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Healthcare access: A sequence-sensitive approach

Marco J. Haenssgen, Proochista Ariana
2017 SSM: Population Health  
First, descriptive analysis of sequential data enables more a comprehensive representation of people's health behaviours, for example the time spent in various healthcare activities, common healthcare  ...  Third, we describe how sequential data enable transparent and flexible evaluations of people's healthcare behaviour.  ...  Acknowledgements We thank Felix Reed-Tsochas, Omar Guerrero, Xiaolan Fu, Gari Clifford, Martin McKee, and Ralph Schroeder for helpful discussions in relation to research design and implementation.  ... 
doi:10.1016/j.ssmph.2016.11.008 pmid:29349202 pmcid:PMC5769022 fatcat:ko6px6qdrbhddkfvzbbmngvkw4

Knowledge Discovery from Healthcare Electronic Records for Sustainable Environment

Naeem Ahmed Mahoto, Asadullah Shaikh, Mana Saleh Al Reshan, Muhammad Ali Memon, Adel Sulaiman
2021 Sustainability  
Furthermore, based on real healthcare data, this paper also demonstrates a case study of discovering knowledge with the help of three data mining techniques: (1) association analysis; (2) sequential pattern  ...  It becomes a challenge for both physicians and healthcare agencies to discover knowledge from many healthcare electronic records.  ...  This study applied three data mining techniques for discovering knowledge from real healthcare electronic records: (i) association analysis; (ii) sequential pattern mining; (iii) clustering.  ... 
doi:10.3390/su13168900 fatcat:mtgsvxbjxze2fp6ajq5mfluxo4

Classification and Sequential Pattern Analysis for Improving Managerial Efficiency and Providing Better Medical Service in Public Healthcare Centers

Keunho Choi, Sukhoon Chung, Hyunsill Rhee, Yongmoo Suh
2010 Healthcare Informatics Research  
Another data mining technique that is useful for the analysis of medical or healthcare data is sequential pattern analysis, for one disease may be progressed into another in many cases. Exarchos et al  ...  mining tool, which is widely used for various data analysis.  ... 
doi:10.4258/hir.2010.16.2.67 pmid:21818426 pmcid:PMC3089866 fatcat:prnnqu3zl5dthmrse5tez3mj3u

Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram

Lacey Colligan, Janet E Anderson, Henry WW Potts, Jonathan Berman
2010 BMC Health Services Research  
The difficulties of determining the boundaries for the analysis and the granularity required were highlighted.  ...  This exploratory study examined whether the type of process map -sequential or hierarchical -affects healthcare practitioners' judgments.  ...  participated in its design, collected the data, constructed the process maps, and drafted the first version of the manuscript.  ... 
doi:10.1186/1472-6963-10-7 pmid:20056005 pmcid:PMC2822834 fatcat:t25epekvirc4tcddc6pyjfgikq

Healthcare Network Modeling and Analysis [chapter]

Dario Antonelli, Giulia Bruno
2014 IFIP Advances in Information and Communication Technology  
This paper aims at describing how to obtain a rigorous modeling and a meaningful analysis of the mass of data produced by a healthcare network.  ...  To achieve these purposes, a non standard quality assessment must be performed, as models for the analysis and evaluation of healthcare systems considered from the point of view of the entire network instead  ...  While these data are collected for administrative data processing, taking advantage of them for other purposes would be highly desirable [3] .  ... 
doi:10.1007/978-3-662-44745-1_68 fatcat:6gzq2vxg4re5vdwwxqnnqe3trm

A systematic review of mixed methods research on human factors and ergonomics in health care

Pascale Carayon, Sarah Kianfar, Yaqiong Li, Anping Xie, Bashar Alyousef, Abigail Wooldridge
2015 Applied Ergonomics  
The most frequent combination involved interview for qualitative data and survey for quantitative data. The use of mixed methods in healthcare HFE research has increased over time.  ...  Using an iterative and collaborative process supported by a structured data collection form, the six authors identified a total of 58 studies that primarily address HFE issues in health information technology  ...  Acknowledgments This research was partially supported by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant  ... 
doi:10.1016/j.apergo.2015.06.001 pmid:26154228 pmcid:PMC4725322 fatcat:6evwwytnsbhvjebbfvx2zabtn4

An Assessment of Data Mining Based CRM Techniques for Enhancing Profitability

Abdur Rahman, M.N.A. Khan
2017 International Journal of Education and Management Engineering  
Data mining is used in organization for decision making and forecasting of prospective customers. We have studied recent literature related to use of data mining techniques for CRM.  ...  The critical review of the data mining techniques which are being used for CRM is provided in this paper.  ...  The authors [11] propose two methods: Cluster analysis for data mining and Apriori algorithm for association rules mining.  ... 
doi:10.5815/ijeme.2017.02.04 fatcat:fofrphbeofce3cyuiut75sj3vi

Mixed methods research: expanding the evidence base

Allison Shorten, Joanna Smith
2017 Evidence-Based Nursing  
analysis and the framework approach for the interview data. 8 What are the strengths and challenges in using mixed methods?  ...  and healthcare has occurred at a time of internationally increasing complexity in healthcare delivery.  ... 
doi:10.1136/eb-2017-102699 pmid:28615184 fatcat:cft4cum7szcmhlnsr6sa57mqwi

In and Out of the Hospital: The Hidden Interface of High Fidelity Research Via RFID [chapter]

Svetlena Taneva, Effie Law
2007 Lecture Notes in Computer Science  
We identify its promising application in the healthcare sector by empowering the process of capturing, extracting and analyzing data, which help understand task patterns underlying human errors and other  ...  RFID can be cost-effective and powerful, especially when combined with the hospital information system and optionally with video analysis.  ...  The types of data and steps of analysis that the Exploratory Sequential Data Analysis framework identifies as requirements for solid theory building [3] are mostly covered by data from a HIS with an  ... 
doi:10.1007/978-3-540-74796-3_62 fatcat:lqjyzsjsz5gijiax22f4rldbdi

Linked data and online classifications to organise mined patterns in patient data

Nicolas Jay, Mathieu d'Aquin
2013 AMIA Annual Symposium Proceedings  
In this paper, we investigate the use of web data resources in medicine, especially through medical classifications made available using the principles of Linked Data, to support the interpretation of  ...  We employ linked data, especially as exposed through the BioPortal system, to create a navigation structure within the patterns obtained form sequential pattern mining.  ...  Although originally designed for billing and financing purposes, claim databases routinely collect healthcare and administrative data, potentially holding valuable information for the analysis of trajectories  ... 
pmid:24551369 pmcid:PMC3900210 fatcat:xpip3io5grd3xcylgu5feg2j6i

A Sequence Mining-Based Novel Architecture for Detecting Fraudulent Transactions in Healthcare Systems

Irum Matloob, Shoab Ahmed Khan, Rukaiya Rukaiya, Muazzam A. Khan Khattak, Arslan Munir
2022 IEEE Access  
Recent literature focuses on the amount-based analysis or medication versus disease sequential analysis rather than detecting frauds using sequence generation of services within each specialty.  ...  The process-based fraud detection methodology is validated using last five years of a local hospital's transactional data that includes many reported cases of fraudulent activities.  ...  According to most of the previous research studies, sequential pattern mining and association rule mining, both methods are suitable for patient data analysis.  ... 
doi:10.1109/access.2022.3170888 fatcat:tf6tm4o4znf6zfsprhup5cn2ci

Modelling of Cancer Patient Records: A Structured Approach to Data Mining and Visual Analytics [chapter]

Jing Lu, Alan Hales, David Rew
2017 Lecture Notes in Computer Science  
This research presents a methodology for health data analytics through a case study for modelling cancer patient records.  ...  The core data was anonymised and put through a series of pre-processing exercises to identify and exclude anomalous and erroneous data, before restructuring within a remote data warehouse.  ...  This research project has been supported in part by a Southampton Solent Research Innovation and Knowledge Exchange (RIKE) award for "Solent Health Informatics Partnership" (Project ID: 1326).  ... 
doi:10.1007/978-3-319-64265-9_4 fatcat:sqjiw5xlonbvpnnxpsp7abrftm

Prediction for Disease Risk and Medical Cost using Time Series Healthcare Data

Masatoshi Nagata, Kazunori Matsumoto, Masayuki Hashimoto
2016 Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies  
Based on sequential latent dirichlet allocation (SeqLDA), which classifies hierarchical sequential data into segments of topics, we tried to predict the number of people with diseases and the one-year  ...  The results suggest that the SeqLDA method serve to predict the number of people with diseases and the related medical costs using time series healthcare data.  ...  Therefore we applied sequential LDA, which has been developed for handling sequential data as segments of topics to healthcare data (Teh et al., 2006; Lan Du et al., 2010; Lan Du et al., 2012) .  ... 
doi:10.5220/0005827405170522 dblp:conf/biostec/NagataMH16 fatcat:k3hktsiyvjbhpclspc5yyzdjeu

LLAD: Life-Log Anomaly Detection Based on Recurrent Neural Network LSTM

Ermal Elbasani, Jeong-Dong Kim, Mihajlo Jakovljevic
2021 Journal of Healthcare Engineering  
Therefore, Life-Log analysis methods are important for real-life monitoring and anomaly detection.  ...  Recurrent neural networks with long short-term memory units are used for analyzing the Life-Log data.  ...  for sequential data fraud detection.  ... 
doi:10.1155/2021/8829403 pmid:33708367 pmcid:PMC7932773 fatcat:ar3k5q2z4zglncffcumfm5r7ry

PrefixSpan based Pattern Mining using Time Sliding Weight from Streaming Data

Ji-Soo Kang, Ji-Won Baek, Kyungyong Chung
2020 IEEE Access  
If a huge amount of lifelog data is used, it is possible to find sequential patterns from the data and predict a user's medical treatment process, healthcare process, and living habits in order for healthcare  ...  SEQUENTIAL PATTERN MINING FOR HEALTHCARE In the healthcare field, time is a significant factor to treat and prevent diseases [25] .  ... 
doi:10.1109/access.2020.3007485 fatcat:7uynlihoobhvdipzvnjoxzgwqa
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