Juniper: M2M, big data to aid mHealth market
The increasing processing power of the smartphone has given rise to innovations in how smartphone apps can bring about new business models in the mHealth sector. mHealth, in combination with the mFitness segment, has created new services and ways of addressing the healthcare industry needs. It has been largely acknowledged that significant cost savings in the health sector can be made if successful mHealth business models are developed.
In most cases mHealth and mFitness are part of a wider trend in the M2M communications market to allow machines to connect with both one another and with humans. M2M starts with the relaying of information, in which the cellular network may be paramount, but it is also part of a wider system of information flow and analysis where feedback leads to positive action. This positive action can then have a bearing on what information is gathered, creating, theoretically at least, a virtuous circle. In mHealth, this is particularly the case for remote patient monitoring, where data collected from the patient can feed directly into reports from the medical establishment to that patient.
In the mHealth industry the positive outcomes that M2M can provide include substantial cost savings and efficiency gains, the improved management of information and the optimisation of resources. For mFitness the gains that M2M offer include the ability to aggregate and analyse data, usually from sporting activity. This may significantly enhance a training session through increased motivation. There may well, of course, be indirect savings to health organisations that accrue from this increased fitness: a fitter populace hopefully results in fewer hospital admissions (and thus lower state expenditure) for an array of illnesses and conditions ranging from cardiovascular complaints to obesity.
As the M2M market matures, several industries are moving from a position of individual connected devices to connected ecosystems. Thus mHealth is developing from individual and scattered remote patient monitoring projects to an infrastructure supporting the entire healthcare system for individuals that are outside medical establishments but still need care, such as those suffering from chronic diseases.
In the healthcare industry the aggregation of data from numerous monitoring events can, in principle, result in the ability to analyse and draw conclusions from the data which becomes available through these monitoring events.
Clearly the benefits of 'Big Data' can be particularly marked in mHealth if the sample of data is large enough. Indeed the use of Big Data has the potential to bring down healthcare spending by hundreds of billions of dollars annually, through linking adverse patient outcomes with the causes of chronic diseases for example. For such cost savings to be achieved stakeholders in the healthcare industry need to come together and have a common goal, premised on what Big Data can achieve.
Efficiency savings, in an industry where there is continuing pressure to reduce costs in both the private and public sectors, represents an important driver for mHealth. Whether via a direct route or indirectly, almost without exception mHealth apps hold the promise of saving significant amounts of money, while improving patient outcomes for the healthcare sector if implemented correctly.
Juniper Research's recent study on Mobile Health & Fitness: Monitoring, App-enabled Devices & Cost Savings 2013-2018 forecasts cumulative cost savings from remote patient monitoring of up to $36 billion globally over the next five years--under Juniper's most optimistic forecast scenario.
This is a significant opportunity, as healthcare in the developed world moves towards the concept of "accountable care", where funding is linked directly to the health of the patient or individual rather than being based upon the cost of treatment.
Even though remote patient monitoring, particularly for chronic diseases, is still at a very early stage in the development cycle, it fits well with new healthcare practices and the goal of keeping patients out of hospital, according to the findings from our report.
Juniper Research believes that, in time, chronic disease management may be carried out through smartphone-based services linking hardware to measure vital signs associated with chronic diseases to powerful cloud-based services. This will create the groundwork for more complex medical apps to come to fruition, the first signs of which are already being seen in fitness and healthcare's most advanced apps.
In conclusion, the healthcare trends above will exert enormous pressure on healthcare systems in coming years, with an increased acceptance of monitoring devices in healthcare, partly brought about through acceptance of mFitness devices.
Nitin Bhas is a Senior Analyst with Juniper Research. His areas of focus include mobile networks, technologies and handsets. This column is based on Juniper's recent research findings from the Mobile Health & Fitness: Monitoring, App-enabled Devices & Cost Savings 2013-2018 report.