國立虎尾科技大學 |

Healthcare service management = a data-driven systems approach /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Healthcare service management/ by Li Tao, Jiming Liu.
其他題名:	a data-driven systems approach /
作者:	Tao, Li.
其他作者:	Liu, Jiming.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xvii, 168 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Health services administration. -
電子資源:	https://doi.org/10.1007/978-3-030-15385-4
ISBN:	9783030153854

Healthcare service management = a data-driven systems approach /
Tao, Li.

Healthcare service managementa data-driven systems approach /[electronic resource] :by Li Tao, Jiming Liu. - Cham :Springer International Publishing :2019. - xvii, 168 p. :ill., digital ;24 cm. - Health information science,2366-0988. - Health information science..

Table of Contents ii -- List of Tables vii -- List of Figures -- Chapter 1 Introduction 1 -- Chapter 2 Data Analytics and Modeling Methods for Healthcare Service Systems 35 -- Chapter 3 Effects of Demand Factors on Service Utilization 52 -- Chapter 4 Effects of Supply Factors on Wait Times 71 -- Chapter 5 Integrated Prediction of Service Performance 95 -- Chapter 6 An Adaptive Strategy for Wait Times Management 115 -- Chapter 7 Spatio-Temporal Patterns in Patient Arrivals and Wait Times 130 -- Chapter 8 An Intelligent Healthcare Decision Support System 176 -- Bibliography 209 -- Notation Index 237 -- List of Abbreviations 240.

Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals. The approach integrates four methods -- Structural Equation Modeling (SEM)-based analysis; integrated projection; service management strategy design and evaluation; and behavior-based autonomy-oriented modeling -- to address respective challenges encountered in performing data analytics and modeling studies on healthcare services. The thrust and uniqueness of this approach lies in the following aspects: Ability to explore underlying complex relationships between observed or latent impact factors and service performance. Ability to predict the changes and demonstrate the corresponding dynamics of service utilization and service performance. Ability to strategically manage service resources with the adaptation of unpredictable patient arrivals. Ability to figure out the working mechanisms that account for certain spatio-temporal patterns of service utilization and performance. To show the practical effectiveness of the proposed systematic approach, this book provides a series of pilot studies within the context of cardiac care in Ontario, Canada. The exemplified studies have unveiled some novel findings, e.g., (1) service accessibility and education may relieve the pressure of population size on service utilization; (2) functionally coupled units may have a certain cross-unit wait-time relationship potentially because of a delay cascade phenomena; (3) strategically allocating time blocks in operating rooms (ORs) based on a feedback mechanism may benefit OR utilization; (4) patients' and hospitals' autonomous behavior, and their interactions via wait times may bear the responsible for the emergence of spatio-temporal patterns observed in the real-world cardiac care system. Furthermore, this book presents an intelligent healthcare decision support (iHDS) system, an integrated architecture for implementing the data-driven complex systems modeling approach to developing, analyzing, investigating, supporting and advising healthcare related decisions. In summary, this book provides a data-driven systematic approach for addressing practical decision-support problems confronted in healthcare service management. This approach will provide policy makers, researchers, and practitioners with a practically useful way for examining service utilization and service performance in various ''what-if" scenarios, inspiring the design of effectiveness resource-allocation strategies, and deepening the understanding of the nature of complex healthcare service systems.

ISBN: 9783030153854

Standard No.: 10.1007/978-3-030-15385-4doiSubjects--Topical Terms:

564005
Health services administration.

LC Class. No.: RA971

Dewey Class. No.: 362.1068

Healthcare service management = a data-driven systems approach /
LDR:04657nam a2200349 a 4500 001 940265
003 DE-He213
005 20190508082752.0
006 m d
007 cr nn 008maaau
008 200417s2019 gw s 0 eng d
020 $a 9783030153854 $q (electronic bk.)
020 $a 9783030153830 $q (paper)
024 7 $a 10.1007/978-3-030-15385-4 $2 doi
035 $a 978-3-030-15385-4
040 $a GP $c GP
041 0 $a eng
050 4 $a RA971
072 7 $a UNH $2 bicssc
072 7 $a COM032000 $2 bisacsh
072 7 $a UNH $2 thema
072 7 $a UDBD $2 thema
082 0 4 $a 362.1068 $2 23
090 $a RA971 $b .T171 2019
100 1 $a Tao, Li. $3 1226820
245 1 0 $a Healthcare service management $h [electronic resource] : $b a data-driven systems approach / $c by Li Tao, Jiming Liu.
260 $a Cham : $c 2019. $b Springer International Publishing : $b Imprint: Springer,
300 $a xvii, 168 p. : $b ill., digital ; $c 24 cm.
490 1 $a Health information science, $x 2366-0988
505 0 $a Table of Contents ii -- List of Tables vii -- List of Figures -- Chapter 1 Introduction 1 -- Chapter 2 Data Analytics and Modeling Methods for Healthcare Service Systems 35 -- Chapter 3 Effects of Demand Factors on Service Utilization 52 -- Chapter 4 Effects of Supply Factors on Wait Times 71 -- Chapter 5 Integrated Prediction of Service Performance 95 -- Chapter 6 An Adaptive Strategy for Wait Times Management 115 -- Chapter 7 Spatio-Temporal Patterns in Patient Arrivals and Wait Times 130 -- Chapter 8 An Intelligent Healthcare Decision Support System 176 -- Bibliography 209 -- Notation Index 237 -- List of Abbreviations 240.
520 $a Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals. The approach integrates four methods -- Structural Equation Modeling (SEM)-based analysis; integrated projection; service management strategy design and evaluation; and behavior-based autonomy-oriented modeling -- to address respective challenges encountered in performing data analytics and modeling studies on healthcare services. The thrust and uniqueness of this approach lies in the following aspects: Ability to explore underlying complex relationships between observed or latent impact factors and service performance. Ability to predict the changes and demonstrate the corresponding dynamics of service utilization and service performance. Ability to strategically manage service resources with the adaptation of unpredictable patient arrivals. Ability to figure out the working mechanisms that account for certain spatio-temporal patterns of service utilization and performance. To show the practical effectiveness of the proposed systematic approach, this book provides a series of pilot studies within the context of cardiac care in Ontario, Canada. The exemplified studies have unveiled some novel findings, e.g., (1) service accessibility and education may relieve the pressure of population size on service utilization; (2) functionally coupled units may have a certain cross-unit wait-time relationship potentially because of a delay cascade phenomena; (3) strategically allocating time blocks in operating rooms (ORs) based on a feedback mechanism may benefit OR utilization; (4) patients' and hospitals' autonomous behavior, and their interactions via wait times may bear the responsible for the emergence of spatio-temporal patterns observed in the real-world cardiac care system. Furthermore, this book presents an intelligent healthcare decision support (iHDS) system, an integrated architecture for implementing the data-driven complex systems modeling approach to developing, analyzing, investigating, supporting and advising healthcare related decisions. In summary, this book provides a data-driven systematic approach for addressing practical decision-support problems confronted in healthcare service management. This approach will provide policy makers, researchers, and practitioners with a practically useful way for examining service utilization and service performance in various ''what-if" scenarios, inspiring the design of effectiveness resource-allocation strategies, and deepening the understanding of the nature of complex healthcare service systems.
650 0 $a Health services administration. $3 564005
650 0 $a Health services administration $x Data processing. $3 659731
650 1 4 $a Information Systems Applications (incl. Internet) $3 815116
650 2 4 $a Database Management. $3 669820
650 2 4 $a Health Informatics. $3 593963
700 1 $a Liu, Jiming. $3 670164
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Health information science. $3 1067741
856 4 0 $u https://doi.org/10.1007/978-3-030-15385-4
950 $a Computer Science (Springer-11645)