Risk Mining in Medicine: Application of Data Mining to Medical Risk Management

Procedia Computer Science

2015

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This paper proposes a method for construction of a clinical pathway based on attribute and sample clustering, called dual clustering. The method consists of the following four steps: first, histories of nursing orders are extracted from hospital information system. Second, orders are classified into several groups by using clustering on the pricipal components (sample clustering). Third, attributes clustering is applied to the data. Finally, original temporal data are split into several sub-tables and the first step will be repeated in a recursive way. After the grouping results are stable, a new pathway will be constructed from all the induced results. The method was applied to datasets of a disease extracted from a hospital information system. The results show that the proposed method constructed a clinical pathway, which was not only similar to the pathway manually acquired from medical experts but also discovered nursing orders which they forget to include.

Section: Introductionmentioning

confidence: 99%

“…A hospital information system (HIS) was introduced about twenty years ago and all the clinical environment has been dramatically changed [1,2,3]. HIS stores all the histories of clinical activities in a hospital, such as electronic patient records, laboratory data, x-ray photos, and so on.…”

Section: Introductionmentioning

confidence: 99%

Mining Schedule of Nursing Care Based on Dual-Clustering

Procedia Computer Science

2015

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“…Due to the traceability of all the information, a hospital cannot function without the information system. All the clinical inputs are shared through the network service in which medical staff can retrieve their information from their terminals [4,8].…”

Section: Introductionmentioning

confidence: 99%

Mining Clinical Pathway Based on Clustering and Feature Selection

Lecture Notes in Computer Science

2013

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Abstract. Schedule management of hospitalization is important to maintain or improve the quality of medical care and application of a clinical pathway is one of the important solutions for the management. This research proposed an data-oriented maintenance of existing clinical pathways by using data on histories of nursing orders. If there is no clinical pathway for a given disease, the method will induce a new clinical care plan from the data. The method was evaluated on 10 diseases. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.

“…Incident or accident reports are not exception: they are also stored in HIS as clinical databases. All the clinical inputs are shared through the network service in which medical staff can retrieve their information from their terminals [1,3].…”

Section: Introductionmentioning

confidence: 99%

Temporal data mining of order entry histories for characterization of medical practice

2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

2012

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Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system. This paper proposes temporal data mining process and applied the method to capture temporal knowledge about nursing practice. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.