Health applications add value to patients and life science organisations
I had a doctors appointment recently where my blood pressure was relatively stable, in line with the norm for a 26year old male. Have you ever been to the doctors though where the blood pressure test revealed a spike (positive or negative) and the clinician looked perplexed? Too much caffeine maybe? Not enough exercise? How do you know without data?
I use a health application on my personal mobile phone which counts the number of steps taken daily, and based on my age and weight, entered as inputs, is converted into calories. I can also monitor the number of cups of tea I drink each day as well as my stress levels. When I was younger, my mother died of Cancer perhaps because we don’t have access to the same data we have access to, and knowledge to generate today.
The raw data can be streamlined to health professionals to influence decision making at my doctors appointments. Patient centred data could tie in with performance related bonuses for clinicians, who are able to utilise the data to make cost savings. In 2016, can we use patient centred data to look at the last 10,000 women who were treated for the same tumour? Yes we can. We can now see which treatment methods were used – medication, radiotherapy, chemotherapy, surgery etc – to understand which was most effective and why it was most effective.
Early adoption is crucial for success
To be successful in life you have to be an early adopter. Work with IT professionals to develop technologies and policies needed to query large databases across institutions. With each new corporate performance management implementation, momentum builds, and implementation risks are diminished.
Ideas for you to implement in the future
- Screening sheets could store questions to ask clients about symptoms – pre diagnosis.
- Store data surrounding treatment plans, medication, lab results and diagnoses against individual patients,doctors, surgeries, regions and nations.
- Hire clinicians to analyse data from lab results to correlate to databases to understand the probabilities of patients incurring exposure to genetic diseases, based upon their own genetic profile.