WEBVTT
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(attendees chattering)
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(attendees chattering continues)
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Thanks.
Thank you for your help.
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Hey, Ericka, how are you?
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Good, how are you?
Good, thank you.
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Hey-
So you must be Vilma?
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Yes, I'm Vilma.
Hello,
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my name is Luke Davis.
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Nice to meet you. (laughs)
Hello, Spanish... (laughs)
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Yeah, I just came to welcome you.
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So I know trying set up with your presentation,
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but I would wanna have a chance to join you and Donna
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for dinner tonight?
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Oh, but not today.
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I'm so late, so we can't have that now.
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I'd love to hear more-
We're working on many,
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many things.
I'd love to hear more,
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and of course I'll learn a lot now,
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and I know you're doing a lot of education-
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Well, you know...
I just wanna...
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Yeah, that's good.
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Some other time.
Well, remember,
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it's my treat.
Okay, thanks very much.
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I really appreciate.
We're ready to turn,
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so if you wanna go to the podium and choose-
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Oh, I see.
You have to do it
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at the podium, yeah. (laughs)
(Vilma laughing)
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All right, I'll go to the podium then. (laughs)
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Oh, okay.
(Vilma laughing)
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So are you ready?
Yeah.
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It's only 12:01.
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We usually give people a little more time
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to arrive.
Okay, I mean, that's good.
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Yeah, we usually do.
Okay.
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Hmm...
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(papers rustling)
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Do you want me to put it in the chat
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that we'll start in about five minutes?
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I can be do that now.
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Can they hear us right now?
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Yeah, we're not muted.
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Okay, yeah, so hi, everyone.
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We're just gonna give people a few more minutes to arrive.
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Hi, everyone, I'm Donna Spiegelman.
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I'm Director of the Center for Methods
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in Implementation and Prevention Science,
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and I'm very pleased today to introduce our speaker,
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Vilma Irazola, who is the Director
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of the South American Center of Excellence
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for Cardiovascular Health and the Institute
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for Clinical Effectiveness and Health Policy,
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both in Buenos Aires, Argentina.
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She's also deputy director
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of the master's degree program in Clinical Effectiveness
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at the University of Buenos Aires.
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She'll be speaking on, "Implementation Science:
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Lessons learned from low- and middle-income countries
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and new challenges."
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And I'm very pleased that this seminar
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is co-sponsored by Yale School of Public Health's
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Department of Chronic Disease Epidemiology,
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and by the Yale Institute for Global Health
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at the Yale School of Medicine,
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and by Cardiovascular Medicine
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at the Yale School of Medicine
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and finally, by our NIH T32 Training Grant
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in Implementation Science Research Methods from NHLBI.
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Vilma is a cardiologist and epidemiologist.
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Her research is focused on implementation science
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in the area of public health, health promotion
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and prevention and management of chronic diseases.
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She has been involved in the design and evaluation
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of community-based and primary care programs
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and interventions related to cardiovascular disease,
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diabetes and aging.
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In addition to her work in Argentina,
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where she also teaches
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Advanced Epidemiologic and Analytic Methods,
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she is Associate Professor of the Cross-Continental MPH
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at the College of Global Public Health at NYU,
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and a scholar and lecturer
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at the Harvard School of Public Health.
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I've known Vilma, I don't know, for how many years?
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15, 20, maybe more.
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We originally met at Harvard
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in connection with the Lown Scholars Program,
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among other things, and I think the last time I saw her
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was in Guatemala before COVID,
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where we were both working in a consortium of projects
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to scale up and implement cardiovascular disease prevention,
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screening and treatment programs around the world,
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a consortium that was sponsored by NHLBI.
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So I'm happy to turn things over to Vilma,
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and I'm looking forward to your talk.
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Thank you.
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Thank you, thank you very much, Donna.
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And thank you for invitation
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and for this opportunity to share some topics
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that we are working on and to listen to you
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and your experiences as well.
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So for today,
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I will share a brief presentation
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about some topics that I'd like to share with you today,
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and I will share my screen in a minute.
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Oh, there it is.
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Okay, so what's the idea today?
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What's the topic?
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This morning actually, Donna and I
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were talking about some aspects
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that are so relevant for our work in implementation science,
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and about which we don't have, still,
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maybe all the methods and tools
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that we may need to approach that.
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So the idea is, today,
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to talk about the role of the control group
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and how to evaluate the control group
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in our implementation science studies,
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the role of context evaluation in this approach
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and the concept of usual care and enhanced usual care
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in our project.
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To do this, I will use two examples from our work
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in Argentina connected with hypertension control.
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These are two cluster-randomized controlled trials
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that we have conducted.
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One of them is finished and the other one is ongoing.
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Well, in terms of context evaluation,
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we all are familiar with the different frameworks
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that we usually use to approach this topic,
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like CFIR, for example,
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which is one of the first ones that approach, in depth,
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the evaluation of outer and inner settings.
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I am sure you are also familiar
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with the RE-AIM-PRISM framework, you know,
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that Dr. Glasgow, who is the developer of the framework,
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I'd say expanded this framework into RE-AIM-PRISM
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to include more aspects related to the context evaluation
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for this framework,
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which in the past was more focused
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only on evaluation and the different aspects of evaluation,
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in terms of reach, effectiveness,
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adoption, implementation among many.
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With RE-AIM-PRISM. we working today several projects
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in Argentina and Brazil and Guatemala,
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and we find it really useful
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for all these other topics that were added
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to the original RE-AIM framework.
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And also, I'd like to share with you this framework,
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which is the CIIP.
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This is a framework that, as far as I know,
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is not very commonly used in implementation research,
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it is more commonly used in training,
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in training projects and programs.
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And I think that there are several things in this framework
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that may be useful for us, as implementation researchers,
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to adopt and to incorporate to our methods.
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And one thing that I find really interesting about CIIP
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is that the context evaluation,
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which is the first step in this framework,
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is then translated into the different stages
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in the framework.
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So according to this framework,
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we keep evaluating the context throughout the project.
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In this case, they are usually education
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or training projects, but the proposal here
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is to keep evaluating these dynamic contexts
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throughout the project and beyond.
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So that's something that might be really useful
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and interesting for us as implementation researchers.
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And this brief introduction about context evaluation
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is connected with the role
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that this type of evaluation might have
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in the description and approach
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to the definition of usual care or enhanced usual care
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in our project.
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And to go into this topic,
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I'd like to share with you an example of a trial,
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a cluster-randomized controlled trial,
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that we conducted in Argentina a few years ago.
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It was about testing a comprehensive intervention
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for improving hypertension control
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in vulnerable population in our country.
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You know that hypertension is a leading global risk factor
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for cardiovascular disease and death,
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and about 75% of people with hypertension
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live in low- and middle income countries.
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And this, again, is pre-pandemic.
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After the pandemic, it's even worse.
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The other thing that is very important and critical for us
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is that less than 10% hypertensive patients in our countries
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are under control,
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or have their blood pressure under control.
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In the case of Argentina,
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the control rate is about 18%,
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according to our last estimations, again, pre-pandemic.
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We have some data from 2021 and early this year
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which indicates that the control rate is even worse.
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Well, so briefly,
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in this trial we selected 18 primary care clinics
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in different provinces in the country,
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and included participants who were adults with hypertension,
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who were really controlled,
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and defined full control of hypertension
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as having a systolic blood pressure
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of 140 millimeters of mercury, or above that number,
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and/or a diastolic blood pressure
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of 90 millimeters of mercury.
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We included these patients,
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their spouses, with or without hypertension,
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because part of the intervention
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was related to the role of peers,
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family members and people living
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with these hypertensive patients,
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and also, any other adult hypertensive family member
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living in the same household.
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That was the population of the study.
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And this is, again, briefly the flow chart of the trial.
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We included 18 public primary care clinics
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that were randomized to the intervention or the control.
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And here is the topic, the control arm.
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We conducted measurements at baseline six, 12 and 18 months,
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the outcomes of the study,
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for changes in systolic and diastolic blood pressure
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and hypertension control rate at 18 months.
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And this is a summary of the intervention.
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We defined three main components.
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The most important one was connected
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with the role of community health workers
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working as part of the primary care team
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and working with the participants, with the patients,
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at their homes.
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In this intervention,
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community health workers visited patients at their homes,
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working with their family as well.
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Patients were provided with BP monitors
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to self-monitor their blood pressure.
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Community health workers trained them
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on how to use these devices
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and to monitor their blood pressure.
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They, community health workers,
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also provided information and tools,
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different tools to improve medication adherence
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and lifestyle modifications.
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So mainly this part of the intervention was very important
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and was led by community health workers
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that were trained to do that.
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The other component was an mHealth component.
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We sent messages, text messages,
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to participants about lifestyle modifications,
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mainly diet and physical activity, that was the focus,
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and again, medication adherence.
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And the third component was directed to physicians,
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primary care physicians.
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Primary care physicians were trained
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in the use of clinical practice guidelines
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and they also received information, feedback,
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about the blood pressure values of their patients.
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What they did when they saw the blood pressure values
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of their patients was something that they decided
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by their own.
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Apart from an initial training on the use
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and contents of clinical practice guidelines,
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we did not do anything else with decisions.
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So they decided what to do, how to manage their patients,
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but they received this information
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that is not part of the initial care.
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Vilma, I have a question.
Yes.
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Can you say
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what blood pressure audit and feedback is?
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Yes.
That's the second component.
270
00:19:09.660 --> 00:19:11.973
Yes, that's the second component.
271
00:19:12.930 --> 00:19:16.390
What we did is the community health worker
272
00:19:18.240 --> 00:19:20.730
visited patient's home each month
273
00:19:20.730 --> 00:19:23.913
during the first six months, and then bimonthly.
274
00:19:25.440 --> 00:19:28.830
When they went to a patient's home,
275
00:19:28.830 --> 00:19:31.250
they reviewed, with the patient,
276
00:19:31.250 --> 00:19:35.336
all the values of their blood pressure,
277
00:19:35.336 --> 00:19:37.188
according to a log
278
00:19:37.188 --> 00:19:40.938
that the participants were asked to complete.
279
00:19:41.940 --> 00:19:45.000
And that information was shared
280
00:19:45.000 --> 00:19:48.630
by the community health worker with the physician.
281
00:19:48.630 --> 00:19:50.064
That's the feedback,
282
00:19:50.064 --> 00:19:55.064
that's the component of sharing data with the physician.
283
00:19:57.360 --> 00:20:02.360
And that's all what we did in that component.
284
00:20:03.960 --> 00:20:06.900
Some physicians were very proactive,
285
00:20:06.900 --> 00:20:10.740
and they take action and adjust medication, et cetera,
286
00:20:10.740 --> 00:20:12.630
and others not.
287
00:20:12.630 --> 00:20:16.330
We haven't had nothing to do directly
288
00:20:17.430 --> 00:20:20.460
through the trial with that.
289
00:20:20.460 --> 00:20:22.083
So that was that component.
290
00:20:23.670 --> 00:20:26.370
And it's important to your question, Donna,
291
00:20:26.370 --> 00:20:27.493
because at the time,
292
00:20:27.493 --> 00:20:32.400
there were no electronic medical records in these clinics.
293
00:20:32.400 --> 00:20:36.330
Now, in these provinces, the situation is different,
294
00:20:36.330 --> 00:20:40.563
so we would be able to do this differently now.
295
00:20:42.060 --> 00:20:45.327
And I can tell you what's happening now
296
00:20:45.327 --> 00:20:47.577
in these provinces as well.
297
00:20:49.411 --> 00:20:53.260
Well, so these are briefly the three components
298
00:20:54.180 --> 00:20:56.343
of the intervention.
299
00:20:57.485 --> 00:21:02.290
This is, for example, a picture of the training sessions
300
00:21:03.420 --> 00:21:06.873
for community health workers at the university,
301
00:21:08.667 --> 00:21:12.570
and these are some examples of the tools
302
00:21:12.570 --> 00:21:17.570
that the community health worker share with participants,
303
00:21:18.355 --> 00:21:20.355
for example, pill boxes,
304
00:21:23.071 --> 00:21:26.488
to help improving adherence to medication
305
00:21:28.471 --> 00:21:33.471
and other tools that they share with patients as well.
306
00:21:36.570 --> 00:21:41.029
They, community health workers, trained participants
307
00:21:41.029 --> 00:21:45.946
on how to measure and monitor their blood pressure as well.
308
00:21:48.510 --> 00:21:51.123
And everything happened at home.
309
00:21:53.520 --> 00:21:57.753
Well, some of the results, what happened with this trial?
310
00:21:59.809 --> 00:22:00.642
In this table,
311
00:22:00.642 --> 00:22:05.642
we describe the main characteristics of our participants.
312
00:22:05.790 --> 00:22:10.790
As you can see, the mean age was around 56 years old,
313
00:22:16.170 --> 00:22:17.320
half of them were women
314
00:22:19.473 --> 00:22:24.150
and what else I'd like to highlight here
315
00:22:24.150 --> 00:22:26.220
were patients were poorly controlled,
316
00:22:26.220 --> 00:22:30.030
that was a criteria to enter the study.
317
00:22:30.030 --> 00:22:32.370
You can see also in this table
318
00:22:32.370 --> 00:22:35.850
that the use of antihypertensive medication was very high.
319
00:22:38.033 --> 00:22:41.566
This is the public system in Argentina
320
00:22:41.566 --> 00:22:45.566
and medication is provided for free to patients.
321
00:22:48.172 --> 00:22:51.953
The problem is that there are periods of time
322
00:23:00.664 --> 00:23:04.110
where the centers don't have enough medication
323
00:23:04.110 --> 00:23:04.943
for patients.
324
00:23:04.943 --> 00:23:07.023
That's very frequent, that's very frequent.
325
00:23:07.860 --> 00:23:10.920
So in spite of being a high percentage,
326
00:23:10.920 --> 00:23:14.760
high proportion of patients being treated,
327
00:23:14.760 --> 00:23:17.820
the problem here was more connected
328
00:23:17.820 --> 00:23:21.393
with continuity of treatment,
329
00:23:22.830 --> 00:23:27.817
in part because of lack of medication during some months.
330
00:23:27.817 --> 00:23:29.634
Can I make a comment right here on this?
331
00:23:29.634 --> 00:23:31.020
Yes, sure.
So I see that you
332
00:23:31.020 --> 00:23:33.960
sort of started off in a bad-luck situation,
333
00:23:33.960 --> 00:23:36.160
where the intervention group
334
00:23:37.170 --> 00:23:40.860
had significantly higher history of CVD
335
00:23:40.860 --> 00:23:43.350
and higher systolic and diastolic blood pressure.
336
00:23:43.350 --> 00:23:45.660
It's not huge differences,
337
00:23:45.660 --> 00:23:47.820
but usually with sample sizes like that,
338
00:23:47.820 --> 00:23:51.370
you don't see significant differences in a randomized trial.
339
00:23:51.370 --> 00:23:52.770
Yeah.
But maybe it's because
340
00:23:52.770 --> 00:23:56.400
of the cluster randomization and there might have been...
341
00:23:56.400 --> 00:23:59.460
I don't know what the ICC was with the clusters,
342
00:23:59.460 --> 00:24:02.940
but maybe there was a lot of variation in the clusters,
343
00:24:02.940 --> 00:24:07.537
so that it's much easier to have a bad-luck randomization
344
00:24:07.537 --> 00:24:08.819
like this.
Yes.
345
00:24:08.819 --> 00:24:10.652
It was just like that.
346
00:24:12.069 --> 00:24:16.113
And in our calculation, our sample size,
347
00:24:18.561 --> 00:24:22.170
we estimated an ICC of 0.06,
348
00:24:22.170 --> 00:24:24.960
that was our sample size calculation,
349
00:24:24.960 --> 00:24:27.723
but then, after conducting the trial,
350
00:24:29.443 --> 00:24:31.053
the actual ICC was 0.15.
351
00:24:32.994 --> 00:24:36.045
Wow, yeah that is-
It was very high.
352
00:24:36.045 --> 00:24:37.462
It was very high.
353
00:24:39.450 --> 00:24:43.920
Well, so this is the population
354
00:24:43.920 --> 00:24:47.400
and what happened with our outcomes,
355
00:24:47.400 --> 00:24:52.400
systolic, diastolic blood pressure and hypertension control.
356
00:24:53.370 --> 00:24:54.930
Before going into that,
357
00:24:54.930 --> 00:24:58.950
I'd like to remind you that...
358
00:24:58.950 --> 00:25:02.040
Or not remind, I think I didn't say it.
359
00:25:02.040 --> 00:25:03.800
I think I didn't say it.
360
00:25:03.800 --> 00:25:07.870
If can go back to the previous slide...
361
00:25:14.067 --> 00:25:15.243
But it doesn't matter.
362
00:25:16.530 --> 00:25:20.250
One important thing here, in terms of our topic today,
363
00:25:20.250 --> 00:25:21.747
which is the control group
364
00:25:21.747 --> 00:25:24.720
and how to evaluate the control group,
365
00:25:24.720 --> 00:25:29.040
is that we conducted evaluation visits,
366
00:25:29.040 --> 00:25:34.040
study evaluation visits, at baseline six, 12 and 18 months.
367
00:25:35.776 --> 00:25:39.817
And who conducted those visits?
368
00:25:39.817 --> 00:25:43.110
We trained the study nurses
369
00:25:43.110 --> 00:25:45.900
who were part of the medical staff
370
00:25:45.900 --> 00:25:50.900
of the primary care team in each clinic,
371
00:25:51.840 --> 00:25:56.520
that is, the nurses in charge of conducting
372
00:25:56.520 --> 00:26:01.520
the evaluation visits were part of the primary care team.
373
00:26:02.340 --> 00:26:04.740
And this is important later
374
00:26:04.740 --> 00:26:08.160
for the interpretation of our results.
375
00:26:08.160 --> 00:26:10.350
Vilma, are you saying that...
376
00:26:10.350 --> 00:26:12.630
Was that by design or in retrospect?
377
00:26:12.630 --> 00:26:14.010
Maybe you wouldn't have preferred that?
378
00:26:14.010 --> 00:26:16.530
I mean, it seems like if they're part of the group,
379
00:26:16.530 --> 00:26:18.090
it might be hard for them to be objective.
380
00:26:18.090 --> 00:26:20.610
Is that the point that you're making?
381
00:26:20.610 --> 00:26:23.070
Yes, yes.
382
00:26:23.070 --> 00:26:27.420
Yes, but it was so by design really,
383
00:26:27.420 --> 00:26:31.440
because in my view, there is a trade-off here, you know?
384
00:26:31.440 --> 00:26:34.200
This is very warm, our population.
385
00:26:34.200 --> 00:26:37.710
So sometimes it's difficult to enter
386
00:26:37.710 --> 00:26:42.180
in the neighborhood and be accepted by people.
387
00:26:42.180 --> 00:26:45.270
People have to open their door
388
00:26:45.270 --> 00:26:50.270
for you to conduct these evaluations,
389
00:26:50.490 --> 00:26:52.980
and for them, it's very important
390
00:26:52.980 --> 00:26:57.630
that they know these people.
391
00:26:57.630 --> 00:27:00.993
So we thought a lot about that and said,
392
00:27:01.950 --> 00:27:04.620
"Well, we can hire nurses
393
00:27:04.620 --> 00:27:09.620
and do this absolutely independent of the primary care team,
394
00:27:10.380 --> 00:27:12.540
but in our opinion,
395
00:27:12.540 --> 00:27:14.580
it would have been very difficult
396
00:27:14.580 --> 00:27:17.397
for them to enter many of these houses."
397
00:27:18.356 --> 00:27:23.356
So we say, "Well, we trained, in depth and intensively,
398
00:27:25.770 --> 00:27:30.573
these nurses on how to make the evaluations,
399
00:27:31.500 --> 00:27:33.570
how to collect the data.
400
00:27:33.570 --> 00:27:36.670
They were trained not to do anything else
401
00:27:37.530 --> 00:27:40.713
when they conducted these evaluation visits,
402
00:27:41.700 --> 00:27:44.941
but they were part of the primary care team,
403
00:27:44.941 --> 00:27:48.963
and people know that, so that's important, yeah,
404
00:27:51.480 --> 00:27:55.860
Well, what happened then with our outcomes?
405
00:27:55.860 --> 00:27:58.620
We can see here the effect of the intervention
406
00:27:58.620 --> 00:28:01.213
on systolic blood pressure.
407
00:28:01.213 --> 00:28:06.213
There was a significant reduction in the intervention group
408
00:28:10.350 --> 00:28:14.657
early at six months, and this effect was present
409
00:28:16.663 --> 00:28:19.470
until the end of the study as well.
410
00:28:19.470 --> 00:28:21.870
So we have these positive results,
411
00:28:21.870 --> 00:28:25.351
in terms of systolic blood pressure.
412
00:28:25.351 --> 00:28:28.991
But if you look at the control group here,
413
00:28:28.991 --> 00:28:33.487
the control group also presented improvement
414
00:28:38.477 --> 00:28:42.503
in the systolic blood pressure of their patients.
415
00:28:43.350 --> 00:28:48.180
And the same happened with diastolic blood pressure.
416
00:28:48.180 --> 00:28:51.090
The reduction was significantly different
417
00:28:51.090 --> 00:28:52.560
between the two groups,
418
00:28:52.560 --> 00:28:55.323
but again, in the control group,
419
00:28:56.340 --> 00:29:00.270
there was an improvement, a significant improvement,
420
00:29:00.270 --> 00:29:03.240
within this arm.
421
00:29:03.240 --> 00:29:06.690
And same thing when we look
422
00:29:06.690 --> 00:29:08.710
into the proportion of participants
423
00:29:10.290 --> 00:29:13.370
with their blood pressure under control.
424
00:29:15.210 --> 00:29:20.210
Again, the difference was significant between the arms,
425
00:29:21.330 --> 00:29:24.873
but there was improvement in the control group.
426
00:29:30.210 --> 00:29:34.380
Well these are some data about mediators,
427
00:29:34.380 --> 00:29:39.380
like adherence to medication, which was improved over time,
428
00:29:41.460 --> 00:29:46.460
and the same happened with adjustment of medication
429
00:29:47.850 --> 00:29:49.623
by physicians.
430
00:29:53.310 --> 00:29:55.410
And here we come to the topic now
431
00:29:55.410 --> 00:29:57.810
that we want to discuss today.
432
00:29:57.810 --> 00:30:00.423
There was this improvement in the control group,
433
00:30:01.530 --> 00:30:06.440
and trying to interpret, the best way we can, these results.
434
00:30:06.440 --> 00:30:10.290
So we conducted several in-depth interviews
435
00:30:10.290 --> 00:30:13.023
with participants from the control group.
436
00:30:18.690 --> 00:30:21.723
Usually we conduct interviews
437
00:30:23.713 --> 00:30:26.963
with a particular focus on participants
438
00:30:28.017 --> 00:30:30.840
in the intervention group, you know?
439
00:30:30.840 --> 00:30:34.290
Because we want to learn about the perceptions
440
00:30:34.290 --> 00:30:36.090
about the intervention,
441
00:30:36.090 --> 00:30:40.650
whether it was more appealing for patients or not,
442
00:30:40.650 --> 00:30:43.503
and things like acceptance and other topics.
443
00:30:44.550 --> 00:30:49.503
We pay a lot of attention usually to the intervention group,
444
00:30:51.371 --> 00:30:56.371
and we do, wrongly, less work with the control of our study.
445
00:30:59.010 --> 00:31:01.833
In this case, and seeing those results,
446
00:31:02.956 --> 00:31:05.760
we conducted these interviews,
447
00:31:05.760 --> 00:31:08.280
and we found that first,
448
00:31:08.280 --> 00:31:12.930
patients valued, really, being visited by nurses
449
00:31:12.930 --> 00:31:17.403
from their clinics, from their primary care centers.
450
00:31:18.960 --> 00:31:22.590
They felt care, you know?
451
00:31:22.590 --> 00:31:26.763
They valued that and that was something positive for them
452
00:31:26.763 --> 00:31:29.180
and for their own healthcare.
453
00:31:30.975 --> 00:31:33.390
The other thing that happened
454
00:31:33.390 --> 00:31:38.390
was that nurses provided some counseling, you know?
455
00:31:39.120 --> 00:31:42.330
I mean, they were in contact with these patients,
456
00:31:42.330 --> 00:31:47.330
they knew them and they provided counseling about,
457
00:31:47.610 --> 00:31:49.860
for example, how to get medication.
458
00:31:49.860 --> 00:31:54.222
You have travel when you go to the primary care center.
459
00:31:54.222 --> 00:31:55.291
What can you do?
460
00:31:55.291 --> 00:31:57.703
"I can help you with this," and comments of this kind.
461
00:31:59.451 --> 00:32:04.451
And the nurses did that and that's a great thing, of course,
462
00:32:04.556 --> 00:32:08.367
that help us understand better the results.
463
00:32:09.530 --> 00:32:14.530
Patients in the control group increased the number of visits
464
00:32:14.701 --> 00:32:19.701
to the clinic, for example, without any other intervention
465
00:32:20.220 --> 00:32:24.783
but these visits, these evaluation visits.
466
00:32:26.640 --> 00:32:29.940
So we know all these aspects
467
00:32:29.940 --> 00:32:31.920
because of this qualitative approach.
468
00:32:31.920 --> 00:32:35.760
It was a very limited qualitative approach
469
00:32:35.760 --> 00:32:38.813
that we were able to do in this case,
470
00:32:40.650 --> 00:32:45.650
but my question for you, and my reflection on that,
471
00:32:45.673 --> 00:32:50.673
is how to better design the qualitative phase,
472
00:32:51.663 --> 00:32:54.930
the qualitative components of our research,
473
00:32:54.930 --> 00:32:56.537
to get information,
474
00:32:56.537 --> 00:32:59.520
not only on the intervention perceptions,
475
00:32:59.520 --> 00:33:01.680
the intervention group, et cetera,
476
00:33:01.680 --> 00:33:06.680
but also what is happening with the usual care group,
477
00:33:06.881 --> 00:33:09.030
or standard care group,
478
00:33:09.030 --> 00:33:14.030
and what people in this arm feel and is exposed to
479
00:33:14.340 --> 00:33:17.670
during the study in general.
480
00:33:17.670 --> 00:33:18.540
And the other thing
481
00:33:18.540 --> 00:33:22.143
that I was talking to Dr. Raphael yesterday
482
00:33:24.330 --> 00:33:27.750
was about the use of existing databases
483
00:33:27.750 --> 00:33:32.700
to get information about not only the control arm,
484
00:33:32.700 --> 00:33:35.010
but all the other centers
485
00:33:35.010 --> 00:33:38.520
that are a part of our target population, and therefore,
486
00:33:38.520 --> 00:33:40.620
not included in the study,
487
00:33:40.620 --> 00:33:43.893
because that would be usual care, really.
488
00:33:45.060 --> 00:33:47.430
And I was talking with Donna this morning,
489
00:33:47.430 --> 00:33:52.340
how to incorporate those things, if those data exist,
490
00:33:53.490 --> 00:33:56.280
how to incorporate them to better understand
491
00:33:56.280 --> 00:33:58.673
what is usual care of centers
492
00:33:59.652 --> 00:34:02.852
that are not part of a clinical trial,
493
00:34:02.852 --> 00:34:05.152
like in this case, for example.
494
00:34:05.152 --> 00:34:10.152
So that's something that we can study and develop, you know,
495
00:34:13.540 --> 00:34:16.197
in that type of approach.
496
00:34:16.197 --> 00:34:18.060
We're trying to do that
497
00:34:18.060 --> 00:34:21.465
in another cluster-randomized controlled trial
498
00:34:21.465 --> 00:34:25.380
that we are conducting now in Guatemala.
499
00:34:25.380 --> 00:34:27.093
Based on these results,
500
00:34:28.740 --> 00:34:33.427
we started a new project with our team in Guatemala.
501
00:34:34.453 --> 00:34:36.570
We adapted this intervention
502
00:34:36.570 --> 00:34:39.040
that I presented a few minutes ago
503
00:34:42.230 --> 00:34:44.907
to the context of Guatemala.
504
00:34:45.938 --> 00:34:47.550
There were a lot of adaptations,
505
00:34:47.550 --> 00:34:51.518
and we don't have time today to go into much detail,
506
00:34:51.518 --> 00:34:52.792
but we designed,
507
00:34:52.792 --> 00:34:56.460
in this cluster-randomized controlled trial in Guatemala,
508
00:34:56.460 --> 00:35:00.280
we included 32 primary care clinics
509
00:35:03.663 --> 00:35:06.897
in different districts in Guatemala,
510
00:35:06.897 --> 00:35:11.280
and they were randomized to the intervention
511
00:35:11.280 --> 00:35:14.397
or the usual care arm of the study.
512
00:35:16.830 --> 00:35:19.560
And the intervention, as I said before,
513
00:35:19.560 --> 00:35:23.280
was based on the experience in Argentina,
514
00:35:23.280 --> 00:35:25.807
but we did a lot of adaptations.
515
00:35:25.807 --> 00:35:27.990
These are the final components
516
00:35:27.990 --> 00:35:31.040
of the intervention in Guatemala.
517
00:35:31.040 --> 00:35:31.873
How was it adapted?
518
00:35:31.873 --> 00:35:34.200
It kinda looks the same to me.
519
00:35:34.200 --> 00:35:36.120
I'm sorry?
How was it adapted,
520
00:35:36.120 --> 00:35:39.030
because it looks very similar, or even the same,
521
00:35:39.030 --> 00:35:41.790
as the Argentina intervention components?
522
00:35:41.790 --> 00:35:44.040
Yes, there are a lot of similarities,
523
00:35:44.040 --> 00:35:46.250
there are a lot of similarities.
524
00:35:46.250 --> 00:35:49.410
But for example, the mHealth component,
525
00:35:49.410 --> 00:35:53.820
which was text messages in Argentina, is not here,
526
00:35:53.820 --> 00:35:55.950
is not part of the trial in Guatemala,
527
00:35:55.950 --> 00:36:00.897
because of the very high proportion of illiteracy
528
00:36:02.040 --> 00:36:03.690
in Guatemala.
529
00:36:03.690 --> 00:36:06.960
So there is a high proportion of people
530
00:36:06.960 --> 00:36:11.070
who cannot read and write,
531
00:36:11.070 --> 00:36:16.070
so we did a lot of work trying to adapt, with visual aids,
532
00:36:17.554 --> 00:36:20.721
the messages, but we didn't find a way
533
00:36:23.379 --> 00:36:25.511
to make it feasible here,
534
00:36:25.511 --> 00:36:28.178
so that's not part of the trial.
535
00:36:29.507 --> 00:36:34.507
There, home blood pressure monitoring is quite the same.
536
00:36:34.680 --> 00:36:37.820
What we adapted here is the training,
537
00:36:40.427 --> 00:36:42.300
or the education of patients,
538
00:36:42.300 --> 00:36:44.760
on how to use these devices,
539
00:36:44.760 --> 00:36:46.350
again, for the same reason.
540
00:36:46.350 --> 00:36:51.030
So we used pictures, for example, for patients
541
00:36:51.030 --> 00:36:54.965
and we did a lot of training with the patient,
542
00:36:54.965 --> 00:36:59.965
just to be sure that they were able to use those devices.
543
00:37:02.628 --> 00:37:06.870
And here, about the team collaborative approach,
544
00:37:06.870 --> 00:37:11.870
in Guatemala, the system is organized in a different way,
545
00:37:12.164 --> 00:37:14.940
compared to Argentina,
546
00:37:14.940 --> 00:37:17.913
so we have to work with more levels.
547
00:37:19.650 --> 00:37:24.123
For example, in this clinic, there is no doctor.
548
00:37:25.443 --> 00:37:28.803
In Argentina, each primary care clinic
549
00:37:28.803 --> 00:37:33.210
has a primary care team with at least a doctor,
550
00:37:33.210 --> 00:37:36.390
in general, a general practitioner,
551
00:37:36.390 --> 00:37:39.120
one nurse and one community health worker.
552
00:37:39.120 --> 00:37:41.243
That's more or less a rule,
553
00:37:41.243 --> 00:37:46.243
and in some clinics there are more people and more doctors
554
00:37:47.460 --> 00:37:50.523
or nurses or community health workers.
555
00:37:50.523 --> 00:37:52.930
In Guatemala, in each clinic,
556
00:37:52.930 --> 00:37:57.060
there is one auxiliary nurse at least,
557
00:37:57.060 --> 00:38:01.173
and maybe that's the only personnel at the clinic.
558
00:38:02.190 --> 00:38:06.600
In the higher level of clinics,
559
00:38:06.600 --> 00:38:08.317
they have also a nurse,
560
00:38:09.971 --> 00:38:14.253
and then they have centers where they have doctors.
561
00:38:15.510 --> 00:38:18.810
These are interconnected,
562
00:38:18.810 --> 00:38:22.099
but you have to work with these different pieces.
563
00:38:22.099 --> 00:38:26.652
So this collaborative team approach was different
564
00:38:26.652 --> 00:38:29.527
as the ones in Argentina.
565
00:38:29.527 --> 00:38:33.944
A lot of other things are very similar, very similar.
566
00:38:35.551 --> 00:38:38.943
So this is the intervention in Guatemala.
567
00:38:38.943 --> 00:38:43.943
In Guatemala, and this maybe is a topic for another meeting,
568
00:38:46.260 --> 00:38:48.930
we have other types of challenges
569
00:38:48.930 --> 00:38:53.930
connected with the different ethnic groups.
570
00:38:54.450 --> 00:38:59.450
In Guatemala, there are many different populations,
571
00:39:01.080 --> 00:39:06.080
that, for example, some of them speak Spanish,
572
00:39:06.717 --> 00:39:08.790
some of them are bilingual,
573
00:39:08.790 --> 00:39:13.290
so they speak Spanish and a Mayan language,
574
00:39:13.290 --> 00:39:17.670
and some of them speak only in Mayan languages,
575
00:39:17.670 --> 00:39:22.670
and some Mayan languages have a written form and others not.
576
00:39:24.570 --> 00:39:29.570
So there we have another very, very challenging situation
577
00:39:31.601 --> 00:39:34.270
and we work a lot with the materials
578
00:39:35.280 --> 00:39:38.767
and according to these different populations.
579
00:39:38.767 --> 00:39:43.767
(participants speaking in foreign language)
580
00:39:55.064 --> 00:40:00.064
(participants speaking in foreign language continues)
581
00:40:08.443 --> 00:40:13.350
Okay, so well, this is study in Guatemala
582
00:40:15.059 --> 00:40:18.123
and the field work.
583
00:40:20.220 --> 00:40:22.401
Equity, this is another topic. (laughs)
584
00:40:22.401 --> 00:40:23.763
This is another big topic.
585
00:40:30.150 --> 00:40:35.040
So what's the state of the study in Guatemala?
586
00:40:35.040 --> 00:40:38.553
We finished the field work last week,
587
00:40:39.810 --> 00:40:43.980
so we are just starting cleaning the database
588
00:40:43.980 --> 00:40:46.770
and preparing it for analysis.
589
00:40:46.770 --> 00:40:49.470
We will have the results in a few months,
590
00:40:49.470 --> 00:40:53.599
so we can share those results with you,
591
00:40:53.599 --> 00:40:58.599
but what I'd like to share here,
592
00:41:00.540 --> 00:41:02.217
in terms of the control group
593
00:41:02.217 --> 00:41:04.590
and how to approach the control group,
594
00:41:04.590 --> 00:41:09.450
is based on our learnings from Argentina,
595
00:41:09.450 --> 00:41:12.420
from the design phase of the study
596
00:41:12.420 --> 00:41:16.200
planned for different evaluations,
597
00:41:16.200 --> 00:41:19.857
not only of the control arm of the trial,
598
00:41:19.857 --> 00:41:24.857
but also on other clinical posts and centers
599
00:41:25.380 --> 00:41:27.510
that were not included in the study,
600
00:41:27.510 --> 00:41:32.510
so I hope we have more data to evaluate this usual care
601
00:41:32.976 --> 00:41:35.059
at the end of this study.
602
00:41:36.030 --> 00:41:38.790
And this has also budget implications.
603
00:41:38.790 --> 00:41:40.260
So for us researchers,
604
00:41:40.260 --> 00:41:42.540
it is important to have that in mind
605
00:41:42.540 --> 00:41:43.630
and plan in advance,
606
00:41:44.910 --> 00:41:47.730
because it's different, it's really difficult,
607
00:41:47.730 --> 00:41:49.620
in particular if,
608
00:41:49.620 --> 00:41:54.093
as it happens in Guatemala and in many other countries,
609
00:41:55.410 --> 00:41:58.317
information is not so easily obtained,
610
00:41:58.317 --> 00:42:02.850
and it's not so easy to access this information
611
00:42:02.850 --> 00:42:04.380
from other centers.
612
00:42:04.380 --> 00:42:07.537
So there is a lot of work there as well.
613
00:42:07.537 --> 00:42:12.537
So that's what I'd like to share with you
614
00:42:14.760 --> 00:42:17.730
and to put on the table, you know?
615
00:42:17.730 --> 00:42:22.730
What can we do as researchers to improve our study
616
00:42:23.349 --> 00:42:24.182
and evaluation of the so-called usual care in our studies.
617
00:42:30.424 --> 00:42:31.753
Yes?
That was a wonderful talk.
618
00:42:31.753 --> 00:42:35.130
You talked a little bit with the first study in Argentina
619
00:42:35.130 --> 00:42:36.660
about some of your hypotheses
620
00:42:36.660 --> 00:42:38.730
about the improvement in the control group
621
00:42:38.730 --> 00:42:42.210
with regards to these individuals making house visits.
622
00:42:42.210 --> 00:42:46.050
I was also interested in to what degree, in either study,
623
00:42:46.050 --> 00:42:48.630
there might be cluster-level differences
624
00:42:48.630 --> 00:42:52.020
between the different clinics that you're randomizing,
625
00:42:52.020 --> 00:42:56.100
and whether you account for those when you do randomization,
626
00:42:56.100 --> 00:42:59.403
say by stratified randomization or restricted randomization,
627
00:43:01.470 --> 00:43:02.730
if you think those factors
628
00:43:02.730 --> 00:43:07.730
might lead to systematic differences between the two groups?
629
00:43:07.980 --> 00:43:09.630
That's something that I've struggled a lot with
630
00:43:09.630 --> 00:43:12.053
in my research and I'm curious how you think about it.
631
00:43:13.290 --> 00:43:14.520
That's a great question.
632
00:43:14.520 --> 00:43:16.723
We struggled (laughs) a lot as well.
633
00:43:16.723 --> 00:43:20.790
We have eligibility criteria for the individuals,
634
00:43:20.790 --> 00:43:23.250
I showed you those criteria,
635
00:43:23.250 --> 00:43:26.276
but also for the clinics, trying to, you know,
636
00:43:26.276 --> 00:43:28.110
have a set of...
637
00:43:28.110 --> 00:43:32.010
I mean, trying to reduce variability between the clinics
638
00:43:32.010 --> 00:43:35.670
that we invited to participate in the study.
639
00:43:35.670 --> 00:43:37.563
So that was one thing,
640
00:43:38.730 --> 00:43:42.243
in terms of resources, size, et cetera.
641
00:43:43.530 --> 00:43:47.536
The other thing is that we live in a federal country,
642
00:43:47.536 --> 00:43:50.253
so each province in our country, in Argentina,
643
00:43:51.750 --> 00:43:56.743
has their own rules, regulations
644
00:43:57.797 --> 00:44:02.137
and let's say, organization of the healthcare system.
645
00:44:03.210 --> 00:44:06.047
So yeah, we were working with several provinces
646
00:44:06.047 --> 00:44:09.830
in the country, so we stratified by province, for example,
647
00:44:09.830 --> 00:44:12.870
to take into account that,
648
00:44:12.870 --> 00:44:15.537
to try to adjust for that variable.
649
00:44:17.716 --> 00:44:22.049
And there was no other stratification in this trial.
650
00:44:23.100 --> 00:44:26.536
We tried to manage variability
651
00:44:26.536 --> 00:44:31.230
through this eligibility criteria, in terms of...
652
00:44:31.230 --> 00:44:33.390
I don't remember exactly,
653
00:44:33.390 --> 00:44:37.350
I think it was three or four variables,
654
00:44:37.350 --> 00:44:39.053
factors we took into account.
655
00:44:39.053 --> 00:44:40.983
One was size of the clinic,
656
00:44:44.688 --> 00:44:45.573
the composition of the primary care team in each clinic,
657
00:44:49.740 --> 00:44:53.280
not to mix, you know, maybe big clinics
658
00:44:53.280 --> 00:44:56.010
with a lot of personnel,
659
00:44:56.010 --> 00:44:59.579
versus other ones that were smaller,
660
00:44:59.579 --> 00:45:02.523
so we took that in account,
661
00:45:03.570 --> 00:45:08.570
provision of medication, because although medication
662
00:45:09.600 --> 00:45:13.470
is provided for free in our country,
663
00:45:13.470 --> 00:45:17.790
for people who has only public insurance,
664
00:45:17.790 --> 00:45:21.783
only public insurance and not other type of coverage,
665
00:45:22.964 --> 00:45:27.946
the quantity and delivery of medication is different
666
00:45:27.946 --> 00:45:32.946
from different clinics or districts within each product.
667
00:45:33.570 --> 00:45:36.420
So we took that in account as well.
668
00:45:36.420 --> 00:45:40.337
That was another way of trying to balance clinics
669
00:45:42.540 --> 00:45:44.610
before randomization.
670
00:45:45.668 --> 00:45:48.985
And after that, it was simple randomization of clinics,
671
00:45:48.985 --> 00:45:52.590
stratified by province and no more than that.
672
00:45:52.590 --> 00:45:55.110
But I agree with you, I agree with you.
673
00:45:55.110 --> 00:46:00.110
It may be for sure something that could have influence
674
00:46:02.611 --> 00:46:05.528
in these differences that we found.
675
00:46:08.504 --> 00:46:09.720
It's always difficult.
676
00:46:09.720 --> 00:46:11.250
In implementation research,
677
00:46:11.250 --> 00:46:12.983
you know that it's always difficult,
678
00:46:12.983 --> 00:46:15.540
this balance and this trade-off,
679
00:46:15.540 --> 00:46:20.540
between what is feasible and what we,
680
00:46:20.933 --> 00:46:25.535
from a design point of view, want for our trial.
681
00:46:25.535 --> 00:46:27.452
It's difficult, really.
682
00:46:28.470 --> 00:46:31.380
One suggestion on a statistical level
683
00:46:31.380 --> 00:46:34.710
for this issue would be secondary analysis,
684
00:46:34.710 --> 00:46:37.680
where you control for baseline patient
685
00:46:37.680 --> 00:46:40.380
and clinical-level characteristics,
686
00:46:40.380 --> 00:46:43.083
and then see how that changes the contrast.
687
00:46:44.520 --> 00:46:46.170
That's a great subject.
688
00:46:46.170 --> 00:46:48.176
Yes, we explore.
689
00:46:48.176 --> 00:46:50.734
Yeah, exactly.
We explored that,
690
00:46:50.734 --> 00:46:53.567
and we didn't find any difference.
691
00:47:00.480 --> 00:47:02.970
We didn't have much data, you know,
692
00:47:02.970 --> 00:47:04.420
just in terms of the clinics,
693
00:47:06.180 --> 00:47:09.450
but we did exploration about that.
694
00:47:09.450 --> 00:47:13.653
We didn't find differences in the results.
695
00:47:18.570 --> 00:47:22.570
So that's something that I proposed to work on
696
00:47:22.570 --> 00:47:24.300
in the future.
697
00:47:24.300 --> 00:47:25.773
I'm curious, Vilma,
698
00:47:28.140 --> 00:47:32.430
has the TREIN/HyTREC consortium discussed this issue at all?
699
00:47:32.430 --> 00:47:36.120
Have the other projects also seen the same sort of,
700
00:47:36.120 --> 00:47:39.270
maybe not necessarily in the same magnitude,
701
00:47:39.270 --> 00:47:43.860
but the direction of improvements in control groups?
702
00:47:43.860 --> 00:47:46.230
Like, was it a consortium-wide phenomena?
703
00:47:46.230 --> 00:47:47.063
Do we know?
704
00:47:48.300 --> 00:47:53.300
No, I don't know, but it hasn't been discussed yet.
705
00:47:53.760 --> 00:47:57.210
We have a meeting in September, I think,
706
00:47:57.210 --> 00:48:01.470
and our idea is to share these results
707
00:48:01.470 --> 00:48:03.330
and see what is happening
708
00:48:03.330 --> 00:48:05.667
in other studies in the consortium,
709
00:48:05.667 --> 00:48:08.013
but it hasn't been discussed yet.
710
00:48:09.750 --> 00:48:12.510
I know we've seen a similar phenomena
711
00:48:12.510 --> 00:48:14.610
in our work site intervention studies,
712
00:48:14.610 --> 00:48:17.130
where we're trying to improve food
713
00:48:17.130 --> 00:48:19.980
and physical activity environment at work sites,
714
00:48:19.980 --> 00:48:23.040
to reduce cardiometabolic risk,
715
00:48:23.040 --> 00:48:26.446
and then we find, just simply by screening
716
00:48:26.446 --> 00:48:28.770
and then waiting six months,
717
00:48:28.770 --> 00:48:31.770
we see big improvements in blood pressure
718
00:48:31.770 --> 00:48:35.370
and smaller ones in blood sugar and so forth,
719
00:48:35.370 --> 00:48:36.750
which I think has been seen.
720
00:48:36.750 --> 00:48:40.170
Like, screening itself is a public health intervention,
721
00:48:40.170 --> 00:48:43.680
but I've also read it's not a durable one,
722
00:48:43.680 --> 00:48:45.990
without additional supports.
723
00:48:45.990 --> 00:48:47.640
So you might see some additional...
724
00:48:47.640 --> 00:48:50.340
People may improve when they find out,
725
00:48:50.340 --> 00:48:52.470
but then, they'll go back, maybe,
726
00:48:52.470 --> 00:48:54.120
if we don't have these other things.
727
00:48:54.120 --> 00:48:55.159
So there's maybe short-term...
728
00:48:55.159 --> 00:48:59.730
Like, would the short-term improvements in the control group
729
00:48:59.730 --> 00:49:03.720
be sustainable, say for two years or five years,
730
00:49:03.720 --> 00:49:05.190
or would they start to go away,
731
00:49:05.190 --> 00:49:07.290
whereas the intervention group
732
00:49:07.290 --> 00:49:09.120
can maintain their improvements
733
00:49:09.120 --> 00:49:12.390
and maybe even continue to improve?
734
00:49:12.390 --> 00:49:13.230
I agree.
735
00:49:13.230 --> 00:49:16.440
I fully agree and I think that...
736
00:49:16.440 --> 00:49:21.440
Actually, we prepare a proposal to measure sustainability
737
00:49:22.110 --> 00:49:26.241
of the resource in Argentina and we didn't make it,
738
00:49:26.241 --> 00:49:29.130
but I think that that's something
739
00:49:29.130 --> 00:49:32.883
to talk with funders about, you know?
740
00:49:33.840 --> 00:49:36.630
Because there is a lot of effort and resources
741
00:49:36.630 --> 00:49:40.560
put in each of these trials that we conduct,
742
00:49:40.560 --> 00:49:45.560
and we don't know, in general, what happened half the time.
743
00:49:46.770 --> 00:49:49.890
I have some data about this trial in particular,
744
00:49:49.890 --> 00:49:54.890
because this program was adopted by one of the provinces
745
00:49:56.400 --> 00:50:00.694
and it was scaled up through the province,
746
00:50:00.694 --> 00:50:04.083
one of the province that I showed in the first map.
747
00:50:05.370 --> 00:50:08.040
So I have data on that,
748
00:50:08.040 --> 00:50:12.993
and they are very, very successful.
749
00:50:14.070 --> 00:50:15.237
That's good data.
750
00:50:16.110 --> 00:50:19.387
The difference is not so big as in the trial,
751
00:50:19.387 --> 00:50:22.220
as usual, but they keep improving.
752
00:50:23.109 --> 00:50:25.617
I don't know what happens in the other provinces,
753
00:50:25.617 --> 00:50:28.620
but I think that's something that would be really great
754
00:50:28.620 --> 00:50:30.180
if we can do that.
755
00:50:30.180 --> 00:50:31.838
In terms of the time,
756
00:50:31.838 --> 00:50:35.250
I mean, the timeline of our project,
757
00:50:35.250 --> 00:50:38.190
in general, we cannot do that.
758
00:50:38.190 --> 00:50:43.190
So it's time budget, but I think it would be great
759
00:50:44.622 --> 00:50:47.490
if, really, it's possible now,
760
00:50:47.490 --> 00:50:49.473
to see what happened with these.
761
00:50:51.000 --> 00:50:53.640
These programs, these projects,
762
00:50:53.640 --> 00:50:56.910
are adopted by the government.
763
00:50:56.910 --> 00:51:01.320
You have data afterwards, but if not,
764
00:51:01.320 --> 00:51:05.193
in general, it's difficult to know what happened.
765
00:51:08.688 --> 00:51:11.588
How did the randomization work out in Guatemala?
766
00:51:12.720 --> 00:51:15.180
In terms of the clinic?
Of the balance?
767
00:51:15.180 --> 00:51:18.929
Yeah, like, in table one, like you showed us-
768
00:51:18.929 --> 00:51:19.893
Yeah.
And did you
769
00:51:19.893 --> 00:51:21.810
have significant differences between-
770
00:51:21.810 --> 00:51:22.643
No.
Oh, good.
771
00:51:22.643 --> 00:51:24.427
No, it was better. (laughs)
772
00:51:24.427 --> 00:51:25.893
In that sense, it was better.
(Donna laughing)
773
00:51:25.893 --> 00:51:27.930
Yeah, it was more balanced.
Uh-huh.
774
00:51:27.930 --> 00:51:30.134
Yeah, and I don't have the table now,
775
00:51:30.134 --> 00:51:32.117
but in Guatemala, it was more balanced.
776
00:51:32.117 --> 00:51:33.060
Uh-huh.
777
00:51:33.060 --> 00:51:33.893
Yeah.
778
00:51:36.150 --> 00:51:37.920
So I'm monitoring the chat,
779
00:51:37.920 --> 00:51:40.933
and it seems that people are being a little shy.
780
00:51:40.933 --> 00:51:42.486
Oh, I have another question.
Oh, good.
781
00:51:42.486 --> 00:51:43.380
(attendees laughing)
I have some too,
782
00:51:43.380 --> 00:51:46.193
but I didn't wanna hog the whole discussion.
783
00:51:46.193 --> 00:51:48.990
So do you know to what degree
784
00:51:48.990 --> 00:51:51.780
the interventions worked in the intervention arm?
785
00:51:51.780 --> 00:51:56.780
Because I'm just wondering, A, how successful they were,
786
00:51:57.270 --> 00:51:58.680
or B, if there were other factors
787
00:51:58.680 --> 00:52:00.420
that restricted the ability to improve?
788
00:52:00.420 --> 00:52:04.290
For example, you were mentioning about a lack of medications
789
00:52:04.290 --> 00:52:05.490
in the health facilities.
790
00:52:05.490 --> 00:52:07.350
I can imagine that no matter what you do
791
00:52:07.350 --> 00:52:09.060
with all those interventions, if there aren't drugs,
792
00:52:09.060 --> 00:52:11.220
things might not get better.
793
00:52:11.220 --> 00:52:13.470
Do you have any information on the fidelity, basically,
794
00:52:13.470 --> 00:52:14.790
of the intervention,
795
00:52:14.790 --> 00:52:18.000
or factors that might have impeded the fidelity?
796
00:52:18.000 --> 00:52:19.580
Yes, we have...
797
00:52:22.423 --> 00:52:26.727
We have quite a lot of information from the Argentina trial.
798
00:52:28.170 --> 00:52:30.480
But there is something I would like to comment
799
00:52:30.480 --> 00:52:33.217
connected with your question in Guatemala.
800
00:52:34.072 --> 00:52:39.072
In Guatemala, the Ministry of Health
801
00:52:39.180 --> 00:52:41.940
was part of the trial, of the project,
802
00:52:41.940 --> 00:52:44.070
from the very beginning.
803
00:52:44.070 --> 00:52:47.900
They were involved in the design of the intervention,
804
00:52:47.900 --> 00:52:49.950
in the monitoring of the intervention,
805
00:52:49.950 --> 00:52:52.683
so they were very much involved.
806
00:52:53.910 --> 00:52:58.582
And they committed themself to assure
807
00:52:58.582 --> 00:53:03.582
that there would be medication at the health posts
808
00:53:06.782 --> 00:53:11.087
at least during the trial or duration of the trial.
809
00:53:11.087 --> 00:53:13.078
And they did it.
810
00:53:13.078 --> 00:53:14.729
With some periods, you know,
811
00:53:14.729 --> 00:53:17.600
that they have problems, limitations,
812
00:53:17.600 --> 00:53:21.130
shortage of medication, but they did it,
813
00:53:21.130 --> 00:53:25.110
and they work a lot to provide medication
814
00:53:25.110 --> 00:53:30.110
and to prioritize these centers, part of the study,
815
00:53:30.360 --> 00:53:32.753
in the provision of medication.
816
00:53:34.620 --> 00:53:37.890
So something that we...
817
00:53:37.890 --> 00:53:42.890
Again, I don't have the data to talk about,
818
00:53:44.546 --> 00:53:49.546
but we know that there was improvement
819
00:53:51.780 --> 00:53:53.490
in both arms in Guatemala,
820
00:53:53.490 --> 00:53:56.403
something similar to what happened in Argentina,
821
00:53:57.570 --> 00:54:00.000
and through qualitative interviews,
822
00:54:00.000 --> 00:54:03.080
we understood that people was really very...
823
00:54:06.810 --> 00:54:09.284
I mean, they felt very well,
824
00:54:09.284 --> 00:54:14.040
because they noticed that there were medication
825
00:54:14.040 --> 00:54:16.873
at the centers, where in the past,
826
00:54:17.820 --> 00:54:22.140
maybe they have much more problem to get those medicines.
827
00:54:22.140 --> 00:54:25.180
That's something that all the participants said.
828
00:54:27.284 --> 00:54:31.034
So a very basic thing like having medication,
829
00:54:31.950 --> 00:54:33.930
access to medication, in the centers,
830
00:54:33.930 --> 00:54:38.930
that was something that was more or less assured
831
00:54:39.060 --> 00:54:40.773
in both arms of the study.
832
00:54:42.330 --> 00:54:47.330
But in our approach to the other centers in Guatemala,
833
00:54:47.383 --> 00:54:51.303
same district, same district, but not part of the study,
834
00:54:52.506 --> 00:54:57.360
we are collecting information about medication,
835
00:54:57.360 --> 00:55:01.553
and the lack of medication is very important.
836
00:55:03.900 --> 00:55:06.099
There were serious problems,
837
00:55:06.099 --> 00:55:09.049
serious problems with the provision of medication
838
00:55:09.049 --> 00:55:13.530
in all the other centers in the same district,
839
00:55:13.530 --> 00:55:15.293
different to the centers in the study.
840
00:55:20.520 --> 00:55:24.120
So that's something that if you cannot assure that,
841
00:55:24.120 --> 00:55:26.940
I mean, if you cannot provide medication,
842
00:55:26.940 --> 00:55:30.960
as you said, whatever you do with the other alternatives,
843
00:55:30.960 --> 00:55:34.950
that is just maybe useless.
844
00:55:34.950 --> 00:55:37.440
And was this in Argentina you're talking about?
845
00:55:37.440 --> 00:55:39.488
Or Guatemala?
Guatemala.
846
00:55:39.488 --> 00:55:42.630
Okay.
In this case, Guatemala.
847
00:55:42.630 --> 00:55:47.000
In this case, Guatemala, because in the preparation phase,
848
00:55:47.000 --> 00:55:49.980
in the pre-implementation phase of the study,
849
00:55:49.980 --> 00:55:54.030
we did a lot of research about what is happening
850
00:55:54.030 --> 00:55:57.537
with the availability of drugs in the centers,
851
00:55:57.537 --> 00:56:00.960
and we found that there were big problems there.
852
00:56:00.960 --> 00:56:04.170
So we talk with the Ministry of Health,
853
00:56:04.170 --> 00:56:09.170
they committed to work on that for these centers,
854
00:56:09.540 --> 00:56:11.613
for these clinics, and they did.
855
00:56:12.870 --> 00:56:17.697
But the rest, again, the usual care in reality in Guatemala
856
00:56:19.898 --> 00:56:20.820
was different.
857
00:56:20.820 --> 00:56:23.750
I don't know how much impact this will have
858
00:56:23.750 --> 00:56:25.323
on this trial yet.
859
00:56:26.474 --> 00:56:28.410
But it happened there.
860
00:56:28.410 --> 00:56:29.610
So Vilma, we've gotten...
861
00:56:29.610 --> 00:56:32.220
It's like three questions now on the chat,
862
00:56:32.220 --> 00:56:35.250
and we only have two or three minutes,
863
00:56:35.250 --> 00:56:36.770
so what I thought I might do
864
00:56:36.770 --> 00:56:39.270
is just ask all of them in four minutes,
865
00:56:39.270 --> 00:56:41.280
I'd ask all of the questions,
866
00:56:41.280 --> 00:56:44.160
and maybe you can just try to address them together?
867
00:56:44.160 --> 00:56:49.057
Yes.
So John Roman asked,
868
00:56:49.057 --> 00:56:50.760
"Was there any incentives given
869
00:56:50.760 --> 00:56:52.950
to either participants or care providers?"
870
00:56:52.950 --> 00:56:55.209
I think he means financial incentives-
871
00:56:55.209 --> 00:56:57.545
No, (laughs) a short question.
872
00:56:57.545 --> 00:56:59.790
Okay, good-
A short answer. (laughs)
873
00:56:59.790 --> 00:57:01.717
Oh, Raphael Perez Escamilla asked,
874
00:57:01.717 --> 00:57:05.070
"Was text messaging used in Argentina and Guatemala
875
00:57:05.070 --> 00:57:06.330
as part of the intervention?
876
00:57:06.330 --> 00:57:07.770
If so, was it helpful?"
877
00:57:07.770 --> 00:57:09.960
You've actually addressed that a little bit,
878
00:57:09.960 --> 00:57:12.030
but maybe if there was data on...
879
00:57:12.030 --> 00:57:14.820
So Raphael, it wasn't used in Guatemala,
880
00:57:14.820 --> 00:57:16.920
because of the literacy issues,
881
00:57:16.920 --> 00:57:18.750
but in Argentina it was used,
882
00:57:18.750 --> 00:57:20.070
and I don't know, Vilma,
883
00:57:20.070 --> 00:57:23.760
if there was any way to independently look at that component
884
00:57:23.760 --> 00:57:25.230
to see how helpful it was,
885
00:57:25.230 --> 00:57:29.220
compared to all these other complex components?
886
00:57:29.220 --> 00:57:31.770
No, it's difficult to separate
887
00:57:31.770 --> 00:57:34.890
and to analyze independently the contribution.
888
00:57:34.890 --> 00:57:37.230
But there was a high correlation
889
00:57:37.230 --> 00:57:40.890
with the dose received of text messages
890
00:57:40.890 --> 00:57:42.320
and the blood pressure control.
891
00:57:42.320 --> 00:57:45.000
Okay.
Okay, so that's something
892
00:57:45.000 --> 00:57:46.500
that can be interpreted
893
00:57:46.500 --> 00:57:51.097
as these were a useful part of the intervention.
894
00:57:52.546 --> 00:57:53.379
Oh, good.
895
00:57:53.379 --> 00:57:55.207
And then Anna Julio asked,
896
00:57:55.207 --> 00:57:57.840
"How sustainable is the intervention?
897
00:57:57.840 --> 00:58:00.750
Was it adopted by the Ministry of Health in total?
898
00:58:00.750 --> 00:58:03.990
Besides the medications, the mHealth component?"
899
00:58:03.990 --> 00:58:06.030
So I think you've discussed that a little bit
900
00:58:06.030 --> 00:58:10.590
maybe about Guatemala, but not so much for Argentina.
901
00:58:10.590 --> 00:58:12.900
In Argentina, the intervention was adopted
902
00:58:12.900 --> 00:58:14.280
by only one province.
903
00:58:14.280 --> 00:58:16.163
Oh, that's right, you did say that.
904
00:58:18.540 --> 00:58:19.800
And it's working. (laughs)
905
00:58:19.800 --> 00:58:21.510
It's working, you know?
906
00:58:21.510 --> 00:58:23.910
But not in the other provinces.
907
00:58:23.910 --> 00:58:28.910
And shortly, this is the base for the HEARTS initiative.
908
00:58:29.220 --> 00:58:31.397
The HEARTS Initiative in the Americas,
909
00:58:31.397 --> 00:58:34.110
in the case of Argentina,
910
00:58:34.110 --> 00:58:36.420
was built on this intervention.
911
00:58:36.420 --> 00:58:40.230
So we could contribute, you know,
912
00:58:40.230 --> 00:58:42.330
with many implementation indicators
913
00:58:42.330 --> 00:58:45.660
for them to implement the initiative.
914
00:58:45.660 --> 00:58:46.943
That's something, not much, but something.
915
00:58:48.857 --> 00:58:51.180
Vilma, maybe like in your remaining few minutes
916
00:58:51.180 --> 00:58:53.867
you could say a little bit more about the HEARTS Initiative,
917
00:58:53.867 --> 00:58:56.130
'cause a number of us, myself included,
918
00:58:56.130 --> 00:58:58.350
are not that familiar with it?
919
00:58:58.350 --> 00:59:01.667
The HEARTS Initiative is a platform initiative
920
00:59:01.667 --> 00:59:02.867
for the Americas.
921
00:59:02.867 --> 00:59:04.350
There are 12 countries
922
00:59:04.350 --> 00:59:07.710
that adopted the HEARTS Initiative
923
00:59:07.710 --> 00:59:11.760
directed to better control hypertension,
924
00:59:11.760 --> 00:59:16.410
and HEARTS is based on a team-based approach protocol
925
00:59:16.410 --> 00:59:20.580
for clinical practice guidelines in the country,
926
00:59:20.580 --> 00:59:22.440
measuring cardiovascular risk
927
00:59:22.440 --> 00:59:27.300
as part of the management of patients with hypertension
928
00:59:27.300 --> 00:59:30.810
and providing free access to medication,
929
00:59:30.810 --> 00:59:34.590
in particular, fixed-dose combinations,
930
00:59:34.590 --> 00:59:37.500
which are supposed to improve adherence,
931
00:59:37.500 --> 00:59:41.430
because these people had and have comorbidities
932
00:59:41.430 --> 00:59:44.400
and sometimes have to take many medications,
933
00:59:44.400 --> 00:59:49.400
so these fixed-dose combinations are an alternative.
934
00:59:49.678 --> 00:59:53.541
Those are the components of the HEARTS Initiative
935
00:59:53.541 --> 00:59:56.949
in the Americas, and we have 12 countries at the moment
936
00:59:56.949 --> 00:59:59.160
as part the initiative.
937
00:59:59.160 --> 01:00:02.289
And who's paying for all these medications?
938
01:00:02.289 --> 01:00:03.400
Each government.
939
01:00:03.400 --> 01:00:04.380
I mean, each government.
940
01:00:04.380 --> 01:00:06.360
They don't receive...
941
01:00:06.360 --> 01:00:10.053
Countries don't receive any financial support.
942
01:00:10.968 --> 01:00:14.468
Technical support, yes, but not financial.
943
01:00:17.050 --> 01:00:19.380
Okay, well, it is 13:00,
944
01:00:19.380 --> 01:00:22.680
so this was an incredibly interesting talk.
945
01:00:22.680 --> 01:00:25.170
I would've loved to have asked more about equity,
946
01:00:25.170 --> 01:00:27.090
which is a very hot topic around here
947
01:00:27.090 --> 01:00:29.910
at the Yale School of Public Health and elsewhere,
948
01:00:29.910 --> 01:00:32.790
but maybe we can save that for another time.
949
01:00:32.790 --> 01:00:34.200
And thank you so much, Vilma,
950
01:00:34.200 --> 01:00:39.200
for coming and providing such amazing information.
951
01:00:40.358 --> 01:00:41.874
Thank you very much.
952
01:00:41.874 --> 01:00:44.870
Thank you very much for giving me the opportunity.
953
01:00:44.870 --> 01:00:46.786
Yeah.
You are like a star.
954
01:00:46.786 --> 01:00:48.545
(attendees laughing)
Thank you.
955
01:00:48.545 --> 01:00:51.795
(attendees chattering)
956
01:00:53.920 --> 01:00:55.050
Hey, how's it going, I'm Luke Davis.
957
01:00:55.050 --> 01:00:56.333
Hi, how are you?