Evaluating eHealth’s generic impact in Africa’s been a bit like the search for the elusive needle in the conceptual haystack. eHealth may have huge, visible potential, but finding it’s probable generic net benefit over time, the difference between estimated costs and benefits, hasn’t found much traction. Instead, modest efforts have been directed to evaluations of specific types of eHealth in specific settings with limited transferability.
In 2014, Denmark planned to break through the barrier. It’s
- Share best practices
- Learn from one another
- Increase the use of welfare technology, which is eHealth and eWelfare.
It’s financed by the government’s Denmark’s Digital Welfare Strategy 2013 to 2020 within a budget between DKK 1.065m ($144m) and 1.5m, (US$217m) for each project. The allocations of the DKK 4.065m budget:
- Evaluation of digitally supported work on early detection, DKK 1.065m
- Use of return systems for the prevention of pressure ulcers and injuries, DKK 1.5m.
- Longer home together will test and evaluate of an intelligent sensor based alarm system for home, DKK1.5m.
Early detection’s led by the municipality of Aalborg. It’ll test solutions for the early detection of health issues in the elderly, including automatic alerts for medical professionals. The municipality of Aabenraa leads on systems that automatically turn bed-ridden patients, so reduces the number of medical staff needed. Using of sensors installed in homes to support home care for peoples with is being evaluated by the city of Aarhus. The next series of applications is expected in mid-2016.
Low and Middle Income Countries (LMIC) have different eHealth priorities, so the need for evaluation data. In 2011, WHO published findings from a review of evaluations of three types of eHealth in Low and Middle Income Countries (LMIC). It included:
- Systems facilitating clinical practice
- Institutional systems
- Systems facilitating care at a distance.
It found that large randomised trials provide strong evidence of eHealth’s efficacy and its potential impact on outcomes, but, highly controlled studies fail to answer questions about:
- eHealth’s reach into vulnerable communities
- Can eHealth systems be adopted, scaled up and maintained outside the environments in which they were originally studied, the conundrum of transferability.
It proposed new approaches to evaluation that emphasise qualitative and quantitative methods, community-based participatory research, and organizational theory in addition to controlled trials and ensure that eHealth’s relevance and flexibility to adapt to different settings. Evaluations comprising several sites are expensive, so a constraint. Their benefits need weighing against two other approaches. One’s larger numbers of smaller and innovative, less definitive evaluations of eHealth adapted to different cultures and environments. The other’s step-wedge designs where eHealth’s gradually rolled out to new sites.
It’s vital that Africa’s health systems adopt this advice to improve their eHealth investment. It seems that eHealth decision-takers may have to keep waiting for facts provided by their eHealth evaluation needles, while their health hay stacks keep steadily expanding. It’s not just time and tide that doesn’t wait.