No CrossRef data available.
Optimizing red blood cell transfusion practices in the intensive care unit: a multi-phased health technology reassessment
Published online by Cambridge University Press: 20 December 2021
Abstract
Background
Health technology reassessment (HTR) is a process to manage existing health technologies to ensure ongoing optimal use. A model to guide HTR was developed; however, there is limited practical experience. This paper addresses this knowledge gap through the completion of a multi-phase HTR of red blood cell (RBC) transfusion practices in the intensive care unit (ICU).
Objective
The HTR consisted of three phases and here we report on the final phase: the development, implementation, and evaluation of behavior change interventions aimed at addressing inappropriate RBC transfusions in an ICU.
Methods
The interventions, comprised of group education and audit and feedback, were co-designed and implemented with clinical leaders. The intervention was evaluated through a controlled before-and-after pilot feasibility study. The primary outcome was the proportion of potentially inappropriate RBC transfusions (i.e., with a pre-transfusion hemoglobin of 70 g/L or more).
Results
There was marked variability in the monthly proportion of potentially inappropriate RBC transfusions. Relative to the pre-intervention phase, there was no significant difference in the proportion of potentially inappropriate RBC transfusions post-intervention. Lessons from this work include the importance of early and meaningful engagement of clinical leaders; tailoring the intervention modalities; and, efficient access to data through an electronic clinical information system.
Conclusions
It was feasible to design, implement, and evaluate a tailored, multi-modal behavior change intervention in this small-scale pilot study. However, early evaluation of the intervention revealed no change in technology use leading to reflection on the important question of how the HTR model needs to be improved.
Keywords
- Type
- Assessment
- Information
- Copyright
- Copyright © The Author(s), 2021. Published by Cambridge University Press
References
Canadian Agency for Drugs and Technologies in Health (CADTH). CADTH 2018–2021 STRATEGIC PLAN. Transforming how we manage health technologies in support of better health, better patient experience, and better value. Ottawa: CADTH; 2018.Google Scholar
Porter, ME. What is value in health care? N Engl J Med. 2010;363:2477–81.CrossRefGoogle ScholarPubMed
Peacock, S, Ruta, D, Mitton, C, Donaldson, C, Bate, A, Murtagh, M. Using economics to set pragmatic and ethical priorities. BMJ. 2006;332:482–5.CrossRefGoogle ScholarPubMed
Haas, M, Hall, J, Viney, R, Gallego, G. Breaking up is hard to do: Why disinvestment in medical technology is harder than investment. Aust Health Rev. 2012;36:148–52.CrossRefGoogle Scholar
Pearson, S, Littlejohns, P. Reallocating resources: How should the national institute for health and clinical excellence guide disinvestment efforts in the national health service? J Health Serv Res Policy. 2007;12:160–5.CrossRefGoogle ScholarPubMed
Daniels, T, Williams, I, Robinson, S, Spence, K. Tackling disinvestment in health care services: The views of resource allocators in the English NHS. J Health Organ Manag. 2013;27:762–80.CrossRefGoogle ScholarPubMed
Harris, C, Green, S, Elshaug, AG. Sustainability in health care by allocating resources effectively (SHARE) 10: Operationalising disinvestment in a conceptual framework for resource allocation. BMC Health Serv Res. 2017;17:632.CrossRefGoogle Scholar
Elshaug, AG, Hiller, JE, Tunis, SR, Moss, JR. Challenges in Australian policy processes for disinvestment from existing, ineffective health care practices. Aust New Zealand Health Policy. 2007;4:23.CrossRefGoogle ScholarPubMed
Calabro, GE, La Torre, G, de Waure, C, Villari, P, Federici, A, Ricciardi, W, et al. Disinvestment in healthcare: An overview of HTA agencies and organizations activities at European level. BMC Health Serv Res. 2018;18:148.CrossRefGoogle ScholarPubMed
Niven, DJ, Mrklas, KJ, Holodinsky, JK, Straus, SE, Hemmelgarn, BR, Jeffs, LP, et al. Towards understanding the de-adoption of low-value clinical practices: A scoping review. BMC Med. 2015;13:255.CrossRefGoogle ScholarPubMed
Prasad, V, Ioannidis, J. Evidence-based de-implementation for contradicted, unproven, and aspiring healthcare practices. Implement Sci. 2014;9:5908–9.CrossRefGoogle ScholarPubMed
van Bodegom-Vos, L, Davidoff, F, Marang-van de Mheen, PJ. Implementation and de-implementation: Two sides of the same coin? BMJ Qual Saf. 2017;26:495–501.CrossRefGoogle ScholarPubMed
Upvall, MJ, Bourgault, AM. De-implementation: A concept analysis. Nursing Forum 2018; 53(3):376–82.Google Scholar
MacKean, G, Noseworthy, T, Elshaug, AG, Leggett, L, Littlejohns, P, Berezanski, J, et al. Health technology reassessment: The art of the possible. Int J Technol Assess Health Care. 2013;29:418–23.CrossRefGoogle ScholarPubMed
Soril, LJ, MacKean, G, Noseworthy, TW, Leggett, LE, Clement, FM. Achieving optimal technology use: A proposed model for health technology reassessment. SAGE Open Med. 2017;5:2050312117704861.CrossRefGoogle ScholarPubMed
Soril, LJJ, Niven, DJ, Esmail, R, Noseworthy, TW, Clement, FM. Untangling, unbundling, and moving forward: Framing health technology reassessment in the changing conceptual landscape. Int J Technol Assess Health Care. 2018;34:212–7.CrossRefGoogle ScholarPubMed
Noseworthy, T, Clement, F. Health technology reassessment: Scope, methodology, & language. Int J Technol Assess Health Care. 2012;28:201–2.CrossRefGoogle ScholarPubMed
Pant, S, Boucher, M, Frey, N. Health CAfdati. Health technology reassessment: An overview of Canadian and international processes. Ottawa: CADTH; 2019. (Environmental scan; no. 85).Google Scholar
Elshaug, AG, Moss, JR, Littlejohns, P, Karnon, J, Merlin, TL, Hiller, JE. Identifying existing health care services that do not provide value for money. Med J Aust. 2009;190:269–73.CrossRefGoogle Scholar
Canada, CW. Recommendations and resources, by Specialty 2018 [cited 2018 Apr 18]. Available from: https://choosingwiselycanada.org/recommendations/.Google Scholar
Soril, LJJ, Seixas, BV, Mitton, C, Bryan, S, Clement, FM. Moving low value care lists into action: Prioritizing candidate health technologies for reassessment using administrative data. BMC Health Serv Res. 2018;18:640.CrossRefGoogle ScholarPubMed
Leon, AC, Davis, LL, Kraemer, HC. The role and interpretation of pilot studies in clinical research. J Psychiatr Res. 2011;45:626–9.CrossRefGoogle ScholarPubMed
Cullen, DJ, Sweitzer, BJ, Bates, DW, Burdick, E, Edmondson, A, Leape, LL. Preventable adverse drug events in hospitalized patients: A comparative study of intensive care and general care units. Crit Care Med. 1997;25:1289–97.CrossRefGoogle ScholarPubMed
Moyen, E, Camire, E, Stelfox, HT. Clinical review: Medication errors in critical care. Crit Care. 2008;12:208.CrossRefGoogle ScholarPubMed
Canadian Institute for Health Information. Care in Canadian ICUs. Ottawa, ON: CIHI; 2016.Google Scholar
Kahn, JM. Disseminating clinical trial results in critical care. Crit Care Med. 2009;37:S147–53.CrossRefGoogle ScholarPubMed
Puri, N, Puri, V, Dellinger, RP. History of technology in the intensive care unit. Crit Care Clin. 2009;25:185–200. ix.CrossRefGoogle ScholarPubMed
Stelfox, HT, Niven, DJ, Clement, FM, Bagshaw, SM, Cook, DJ, McKenzie, E, et al. Stakeholder engagement to identify priorities for improving the quality and value of critical care. PLoS One. 2015;10:e0140141.CrossRefGoogle Scholar
Shander, A, Javidroozi, M, Lobel, G. Patient blood management in the intensive care unit. Transfus Med Rev. 2017;31:264–71.CrossRefGoogle ScholarPubMed
Soril, LJJ, Noseworthy, TW, Stelfox, HT, Zygun, DA, Clement, FM. A retrospective observational analysis of red blood cell transfusion practices in stable, non-bleeding adult patients admitted to nine medical-surgical intensive care units. J Intensive Care. 2019;7:19.CrossRefGoogle ScholarPubMed
Soril, LJJ, Sparling, M, Gill, S, Noseworthy, T, Clement, F. The effectiveness of behavioural interventions targeting inappropriate physician transfusion practices: A systematic review protocol. University of York: Centre for Reviews and Dissemination; 2015. [cited 2016 Nov 25]. Available from: http://www.crd.york.ac.uk/prospero/display_record.asp?ID=CRD42015024757.Google Scholar
Soril, LJJ, Noseworthy, TW, Stelfox, HT, Zygun, DA, Clement, FM. Facilitators of and barriers to adopting a restrictive red blood cell transfusion practice: A population-based cross-sectional survey. CMAJ Open. 2019;7:E252–e7.CrossRefGoogle ScholarPubMed
Bagshaw, SM, Wang, X, Zygun, DA, Zuege, D, Dodek, P, Garland, A, et al. Association between strained capacity and mortality among patients admitted to intensive care: A path-analysis modeling strategy. J Crit Care. 2018;43:81–7.CrossRefGoogle ScholarPubMed
Michie, S, Johnston, M, Francis, J, Hardeman, W, Eccles, M. From theory to intervention: Mapping theoretically derived behavioural determinants to behaviour change techniques. Appl Psychol. 2008;57:660–80.CrossRefGoogle Scholar
Soril, LJJ, Noseworthy, TW, Dowsett, LE, Memedovich, K, Holitzki, HM, Lorenzetti, DL, et al. Behaviour modification interventions to optimise red blood cell transfusion practices: A systematic review and meta-analysis. BMJ Open. 2018;8:e019912.CrossRefGoogle ScholarPubMed
Brundin-Mather, R, Soo, A, Zuege, DJ, Niven, DJ, Fiest, K, Doig, CJ, et al. Secondary EMR data for quality improvement and research: A comparison of manual and electronic data collection from an integrated critical care electronic medical record system. J Crit Care. 2018;47:295–301.CrossRefGoogle ScholarPubMed
Carson, JL, Stanworth, SJ, Roubinian, N, Fergusson, DA, Triulzi, D, Doree, C, et al. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2016;10:Cd002042.Google ScholarPubMed
Lagerquist, O, Poseluzny, D, Werstiuk, G, Slomp, J, Maier, M, Nahirniak, S, et al. The cost of transfusing a unit of red blood cells: A costing model for Canadian hospital use. ISBT Sci Ser. 2017;12(3):375–80.CrossRefGoogle Scholar
Bank of Canada. Inflation Calculator 2019 [cited 2019 Apr 26]. Available from: https://www.bankofcanada.ca/rates/related/inflation-calculator/.Google Scholar
Polisena, J, Clifford, T, Elshaug, AG, Mitton, C, Russell, E, Skidmore, B. Case studies that illustrate disinvestment and resource allocation decision-making processes in health care: A systematic review. Int J Technol Assess Health Care. 2013;29:174–84.CrossRefGoogle ScholarPubMed
Leggett, L, Noseworthy, TW, Zarrabi, M, Lorenzetti, D, Sutherland, LR, Clement, FM. Health technology reassessment of non-drug technologies: Current practices. Int J Technol Assess Health Care. 2012;28:220–7.CrossRefGoogle ScholarPubMed
Leggett, LE, Mackean, G, Noseworthy, TW, Sutherland, L, Clement, F. Current status of health technology reassessment of non-drug technologies: Survey and key informant interviews. Health Res Policy Syst. 2012;10:38.CrossRefGoogle ScholarPubMed
Cane, J, O'Connor, D, Michie, S. Validation of the theoretical domains framework for use in behaviour change and implementation research. Implement Sci. 2012;7:37.CrossRefGoogle ScholarPubMed
Michie, S, Johnston, M, Abraham, C, Lawton, R, Parker, D, Walker, A. Making psychological theory useful for implementing evidence based practice: A consensus approach. Qual Saf Health Care. 2005;14:26–33.CrossRefGoogle ScholarPubMed
Stelfox, HT, Brundin-Mather, R, Soo, A, Parsons Leigh, J, Niven, DJ, Fiest, KM, et al. A multicentre controlled pre-post trial of an implementation science intervention to improve venous thromboembolism prophylaxis in critically ill patients. Intensive Care Med. 2019;45:211–22.CrossRefGoogle ScholarPubMed
Voorn, VMA, Marang-van de Mheen, PJ, van der Hout, A, Hofstede, SN, So-Osman, C, van den Akker-van Marle, ME, et al. The effectiveness of a de-implementation strategy to reduce low-value blood management techniques in primary hip and knee arthroplasty: A pragmatic cluster-randomized controlled trial. Implement Sci. 2017;12:72.CrossRefGoogle ScholarPubMed
Miech, EJ, Rattray, NA, Flanagan, ME, Damschroder, L, Schmid, AA, Damush, TM. Inside help: An integrative review of champions in healthcare-related implementation. SAGE Open Med. 2018;6:2050312118773261.CrossRefGoogle ScholarPubMed
Ivers, N, Jamtvedt, G, Flottorp, S, Young, JM, OdgaardJensen, J, French, SD, et al. Audit and feedback: Effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012:CD000259.Google ScholarPubMed
Soril, LJ, Clement, FM, Noseworthy, TW. Bioethics, health technology reassessment, and management. Healthcare Manage Forum. 2016;29:275–8.CrossRefGoogle ScholarPubMed
Buist, DS, Chang, E, Handley, M, Pardee, R, Gundersen, G, Cheadle, A, et al. Primary care clinicians’ perspectives on reducing low-value care in an integrated delivery system. Perm J. 2016;20:41–6.Google Scholar
Colla, CH, Kinsella, EA, Morden, NE, Meyers, DJ, Rosenthal, MB, Sequist, TD. Physician perceptions of choosing Wisely and drivers of overuse. Am J Manag Care. 2016;22:337–43.Google ScholarPubMed
Craig, P, Dieppe, P, Macintyre, S, Michie, S, Nazareth, I, Petticrew, M, et al. Developing and evaluating complex interventions. UK: Medical Reserach Council; 2019.Google Scholar
Kaur, N, Figueiredo, S, Bouchard, V, Moriello, C, Mayo, N. Where have all the pilot studies gone? A follow-up on 30 years of pilot studies in clinical rehabilitation. Clin Rehabil. 2017;31:1238–48.CrossRefGoogle Scholar
Netzer, G, Liu, X, Harris, AD, Edelman, BB, Hess, JR, Shanholtz, C, et al. Transfusion practice in the intensive care unit: A 10-year analysis. Transfusion. 2010;50:2125–34.CrossRefGoogle ScholarPubMed
Wagner, AK, Soumerai, SB, Zhang, F, Ross-Degnan, D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27:299–309.CrossRefGoogle ScholarPubMed
Johnson, TP, Wislar, JS. Response rates and nonresponse errors in surveys. Jama. 2012;307:1805–6.CrossRefGoogle ScholarPubMed
Lord, CG, Taylor, CA. Biased assimilation: Effects of assumptions and expectations on the interpretation of new evidence. Soc Personal Psychol Compass. 2009;3:827–41.CrossRefGoogle Scholar
Payne, VL, Hysong, SJ. Model depicting aspects of audit and feedback that impact physicians’ acceptance of clinical performance feedback. BMC Health Serv Res. 2016;16:260.CrossRefGoogle ScholarPubMed
Carroll, C, Patterson, M, Wood, S, Booth, A, Rick, J, Balain, S. A conceptual framework for implementation fidelity. Implement Sci. 2007;2:40.CrossRefGoogle ScholarPubMed
Hulscher, ME, Laurant, MG, Grol, RP. Process evaluation on quality improvement interventions. Qual Saf Health Care. 2003;12:40–6.CrossRefGoogle ScholarPubMed
Soril et al. supplementary material
Soril et al. supplementary material
File
974.2 KB