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Appl Clin Inform 2015; 06(02): 418-428
DOI: 10.4338/ACI-2015-04-RA-0037
Research Article
Schattauer GmbH

A Nursing Intelligence System to Support Secondary Use of Nursing Routine Data

W.O. Hackl
1   Institute of Biomedical Informatics, UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
,
F. Rauchegger
2   Nursing Management Board, Nursing Informatics, TILAK, Innsbruck, Austria
,
E. Ammenwerth
1   Institute of Biomedical Informatics, UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
› Author Affiliations
Further Information

Correspondence to:

Dr. Werner O. Hackl
Institute of Biomedical Informatics, UMIT-University of
Health Sciences, Medical Informatics and Technology
Eduard Wallnöfer Zentrum 1
6060 Hall in Tirol, Austria

Publication History

received: 01 April 2014

accepted in revised form: 02 May 2015

Publication Date:
19 December 2017 (online)

Also available at
 
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Summary

Background: Nursing care is facing exponential growth of information from nursing documentation. This amount of electronically available data collected routinely opens up new opportunities for secondary use.

Objectives: To present a case study of a nursing intelligence system for reusing routinely collected nursing documentation data for multiple purposes, including quality management of nursing care.

Methods: The SPIRIT framework for systematically planning the reuse of clinical routine data was leveraged to design a nursing intelligence system which then was implemented using open source tools in a large university hospital group following the spiral model of software engineering.

Results: The nursing intelligence system is in routine use now and updated regularly, and includes over 40 million data sets. It allows the outcome and quality analysis of data related to the nursing process.

Conclusions: Following a systematic approach for planning and designing a solution for reusing routine care data appeared to be successful. The resulting nursing intelligence system is useful in practice now, but remains malleable for future changes.

Citation: Hackl WO, Rauchegger F, Ammenwerth E A Nursing Intelligence System to Support Secondary Use of Nursing Routine Data. Appl Clin Inform 2015; 6: 418–428

http://dx.doi.org/10.4338/ACI-2015-04-RA-0037


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Keywords

Medical informatics - nursing informatics - databases - data integration - data mining

 


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Conflict of Interest

The authors declare that they have no conflicts of interest in the research.

  • References

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Correspondence to:

Dr. Werner O. Hackl
Institute of Biomedical Informatics, UMIT-University of
Health Sciences, Medical Informatics and Technology
Eduard Wallnöfer Zentrum 1
6060 Hall in Tirol, Austria

  • References

  • 1 Berner E, Moss J. Informatics Challenges for the Impending Patient Information Explosion. J Am Med Inform Assoc 2005; 12 (06) 614-617.
    CrossrefPubMedSearch in Google Scholar
  • 2 Leiner F, Haux R. Systematic Planning of Clinical Documentation. Methods Inf Med 1996; 35 (01) 25-34.
    Thieme ConnectPubMedSearch in Google Scholar
  • 3 Mayer-Schönberger V, Cukier K. Big Data: A Revolution that Will Transform how We Live, Work, and Think: Houghton Mifflin Harcourt. 2013
    PubMedSearch in Google Scholar
  • 4 Safran C, Bloomrosen M, Hammond WE, Labkoff S, Markel-Fox S, Tang PC, Detmer DE, Expert P. Toward a national framework for the secondary use of health data: an American Medical Informatics Association White Paper. J Am Med Inform Assoc 2007; 14 (01) 1-9.
    CrossrefPubMedSearch in Google Scholar
  • 5 Joint Commission on Accreditation of Healthcare Organizations.. Primer on indicator development and application : measuring quality in health care. Oakbrook Terrace, Ill.: Joint Commission on Accreditation of Healthcare Organizations; 1990
    Search in Google Scholar
  • 6 Burston S, Chaboyer W, Gillespie B. Nurse-sensitive indicators suitable to reflect nursing care quality: a review and discussion of issues. J Clin Nurs 2014; 23 13–14 1785-1795.
    CrossrefPubMedSearch in Google Scholar
  • 7 Prokosch HU, Ganslandt T. Perspectives for medical informatics. Reusing the electronic medical record for clinical research. Methods Inf Med 2009; 48 (01) 38-44.
    Thieme ConnectPubMedSearch in Google Scholar
  • 8 Hackl WO. Erschließung und Sekundärnutzung von Routinedaten aus der klinischen und pflegerischen Prozessdokumentation: Ein Rahmenkonzept, Vorgehensmodell und Leitfaden. Hall in Tirol: UMIT –University for Health Sciences, Medical Informatics and Technology; 2013
    Search in Google Scholar
  • 9 Hackl WO, Ammenwerth E. SPIRIT: A Conceptual Framework and Procedure Model for Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data. Methods Inf Med.; 2015 ; submitted
    PubMedSearch in Google Scholar
  • 10 Mahoney FI, Barthel DW. Functional Evaluation: The Barthel Index. Md State Med J 1965; 14: 61-65.
    PubMedSearch in Google Scholar
  • 11 Braden BJ, Bergstrom N. Clinical utility of the Braden scale for Predicting Pressure Sore Risk. Decubitus 1989; 2 (03) 44-46 50-51.
    PubMedSearch in Google Scholar
  • 12 Ammenwerth E, Buchberger W, Kofler A, Krismer M, Lechleitner G, Pfeiffer K-P, Schaubmayr C, Triendl C, Vogl R. IT-Strategie 2008 –2012 der Tiroler Landeskrankenanstalten (TILAK): Informationstechnologie im Dienste von Medizin und Pflege. 2007
    PubMedSearch in Google Scholar
  • 13 Bauer A, Günzel H. Data-Warehouse-Systeme: Architektur, Entwicklung, Anwendung. Heidelberg: dpunkt-Verlag; 2009
    Search in Google Scholar
  • 14 Boehm B. A spiral model of software development and enhancement. IEEE Computer. 1988; 21 (05) 61-72.
    PubMedSearch in Google Scholar
  • 15 Junttila K, Meretoja R, Seppala A, Tolppanen EM, Ala-Nikkola T, Silvennoinen L. Data warehouse approach to nursing management. J Nurs Manag 2007; 15 (02) 155-161.
    CrossrefPubMedSearch in Google Scholar
  • 16 Li P, Wu T, Chen M, Zhou B, Xu WG. A study on building data warehouse of hospital information system. Chin Med J (Engl) 2011; 124 (15) 2372-2377.
    PubMedSearch in Google Scholar
  • 17 Samaha T, Croll P. A Data Warehouse Architecture for Clinical Data Warehousing. In: Roddick F, Warren J. editors. Proceedings Australasian Workshop on Health Knowledge Management and Discovery (HKMD 2007) CRPIT. Ballarat, Victoria: Australian Computer Society; 2007: 227-232.
    PubMedSearch in Google Scholar
  • 18 Aller RD. The clinical laboratory data warehouse. An overlooked diamond mine. Am J Clin Pathol 2003; 120 (06) 817-819.
    CrossrefPubMedSearch in Google Scholar
  • 19 Webster PC. Sweden’s health data goldmine. CMAJ. 2014; 186 (09) E310.
    CrossrefPubMedSearch in Google Scholar
  • 20 Dehmer M, Hackl WO, Emmert-Streib F, Schulc E, Them C. Network nursing: connections between nursing and complex network science. Int J Nurs Knowl 2013; 24 (03) 150-156.
    PubMedSearch in Google Scholar
  • 21 Collins SA, Cato K, Albers D, Scott K, Stetson PD, Bakken S, Vawdrey DK. Relationship between nursing documentation and patients’ mortality. Am J Crit Care 2013; 22 (04) 306-313.
    CrossrefPubMedSearch in Google Scholar

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