Technological developments in healthcare have changed the approach of looking at data. They no longer exist just to manage operations or a business seamlessly but now have also become useful to unlock a plethora of real-time health information at every step of the value chain to improve performance, care, resource utilisation, business and management of all types of diseases, outbreaks, and study them closely.
What is the status today?
Source: Analysis Based on a study by HBRAS Digital Diagnostic Transformation Webinar, April 2019
According to the Harvard Business Review Analytic Services (HBRAS)’s Global survey about data-driven diagnostics in healthcare in 2019, where most organisations believed data management across various settings is important but very few does it well. The survey that included senior healthcare leaders, and was sponsored by Roche, observed that there is a major gap between leaders and laggards in terms of adopting data-driven practices and the ability to make decisions by utilizing it.
“A lot of our digital architecture [in health care] was not designed to be interoperable.”
—William Morice, Mayo Clinic
Leaders: Hospitals and healthcare institutions visualize healthcare data to learn the increasing trends for various diseases to make decisions on vaccine distribution, medicines, and also to improvise on medical aid. Thus, data is helpful in driving decisions, predictions, and clinical outcomes for patient care across different types of care settings.
Laggards: Diagnostic industry is yet to observe a complete shift for digital adoption. Data and technology are mostly used to manage business operations smoothly, wherein business analytics is utilized more often rather than clinical analytics (like test analytics) which can be proven to derive qualitative outcomes for the industry.
“The problem is we haven’t historically trained the majority of people working in health care to have a comfort around the use of data and an ability and a desire to use it.”
—Nick de Pennington, Oxford University Hospitals
However, there is a shift. The top diagnostic leaders have now begun to use it to evaluate current methods, speed up and improve treatment, and track inventory more efficiently.
As per the highlights of the survey findings –
- 95% OF ALL RESPONDENTS SAY MANAGING CLINICAL DATA ACROSS CARE SETTINGS IS VERY IMPORTANT
- 15% OF RESPONDENTS DESCRIBE THEIR ORGANIZATION TODAY AS BEING MATURE IN ITS ABILITY TO ACCESS, INTEGRATE, AND ANALYZE HEALTHCARE DATA FROM DIVERSE SOURCES
- 19% ARE VERY SUCCESSFUL AT MANAGING CLINICAL DATA ACROSS CARE SETTINGS TODAY
While diagnostics has been the laggard from the perspective of both private and public investment in this space, COVID-19 has served as a reality check for investment in tech in diagnostics. Now that the pandemic has changed the norms of managing diagnostic operations using technology, the industry too has begun to discover the importance of healthcare analytics. It has helped in many ways to learn the changing trends of COVID-19 across specific areas repeatedly and hence, the diagnostic industry has begun to see it as a crucial tool. Know how you can improve future outcomes using the same.
The Future Potential of Analytics in Diagnostics
Analytics for diagnostics is a means for prediction to help you learn different aspects of the conducted tests. Right from knowing the changes in the count (for an illness) in real-time or over a period to learning demographic relations of diseases w.r.t. city, gender, age, etc., analytics is useful to monitor the changing healthcare status and prevent it before it’s too late.
The COVID-19 seroprevalence survey was carried out using a high-end technological system. The findings from the survey were then utilized to improve the course of treatment, setup COVID-19 centres (quarantine centres), and improve testing qualities, time & even cost. As a result, the pandemic is a testimonial of how we can leverage data-driven technological systems for improving healthcare diagnostics for the future.
How data Improves Clinical Outcomes for Diagnostics?
- Predict outbreaks or acceleration for a specific disease – Monitor real-time health data across geographies, age groups and predict outbreaks of various seasonal, common, and lifestyle and chronic diseases (based on historical data)
- Circumvent preventable illnesses
- Improves precision of time and quality of care given to patients – Looking at health trends using patients’ past health records (For example, trends report)
- Improve Operational efficiencies – Better management of medical supplies and healthcare personnel, for example, if an outbreak is predicted in some area, resources can be distributed & diverted on a larger scale there
- Manage & redesigned quantitative approach – Have more setups or systems for frequently performed or increased number tests, medical procedures, or care
- Reduce costs during seasonal outbreaks – Patients require better access to care in the monsoon season where common cold, malaria, and dengue numbers are accelerated. This is when the cost can be reduced since numbers are higher than usual
- Reach out to target patients by looking at recent data to market common health packages (general checkups, senior citizen checkup, full body checkup) or special packages (for lifestyle diseases, chronic diseases, expecting mothers, pediatric checkups)