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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2017

Open Access 01-12-2017 | Research article

Advancing beyond the system: telemedicine nurses’ clinical reasoning using a computerised decision support system for patients with COPD – an ethnographic study

Authors: Tina Lien Barken, Elin Thygesen, Ulrika Söderhamn

Published in: BMC Medical Informatics and Decision Making | Issue 1/2017

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Abstract

Background

Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses’ reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses’ clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated.

Methods

In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis.

Results

When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: “the process of telemedicine nurses’ reasoning to assess health change” and “the influence of the telemedicine setting on nurses’ reasoning and decision-making processes”. An overall theme, termed “advancing beyond the system”, represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses’ clinical reasoning process.

Conclusion

In the telemedicine setting, when supported by a computerised decision support system, nurses’ reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision-making with the patient. These factors fostered an in-depth knowledge of the patients and acted as a foundation for the nurses’ reasoning process. Nurses’ reasoning frequently advanced beyond the computerised decision support system recommendations. Future studies are warranted to develop more accurate algorithms, increase system maturity, and improve the integration of the digital clinical information with clinical experiences, to support telemedicine nurses’ reasoning process.
Literature
1.
Peck A. Changing the face of standard nursing practice through telehealth and telenursing. Nurs Adm Q. 2005;29:339–43.CrossRefPubMed
2.
Fish D, Higgs J. The context for clinical decision making in the 21st century. In: Higgs J, Jones MA, Loftus S, Christensen N, editors. Clinical Reasoning in the Health Professions. UK: Butterworth-Heinemann; 2008. p. 19–30.
3.
Carnwell R, Daly WM. Advanced nursing practitioners in primary care settings: an exploration of the developing roles. J Clin Nurs. 2003;12:630–42.CrossRefPubMed
4.
5.
6.
7.
8.
9.
Barken TL, Thygesen E, Soderhamn U. Unlocking the limitations: living with chronic obstructive pulmonary disease and receiving care through telemedicine-a phenomenological study. J Clin Nurs. 2017; doi:10.​1111/​jocn.​13857.
10.
Oudshoorn N. Telecare technologies and the transformation of health care. The Netherlands: Palgrave McMillian; 2016.
11.
Pols J. Care at a Distance: on the closeness of technology. Amsterdam: Amsterdam University Press; 2006.
12.
13.
14.
15.
16.
Fonteyn ME, Ritter BJ. Clinical reasoning in nursing. In: Higgs J, Jones MA, Loftus S, Christensen N, editors. Clinical reasoning in the health professions. UK: Butterworth-Heinemann; 2008. p. 235–44.
17.
Higgs J, Jones MA. Clinical decision making and multiple problem spaces. In: Higgs J, Jones MA, Loftus S, Christensen N, editors. Clinical reasoning in the health professions. UK: Butterworth-Heinemann; 2008. p. 3–18.
18.
Alfaro-LeFevre R. Critical thinking, clinical reasoning, and clinical judgement. A critical approach fifth edn. United States: Elsevier; 2013.
19.
20.
Grimmer K, Loftus S. Algorithms, clinical pathways amd clinical guidelines. In: Higgs J, Jones MA, Loftus S, Christensen N, editors. Clinical reasoning in the health professions. UK: Butterworth-Heinemann; 2008. p. 309–18.
21.
Greenes RA. Computer-based clinical decision support: concepts and origins. In: Greenes RA, editor. Clinical decision support: the road ahead. London: Elsevier; 2007. p. 1–107.
22.
23.
24.
25.
Tanner CA. Thinking like a nurse: a research-based model of clinical judgment in nursing. J Nurs Educ. 2006;45:204–11.PubMed
26.
27.
28.
Bucknall T. The clinical landscape of critical care: nurses' decision-making. J Adv Nurs. 2003;43:310–9.CrossRefPubMed
29.
30.
31.
Roshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, Weise-Kelly L, Navarro T, Wilczynski NL, Haynes RB. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implementation science : IS. 2011;6:92. doi:10.​1186/​1748-5908-6-92.CrossRefPubMedPubMedCentral
32.
33.
O'Cathain A, Sampson FC, Munro JF, Thomas KJ, Nicholl JP. Nurses' views of using computerized decision support software in NHS direct. J Adv Nurs. 2004;45:280–6.CrossRefPubMed
34.
35.
36.
37.
Bucknall TK. Critical care nurses' decision-making activities in the natural clinical setting. J Clin Nurs. 2000;9:25–35.CrossRefPubMed
38.
39.
40.
Hammersley M, Atkinson P. Etnography - principles in practice. 3rd ed. London: Routlegde Taylor and Francis Group; 2007.
41.
Madden R. Being ethnographic: a guide to the theory and practice of ethnography. London: Sage Publication; 2010.
42.
43.
44.
45.
Krueger RA, Casey MA. Focus groups: a practical guide for applied research. 5th ed. California: Sage Publications, Inc; 2015.
46.
47.
48.
Gerdes M, Gallefoss F, Fensli RW. The EU project "United4Health": Results and experiences from automatic health status assessment in a Norwegian telemedicine trial system. J Telemed Telecare 2017:1357633x17735558. doi:10.​1177/​1357633x17735558​
49.
50.
Kvale S, Brinkmann S. Det kvalitative forskningsintervjuet. 2nd ed. Oslo: Gyldendal Norsk Forlag; 2009.
51.
52.
QSR International. NVivo qualitative data analysis Software. In., vol. Version 10: QSR International Pty Ltd; 2012.
53.
Biondich P, Mamlin B, Tierney W, Overhage M, McDonald C. Regenstrief Medical Informatics: Experiences with clinical decision support systems. In: Greenes RA, editor. Clinical Decision Support: The Road Ahead. London: Elsevier; 2007. p. 111–26.CrossRef
54.
55.
Sim I, Gorman P, Greenes RA, Haynes RB, Kaplan B, Lehmann H, Tang PC. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc. 2001;8:527–34.CrossRefPubMedPubMedCentral
56.
57.
Trede F, Higgs J. Collaborative decision-making. In: Higgs J, Jones MA, Loftus S, Christensen N, editors. Clinical reasoning in the health professions. UK: Butterworth-Heinemann; 2008. p. 43–54.
58.
59.
60.
61.
62.
Fairbrother P, Pinnock H, Hanley J, McCloughan L, Sheikh A, Pagliari C. Mcn but at what cost? The impact of telemonitoring COPD on continuities of care: a qualitative study. Prim Care Respir J. 2012;21:322–8. doi:10.​4104/​pcrj.​2012.​00068.CrossRefPubMed
63.
64.
Polit DF, Beck CT. Essentials of nursing research: appraising evidence for nursing practice. 7th ed. Philadelphia: Lippincott, Williams & Wilkins; 2010.
65.
66.
Declaration of Helsinki. Ethical principles for medical research involving human subjects. In., vol. 2017. Fortaleza, Brasil: 64th WMA General Assembly; 2013.
67.
Beauchamp TL, Childress JF. Principles of biomedical ethics. 7th ed. Oxford: Oxford University Press; 2013.
Metadata
Title
Advancing beyond the system: telemedicine nurses’ clinical reasoning using a computerised decision support system for patients with COPD – an ethnographic study
Authors
Tina Lien Barken
Elin Thygesen
Ulrika Söderhamn
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2017
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-017-0573-7

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