In the year 1955, the computer scientist ‘John McCarthy’ coined the term ‘Artificial Intelligence’. From 1955 to 2005 computer scientist mostly used ‘Artificial Intelligence’ for research purpose. Additionally, they also checked if AI could be implemented across different industries.
In the year 2011, Apple introduced ‘Siri’ into the market and quickly the whole world started thinking about AI to solve the day-to-day activities. The recent example of this is ‘Google Duplex’, which can help to book an appointment by using AI and Machine learning technologies.
Similar to other industries, many companies in the healthcare market are investing a lot on AI and Machine Learning to enhance the quality of care, operations and engagement. Many healthcare IT companies are investing a lot in tech space for getting more data insights, enhance the virtual care and move patient’s risk zone from ‘At Risk’ to ‘Healthy’. For Healthcare community enhancing patient engagement has become the topmost priority. Artificial intelligence can certainly play an important role in achieving those outcomes.
Why AI is required in Patient Engagement
As healthcare industry is moving from FFS (fee For Service) to value-based system, the patient should be aligned to the centre position to get a better quality of service at minimum healthcare cost. To achieve this alignment, patient engagement tool is vital, which helps patients, providers and payers. In last 8 to 10 years, we have observed remarkable progress in patient engagement technology, which has been helpful to solve multiple challenges like access to patients about their patient info, web/ mobile based scheduling, communication with caregivers and many more. On the other hand, patient engagement still faces many challenges that need to be addressed. Some of the challenges are below:
- More patient information to capture (habits, behaviour trend, emotional quotient, etc.)
- Capture patient info before appointment though HRA (Health Risk Assessment)
- Not having personalized healthcare education
- Not having personalized care plan and tracking of the care plan
Current patient engagement processes are allowing patient to participate in care delivery. But this participation is only restricted when system/app informs them to participate (feed the questionnaire, upload reports etc.). Moreover, the patient should participate more ‘Pro-Actively’ in care delivery process. In an ideal scenario, patient should participate in care delivery process in form of suggestions, sharing their thoughts/emotions/ feelings/symptoms, feedback about physicians, etc.
Patient Engagement: Access-> participation-> Pro-Active participation
For last 5-6 years, the penetration of web and mobile patient portals has increased at the moderate pace. However, the patient data these systems are generating is humongous and we are not utilizing it for ‘Pro-Active Patient participation’. Let us look at how patient engagement has evolved over a period of time, and how is going to look like in the near future.
Tomorrow’s Patient Engagement
While implementing ‘Pro-Active patient Participation’, technologies like AI and ML will be used for data aggregation, data analysis and extracting deeper insights.
Most of the providers have started online appointment scheduling for their patients. In upcoming months, we can use AI and ML to automate the scheduling part, which could be helpful to reduce the admin cost of providers. At the time of scheduling, one can extract detailed patient information through personalized health risk assessment by using AI technologies. In the current patient world, nearly 74% patients forget their care plan after leaving doctor’s appointment. To reduce the percentages health systems should suggest personalize care plan to physicians based on aggregated data from multiple data sources.
Technology acts as a bridge between caregivers and patients to connect patients at the personal level and improve their health. ‘Pro-active patient engagement’ is the way forward to achieve the goal. It is quite evident how advanced technologies are helpful for building powerful patient engagement solutions.
In the future, during care plan tracking, personalized AI based patient education will be the key to boost ‘Pro-Active patient Participation’. These advance patient engagement activities will be helpful for better ‘Patient – Physician’ relationship.
Now that it is established that AI and ML will be a win-win for every healthcare entity, when are you planning to implement AI-ML techniques to enhance your quality of care? If you would like to find out more, feel free to write to us at email@example.com/
Works at Nitor’s Healthcare Practice. Has expertise in requirement gathering, requirement elicitation, and acts as a bridge between offshore team and customer, business process optimization.
- Big Data