Driver Project 12 - The Impact of COVID-19 on Chronic Care Patients’ Health Care Utilization and Health Outcomes in Haiti, Malawi, Mexico and Rwanda
To evaluate the impact of the COVID-19 pandemic on care provision and utilisation, and the health of patients with chronic diseases like HIV and diabetes in Haiti, Malawi, Mexico, and Rwanda, by collecting and analysing electronic medical records.
Dale Barnhart and colleagues at Harvard Medical School in the U.S. and Partners in Health of Haiti, Malawi, Mexico, and Rwanda aimed to determine how the COVID-19 pandemic has impacted health care provision and utilisation for patients with HIV, heart disease, and diabetes, and the health outcomes of these patients, in all four countries. They have pooled existing electronic medical data on chronic care patients collected from up to 30 health facilities in each country and create a harmonised database to identify the impacts of COVID-19 and any successful strategies used to improve care. They have also developed a predictive model to identify which patient populations are most at risk from care disruption during the pandemic, which can help prioritise clinical and geographic areas that need interventions. Finally, they have developed data visualisation tools to facilitate the communication and interpretation of the data by chronic care managers across the four different countries.
Driver Project 12
|Aridhia||Mar 2022||Article||This driver project from Partners In Health and Harvard Medical School looks to examine how the pandemic has impacted the care received by chronic care patients in four countries: Haiti, Malawi, Mexico and Rwanda…|
|COVID-19 impact on patient healthcare use/outcomes Haiti, Malawi, Mexico, Rwanda||Metadata||A harmonized, pooled, multi-country database using aggregated data of patients with HIV, cardiovascular and diabetes clinical outcomes datasets has been completed|
This project is a retrospective cohort study which means what we’re going to do is we’re going to be using an existing clinical data source, and compare patient outcomes before and after the COVID pandemic, to understand how the pandemic is disrupted care for HIV, diabetes and cardiovascular disease patients. Our data source is coming from a site supported by Partners in Health which is a nonprofit global health organisation that seeks to provide equitable access to health care. And so many PIH supported sites are using open Mrs. Space electronical medical record system or EMR to inform and shape programmes for their chronic care patients. But we’re going to do is we’re going to take the CMR data, combine it and harmonise it from four countries and those four countries are Haiti Malawi, Mexico, and this project Mercer first time that pH is combined EMR records from multiple countries into a single research study. Collaborating with research journals from four countries and ensuring that the data can be shared and harmonised analysis involves not only a high level of technical skill, but also a huge investment in developing relationships. As well as developing data sharing and data storage processes. So the key factor, as well as the addresses analysis is going to support from the larger VMH ProSite COVID-19 research network. Right now we still don’t really understand the impact of the COVID 19 pandemic on patients with chronic illnesses was particularly true in low income settings. As you might recall, at the start of the pandemic, many in the global health community were making dire predictions about how poorly low income countries would respond. However, as we now know, many of those countries were able to really effectively implement strong pandemic control strategies. So, right now, I think our current assumption is that chronic care patients have universally experienced major gaps in care during the pandemic and that these gaps have resulted in poor health outcomes. However, I know that my clinician colleagues have implemented many novel strategies, which could mitigate these effects. What we’re hoping is that by looking at three types of chronic care patients across four countries, we can first provide real empirical evidence on the actual impact of the pandemic on chronic care patients globally. Second, identify where gaps have occurred and use this evidence to provide targeted support for those specific programmes. And third, identify patient populations that did not experience four outcomes. And we actually think that this third objective is really important because the commission to conserving those patients are the people who can help us identify effective strategies to promote continuity of care for patients also. With a lot of the processing to go but we’re hoping for internal dissemination of results. As a global health researcher, my number one priority for health data science is to invest in educational opportunities and long term membership opportunities with the MLS that stations in low income countries. I live in work in Rwanda, and I’m constantly surprised by the museum barista sharing. At the same time, despite this enthusiasm, there just aren’t enough analysts to meet the demands placed on them. So ultimately, I really believe that investing in the careers of these analysts is going to be the best way to ensure that the people with the right skills in the right place at the right time, and that’s what’s going to enable us to address any emerging health disease. The second priority for the field to me is to reflect on whether data science is moving in a way that promotes global research equity. So open access data is a great example of this. I think in principle, it’s a really great thing really powerful. In practice, creating and publishing those open access datasets creates a huge burden for the research team. And then once the data is published, it becomes most accessible and most useful to those who already have surplus analytic resources. This dynamic I think, can really disadvantage anyone who’s working outside of the large research institution and I worried, especially disadvantaged researchers in low and middle income countries. That’s not to say that I think we should expand on the idea of open access data. However, I do think, very thoughtful about how these extra efforts and resource how this labour is being recognised and how to ensure that the data is not becoming divorce researchers collected it in the context in which are being collected.
Absolutely, our research question really relies on the data from the four countries that I mentioned before. Again, it’s the Malawi next summer Wanda, and I really think that the data sharing that has been able to be possible for this project would not be possible without long term collaboration of its site, local long term partnership with locations, but also without the kind of new pH ProSite COVID-19 research network that we built responsible for that. And so this is a new organisation that we are in the organisation, the new team that we’ve developed in order to address some common questions that we realised were occurring at multiple locations at once, the basic network is really unique in lab it is bringing together researchers from eight countries, and then a small team of methodologists to address these kinds of research questions. This is a big departure from how receptions historically been done at each site because they had small research teams, working largely independently or perhaps with some centralised support from Boston. This is a big change. This has been a really challenging collaboration to get off the ground and pandemic of course, but also has it has already become a really incredible resource. You’ve seen that the researchers from different sides are now able to collaborate directly with each other and a stronger role in setting research agenda. We’ll do two factors that really helped promote research equity within our team. The other cool thing has been we’ve been able to build across it but I mean, and that means that our research shows that at one site we quickly shared and adapted with other sites.
I think one thing I’m really excited to see as his progress as his projects progress, is the ways in which these initial investments in high quality data are going to be involved to create many new opportunities for collaboration and the new spin off products. I think something that I hope everyone is starting to think about now already in the young business programme is how can we sustain the investment in the US sort of novel and powerful and cross country datasets in a way that can be useful for years to come?