919408 _zWiley Online Library |
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