Medical Adherence – Building a Digital Health App

Medical Adherence – Building a Digital Health App

Medication adherence or taking medications correctly is generally defined as the extent to which patients take medicines as prescribed by their health care provider. This involves factors such as getting prescriptions filled,remembering to take medication on time understanding the directions.

medical adherence — half of all medications are not taken as prescribed

One area where digital health mobile applications have not made much progress is in the field of medical adherence.

The effect of chronic diseases on the health and wellness of individuals is increasing in every region of the world. One in three adults worldwide has raised blood pressure and one in 10 adults have diabetes.

Globally, there are approximately 422 million adults with diabetes as compared to 108 million in 1980 (4.7%-8.5% in the adult population).

Treatment of chronic conditions such as Diabetes and Hyper tension often includes prescription medications. Non adherence to medication therapy can compound the increases in morbidity and mortality, and can further add to additional health care costs. It is estimated that increased prescription medication adherence could save the United States US $300 billion annually in health care costs, including decreasing expensive emergency department visits and hospitalizations.

Medication non adherence contributes significantly to the growing burden of disease and high costs associated with care. For patients living with HIV, Taking HIV medicines every day prevents HIV from multiplying, which reduces the risk that HIV will mutate and produce drug-resistant HIV strains.

In recent years, drug-resistant strains of TB have created a growing sense of urgency to control the spread of the disease. Two strains have emerged: multidrug-resistant TB (MDR-TB), a form that is resistant to first-line drugs, and extensively drug-resistant TB (XDR-TB), which is also resistant to some second-line drugs. MDR-TB has appeared in nearly every country, with an estimated 490,000 new cases in 2016.

Reasons for medical non adherence

These can be classified in two categories, intentional versus unintentional.


· No symptoms

· High Costs — the inability to pay for medication

· Depression

· Too many medications

· Side effects

· Mistrust — disbelief that the treatment is necessary or working


· Forgetfulness — we are all human after all

· They don’t realize they are supposed to take them

· Illness — dementia, visual problems or arthritis in the hands (they cant open the bottle)

· Complex dosing schedules and different pill combinations

3 pillars of success for Drug adherence

The way we have to looked at this problem, you have to satisfy 3 pillars of success, whether you want your spouse to take the garbage out

Value: Patients have to realize there’s value. You have to educate them to taking the medication has the benefits of controlling the diseases, reducing the progress.

Convenient: Making sure they can afford it but also the regiment is simple, e.g. 1 pill per day. Patient needs to be able to monitor the effect of their medicines, e.g. giving patient blood pressure monitors.

Trust: Patients need to believe that its important. Gallups polls indicate people trust nurses more than doctors.

Basically these are the 3 Us, Useful, Usable and you have to develop trust.

Digital Health apps have struggled in this realm, in trying to solve the adherence hoodoo. This is mainly because most digital health apps are basic are not very useful. While developing an app for a healthcare client, I scoped out existing apps and I was baffled by what I found on the market. One app I downloaded was developed on the premise that medication is taken once a day. In order to develop an effective Medical Adherence app we decided to incorporate personalization and user awareness.

Consider someone living with diabetes. Patient Care plans for this illness vary from individual to individual and are riddled with complexity.

The patient has to regularly check their blood sugar levels (glucose) inject insulin and take pills, while following a strict diet and exercise plan. What’s more, these steps have to be coordinated with needle perfect precision; otherwise if they forget to check their blood sugar levels before exercising, they could suffer a hypoglycemic reaction mid-workout and end up in the emergency room. Or, if they mix up short- and long-acting insulin, they could overdose. In addition, stress levels, sleeping patterns, and other factors affect glucose balance.

Existing apps struggle to navigate this maze. User-aware apps are able to solve this mess by doing the following.

· The app knows the user’s historical health patterns and senses when they are driving to their local gym

· The app prompts the user to check their glucose levels and/or to eat an apple before exercising (when the user needs it most)

· The app knows when the user is going to sleep versus waking up versus driving 30 minutes to work

· It tells the user to take long-acting or short-acting insulin at appropriate times. It also sends accurate, perfectly timed pill reminders

· The app knows key data about the user such as their sleeping patterns, exercise habits, average work hours each week, and much more

· Based on this data, it creates an activity report that enables the app to share tailored insights with the user, helps users see where they need to change behaviors or reveals causes behind certain symptoms, and/or gives the user’s healthcare provider information that they can use to help the user better manage their condition

The problem with user personalization and user awareness apps is that the technology is still nascent and extremely difficult to build, as it requires advanced knowledge of machine learning. There is also the annoyance factor and battery draining aspects as the app has to access the user’s location and access other features in order to fully function.

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