Nursing intensity and patient classification at an adult intensive care unit (ICU)

Intensive and Critical Care Nursing

Volumn 23, Issue 2, 2007, Pages 97-103

  Lundgrén Laine, Heljä ^a   Suominen, Tarja ^a  

^a UNIVERSITY OF TURKU   (Finland)

Author keywords

Classification; Information system; Nursing intensity

Indexed keywords

ADULT; AGED; APACHE; ARTICLE; FEMALE; FINLAND; HUMAN; INTENSIVE CARE UNIT; MALE; MEDICAL RECORD; MIDDLE AGED; RETROSPECTIVE STUDY; STATISTICS; WORKLOAD;

ADULT; AGED; AGED, 80 AND OVER; APACHE; FEMALE; FINLAND; HUMANS; INTENSIVE CARE UNITS; MALE; MIDDLE AGED; NURSING RECORDS; RETROSPECTIVE STUDIES; WORKLOAD;

EID: 33847657118     PISSN: 09643397     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.iccn.2006.10.006     Document Type: Article

References (29)

1. Ball C. Patient:nurse ratios in critical care-time for some radical thinking. Intens Critical Care Nurs 17 3 (2001) 125-127
2. Beun J.G. Electronic healthcare record; a way to empower the patient. Int J Med Inform 69 (2003) 191-196
3. Burns N., and Grove S.K. The practice of nursing research. Conduct, critique and utilization. Fourth ed. (2001), W.B. Saunders Company, Philadelphia, USA
4. DeGroot H.A. Patient classification systems and staffing. Part 1. Problems and promise. J Nurs Admin 24 9 (1994) 43-51
5. Fagerström L. Patient's caring needs. To understand and measure the unmeasurable. Dissertation. Åbo, Finland: Åbo Univeristy Press; 1999.
6. Fagerström L., Bergbom-Engberg I., and Eriksson K. A comparison between patients' experience of how their caring needs have been met and the nurses' patient classification-an explorative study. J Nurs Manage 6 (1998) 369-377
7. Fagerström L., and Rainio A.-K. Professional assessment of optimal nursing care intensity level: a new method of assessing personnel resources for nursing care. J Clini Nurs 8 (1999) 369-379
8. Fagerström L., Rainio A.-K., Rauhala A., and Nojonen K. Professional assessment of optimal nursing care intensity level. A new method for resource allocation as an alternative to classical time studies. Scand J Caring Sci 14 2 (2000) 97-104
9. Fagerström L, Rauhala A. Finnhoitoisuus-hoitotyön benchmarking. Pilottiprojektin raportti vuodelta 2000. (Finn intensity-benchmarking in nursing. A report of the pilot project from year 2000. The Association of Finnish Local and Regional Authorities) Suomen Kuntaliitto: Helsinki; 2001 (in Finnish).
10. Fagerström L, Rauhala A. Finnhoitoisuus-hoitotyön benchmarking. Projektin loppuraportti 2000-2002. (Finn intensity-benchmarking in nursing. A report of the pilot project 2000-2002. The Association of Finnish Local and Regional Authorities) Suomen Kuntaliitto: Helsinki; 2003 (in Finnish).
11. Fraenkel D.J., Cowie M., and Daley P. Quality benefits of an intensive care clinical information system. Crit Care Med 31 1 (2003) 120-125
12. Frantz A.K. Evaluating technology for success in home care. Caring 20 9 (2001) 10-12
13. Giovannetti P. Staffing methods-implications for nurse staffing. In: Willis L., and Linwood M. (Eds). Measuring the quality of care (1984), Livingstone, London pp. 123-50
14. Goossen W.T.F., Jonker M.J., Heitmann K.U., Jongeneel-de Haas I.C., de Jong T., van der Slikke J.W., and Kabbes B.L. Electronic patient records: domain message information model perinatology. Int J Med Inform 70 (2003) 265-276
15. Hardiker N.-R., and Bakken S. Requirements of tools and techniques to support the entry of structured nursing data. Medinfo (2004) 621-625
16. Kaustinen T. Hoitoisuusluokituksen kehittäminen ja arviointi Oulun yliopistollisessa keskussairaalassa v. 1991-1993. Lisensiaatintutkielma. (The development and evaluation of patient classification. Licentiate thesis. Department of nursing science. University of Oulu.) Hoitotieteen laitos. Oulun yliopisto; 1995 (in Finnish/English abstract).
17. Lekan-Rutledge D. Diffusion of innovation: a model for implementation of prompted voiding in long-term care settings. J Gerontol Nurs 26 4 (2000) 25-33
18. McHugh M.L., and Dwyer V.L. Measurement issues in patient acuity classification for prediction of hours in nursing care. Nurs Admin Q 16 4 (1992) 20-31
19. Malloch K., and Conovaloff A. Patient Classification Systems, Part 1. The third generation. JONA 7-8 29 (1999) 49-56
20. Malloch K., Pellissier Needl A., McMurry C., Meeks L., Wallach M., Williams S., and Conovalof A. Patient classiification systems, part 2. The third generation. JONA 29 9 (1999) 33-42
21. Ministry of Social Affairs and Health, 2003. Health and well-being by evidence-based nursing. The national target and action plan 2004-2007. Helsinki: Ministry of Social Affairs and Health; 2003 (in Finnish/English abstract).
22. Moreno R., and Miranda D.R. Nursing staff in intensive care in Europe. The mismatch between planning and practice. Chest 113 3 (1998) 752-758
23. Partanen P. Nurse staffing in acute care tertiary hospitals. University of Kuopio Publications E. Social Sciences 99; 2002 (in Finnish/English abstract).
24. Pyykkö A., Laurila J., Ala-Kokko T.I., and Hentinen M. Intensive Care Nursing Scoring System. Part 2: Nursing interventions and outcomes. Intens Crit Care Nurs 17 (2001) 16-28
25. Pyykkö A. Development and evaluation of a model of intensive care nursing. University of Oulu, Department of Nursing Science and Health Administration; 2004 (in Finnish/English abstract).
26. Rainio A.-K., and Ohinmaa A.E. Assessment of nursing management and utilization of nursing resources with the RAFAELA patient classification system - case study from the general wards of one central hospital. J Clin Nurs 14 (2005) 674-684
27. Ting-Ting L., Tzu-Ying L., Kuan-Chia L., and Pi-Chen C. Factors affecting the use of nursing information systems in Taiwan. J Adv Nurs 50 2 (2005) 170-178
28. Williams G., Chaboyer W., Thornsteindóttir R., Fulbrook P., Shelton C., Chan D., and Wojner A. Worldwide overview of critical care nursing organizations and their activities. Int Nurs Rev 48 (2001) 208-217
29. Zerwekh J., Thibodeaux R., and Plesko R. Chart it once: innovation in public health documentation. J Commun Health Nurs 17 2 (2000) 75-83