Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-19T07:37:39.308Z Has data issue: false hasContentIssue false

EXPLORING MEDICAL DEVICES: THE USE OF RISK ASSESSMENT TOOLS AND THEIR LINK WITH TRAINING IN HOSPITALS

Published online by Cambridge University Press:  16 April 2018

Petra J. Porte
Affiliation:
The Netherlands Institute for Health Services Research (NIVEL) Department of Public and Occupational Health, Amsterdam Public Health Research Institute (APH)[email protected]
Lisanne M. Verweij
Affiliation:
The Netherlands Institute for Health Services Research (NIVEL)
Martine C. de Bruijne
Affiliation:
Department of Public and Occupational Health, Amsterdam Public Health Research Institute (APH)
Cees P.M. van der Vleuten
Affiliation:
Department of Educational Development and Research, Maastricht University
Cordula Wagner
Affiliation:
The Netherlands Institute for Health Services Research (NIVEL) Department of Public and Occupational Health, Amsterdam Public Health Research Institute (APH)

Abstract

Objectives: The aim of this study was to explore the risk assessment tools and criteria used to assess the risk of medical devices in hospitals, and to explore the link between the risk of a medical device and how those risks impact or alter the training of staff.

Methods: Within a broader questionnaire on implementation of a national guideline, we collected quantitative data regarding the types of risk assessment tools used in hospitals and the training of healthcare staff.

Results: The response rate for the questionnaire was 81 percent; a total of sixty-five of eighty Dutch hospitals. All hospitals use a risk assessment tool and the biggest cluster (40 percent) use a tool developed internally. The criteria used to assess risk most often are: the function of the device (92 percent), the severity of adverse events (88 percent) and the frequency of use (77 percent). Forty-seven of fifty-six hospitals (84 percent) base their training on the risk associated with a medical device. For medium- and high-risk devices, the main method is practical training. As risk increases, the amount and type of training and examination increases.

Conclusions: Dutch hospitals use a wide range of tools to assess the risk of medical devices. These tools are often based on the same criteria: the function of the device, the potential severity of adverse events, and the frequency of use. Furthermore, these tools are used to determine the amount and type of training required for staff. If the risk of a device is higher, then the training and examination is more extensive.

Type
Policy
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Balka, E, Doyle-Waters, M, Lecznarowicz, D, FitzGerald, JM. Technology, governance and patient safety: Systems issues in technology and patient safety. Int J Med Inform. 2007;76 Suppl 1:S35-S47.CrossRefGoogle ScholarPubMed
2. Hefflin, BJ, Gross, TP, Schroeder, TJ. Estimates of medical device-associated adverse events from emergency departments. Am J Prev Med. 2004;27:246-253.CrossRefGoogle ScholarPubMed
3. Wagner, U. Risks in application of medical devices: Human factors in the medical environment. Qual Manag Health Care. 2010;19:304-311.Google Scholar
4. Gullikson, ML, David, Y, Blair, CA. The role of quantifiable risk factors in a medical technology management program. Health care technology: Trends and outcomes, The Environment of Care Series. 1996. http://www.biomedeng.com/wp-content/uploads/2011/05/RoleofQuantifiableRiskFactors.pdf (accessed March 31, 2018).Google Scholar
5. Tawfik, B, Ouda, BK, Abd El Samad, YM. A fuzzy logic model for medical equipment risk classification. J Clin Eng. 2013;38:185-190.Google Scholar
6. Karsh, BT. Beyond usability: Designing effective technology implementation systems to promote patient safety. Qual Saf Health Care. 2004;13:388-394.CrossRefGoogle ScholarPubMed
7. Hamilton, C. Critical assessment of new devices. Perfusion. 2007;22:167-171.Google Scholar
8. WHO. Medical device regulations: Global overview and guiding principles. Geneva: World Health Organization; 2003.Google Scholar
9. ASHE. ASHE risk assessment tool. http://www.ashe.org/resources/riskassessmenttool.shtml (accessed March 31, 2018).Google Scholar
10. Collins, JT. Maintenance risk assessment of medical equipment. Chicago, IL: American Society of Healthcare Engineering. 2007.Google Scholar
11. Porte, PJ, Meijs, JDM, Verweij, LM, et al. Hospitals need more guidance on implementing guidelines for the safe use of medical devices. Health Policy Technol. 2018. In press.Google Scholar
12. Nationale Atlas Volksgezondheid. Locaties Algemene en Academische ziekenhuizen 2014. http://www.zorgatlas.nl/zorg/ziekenhuiszorg/: RIVM; (accessed March 31, 2018).Google Scholar
13. Medical devices directive, (1993). https://cemarking.net/medical-devices-directive/ (accessed March 31, 2018).Google Scholar
14. US FDA. Classify your medical device. http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/Overview/ClassifyYourDevice/default.htm: Food and Drug Administration; 2014 (accessed March 31, 2018).Google Scholar
15. Guez, G, Garg, A. The FDA and the medical device approval process. Dent Implantol Update. 2012;23:33-40.Google Scholar
16. French-Mowat, E, Burnett, J. How are medical devices regulated in the European Union? J R Soc Med. 2012;105 (Suppl 1):S22-S28.Google Scholar
17. Hwang, TJ, Sokolov, E, Franklin, JM, Kesselheim, AS. Comparison of rates of safety issues and reporting of trial outcomes for medical devices approved in the European Union and United States: Cohort study. BMJ. 2016;353:i3323.Google Scholar
18. Wyatt, JC, Altman, DG. Commentary: Prognostic models: Clinically useful or quickly forgotten? BMJ. 1995;311:1539-1541.Google Scholar
19. Harrell, FE, Lee, KL, Matchar, DB, Reichert, TA. Regression models for prognostic prediction: Advantages, problems, and suggested solutions. Cancer Treat Rep. 1985;69:1071-1077.Google Scholar
20. Oliver, D, Daly, F, Martin, FC, McMurdo, ME. Risk factors and risk assessment tools for falls in hospital in-patients: A systematic review. Age Ageing. 2004;33:122-130.Google Scholar
21. Healey, C, Osler, TM, Rogers, FB, et al. Improving the Glasgow Coma Scale score: Motor score alone is a better predictor. J Trauma. 2003;54:671-80.Google Scholar
22. Jennett, B. Development of Glasgow Coma and Outcome Scales. Nepal J Neurosci. 2005;2:24-28.Google Scholar
23. Health and Safety Executive. Risk assessment. A brief guide to controlling risks in the workplace. http://www.hse.gov.uk/pubns/indg163.pdf: Health and Safety Executive; 2014 [updated 08/14.Google Scholar
24. Glendon, AI, Clarke, S, McKenna, E. Human safety and risk management. 2nd ed. Boca Raton, FL: CRC Press; 2016.Google Scholar
25. Top 10 health technology hazards for 2014. ECRI institute; 2013.Google Scholar
26. Top 10 health technology hazards for 2016. ECRI institute; 2015.Google Scholar
27. Greiner, AC, Knebel, E. Health professions education: A bridge to quality. Washington, DC: National Academies Press; 2003.Google Scholar
28. Flottorp, S, Oxman, A, Krause, J, et al. A checklist for identifying determinants of practice: A systematic review and synthesis of frameworks and taxonomies of factors that prevent or enable improvements in healthcare professional practice. Implement Sci. 2013; 8:35.Google Scholar