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Expanding Health Coverage Using Mobile Phone Data

Authored By: Rachel Sibande (Digital Impact Alliance), Erwin Knippenberg (Cooper/Smith)

On April 10th 2019, the Digital Impact Alliance (DIAL) in partnership with the Malawi Ministry of Health and Cooper/Smith held a workshop showcasing the recent use of Mobile Network Operator (MNO) data to inform policymaking. Check out the video overview here and full report!


Often, when people think of using network data for development; there are concerns around access and use of personally identifiable information. However, we have found that we can answer development questions using basic insights from network data without the use of personally identifiable information.


There are several elements of Mobile Network Operator (MNO) data that generate basic to complex insights valuable to answer key development questions in a safe and responsible way. For example: questions on understanding population density and migration patterns of people to know where to deploy schools, water points, health facilities and other service delivery facilities can be answered using aggregated location data from network data without accessing personally identifiable information. Questions around income profiles or poverty index to inform food security outcomes can be answered by analyzing airtime top ups, spending data and transactional data on mobile money platforms. Demographic data on gender, age, sex can generate insights on community profiles, lifestyles and usage behavior.

DIAL and its partners have been working to support governments, development practitioners and technology implementers to enhance their efforts in delivering public services. DIAL was commissioned to create turnkey replicable models that uses MNO data to answer development questions in a safe and responsible way. DIAL engages with a cross range of digital ecosystem actors including donors, governments, NGOs, MNOs, Companies and Regulators.

In Malawi, DIAL has partnered with the Ministry of Health as the end user, Cooper/Smith and Infosys (technical partners) to leverage the responsible use of network data to demonstrate how MNO data can be used to inform the placement of new health facilities and direct future investments priorities in health.

 
The analysis of MNO data, disease burden data from the Ministry of Health, and existing data on location of current health facilities across the country; confirmed that access to primary healthcare remains a challenge in Malawi, with an estimated 45% of people living more than 5 km from a health facility. Without action, this number is projected to increase to 9.7 million by 2023. To remedy this, the Malawi Ministry of Health is evaluating the investment required to build 900 new health posts by 2023.


To inform this potential investment and resulting impact, the Malawi demonstration project has been working since 2017 to develop usable metrics from network data on population density and migration patterns without using personally identifiable information. Using two years of network data containing 12.9 billion records, the analysis counted the density of unique-users in each administrative area and compared it to historical population density.

Shifts in population density over time, (which cannot be directly observed), could then be inferred using shifts in the observed density of unique-users over time. This inference was then validated using preliminary results from the 2018 census. It was established that there is no significant difference between the population projections made by this model using MNO data and the population figures from the 2018 preliminary census report. This result alone validates the credibility of using MNO data to understand population densities. The analysis offered a detailed projection of population movement and population growth patterns, nationwide.


The team then optimized the data to reflect the possible placement of new health posts, specifically in under-served areas with rapidly growing populations. Additionally, the model allowed for inclusion of location specific disease burden and disability adjusted life years (DALYs) data. Based on the projected placement of the new health posts, the model projected that the number of Malawians living within 5-6 km of a health facility could increase from 55% to 95% of the population by 2023.

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The culmination of this data demonstration project took place on April 10th, when DIAL together with the Ministry of Health and Cooper/Smith, convened a results dissemination workshop for the Malawi data demonstration project in Lilongwe, Malawi. The gathering consisted of policy makers, development practitioners, academia, regulators and MNOs among others. The workshop was a culmination of a year and a half-long process, of among other things; ensuring regulatory compliance, building the infrastructure to house the data, and demonstrating its potential to inform real-world policymaking.

 Dr. Charles Mwansambo, Chief of Health Services in the Ministry of Health and Population in Malawi, stated in his opening remarks,

“The mobile platform has brought huge possibilities in how the delivery of health services can be improved. The data that is generated through the platforms can go a long way in making it easier to plan and to provide quality health services.”

During the workshop, development partners named a number of potential follow-up use cases in the domain of education, disaster relief, and public health, where similar methodologies could be applied. MNO providers and regulators also expressed their openness to such uses but emphasized the importance of developing detailed use cases when negotiating access to the data. The workshop also provided a venue for focused dialogue on the potential to harness MNO data for the public good, nation-wide.

 
In terms of sustainability, members of the academia expressed their interest in developing partnership agreements with the Ministry and implementing partners in order to build the analytical capacity available in country. As a next step, the project consortium will evaluate the possibility of leveraging support to create a viable data pipeline with these capabilities, that will plug into existing data systems in Malawi.

  
With this groundwork in place, the consortium is focused on engaging directly with data-users in the government, academia, and civil society to consider replication and scale of this model and to stimulate the appetite for use of non-traditional data such as MNO data to answer development questions. As an initial step, government and development practitioners shall consider replication of this model to answer questions such as where to place schools, water points, and other social services based on gaps in service delivery, population density, and other social dynamics.

 
We believe that through dissemination and replication, there can be a holistic showcase of how MNO data can be leveraged for the public good. This story is about a unique public private collaboration that has contributed to helping answer critical questions that can improve health access but which is also relevant to multiple sectors. Let us know if you are interested in replicating this model to enhance the delivery of public services and improved decision making in the public sector.      

Questions? Check out our FAQs or contact us!

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March Floods in Southern Malawi Risk Exacerbating Food Insecurity & Malaria

In support of the USAID-funded Measurement Indicators for Resilience Analysis (MIRA) data collection protocol, part of the United in Building and Advancing Life Expectations (UBALE) project, CRS is working with data analytics partner, Cooper/Smith, to report on household-level food insecurity risks in Malawi following the cyclone-related flooding which impacted the region from March 4, 2019 to March 21, 2019.

Using data from 2100 households reporting monthly under the MIRA project, and including GeoSpatial Data from the Humanitarian Data Exchange (courtesy of the Red Cross), these results are able to more effectively pinpoint shocks and food security risks throughout Southern Malawi.

Early reports from households in areas affected by the March 2019 Floods suggest a spike in food insecurity, as crops and stored grains have been washed away. The Shire River Floodplain was the area most impacted, where thousands of residents were displaced when flooding broke the banks as a result of heavy rains, as demarcated in light blue below.

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The data shows household food storage to be critically low with hunger increasing. As of March 25th, 2019, many households in affected areas had less than a week’s worth of food and were reporting high levels of malaria.

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What is the true cost of mHealth?

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What is the true cost of mHealth?

By Maganizo Monawe, Tyler Smith, and Andrea Fletcher

As the team that worked on the Malawi mHealth Landscape Analysis, we want to respond to the recent ICTWorks post about the cost of mHealth.

The purpose of our mHealth 360 analysis is to develop an inventory of mobile health technology systems currently implemented in Malawi, and provide concrete recommendations for Malawi’s Ministry of Health to assess and evaluate the evidence when formulating policies, standards, and strategies in mhealth.

There is indeed insufficient literature guiding the costing of mHealth applications. Our study produced an estimated cost of mHealth interventions by generating a financial indicator based on a ballpark estimate of resources used for mHealth in Malawi. We understand the limitations of this approach and intend to refine it moving forward. We hope these numbers can move us closer to understanding how much mhealth costs, demonstrate how we can conduct better costing studies, and uncover methods for reducing inefficiencies and demonstrating the return on investment of mhealth.

While this data is insufficiently precise to allow for future budgeting, it offers a snapshot of the situation in the field. As a first step, there is value in identifying how partners are spending in various categories in order to understand the order of magnitude of funding necessary for mHealth as we plan and strategize in the future.

31 different mobile applications under implementation to support health service delivery in Malawi with some of the geographical locations having as many as half of these applications being implemented in the same district reflects a fundamental challenge in the implementation of mHealth in developing countries. It is a clear demonstration of lack of harmonization among implementing partners resulting in duplicate efforts and inefficiencies in use of investments.
— Malawi ministerial statement at the 2018 World Health Assemby

The analysis reveals a project’s average lifespan to be 5 years, coincidentally, most donor funding is on a 5-year timeline. Just as projects are starting to ramp up, the funding dies down. For governments to absorb projects, realistic planning and budgeting for scale must begin from the onset of the project with a clear return on investment demonstrated. We need consistent, timely financial data to make that happen.

We believe there needs to be a strong methodology upfront to understand how plans and expenditures are used and on what inputs they are based. In the current status quo, we don’t validate the total cost of ownership and the budgets, we just know that the money is spent. Currently, the global mHealth community also does not compare actual resource use with actual scope and scale achieved by each project over time, which precludes us from having quality empirical data for making future funding decisions. We need to change that.

While we agree that the value of mHealth interventions are not only monetary, it is challenging to get partners to share their expenditure data. Only 12 of the 31 projects who responded to the national registration were willing to provide cost data and much of what was provided was incomplete. Moving toward a global standard around how best to document true cost for mHealth, then getting everyone to share this information so it can be used to improve how we’re actually paying for services in mHealth --  that is the end state that we hope to achieve.

In-depth after-the-fact costing studies are not the way to track costing for mHealth. We need something that is more routine and lightweight. It requires relentless coordination, lots of elbow grease, and consistent openness with data. Using the project data that already exists, expenditure analysis can lead us to the answers of how much mHealth cost.



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What’s APPening in Malawi? An overview of the National mHealth Landscape Analysis

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What’s APPening in Malawi? An overview of the National mHealth Landscape Analysis

By Andrea Fletcher, Lead Data Strategist

Chances are if you aren’t reading this on your mobile phone, you at least have one within reach. Mobile phones have become ubiquitous and are changing the way we do everything from banking to healthcare. This is true globally and even more pronounced in countries such as Malawi, where the uptake of smart phones skyrocketed in the past few years and now 85% of households have access to a mobile phone. It’s therefore not surprising that the Malawian healthcare industry is seeing a large influx of mobile projects as a means of reaching the population for healthcare delivery, data collection, and supervision.

Over the past few months, Cooper/Smith worked with Malawi’s Ministry of Health and Population to register the numerous mHealth projects deployed in the country by various development partners. The analysis kicked off with a memo from the Secretary for Health requiring all projects to register, which allowed us to identify and gather information on 31 mHealth projects. The 2018 mHealth Landscape Analysis provides aggregate information regarding the scale of projects, health domains, alignment with national strategies, and budgetary information.

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mHealth projects in Malawi have existed since at least 2007, with an average of 2 new projects coming online each year. The average lifespan of a mHealth project is 5 years. 2016 was the most active year for new projects with 7 new projects coming online. As of March of 2018, there were 22 live mHealth projects.

With so many active projects, the report provides a foundation for decision-makers to better understand the role of mHealth in the National Health Information System and coordinate the efforts of partners. It is already being used to provide recommendations for the development of the new National eHealth Strategy and is a valuable tool for communicating with stakeholders on the successes and challenges with mHealth deployments. Some key questions we’ve been asking based on the results of the landscape analysis include:

  • How do we do a better job of coordinating mHealth in Malawi?
  • How do we minimize duplication of efforts among partners?
  • Where should we invest mHealth resources to see the most impact?
  • What standards are necessary to achieve integrated service delivery at community level with mHealth?

Enjoy reading! And stay tuned for the results of the technical deep dive report from the Kuunika Project, where we go under the hood of several mHealth projects!

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What we’re learning about using technology to enhance teamwork, improve productivity, and communicate more efficiently

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What we’re learning about using technology to enhance teamwork, improve productivity, and communicate more efficiently

Authored by Michelle Jenn, Administrative Director

Figuring out the best way to communicate with co-workers, peers, clients, and vendors has become a major issue even for the most established business.  Start with a myriad of options to choose from that continually evolve (email, phone, text, chat apps, collaboration tools, social media, task-oriented apps, etc), add varying preferences among participants, and you end up with an ever-changing toolbox full of halfheartedly used apps and software tools. 

But maybe our trials and tribulations can help you avoid this. Whether you are a start-up yourself, have lots of staff that work remotely, or just want to use technologically to be more productive across teams, we hope our experience is useful.

We took advantage of a small core staff, knowing we could adjust or change tools altogether with little effort, and explored freely tools we stumbled upon or that were recommended.   Now that we are 2+ years into this journey, let’s look inside our toolbox to see what made the cut:

·         Email & Calendar

Google Suite

We started with Outlook, but quickly realized Suite was more powerful and provides better integration with Apple products/software. About half of our staff use Mac and half PCs. We noticed strange quirks in mail exchange between our Outlook account and all other providers. Given more and more orgs are switching to Google, this just made sense. Plus, the search function in Outlook is maddening and absolutely can’t compete with Google. (If you’re smart, you’ve stopped sorting emails into folders and now archive everything for search later). Also, some of our staff prefer to use local email/calendar clients on their computers. This is especially valuable if you travel extensively to places with limited connectivity, as we routinely do. Google works so much better across a range of people’s preferences for local clients.

 ·         Chat

WhatsApp

Great encryption, indicates when a comment has been seen, can create different groups, searchable, wi-fi calling, pdf sharing, and best of all...free. We do participate in other chat groups that are administered through Slack or some of the task tracking apps (Asana, Trello, etc.), but seem to always default to WA. We’ve noticed there is a different platform for different ways of speaking to each other. For example, we try never to use email for internal communications; we try to not task someone in a chat group; and we try not to have conversations in Asana. It really takes some trial and error to get this right, and standard operating procedures to make expectations clear, but ultimately everyone knows where to look for each type of information, increasing our ability to communicate with speed and accuracy.

·         Time tracker 

Toggl: 

The free version provides all the functionality we need for consultants.  We can create various projects and tags for each client and can have unlimited workspaces of up to 5 users each.  The “reports” options allow for meaningful analysis or can simply serve as a time sheet.  However, it works best when the user tracks in real time because manual entry is cumbersome to say the least.

·         Collaboration

Google Sheets, Google Docs, and Dropbox:  

We primarily use Dropbox as internal file storage for collaboration.  But it creates conflict copies if 2 people are editing at the same time.  So, for those times when we are up against a deadline and all hands are on deck, and often for external collaborations regardless, we use Google Sheets/Docs.  It’s a bit less intuitive and Sheets does not have full functionality of Excel, but we can all work on the same document at once without issue. The other challenge with Google Suite is its surprising lack of intuitive file storage. If I create a doc, it lives in my individual drive storage (even with a company account). I must share this document with others to have them work on it. We haven’t been able to create a company space where files can be stored and everyone with permission access them. This is a bit frustrating and often leads to unnecessary back and forth. (Please fix it Google!)

·         Expense reports

Expensify:

We started with this from the beginning and it serves its purpose well.  Some highlights: a photo of a receipt automatically creates a report, admin role can create different work groups with unique clients/projects/tags and rules, ACH direct deposit to employee/contractor’s bank for next-day reimbursement, automatic approval workflows with custom rules, and you can sync to your accounting software.  Basically, for only $9/user/month, they live up to their tagline “Expense reports that don’t suck.”  Our staff that travel all the time swear by Expensify. It really is a game changer.

·         Notes

Microsoft Office OneNote: This is basically a digital notebook where we can all view, add, and/or edit at the same time.  There is no forced structure or page layout.  We use it to keep meeting minutes, notes from phone calls, etc.  It is organized similar as a 3-ring binder with pages organized into sections within notebooks.  Many note-taking options exist today (Evernote, Dropbox Paper, etc.), but there’s a couple reasons why we chose this OneNote. First, we already pay for Office 365 (see below). Second, OneNote offers an offline client.  We are often taking notes in the field, so a web-only interface is just not an option.

·         Documents and Spreadsheets

Office 365, Piktochart, LucidPro:

The reality is that most of the world still relies on Microsoft products (Word, Excel, and PowerPoint), and this is true of our clients and partners. As such, we maintain an Office 365 membership for all our staff so we have access to the latest versions of each software. The big limitations of these products are they are heavy, consume lots of memory and space, and don’t work well on Mac. The Excel for Mac is so limited that our Technical Director runs 2 hard drives on his Apple computer, one with OSX and one with Windows—only for the Excel version. This definitely is not ideal and we hope Microsoft can get it together one day.

For fancier documents and charts (basic) we’ve been relying more on Piktochart and LucidPro. Both are web-based products that allow for much more visually appealing formats and graphics. Both require a subscription for downloading final products, but we tend to turn them on and off based on our needs each month.

·         Project management, Tasks

Asana: 

Where would we be without Asana?  This tool is super powerful as a project manager and task master and is certain to improve productivity.  But the possibilities don’t end there and are limited only by your imagination.   It can be used to keep meetings organized, for event management/planning, to keep pipelines (think recruiting or blog or biz dev), marketing launches, HR onboarding, tracking interviews, etc.  Seriously, I am in love.

Ultimately, we’ve learned that most offerings have one or two things they are really good at, but none are master of all.  Luckily, many of these products interact with one another without requiring an understanding of “APIs” and other scary integrations.  We therefore can use common nomenclature and tags for clients and projects across Expensify, Toggl, and Asana.  We’ve found this to be incredibly useful, and it results in a cohesive communications platform.

Work Smarter, Not Harder

The nature of our business requires team members to travel often and work remotely.  This work also necessitates coordination with many different partners and consultants around the world. 

We’ve discovered some powerful tools available to bridge these geographical gaps, and they are certainly worth the effort needed to get past their learning curves.  Without such a strong communications platform, we’d likely waste a lot of valuable time trying to perform even basic daily activities necessary to run a business (such as time tracking and expense reports) not to mention coordinating work efforts around the globe. 

We may have to navigate several tools to get the job done, but even speaking as a Gen-Xer, reluctant to take this plunge in the beginning, I can see the net positive.   With all this technology at our fingertips, business communication has the potential to be both more effective and more efficient than ever before.  And that’s speaking our language.

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Discrete Choice Experiment for Data Use Incentives in Malawi

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Discrete Choice Experiment for Data Use Incentives in Malawi

Our Lead Data Strategist Andrea Fletcher presented at the Global Digital Health Forum 2017 in Washington, DC as part of a panel on exploring methodologies.

Cooper/Smith conducted a Discrete Choice Experiment in Malawi to better understand data use incentives and how to prioritize investments in incentive programs for healthcare workers. This approach allows researchers to quantitatively measure perceived value and trade-offs between options provided to participants in simple survey form, which in turn allows policymakers to choose those factors that will most affect the desired outcome.

Click through the slides below to see her full presentation and learn more about Discrete Choice Experiments!

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