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Concierge health care, the effects of climate change, and more of what's to come.
It’s been ten years since the first truly affordable smartphone was introduced and unleashed a transformation across the African continent. These days, over 40% of all Africans use smartphones, and the technology generates 8.6% of GDP in sub-Saharan Africa.
But the tech transformation hasn’t stopped with telecommunications. The field of digital health has expanded, too. To kick off 2020, IntraHealth International’s digital health team examined the existing health care ecosystem and emerging technologies to identify the trends we believe will define digital health over the next decade.
From frontline health workers using data to improve their services, to health administrators using data to accurately deploy health resources; from clinics, to people, to commodities— these examples of using data in more sophisticated ways will be standard practice, not the innovations they’re seen as today.
Data collection, sharing, and analysis practices will become more sophisticated. This trend is already obvious in the spread of DHIS2, the move to facility- and patient-level data, and an increasing focus on health systems interoperability. By 2030, we hope to see widespread maturity in data use at all levels of the health system.
The last decade saw a dramatic shift from storing data and running applications on local servers to using cloud hosting. Many countries are still working through political barriers to hosting data outside of ministry servers. But soon enough, the convenience of the cloud will be overwhelming.
For this trend to be fully realized, digital health practitioners will need to reassure governments and other health data managers that cloud hosting has fail-safe data security—a tall order when hackers will become more skilled and plentiful.
“The Internet has so many advantages for digital health,” says IntraHealth’s senior digital health product manager, Richard Stanley. “Yet it is still a hostile environment for any digital health solution, especially those that contain information on patients and practitioners.”
Kenya is leading the continent in a “devolution revolution”—the transfer of health decision-making from national to county leaders. This shift means that software solutions and data sharing agreements will need to be spread across dozens of political entities, not just concentrated at the national level.
“We must be responsive to national priorities that devolve health responsibilities to the county or district level,” says Ummuro Adano, IntraHealth’s regional director for East Africa, “with health care technology that supports devolution without sacrificing data interoperability.”
IntraHealth already experienced this when we reconfigured our iHRIS software to support 47 counties’ independent health worker decisions, using a central database with county-level data views. When countries like Uganda, with 134 districts, move decision-making authority from the national to the district level, technology vendors will need to invest heavily in solutions and implementation plans that can convert the national government and most districts to achieve realistic national scale and data sharing.
Organizations are already using machine learning in global health. Advanced image processing algorithms can diagnose cancer and eye diseases, and natural language processing allows chatbots to detect depression in real time.
“At IntraHealth, we’ve already used data science and machine learning to find new insights from existing health data sets in Uganda,” says IntraHealth data scientist Amy Finnegan. “In the future, analyzing interoperable big health data will make precision public health a reality in low- and middle-income settings.”
In the coming years, such artificial intelligence applications will “eat everything” in the same way that software ate everything by finding faster, better ways to provide needed services.Western countries may see this as a threat to traditional medicine, but in low- and middle-income countries, health care will now be accessible to millions of people who would otherwise never be able to access advanced health services.
Imagine smartphones, in everyone’s pockets, supercharged by artificial intelligence. These solutions will augment existing services and extend personalized health care virtually, where few or no services exist today.
For example, in Nigeria, 50 million people are suffering from some sort of mental illness, according to the World Health Organization, yet there are only eight federal neuropsychiatric hospitals. Instead of waiting decades for new clinicians to be trained, Nigerians can access Wysa today—a smartphone application that uses natural language processing to converse naturally with clients and, for many, can ease their feelings of loneliness and depression.
Governments trying to reach universal health coverage may repeat the mistakes others made during the push toward universal primary education in the 2000s. At that time, governments eliminated school fees, creating an exponential demand for primary education. But without investments in infrastructure (schools, teachers, etc.), this sometimes led to a decrease in public education quality.
Digital health practitioners will need to anticipate governments increasing the demand for health services, the way Mali already has for mother-and-child services—and develop high-quality solutions that can respond without adding many more clinicians or facilities.
The use of health insurance, be it government or private, will increase as a way for communities to reduce the financial burden of health services. The need for financial accountability for health insurance will drive demand for accurate health data at all levels of the health system.
Facilities, and maybe even health workers themselves, will need to track their clients and services in order to receive payment. This demand for data will require accurate data flows that can drastically increase understanding of health system coverage and performance. For example, the need for unique patient identifiers for insurance purposes will finally allow administrators to know exactly how many clients are served by each facility.
Noncommunicable diseases (NCDs) are on the rise worldwide. In African countries, such as Mauritius, Namibia, and Seychelles, NCDs cause over 50% of all reported adult deaths. In low-income countries, nearly 30% of NCD-related deaths occur under the age of 60 - a major difference from rich countries. NCDs are poised to eclipse HIV as a core health problem in the near future.
Digital health practitioners will need to find ways to use technology to reduce common risk factors—tobacco and alcohol use, diet, and physical inactivity. And there will be failures in our search for effective solutions, because NCDs are long-term problems that often require long-term interventions.
As temperatures rise and generate negative consequences that affect community health, we will need to find ways to reduce the negative consequences of digital technologies—from hardware production to energy consumption—and use digital health to benefit communities. Currently, digital technology is a net contributor to the problem—a core challenge that will require all of us to change our behaviors.
We’ve left the last trend blank in recognition that this isn’t a perfect list of predictions. It skews toward efforts that we’re thinking about—a tiny microcosm of the global digital health ecosystem. What do you think #digitalhealth will look like in 2030?Tweet @IntraHealth with your emerging trends and predictions for the future.
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