Variance Analysis and Handling of Clinical Pathway: An Overview of the State of Knowledge

Clinical pathway is a multi-disciplinary treatment plan and work mode, which is favorable for improving healthcare service quality and reducing medical costs. Most of references demonstrate that variance analysis and handling is the key to clinical pathway management. Thus, the clinical pathway variance has become the focus of scholars. This paper uses the text mining technique to present a literature review of 496 academic articles in the field of clinical pathway variance analysis and handling, which published between 1994 and 2018. Moreover, this paper conducts a bibliometric analysis to visualize the clinical pathway variance research. In variance analysis and handling, there are a lot of imprecise knowledge and fuzzy relations to be reasoned with knowledge of different domains. In this study, methods of clinical pathway variance analysis and handling are illustrated. In addition, this paper points out the limitations of each method. Based on the results, the future prospects of clinical pathway variance analysis and handling research is proposed.

[1]  Boudewijn F. van Dongen,et al.  Workflow mining: A survey of issues and approaches , 2003, Data Knowl. Eng..

[2]  T. Jiang,et al.  Clinical Pathway for Early Diagnosis of COVID-19: Updates from Experience to Evidence-Based Practice , 2020, Clinical Reviews in Allergy & Immunology.

[3]  C. Lau,et al.  Guideline-Based Critical Care Pathway Improves Long-Term Clinical Outcomes in Patients with Acute Coronary Syndrome , 2019, Scientific Reports.

[4]  Nick Santamaria,et al.  Valuing variance: the importance of variance analysis in clinical pathways utilisation. , 2007, Australian health review : a publication of the Australian Hospital Association.

[5]  Dr. Alex A. Freitas Data Mining and Knowledge Discovery with Evolutionary Algorithms , 2002, Natural Computing Series.

[6]  Huilong Duan,et al.  Discovery of clinical pathway patterns from event logs using probabilistic topic models , 2014, J. Biomed. Informatics.

[7]  Jianmin Wang,et al.  Incorporating Topic Assignment Constraint and Topic Correlation Limitation into Clinical Goal Discovering for Clinical Pathway Mining , 2017, Journal of healthcare engineering.

[8]  Huilong Duan,et al.  On local anomaly detection and analysis for clinical pathways , 2015, Artif. Intell. Medicine.

[9]  Geoff Hall,et al.  Process mining routinely collected electronic health records to define real-life clinical pathways during chemotherapy , 2017, Int. J. Medical Informatics.

[10]  Zhibin Jiang,et al.  Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO , 2012, Journal of Medical Systems.

[11]  M. Ulivelli,et al.  Prevalence of Multiple Sclerosis in Tuscany (Central Italy): A Study Based on Validated Administrative Data , 2015, Neuroepidemiology.

[12]  Silvana Quaglini,et al.  Guideline-based careflow systems , 2000, Artif. Intell. Medicine.

[13]  Gregoris Mentzas,et al.  Adaptive Clinical Pathways with Semantic Web Rules , 2008, HEALTHINF.

[14]  Uzay Kaymak,et al.  Variance analysis in Task-Time matrix clinical pathways , 2017, 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[15]  A. Vanasse,et al.  The '6W' multidimensional model of care trajectories for patients with chronic ambulatory care sensitive conditions and hospital readmissions. , 2018, Public health.

[16]  Silvana Quaglini,et al.  Evidence-based careflow management systems: the case of post-stroke rehabilitation , 2002, J. Biomed. Informatics.

[17]  Mohd Soperi Mohd Zahid,et al.  Clinical pathway variance prediction using artificial neural network for acute decompensated heart failure clinical pathway , 2018 .

[18]  Zhengxing Huang,et al.  Probabilistic modeling personalized treatment pathways using electronic health records , 2018, J. Biomed. Informatics.

[19]  C. Iber,et al.  A multisite randomized trial of portable sleep studies and positive airway pressure autotitration versus laboratory-based polysomnography for the diagnosis and treatment of obstructive sleep apnea: the HomePAP study. , 2012, Sleep.

[20]  Min Han,et al.  An improved fuzzy neural network based on T-S model , 2008, Expert Syst. Appl..

[21]  Birger Hjørland,et al.  Practical potentials of Bradford's law: a critical examination of the received view , 2007, J. Documentation.

[22]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

[23]  Li Chen,et al.  Research and Development of Semantics-based Sharable Clinical Pathway Systems , 2015, Journal of Medical Systems.

[24]  Gian Franco Gensini,et al.  The future of telemedicine for the management of heart failure patients: a Consensus Document of the Italian Association of Hospital Cardiologists (A.N.M.C.O), the Italian Society of Cardiology (S.I.C.) and the Italian Society for Telemedicine and eHealth (Digital S.I.T.) , 2017, European heart journal supplements : journal of the European Society of Cardiology.

[25]  Zhibin Jiang,et al.  An ontology-based hierarchical semantic modeling approach to clinical pathway workflows , 2009, Comput. Biol. Medicine.

[26]  Kris Vanhaecht,et al.  Clinical pathway audit tools: a systematic review. , 2006, Journal of nursing management.

[27]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[28]  Cheng-Lung Huang,et al.  A GA-based feature selection and parameters optimizationfor support vector machines , 2006, Expert Syst. Appl..

[29]  K. Rolston The use of new and better antibiotics for bacterial infections in patients with leukemia. , 2009, Clinical lymphoma & myeloma.

[30]  Mor Peleg,et al.  Mining Process Execution and Outcomes - Position Paper , 2007, Business Process Management Workshops.

[31]  Liliana Ardissono,et al.  Adaptive Medical Workflow Management for a Context-Dependent Home Healthcare Assistance Service , 2006, Electron. Notes Theor. Comput. Sci..

[32]  Shannon D. Scott,et al.  What is a clinical pathway? Refinement of an operational definition to identify clinical pathway studies for a Cochrane systematic review , 2016, BMC Medicine.

[33]  Ayca Tarhan,et al.  Systematic Mapping of Process Mining Studies in Healthcare , 2018, IEEE Access.

[34]  P. Fourie,et al.  The particle swarm optimization algorithm in size and shape optimization , 2002 .

[35]  A. Bryett,et al.  Digital pen and paper technology is an effective way of capturing variance data when using arthroplasty clinical pathways. , 2009, Australian health review : a publication of the Australian Hospital Association.

[36]  Akhil Kumar,et al.  CONFlexFlow: Integrating Flexible clinical pathways into clinical decision support systems using context and rules , 2013, Decis. Support Syst..

[37]  Huilong Duan,et al.  Online Treatment Compliance Checking for Clinical Pathways , 2014, Journal of Medical Systems.

[38]  Taïeb Mellouli,et al.  A Clinical Pathway Mining Approach to Enable Scheduling of Hospital Relocations and Treatment Services , 2015, BPM.

[39]  Jiafu Tang,et al.  Study on Self-Adaptive Clinical Pathway Decision Support System Based on Case-Based Reasoning , 2014 .

[40]  Huilong Duan,et al.  Predictive monitoring of clinical pathways , 2016, Expert Syst. Appl..

[41]  Yi Su,et al.  A new literature growth model: Variable exponential growth law of literature , 1998, Scientometrics.

[42]  Z. B. Jiang,et al.  RECONFIGURABLE MODELLING WITH DEADLOCK AVOIDANCE FOR THE CLINICAL PATHWAY BASED ON MCPN-CS , 2010 .

[43]  Huilong Duan,et al.  Anomaly detection in clinical processes , 2012, AMIA.

[44]  Gregoris Mentzas,et al.  A Holistic Environment for the Design and Execution of Self-Adaptive Clinical Pathways , 2011, IEEE Transactions on Information Technology in Biomedicine.

[45]  D Kopec,et al.  Development of a clinical pathways analysis system with adaptive Bayesian nets and data mining techniques. , 2004, Studies in health technology and informatics.

[46]  J. Burnett,et al.  Isolated elevated blood neutrophil concentration at altitude does not require NICU admission if appropriate reference ranges are used , 2009, Journal of Perinatology.

[47]  Runqi Cao Uncertain Event Presentation and ECA Modeling in Clinical Pathway Variation , 2016 .

[48]  Zhibin Jiang,et al.  Variances Handling Method of Clinical Pathways Based on T-S Fuzzy Neural Networks with Novel Hybrid Learning Algorithm , 2012, Journal of Medical Systems.

[49]  San-Yih Hwang,et al.  A process-mining framework for the detection of healthcare fraud and abuse , 2006, Expert Syst. Appl..

[50]  Zhibin Jiang,et al.  Extended event-condition-action rules and fuzzy Petri nets based exception handling for workflow management , 2011, Expert Syst. Appl..

[51]  Diogo R. Ferreira,et al.  Business process analysis in healthcare environments: A methodology based on process mining , 2012, Inf. Syst..

[52]  Ferdinand F. Leimkuhler,et al.  A relationship between Lotka's Law, Bradford's Law, and Zipf's Law , 1986, J. Am. Soc. Inf. Sci..

[53]  Jacques Wainer,et al.  Algorithms for anomaly detection of traces in logs of process aware information systems , 2013, Inf. Syst..

[54]  Gregoris Mentzas,et al.  SEMPATH: Semantic Adaptive and Personalized Clinical Pathways , 2009, 2009 International Conference on eHealth, Telemedicine, and Social Medicine.

[55]  H. Sofia Pinto,et al.  Ontologies: How can They be Built? , 2004, Knowledge and Information Systems.

[56]  Schahram Dustdar,et al.  Modeling and implementing medical Web services , 2005, Data Knowl. Eng..

[57]  Manfred Reichert,et al.  IT support for healthcare processes - premises, challenges, perspectives , 2007, Data Knowl. Eng..

[58]  Zhibin Jiang,et al.  Modelling, variation monitoring, analyzing, reasoning for intelligently reconfigurable Clinical Pathway , 2009, 2009 IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics.

[59]  Kazunobu Yamauchi,et al.  A new approach to systematization of the management of paper-based clinical pathways , 2006, Comput. Methods Programs Biomed..

[60]  Syed SR ABIDIa,et al.  Adaptable Personalized Care Planning via a Semantic Web Framework , 2006 .

[61]  Paul Robert Harper,et al.  Clinical pathway modelling: a literature review , 2019, Health systems.

[62]  Aijun Liu,et al.  Variance Risk Identification and Treatment of Clinical Pathway by Integrated Bayesian Network and Association Rules Mining , 2019, Entropy.

[63]  Zhibin Jiang,et al.  A Knowledge-Based Variance Management System for Supporting the Implementation of Clinical Pathways , 2009, 2009 International Conference on Management and Service Science.

[64]  Chih-Hong Lin,et al.  Self-constructing fuzzy neural network speed controller for permanent-magnet synchronous motor drive , 2001, IEEE Trans. Fuzzy Syst..

[65]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[66]  Zhibin Jiang,et al.  Knowledge-based hybrid variance handling for patient care workflows based on clinical pathways , 2009, 2009 IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics.

[67]  Chris D. Nugent,et al.  An Adaptive Semantic based Mediation System for Data Interoperability among Health Information Systems , 2014, Journal of Medical Systems.

[68]  Uzay Kaymak,et al.  On process mining in health care , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[69]  Huilong Duan,et al.  Similarity Measure Between Patient Traces for Clinical Pathway Analysis: Problem, Method, and Applications , 2014, IEEE Journal of Biomedical and Health Informatics.

[70]  E. James,et al.  What is a clinical pathway? Development of a definition to inform the debate , 2010, BMC medicine.

[71]  Wil M. P. van der Aalst,et al.  Trace Clustering in Process Mining , 2008, Business Process Management Workshops.

[72]  Bo Yang,et al.  Automatic Design of Hierarchical Takagi–Sugeno Type Fuzzy Systems Using Evolutionary Algorithms , 2007, IEEE Transactions on Fuzzy Systems.

[73]  Shih-Wei Lin,et al.  Applying enhanced data mining approaches in predicting bank performance: A case of Taiwanese commercial banks , 2009, Expert Syst. Appl..