ABSTRACT
BACKGROUND: There are increasing publications on meaningful collaboration between researchers and patient research partners (PRPs), but fewer publications of such work from the PRP perspective using an evaluation framework. Our aim is to present our own perspectives and reflections on meaningful collaboration as PRPs working on a qualitative research study. MAIN BODY: We were part of a study team that comprised of PRPs, clinicians and academic researchers, and was led by a PRP. The team designed and conducted a qualitative study aimed at understanding how patients make decisions around tapering of biologics for inflammatory bowel disease. The study was conducted online. The PRP lead was trained in qualitative methodology through a one-year certificate program called Patient and Community Engagement Research offered through the University of Calgary Continuing Education. We had received patient-oriented research training and qualitative research training prior to this project. Team members were assigned tasks by our group lead based on member interests and willingness. Some group members were part of the Strategy for Patient-Oriented Research, Inflammation, Microbiome, and Alimentation: Gastro-Intestinal and Neuropsychiatric Effects Network, one of five chronic disease networks in the Strategy for Patient Oriented Research initiative of the Canadian Institutes of Health Research. We describe the five key ingredients to successful collaboration based on our experiences and reflections utilizing the Experience-Reflection-Action Cycle as our framework. The five key ingredients that we identified were: inclusiveness, goal and role clarity, multi-level training and capacity building, shared decision making, and a supportive team lead. CONCLUSION: Overall, our experience was positive. With successful collaboration came an increased level of trust, commitment and performance. There is a need for more studies with diverse PRPs in different settings to validate and/or identify additional factors to improve collaboration in patient-oriented research.
ABSTRACT
BACKGROUND: Outside of a clinical setting, oscillometric devices make remote monitoring of blood pressure and virtual care more convenient and feasible. HeartBeat Technologies Ltd developed a novel approach to measuring blood pressure remotely after an initial blood pressure reading by a nurse using the conventional measurement method. Using a finger pulse oximeter, a photoplethysmogram wave is transmitted by Bluetooth to a smartphone or tablet. A smartphone app (MediBeat) transmits the photoplethysmogram to a server for analysis by a proprietary algorithm-the person's current blood pressure is sent back to the smartphone and to the individual's health care provider. OBJECTIVE: This study sought to determine whether the HeartBeat algorithm calculates blood pressure as accurately as required by the European Society of Hypertension International Protocol revision 2010 (ESH-IP2) for validation of blood pressure measuring devices. METHODS: ESH-IP2 requirements, modified to conform to a more recent international consensus statement, were followed. The ESH-IP2 establishes strict guidelines for the conduct and reporting of any validation of any device to measure blood pressure, including using the standard manual blood pressure instrument as a comparator and specific required accuracy levels for low, medium, and high ranges of blood pressure readings. The consensus statement requires a greater number of study participants for each of the blood pressure ranges. The validation of the accuracy of the algorithm was conducted with a Contec CMS50EW pulse oximeter and a Samsung Galaxy XCover 4 smartphone. RESULTS: The differences between the HeartBeat-calculated and the manually measured blood pressures of 62 study participants did not meet the ESH-IP2 standards for accuracy for either systolic or diastolic blood pressure measurements. There was no discernible pattern in the inaccuracies of the HeartBeat-calculated measurements. CONCLUSIONS: The October 4, 2019 version of the HeartBeat algorithm, implemented in combination with the MediBeat app, a pulse oximeter, and an Android smartphone, was not sufficiently accurate for use in a general adult population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04082819; http://clinicaltrials.gov/ct2/show/NCT04082819.
