Monitoring of whole blood viscosity (WBV) is critical in patients at risk of hyperviscosity (The

Royal College of Pathologies of Australia, 2019). Prothrombin Time Test (PT/INR), which is currently used is insufficient to predict bleeding risk (Cao et al., 2024). There is a test for blood viscosity, which is cheaper than currently recommended plethora of tests, but clinicians are unaware that haematocrit and serum protein, can be used in an algorithm to obtain eWBV that is specific for the cardiovascular phenomenon (Nwose & Bwititi, 2022).

Study design: This study employs a Community-Based Participatory Research (CBPR) approach (Holkup et al., 2004; Sanders & Baisch, 2008; Wynn et al., 2011). This is also designed to be observational cohort and pilot studies, hence the methods’ section of STROBE checklist (Kang & Foster, 2022), is adopted in this protocol layout. The cohort component would involve eWBV analysis of deidentified patients’ data, while pilot component is on participant healthcare personnel.

Participants: The participants would comprise Australian-based general practitioners (GPs) and clinicians

specialising in diabetes and cardiovascular management. This includes GPs, registrars, cardiology and mental health registrars, nurses. Participants will provide informed consent and receive detailed written information about the study. Inability to provide de-identified necessary clinical and laboratory data and/or be available at seminar, workshop and survey constitute exclusion criteria.

Variables: This will include the numbers of seminars and workshops organised, attendance at the events, number of clinicians and health facilities reached. There would be results of ‘perception and uptake’ survey, and publications. Summary of metrics matching study objectives is presented in table 1. Further, data variables for the workshop would include:

• Clinical data of patients’ diagnosis and treatment in-between serial laboratory tests.
• Laboratory data including series of routine haematology and liver function test – at least two sets per patients, with known clinical intervention between tests’ dates. Also, serial INR results done on the same blood collection with routine haematology and liver function test.
• Survey dataset: Likert scale data on perception and uptake

Table 1: The objectives of the current study and the measurable metrics.

A	B
Objective/goal	Metrics
Engage with Public Health Network (PHN) to recruit participants	No. of health facilities and individual recruited
Propagate the developed digital and manual algorithm	No of viewers of the digital and manual algorithm
Organise seminars to promote agenda (intervention step1 of 2)	No. of seminars and attendances
Organise workshops among participants (the intervention step 2 of 2)	No. of workshops and attendances
Assess uptake and user-friendliness of the tools	Qualitative and quantitative analysis of perception

The process

Dynamic flow chart protocol. CBPA for laboratory test implementation study - draft2

Fig 1: Dynamic flow chart

Seminars and workshops would be

convened in at least one facility in the 6 states/territory. Primary

outcome measures include attendance, survey analysis. Secondary outcome

measures include quantitative analysis of eWBV from workshop (Fig 2).

Based on the participants’ capacities, survey of ability and willingness to adopt/integrate the laboratory method into practice would be conducted. Analysis of the perception survey will inform next direction in the implementation research.

Cao, C., Xu, Y., Jiang, W., Wu, S., Shen, Y., Xia, X., Wang, L., Zhang, H., Jiang, H., Li, X., Li, X., & Ye, Y. (2024). Nomogram for predicting bleeding events in nonvalvular atrial fibrillation patients receiving rivaroxaban: A retrospective study. Health Sci Rep , 7 (1), e1792. http://doi.org/10.1002/hsr2.1792

Holkup, P. A., Tripp-Reimer, T., Salois, E. M., & Weinert, C. (2004). Community-based participatory research: an approach to intervention research with a Native American community. ANS Adv Nurs Sci , 27 (3), 162-175. http://doi.org/10.1097/00012272-200407000-00002

Kang, E., & Foster, E. R. (2022). Use of implementation mapping with community-based participatory research: Development of implementation strategies of a new goal setting and goal management intervention system. Front Public Health , 10 , 834473. http://doi.org/10.3389/fpubh.2022.834473

Nwose, E. U., & Bwititi, P. T. (2022). Whole blood viscosity: Affordances and re-evaluation of sensitivity and specificity for clinical use. Int J Bio Lab Sci , 11 (2), 96 - 103. http://www.ijbls.org/index.php/current-issue/101-articles-2022/187-research-article-whole-blood-viscosity-affordances-and-re-evaluation-of-sensitivity-and-specificity-for-clinical-use

Sanders, J., & Baisch, M. J. (2008). Community-based participatory action: impact on a neighborhood level community health improvement process. Prog Community Health Partnersh , 2 (1), 5, 7-15. http://doi.org/10.1353/cpr.2008.0000

The Royal College of Pathologies of Australia. (2019). Viscosity . Retrieved 22nd Aug 2022 from http://www.rcpa.edu.au/Manuals/RCPA-Manual/Pathology-Tests/V/Viscosity

Wynn, T. A., Taylor-Jones, M. M., Johnson, R. E., Bostick, P. B., & Fouad, M. (2011). Using community-based participatory approaches to mobilize communities for policy change. Fam Community Health , 34 Suppl 1 , S102-114. http://doi.org/10.1097/FCH.0b013e318202ee72