A 2-hour data for global health conversation, synthesized
Short on time, but curious what data for health delivery experts are talking about right now? Devex sought out two experts to break down a recent conversation organized by Johnson & Johnson on what's next for data and measurement in global health. Here are three big picture ideas to keep in mind.
By Kelli Rogers // 06 October 2015Curious what’s currently piquing the interest of experts in data for global health delivery? In short, it’s that better access to data — and to quality training and tools to help professionals effectively analyze and use it for health delivery — will be a critical piece of achieving the global goals. After a recent Johnson & Johnson-organized conversation on the topic, we sought the expertise of Global Health Data Exchange’s Peter Speyer and McMaster Health Forum Scientific Lead Kaelan Moat to help boil down what’s next for data and measurement in global health. Here are three big picture ideas to keep in mind right now. 1. Data, at the end of the day, is about collaboration, partnership and trust. There can be actual problems with respect to the confidentiality of health data, but this is often used as an argument not to share — even when it’s technically possible, said Speyer, chief data and technology officer at the Institute for Health Metrics and Evaluation at the University of Washington. There can also be a hesitation to share based on the transparency issue and the realization that people will see if things did or didn’t work. Speyer, who manages IHME’s public catalog and repository of health-related data, has plenty of experience with these issues, having worked with stakeholders from academics to government officials in 188 different countries. There’s a whole spectrum of sharing, he noted, from “I don’t want to” to “I can’t.” There are also capacity constraints, he added, when an organization might have data just sitting on a server waiting for someone to pull it out and share it. He cited the example of survey data he was on the hunt for from a particular organization in Iraq. “They said ‘You can pick it up. It’s in the green zone in Baghdad,’” Speyer told Devex. “I had to actually find someone who could go to Baghdad and retrieve it … those challenges still exist.” The challenge extends beyond raw data to research evidence, according to Kaelan Moat, who leads the maintenance and ongoing content development of Health Systems Evidence, a comprehensive access point for evidence about how to strengthen or reform health systems. The open access issue is what becomes the challenge, he said, with respect to where it’s published and whether it’s free. If a systematic review is published by Cochrane, a well-known international organization that prepares, maintains and promotes the accessibility of systematic reviews of the effects of health care, it’s inaccessible without a paid subscription. One of the ways this is being overcome in low- and middle-income countries is through Hinari, a program set up by the World Health Organization together with major publishers that enables these countries to gain access to one of the world's largest collections of biomedical and health literature. Governments can sign up for subscription at country level, which will provide IP addresses within that country the ability to access information that would normally be out of reach behind a paywall. 2. One-stop shops are part of the answer to better data alignment. So is creating an ecosystem of data collaborators. Every survey about tobacco use will frame the question about tobacco smoking a little differently. The same goes for education — yet these studies must still be mapped together even when data has been collected in another form. “There are 106 different versions of health data coding just for diseases that we need to map to our disease categories,” Speyer explained of his work with IHME. Collaboration is vital, and the more stakeholders can make an effort of bringing different collectors and users together to agree on standards, the better, but “realistically, I don’t think you’re going to get everyone that could be involved in the conduct, dissemination and synthesis of evidence together,” Moat said. In the research world, where data has already been analyzed and synthesized, the key is where it lives. Cue one-stop shopping, Moat said. Health Systems Evidence, for example, is a shop for public health systems decision, while Cochrane plays that role for synthesis of clinical program services and drugs. Now, the same thing is happening at a local level, Moat said. The analyst sitting at the Ministry of Health in Zambia, asking “How is this global data relevant to me?” can turn to a contextualized one-stop shop that draws from global sources while also pulling in local single studies. This adds the ability for decision-makers to consider options — like certain incentives for community health workers, for example — by also looking to what local studies say. At the end of the day, projects like Speyer’s global disease study want the data used. IHME developed a global network of collaborators — about 1,000 in 106 countries — and gave them preliminary results to invite feedback and conversation from local disease experts before peer review. “Once we had this process, these are the same people who take our data and get it used locally or send out local press releases,” Speyer said. “It becomes an ecosystem.” 3. Open data doesn’t mean accessible data. Or even quality data. Maybe “knowledge brokers” can help? Once you get into analyzation, it’s immediately: Is this good good analyzation? Can I replicate it? What kind of peer review happened? “In the value chain of data, complexity increases with every step,” Speyer said. If someone who supports decision-makers goes to their local health ministry wanting to communicate the need to ban sugary drinks to combat diabetes, for example, what are the best interventions? And what if you’re trying to base those on unclear evidence? The same questions apply whether you’re talking about raw data or research evidence, according to Moat. There are a few ways to address this, he added. One would be to require clearinghouses — or one-stop shops — to be explicit and transparent about how they obtain their data and provide users with a sense of what the quality of that data is. Secondly, when talking about getting policymakers to use existing data, it’s about scaling up capacity building, Moat said. It’s about going into a ministry of health, sitting down with analysts for two-three days and saying, “What questions are you working on right now?” “Peter and I may know, within our fields, every database, the quality of it and are even familiar with the people who run it,” Moat said. “But an analyst in a developing country doesn’t care why something is high or low quality. They want to know: Is this high quality enough for me to take to the minister? How do we help them reach into our world at the end of the day?” One means is through knowledge brokers, or experts whose job would be to set up forums, workshops and translate technical legalese into what’s needed for policymaking. These general methodolists would understand how to link data and policy and decision making, and have been referred to as “data intermediaries” — people or tools that can take data and visualize it in a way that is most useful for policymakers, civil society, implementers and other stakeholders — by Tony Pipa, U.S. special coordinator for the post-2015 development agenda, in previous conversations with Devex. Aside from data intermediaries, visualization is another game changer for large data sets, Speyer added. The results of his global burden of disease study included 2 billion data points — clearly not shareable via spreadsheet. Instead, it’s about making it accessible at the right level of detail, by asking what academic research wants, what analysts want, what ministers want. “We see people hang out over half an hour on one visualization and play with data,” Speyer said, referring to the GBD compare visualization available on IHME’s website. Synthesizing data with the full range of global research evidence that addresses the same problem for decision-makers also means creating an evidence brief in a way that policymakers can digest quickly. “What does that three-page summary look like that’s going to get traction, identify the burden of disease in your context as well as options and what barriers exist? At the end of the day, it’s often about the take home message,” Moat said. To read additional content on global health, go to Focus On: Global Health in partnership with Johnson & Johnson.
Curious what’s currently piquing the interest of experts in data for global health delivery?
In short, it’s that better access to data — and to quality training and tools to help professionals effectively analyze and use it for health delivery — will be a critical piece of achieving the global goals.
After a recent Johnson & Johnson-organized conversation on the topic, we sought the expertise of Global Health Data Exchange’s Peter Speyer and McMaster Health Forum Scientific Lead Kaelan Moat to help boil down what’s next for data and measurement in global health. Here are three big picture ideas to keep in mind right now.
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Kelli Rogers has worked as an Associate Editor and Southeast Asia Correspondent for Devex, with a particular focus on gender. Prior to that, she reported on social and environmental issues from Nairobi, Kenya. Kelli holds a bachelor’s degree in journalism from the University of Missouri, and has reported from more than 20 countries.