Appl Clin Inform 2011; 02(04): 420-436
DOI: 10.4338/ACI-2011-07-RA-0043
Research Article
Schattauer GmbH

An Evaluation of the Usability of a Computerized Decision Support System for Nursing Homes

M. Fossum
1   School of Health and Medical Sciences, Örebro University, Örebro, Sweden
2   Centre for Caring Research – Southern Norway, Department of Health and Nursing Sciences, Faculty of Health and Sport Sciences, University of Agder, Grimstad, Norway
,
M. Ehnfors
1   School of Health and Medical Sciences, Örebro University, Örebro, Sweden
,
A. Fruhling
3   School of Interdisciplinary Informatics, College of Information Science and Technology, University of Nebraska, Omaha, USA
,
A. Ehrenberg
4   School of Health and Social Studies, Dalarna University, Falun, Sweden
› Author Affiliations
Further Information

Correspondence to:

Mariann Fossum RN, MSc
Department of Health and Nursing Science,
Faculty of Health and Sport Sciences,
University of Agder, PO Box 509
NO-4898 Grimstad, Norway
Phone: +4737233756

Publication History

received: 08 July 2011

accepted: 09 September 2011

Publication Date:
16 December 2017 (online)

 

Summary

Background: Computerized decision support systems (CDSSs) have the potential to significantly improve the quality of nursing care of older people by enhancing the decision making of nursing personnel. Despite this potential, health care organizations have been slow to incorporate CDSSs into nursing home practices.

Objective: This study describes facilitators and barriers that impact the ability of nursing personnel to effectively use a clinical CDSS for planning and treating pressure ulcers (PUs) and malnutrition and for following the suggested risk assessment guidelines for the care of nursing home residents.

Methods: We employed a qualitative descriptive design using varied methods, including structured group interviews, cognitive walkthrough observations and a graphical user interface (GUI) usability evaluation. Group interviews were conducted with 25 nursing personnel from four nursing homes in southern Norway. Five nursing personnel participated in cognitive walkthrough observations and the GUI usability evaluation. Text transcripts were analyzed using qualitative content analysis.

Results: Group interview participants reported that ease of use, usefulness and a supportive work environment were key facilitators of CDSS use. The barriers identified were lack of training, resistance to using computers and limited integration of the CDSS with the facility’s electronic health record (EHR) system. Key findings from the usability evaluation also identified the difficulty of using the CDSS within the EHR and the poorly designed GUI integration as barriers.

Conclusion: Overall, we found disconnect between two types of nursing personnel. Those who were comfortable with computer technology reported positive feedback about the CDSS, while others expressed resistance to using the CDSS for various reasons. This study revealed that organizations must invest more resources in educating nursing personnel on the seriousness of PUs and poor nutrition in the elderly, providing specialized CDSS training and ensuring that nursing personnel have time in the workday to use the CDSS.


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Conflict of Interest

The authors declare no conflicts of interest in the research.

  • References

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  • 2 Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J. et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005; 293 (10) 1223-1238.
  • 3 Randell R, Mitchell N, Dowding D, Cullum N, Thompson C, Randell R. et al. Effects of computerized decision support systems on nursing performance and patient outcomes: a systematic review. J Health Serv Res Policy 2007; 12 (04) 242-249.
  • 4 Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Br Med J 2005; 330 (7494) 765-768.
  • 5 Greenes RA. Clinical decision support: the road ahead. Boston, USA: Amsterdam : Elsevier; 2007
  • 6 Alexander GL, Wakefield DS. Information technology sophistication in nursing homes. J Am Med Dir Assoc 2009; 10 (06) 398-407.
  • 7 Alexander GL. Analysis of an integrated clinical decision support system in nursing home clinical information systems. J Gerontol Nurs 2008; 34 (02) 15-20.
  • 8 Fossum M, Alexander G, Ehnfors M, Ehrenberg A. Effects of a computerized decision support system on pressure ulcers and malnutrition in nursing homes for the elderly. Accepted to: Int J Med Inf 2011
  • 9 Lindgren M. Pressure sores risk assessment and prevention [Medical Dissertations No 784]. Linköping: Linköping University; 2003
  • 10 Guigoz Y. The Mini Nutritional Assessment (MNA) review of the literature. What does it tell us?. J Nutr Health Aging 2006; 10 (06) 466-485.
  • 11 Wipke-Tevis DD, Williams DA, Rantz MJ, Popejoy LL, Madsen RW, Petroski GF. et al. Nursing home quality and pressure ulcer prevention and management practices. J Am Geriatr Soc 2004; 52 (04) 583-588.
  • 12 Langer G, Knerr A, Kuss O, Behrens J, Schlömer Gabriele J. Nutritional interventions for preventing and treating pressure ulcers. Cochrane Database Syst Rev. 2003 4..
  • 13 Anderson JA, Willson P. Clinical decision support systems in nursing: synthesis of the science for evidence-based practice. Comput Inform Nurs 2008; 26 (03) 151-158.
  • 14 Randell R, Dowding D. Organisational influences on nurses’ use of clinical decision support systems. Int J Med Inf 2010; 79 (06) 412-421.
  • 15 Sittig DF, Krall MA, Dykstra RH, Russell A, Chin HL. A survey of factors affecting clinician acceptance of clinical decision support. BMC Med Inf Decis Making 2006; 6: 6.
  • 16 Galitz WO. The essential guide to user interface design: an introduction to GUI design principles and techniques. New York: Wiley; 1997
  • 17 Jaspers MWM. A comparison of usability methods for testing interactive health technologies: Methodological aspects and empirical evidence. Int J Med Inf 2009; 78 (05) 340-353.
  • 18 Alexander G, Staggers N. A systematic review of the designs of clinical technology: findings and recommendations for future research. ANS Adv Nurs Sci 2009; 32 (03) 252-279.
  • 19 DeLone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems 2003; 19 (04) 9-30.
  • 20 Davis FD. Perceived Usefulness, Perceived ease of use, and user acceptance of information technology. MIS Quarterly 1989; 13 (03) 319-340.
  • 21 Goodhue DL. Task-technology fit. In: DF G P Z. editors. Human-computer interaction and management information systems: applications. New York: Sharpe; 2006: 184-204.
  • 22 Goodhue DL, Thompson RL. Task-technology fit and individual performance. MIS Quarterly 1995; 19 (02) 213-236.
  • 23 Goodhue DL. Understanding user evaluations of information systems. Manage sci 1995; 41 (12) 1827.
  • 24 Tsiknakis M, Kouroubali A. Organizational factors affecting successful adoption of innovative eHealth services: A case study employing the FITT framework. Int J Med Inf 2009; 78 (01) 39-52.
  • 25 Wills MJ, El-Gayar OF, Deokar AV. Evaluating task-technology fit and user performance for an electonic health record system. Proceedings of the Fifteenth Americas Conference on Information Systems; San Francisco; California: August 6th-9th 2009
  • 26 Dishaw MT, Strong DM. Extending the technology acceptance model with task-technology fit constructs. Inf manage 1999; 36 (01) 9-21.
  • 27 Cane S, McCarthy R. Analyzing the factors that affect information systems use: A task- technology fit meta-analysis. J Comput Inf Syst 2009; 50 (01) 108-123.
  • 28 Kilmon CA, Fagan MH, Pandey V, Belt T. Using the task technology fit model as a diagnostic tool for electronic medical records systems evaluation. Issues in Information Systems 2008; IX (01) 196-204.
  • 29 Ward R, Stevens C, Brentnall P, Briddon J. The attitudes of health care staff to information technology: a comprehensive review of the research literature. Health Info Libr J 2008; 25 (02) 81-97.
  • 30 Bates DW, Gawande AA. Improving safety with information technology. New Engl J Med 2003; 348 (25) 2526.
  • 31 Statistics Norway.. Municipal nursing and care statistics. Preliminary figures, 2008. Oslo: Statistics Norway;. 2008 [cited 2009]; Available from: http://www.ssb.no/english/subjects/03/02/pleie_en.
  • 32 Helse-og omsorgsdepartementet [Norwegian Ministry of Health and Care Services]. Samhandlingsreformen: rett behandling –på rett sted –til rett tid [ The Coordination Reform. Proper treatment –at the right place and right time.]. Oslo: Departementenes servicesenter, Informasjonsforvaltning; 2009
  • 33 Ministry of Health & Care Services. Lov om helsepersonell [Act Relating to Health Personnell]. Oslo: Helseog Omsorgsdepartementet; 1999
  • 34 Lazar J, Feng JH, Hochheiser H. Research methods in human-computer interaction. West Sussex: John Whiley; 2010
  • 35 Alexander GL, Rantz M, Flesner M, Diekemper M, Siem C. Clinical information systems in nursing homes: an evaluation of initial implementation strategies. Comput Inform Nurs 2007; 25 (04) 189-197.
  • 36 Whittaker AA, Aufdenkamp M, Tinley S. Barriers and facilitators to electronic documentation in a rural hospital. J Nurs Scholarsh 2009; 41 (03) 293-300.
  • 37 Ammenwerth E, Mansmann U, Iller C, Eichstädter R. Factors affecting and affected by user acceptance of computer-based nursing documentation: results of a two-year study. J Am Med Inform Assoc 2003; 10 (01) 69-84.
  • 38 Fruhling L, Ann S. The influence of user interface usability on rural consumers’ trust of e-health services. International Journal of Electronic Health Care 2006; 2 (04) 305-321.
  • 39 Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today 2004; 24 (02) 105-112.
  • 40 Toth-Pal E, Wårdh I, Strender L, Nilsson G. Implementing a clinical decision-support system in practice: a qualitative analysis of influencing attitudes and characteristics among general practitioners. Inform Health Soc Care 2008; 33 (01) 39-54.
  • 41 Eley R, Fallon T, Soar J, Buikstra E, Hegney D. Barriers to use of information and computer technology by Australia’s nurses: a national survey. J Clin Nurs 2009; 18 (08) 1151-1158.
  • 42 Mikkelsen G, Aasly J. Concordance of information in parallel electronic and paper based patient records. Int J Med Inf 2001; 63 (03) 123-131.
  • 43 Koch S, Hagglund M. Health informatics and the delivery of care to older people. Maturitas 2009; 63 (03) 195-199.
  • 44 Scandurra I, Hägglund M, Koch S, Lind M. Usability laboratory test of a novel mobile homecare application with experienced home help service staff. Open Med Inform J 2008; 2: 117-128.

Correspondence to:

Mariann Fossum RN, MSc
Department of Health and Nursing Science,
Faculty of Health and Sport Sciences,
University of Agder, PO Box 509
NO-4898 Grimstad, Norway
Phone: +4737233756

  • References

  • 1 Anderson GF, Frogner BK, Johns RA, Reinhardt UE. Health care spending and use of information technology in OECD countries. Health Aff (Millwood) 2006; 25 (03) 819-831.
  • 2 Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J. et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005; 293 (10) 1223-1238.
  • 3 Randell R, Mitchell N, Dowding D, Cullum N, Thompson C, Randell R. et al. Effects of computerized decision support systems on nursing performance and patient outcomes: a systematic review. J Health Serv Res Policy 2007; 12 (04) 242-249.
  • 4 Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Br Med J 2005; 330 (7494) 765-768.
  • 5 Greenes RA. Clinical decision support: the road ahead. Boston, USA: Amsterdam : Elsevier; 2007
  • 6 Alexander GL, Wakefield DS. Information technology sophistication in nursing homes. J Am Med Dir Assoc 2009; 10 (06) 398-407.
  • 7 Alexander GL. Analysis of an integrated clinical decision support system in nursing home clinical information systems. J Gerontol Nurs 2008; 34 (02) 15-20.
  • 8 Fossum M, Alexander G, Ehnfors M, Ehrenberg A. Effects of a computerized decision support system on pressure ulcers and malnutrition in nursing homes for the elderly. Accepted to: Int J Med Inf 2011
  • 9 Lindgren M. Pressure sores risk assessment and prevention [Medical Dissertations No 784]. Linköping: Linköping University; 2003
  • 10 Guigoz Y. The Mini Nutritional Assessment (MNA) review of the literature. What does it tell us?. J Nutr Health Aging 2006; 10 (06) 466-485.
  • 11 Wipke-Tevis DD, Williams DA, Rantz MJ, Popejoy LL, Madsen RW, Petroski GF. et al. Nursing home quality and pressure ulcer prevention and management practices. J Am Geriatr Soc 2004; 52 (04) 583-588.
  • 12 Langer G, Knerr A, Kuss O, Behrens J, Schlömer Gabriele J. Nutritional interventions for preventing and treating pressure ulcers. Cochrane Database Syst Rev. 2003 4..
  • 13 Anderson JA, Willson P. Clinical decision support systems in nursing: synthesis of the science for evidence-based practice. Comput Inform Nurs 2008; 26 (03) 151-158.
  • 14 Randell R, Dowding D. Organisational influences on nurses’ use of clinical decision support systems. Int J Med Inf 2010; 79 (06) 412-421.
  • 15 Sittig DF, Krall MA, Dykstra RH, Russell A, Chin HL. A survey of factors affecting clinician acceptance of clinical decision support. BMC Med Inf Decis Making 2006; 6: 6.
  • 16 Galitz WO. The essential guide to user interface design: an introduction to GUI design principles and techniques. New York: Wiley; 1997
  • 17 Jaspers MWM. A comparison of usability methods for testing interactive health technologies: Methodological aspects and empirical evidence. Int J Med Inf 2009; 78 (05) 340-353.
  • 18 Alexander G, Staggers N. A systematic review of the designs of clinical technology: findings and recommendations for future research. ANS Adv Nurs Sci 2009; 32 (03) 252-279.
  • 19 DeLone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems 2003; 19 (04) 9-30.
  • 20 Davis FD. Perceived Usefulness, Perceived ease of use, and user acceptance of information technology. MIS Quarterly 1989; 13 (03) 319-340.
  • 21 Goodhue DL. Task-technology fit. In: DF G P Z. editors. Human-computer interaction and management information systems: applications. New York: Sharpe; 2006: 184-204.
  • 22 Goodhue DL, Thompson RL. Task-technology fit and individual performance. MIS Quarterly 1995; 19 (02) 213-236.
  • 23 Goodhue DL. Understanding user evaluations of information systems. Manage sci 1995; 41 (12) 1827.
  • 24 Tsiknakis M, Kouroubali A. Organizational factors affecting successful adoption of innovative eHealth services: A case study employing the FITT framework. Int J Med Inf 2009; 78 (01) 39-52.
  • 25 Wills MJ, El-Gayar OF, Deokar AV. Evaluating task-technology fit and user performance for an electonic health record system. Proceedings of the Fifteenth Americas Conference on Information Systems; San Francisco; California: August 6th-9th 2009
  • 26 Dishaw MT, Strong DM. Extending the technology acceptance model with task-technology fit constructs. Inf manage 1999; 36 (01) 9-21.
  • 27 Cane S, McCarthy R. Analyzing the factors that affect information systems use: A task- technology fit meta-analysis. J Comput Inf Syst 2009; 50 (01) 108-123.
  • 28 Kilmon CA, Fagan MH, Pandey V, Belt T. Using the task technology fit model as a diagnostic tool for electronic medical records systems evaluation. Issues in Information Systems 2008; IX (01) 196-204.
  • 29 Ward R, Stevens C, Brentnall P, Briddon J. The attitudes of health care staff to information technology: a comprehensive review of the research literature. Health Info Libr J 2008; 25 (02) 81-97.
  • 30 Bates DW, Gawande AA. Improving safety with information technology. New Engl J Med 2003; 348 (25) 2526.
  • 31 Statistics Norway.. Municipal nursing and care statistics. Preliminary figures, 2008. Oslo: Statistics Norway;. 2008 [cited 2009]; Available from: http://www.ssb.no/english/subjects/03/02/pleie_en.
  • 32 Helse-og omsorgsdepartementet [Norwegian Ministry of Health and Care Services]. Samhandlingsreformen: rett behandling –på rett sted –til rett tid [ The Coordination Reform. Proper treatment –at the right place and right time.]. Oslo: Departementenes servicesenter, Informasjonsforvaltning; 2009
  • 33 Ministry of Health & Care Services. Lov om helsepersonell [Act Relating to Health Personnell]. Oslo: Helseog Omsorgsdepartementet; 1999
  • 34 Lazar J, Feng JH, Hochheiser H. Research methods in human-computer interaction. West Sussex: John Whiley; 2010
  • 35 Alexander GL, Rantz M, Flesner M, Diekemper M, Siem C. Clinical information systems in nursing homes: an evaluation of initial implementation strategies. Comput Inform Nurs 2007; 25 (04) 189-197.
  • 36 Whittaker AA, Aufdenkamp M, Tinley S. Barriers and facilitators to electronic documentation in a rural hospital. J Nurs Scholarsh 2009; 41 (03) 293-300.
  • 37 Ammenwerth E, Mansmann U, Iller C, Eichstädter R. Factors affecting and affected by user acceptance of computer-based nursing documentation: results of a two-year study. J Am Med Inform Assoc 2003; 10 (01) 69-84.
  • 38 Fruhling L, Ann S. The influence of user interface usability on rural consumers’ trust of e-health services. International Journal of Electronic Health Care 2006; 2 (04) 305-321.
  • 39 Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today 2004; 24 (02) 105-112.
  • 40 Toth-Pal E, Wårdh I, Strender L, Nilsson G. Implementing a clinical decision-support system in practice: a qualitative analysis of influencing attitudes and characteristics among general practitioners. Inform Health Soc Care 2008; 33 (01) 39-54.
  • 41 Eley R, Fallon T, Soar J, Buikstra E, Hegney D. Barriers to use of information and computer technology by Australia’s nurses: a national survey. J Clin Nurs 2009; 18 (08) 1151-1158.
  • 42 Mikkelsen G, Aasly J. Concordance of information in parallel electronic and paper based patient records. Int J Med Inf 2001; 63 (03) 123-131.
  • 43 Koch S, Hagglund M. Health informatics and the delivery of care to older people. Maturitas 2009; 63 (03) 195-199.
  • 44 Scandurra I, Hägglund M, Koch S, Lind M. Usability laboratory test of a novel mobile homecare application with experienced home help service staff. Open Med Inform J 2008; 2: 117-128.