Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.
[1] P. Horner and A. Basu. “Analytics & the future of healthcare,”Analytics
Magazine, 2012, pp. 11-18.
[2] W. Raghupathi and V. Raghupathi, "An Overview of Health Analytics,"
J Health Med Informat, vol. 4, p. 2, 2013.
[3] Ó. Marbán and J. Segovia, "Extending UML for Modeling Data Mining
Projects (DM-UML)," Journal of Information Technology & Software
Engineering, vol. 3, 2013.
[4] Q. Yang and X. Wu, "10 challenging problems in data mining research,"
International Journal of Information Technology & Decision Making,
vol. 5, pp. 597-604, 2006.
[5] R. Bellazzi and B. Zupan, "Predictive data mining in clinical medicine:
current issues and guidelines," International journal of medical
informatics, vol. 77, pp. 81-97, 2008.
[6] O. Marbán, J. Segovia, E. Menasalvas, and C. Fernández-Baizán,
"Toward data mining engineering: A software engineering approach,"
Information systems, vol. 34, pp. 87-107, 2009.
[7] P. Chapman, J. Clinton, R. Kerber, T. Khabaza, T. Reinartz, C. Shearer,
and R. Wirth, CRISP-DM 1.0 Step-by-step data mining guide, 2000.
[8] J. Zubcoff and J. Trujillo, "Conceptual modeling for classification
mining in data warehouses," in Data Warehousing and Knowledge
Discovery, ed: Springer, 2006, pp. 566-575.
[9] N. Prat, J. Akoka, and I. Comyn-Wattiau, "A UML-based data
warehouse design method," Decision Support Systems, vol. 42, pp.
1449-1473, 2006.
[10] S. Luján-Mora, J. Trujillo, and I.-Y. Song, "A UML profile for
multidimensional modeling in data warehouses," Data & Knowledge
Engineering, vol. 59, pp. 725-769, 2006.
[11] A. R. Hevner, S. T. March, J. Park, and S. Ram, "Design science in
information systems research," MIS Quarterly, vol. 28, pp. 75-105,
2004.
[12] J. Pries-Heje and R. Baskerville, "The design theory nexus," MIS
Quarterly, pp. 731-755, 2008.
[13] C. Westphal and T. Blaxton, Data mining solutions: methods and tools
for solving real-world problems, 1998.
[14] R. Wirth and J. Hipp, "CRISP-DM: Towards a standard process model
for data mining," presented at the Proceedings of the 4th International
Conference on the Practical Applications of Knowledge Discovery and
Data Mining, 2000.
[15] R. Matignon, Data mining using SAS enterprise miner vol. 638: John
Wiley & Sons, 2007.
[16] SAS. SAS Enterprise Miner: SEMMA, 2008 Available:
http://www.sas.com/technologies/analytics/datamining/miner/semma.ht
ml
[17] O. Marban, G. Mariscal, and J. Segovia, "A Data Mining & Knowledge
Discovery Process Model," Data Mining and Knowledge Discovery in
Real Life Applications. IN-TECH, vol. 2009, p. 8, 2009.
[18] G. Mariscal, Ó. Marbán, and C. Fernández, "A survey of data mining
and knowledge discovery process models and methodologies," The
Knowledge Engineering Review, vol. 25, pp. 137-166, 2010.
[19] I. Jacobson, G. Booch, and J. Rumbaugh, The unified software
development process vol. 1: Addison-Wesley Reading, 1999. [20] P. Britos, O. Dieste, and R. García-Martínez, "Requirements Elicitation
in Data Mining for Business Intelligence Projects," in Advances in
Information Systems Research, Education and Practice, ed: Springer,
2008, pp. 139-150.
[21] K. J. Cios and W. G. Moore, "Uniqueness of medical data mining,"
Artificial intelligence in medicine, vol. 26, pp. 1-24, 2002.
[22] M. Kwiatkowska, M. S. Atkins, N. T. Ayas, and C. F. Ryan,
"Knowledge-based data analysis: first step toward the creation of clinical
prediction rules using a new typicality measure," Information
Technology in Biomedicine, IEEE Transactions on, vol. 11, pp. 651-660,
2007.
[23] N. Esfandiary, M. R. Babavalian, A.-M. E. Moghadam, and V. K. Tabar,
"Knowledge Discovery in Medicine: Current Issue and Future Trend,"
Expert Systems with Applications, vol. 41, pp. 4434–4463, 2014.
[24] X.-B. Li and J. Qin, "A Framework for Privacy-Preserving Medical
Document Sharing," in Thirty Fourth International Conference on
Information Systems, Milan, Italy, 2013.
[25] H. Chen, R. H. Chiang, and V. C. Storey, "Business Intelligence and
Analytics: From Big Data to Big Impact," MIS quarterly, vol. 36, 2012.
[26] T. J. Eggebraaten, J. W. Tenner, and J. C. Dubbels, "A health-care data
model based on the HL7 reference information model," IBM Systems
Journal, vol. 46, pp. 5-18, 2007.
[27] Jibitesh Mishra and A. Mohanty, Software Engineering: Pearson
Education India, 2011.
[28] P. Naur and B. Randell, Software Engineering: Report of a conference
sponsored by the NATO Science Committee, Garmisch, Germany, 7-11
Oct. 1968, Brussels, Scientific Affairs Division, NATO, 1969.
[29] K. Beck, M. Beedle, A. Van Bennekum, A. Cockburn, W. Cunningham,
M. Fowler, J. Grenning, J. Highsmith, A. Hunt, and R. Jeffries,
Manifesto for agile software development, 2001, Available:
http://agilemanifesto.org/
[30] S. Gregor and A. R. Hevner, "Positioning and presenting design science
research for maximum impact," MIS Quarterly, vol. 37, pp. 337-356,
2013.
[31] S. L. Pan and B. Tan, "Demystifying case research: A structured–
pragmatic–situational (SPS) approach to conducting case studies,"
Information and Organization, vol. 21, pp. 161-176, 2011.
[32] S. W. Ambler, "Agile Model Driven Development (AMDD)," in
XOOTIC Symposium 2006, 2006, p. 13.
[33] M. Cohn, User stories applied: For agile software development:
Addison-Wesley Professional, 2004.
[34] K. Collier, Agile analytics: A value-driven approach to business
intelligence and data warehousing: Addison-Wesley, 2011.
[35] J. Zubcoff and J. Trujillo, "A UML 2.0 profile to design Association
Rule mining models in the multidimensional conceptual modeling of
data warehouses," Data & Knowledge Engineering, vol. 63, pp. 44-62,
2007.
[36] OMG, "Omg Unified Modeling Language (OMG UML) Superstructure
specification version 2.4. 1," document formal/2011-08-06. Technical
report, OMG, 2011.
[37] M. A. Hamburg and F. S. Collins, "The path to personalized medicine,"
New England journal of medicine, vol. 363, pp. 301-304, 2010.
[1] P. Horner and A. Basu. “Analytics & the future of healthcare,”Analytics
Magazine, 2012, pp. 11-18.
[2] W. Raghupathi and V. Raghupathi, "An Overview of Health Analytics,"
J Health Med Informat, vol. 4, p. 2, 2013.
[3] Ó. Marbán and J. Segovia, "Extending UML for Modeling Data Mining
Projects (DM-UML)," Journal of Information Technology & Software
Engineering, vol. 3, 2013.
[4] Q. Yang and X. Wu, "10 challenging problems in data mining research,"
International Journal of Information Technology & Decision Making,
vol. 5, pp. 597-604, 2006.
[5] R. Bellazzi and B. Zupan, "Predictive data mining in clinical medicine:
current issues and guidelines," International journal of medical
informatics, vol. 77, pp. 81-97, 2008.
[6] O. Marbán, J. Segovia, E. Menasalvas, and C. Fernández-Baizán,
"Toward data mining engineering: A software engineering approach,"
Information systems, vol. 34, pp. 87-107, 2009.
[7] P. Chapman, J. Clinton, R. Kerber, T. Khabaza, T. Reinartz, C. Shearer,
and R. Wirth, CRISP-DM 1.0 Step-by-step data mining guide, 2000.
[8] J. Zubcoff and J. Trujillo, "Conceptual modeling for classification
mining in data warehouses," in Data Warehousing and Knowledge
Discovery, ed: Springer, 2006, pp. 566-575.
[9] N. Prat, J. Akoka, and I. Comyn-Wattiau, "A UML-based data
warehouse design method," Decision Support Systems, vol. 42, pp.
1449-1473, 2006.
[10] S. Luján-Mora, J. Trujillo, and I.-Y. Song, "A UML profile for
multidimensional modeling in data warehouses," Data & Knowledge
Engineering, vol. 59, pp. 725-769, 2006.
[11] A. R. Hevner, S. T. March, J. Park, and S. Ram, "Design science in
information systems research," MIS Quarterly, vol. 28, pp. 75-105,
2004.
[12] J. Pries-Heje and R. Baskerville, "The design theory nexus," MIS
Quarterly, pp. 731-755, 2008.
[13] C. Westphal and T. Blaxton, Data mining solutions: methods and tools
for solving real-world problems, 1998.
[14] R. Wirth and J. Hipp, "CRISP-DM: Towards a standard process model
for data mining," presented at the Proceedings of the 4th International
Conference on the Practical Applications of Knowledge Discovery and
Data Mining, 2000.
[15] R. Matignon, Data mining using SAS enterprise miner vol. 638: John
Wiley & Sons, 2007.
[16] SAS. SAS Enterprise Miner: SEMMA, 2008 Available:
http://www.sas.com/technologies/analytics/datamining/miner/semma.ht
ml
[17] O. Marban, G. Mariscal, and J. Segovia, "A Data Mining & Knowledge
Discovery Process Model," Data Mining and Knowledge Discovery in
Real Life Applications. IN-TECH, vol. 2009, p. 8, 2009.
[18] G. Mariscal, Ó. Marbán, and C. Fernández, "A survey of data mining
and knowledge discovery process models and methodologies," The
Knowledge Engineering Review, vol. 25, pp. 137-166, 2010.
[19] I. Jacobson, G. Booch, and J. Rumbaugh, The unified software
development process vol. 1: Addison-Wesley Reading, 1999. [20] P. Britos, O. Dieste, and R. García-Martínez, "Requirements Elicitation
in Data Mining for Business Intelligence Projects," in Advances in
Information Systems Research, Education and Practice, ed: Springer,
2008, pp. 139-150.
[21] K. J. Cios and W. G. Moore, "Uniqueness of medical data mining,"
Artificial intelligence in medicine, vol. 26, pp. 1-24, 2002.
[22] M. Kwiatkowska, M. S. Atkins, N. T. Ayas, and C. F. Ryan,
"Knowledge-based data analysis: first step toward the creation of clinical
prediction rules using a new typicality measure," Information
Technology in Biomedicine, IEEE Transactions on, vol. 11, pp. 651-660,
2007.
[23] N. Esfandiary, M. R. Babavalian, A.-M. E. Moghadam, and V. K. Tabar,
"Knowledge Discovery in Medicine: Current Issue and Future Trend,"
Expert Systems with Applications, vol. 41, pp. 4434–4463, 2014.
[24] X.-B. Li and J. Qin, "A Framework for Privacy-Preserving Medical
Document Sharing," in Thirty Fourth International Conference on
Information Systems, Milan, Italy, 2013.
[25] H. Chen, R. H. Chiang, and V. C. Storey, "Business Intelligence and
Analytics: From Big Data to Big Impact," MIS quarterly, vol. 36, 2012.
[26] T. J. Eggebraaten, J. W. Tenner, and J. C. Dubbels, "A health-care data
model based on the HL7 reference information model," IBM Systems
Journal, vol. 46, pp. 5-18, 2007.
[27] Jibitesh Mishra and A. Mohanty, Software Engineering: Pearson
Education India, 2011.
[28] P. Naur and B. Randell, Software Engineering: Report of a conference
sponsored by the NATO Science Committee, Garmisch, Germany, 7-11
Oct. 1968, Brussels, Scientific Affairs Division, NATO, 1969.
[29] K. Beck, M. Beedle, A. Van Bennekum, A. Cockburn, W. Cunningham,
M. Fowler, J. Grenning, J. Highsmith, A. Hunt, and R. Jeffries,
Manifesto for agile software development, 2001, Available:
http://agilemanifesto.org/
[30] S. Gregor and A. R. Hevner, "Positioning and presenting design science
research for maximum impact," MIS Quarterly, vol. 37, pp. 337-356,
2013.
[31] S. L. Pan and B. Tan, "Demystifying case research: A structured–
pragmatic–situational (SPS) approach to conducting case studies,"
Information and Organization, vol. 21, pp. 161-176, 2011.
[32] S. W. Ambler, "Agile Model Driven Development (AMDD)," in
XOOTIC Symposium 2006, 2006, p. 13.
[33] M. Cohn, User stories applied: For agile software development:
Addison-Wesley Professional, 2004.
[34] K. Collier, Agile analytics: A value-driven approach to business
intelligence and data warehousing: Addison-Wesley, 2011.
[35] J. Zubcoff and J. Trujillo, "A UML 2.0 profile to design Association
Rule mining models in the multidimensional conceptual modeling of
data warehouses," Data & Knowledge Engineering, vol. 63, pp. 44-62,
2007.
[36] OMG, "Omg Unified Modeling Language (OMG UML) Superstructure
specification version 2.4. 1," document formal/2011-08-06. Technical
report, OMG, 2011.
[37] M. A. Hamburg and F. S. Collins, "The path to personalized medicine,"
New England journal of medicine, vol. 363, pp. 301-304, 2010.
@article{"International Journal of Medical, Medicine and Health Sciences:68301", author = "Supunmali Ahangama and Danny Chiang Choon Poo", title = "Unified Structured Process for Health Analytics", abstract = "Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.
", keywords = "Agile methodology, health analytics, unified process
model, UML.", volume = "8", number = "11", pages = "795-9", }
