Healthcare organizations are turning to predictive analytics as it helps them in solving difficult problems and discover new opportunities. By leveraging IT and effective communication tools, Healthcare analytics, which is a part of the digital healthcare system renders enhanced health management services. Though Healthcare analytics is at a nascent stage in India, it has the potential to bridge the gap between the lack of availability of clinicians and the limited capacity of clinics to serve patients. This is achieved with the help of AI and Big data analytics.
Intending to enhance patient outcomes, Healthcare analytics assists healthcare practitioners with the use of medical knowledge. This medical knowledge is being memorized and analyzed by computer-enabled robotic systems, which helps in providing an effective medical solution. Healthcare Analytics encompasses mainly 3 types of analytics solutions, such as descriptive, predictive, and prescriptive analytics and the major end-users of these solutions are the Healthcare practitioners, healthcare providers, the government, and pharmaceutical enterprises.
Today let us look at how useful is Predictive analytics in the healthcare industry.
Predictive analytics applied in the healthcare industry facilitates in detecting early signs of patient deterioration in the Intensive Care Unit and general wards. Furthermore, Predictive analytics also helps identify at-risk patients in their homes to not only prevent hospital readmissions but also prevent avoidable downtime of medical equipment.
Medicine is mostly about anticipating and reducing risk based on current and historical patient data. Some examples of this include the following as how likely is a cancer patient to suffer complications if he/she undergoes surgery? What is the chance that a pneumonia patient will be readmitted to the intensive care unit within 48 hours if she/he is discharged? etc.
While Clinicians always had to make decisions without absolute certainty. However, with the advance of predictive analytics in the healthcare industry, these decisions promise to be better informed than ever.
Supporting clinical decision making for individual patients
Predictive analytics intends to alert clinicians and caregivers of the likelihood of events and outcomes before they occur. And this would help them to prevent as much as cure health issues. To make meaningful predictions, the industry is driven by the rise of Artificial Intelligence and the Internet of Things, there are algorithms made available today, which can be fed with historical as well as real-time data and such predictive algorithms cannot only be used in supporting clinical decision making for individual patients but also to inform interventions on a cohort or population level. Moreover, these can also be applied to hospitals’ operational and administrative challenges as well.
As per one of the surveys conducted in 2019 survey by the Society of Actuaries, it was found that 60 percent of the health care executives have adopted predictive analytics in their organizations. They adopted it after recognizing the merits of predictive analytics. And out of which, 42 percent of these healthcare executives stated that they have observed improved patient satisfaction after implementing predictive analytics.
How healthcare organizations are turning their data into forward-looking insights, intending to support better patient care
An instance of predictive analytics in healthcare in use today
- Detecting early signs of patient deterioration
Predictive insights can be specifically valuable in the Intensive Care Units, where a patient’s life may be saved owing to timely intervention, especially when their condition is about to deteriorate. In most countries such as the United States, ICUs were already overstrained even before the COVID-19 pandemic owing to aging populations, a rise in the use of complex surgical procedures, and a shortage of ICU specialists. Since the outbreak of the coronavirus, there is a huge increase in the number of patients requiring acute care in the Intensive Care units, which further fueled the need for technology to help caregivers in rapid decision-making.
As the important/vital signs of patients are continuously being monitored and analyzed, predictive algorithms help in mainly identifying patients with the highest probability of requiring intervention within the next one hour, which is highly imperative, today and this lets caregivers intervene at an early stage, proactively, owing to the observations made based on subtle signs of deterioration in the patients’ condition. Likewise, predictive analytics can also help in estimating the probability that patients risk death and readmission within 2 days if the patient was discharged from the Intensive Care Unit. And, therefore, this facilitates the caregiver to decide on which patients can be discharged and which ones cannot be discharged.
Such predictive algorithms are now being deployed in tele-ICU settings as well. Here the patients are being monitored remotely by intensivists and critical care nurses are in regular contact with bedside clinical teams.
Besides, predictive analytics can also help in spotting early warning signs of adverse events, where deterioration of patients often goes unnoticed for prolonged periods like in general wards. What the Automated early warning scoring does is that it lets the caregivers trigger an appropriate and early response from Rapid Response Teams, at the point of care. As and as a result of following this particular approach, one of the hospitals reported a decrease in adverse events by 35 percent.
Impact of cloud and data analytics on India’s healthcare sector
Talking about the impact of cloud and data analytics on India’s healthcare sector, Vimal Venkatram, Country Manager, India, Snowflake, in one of his interviews to Express Healthcare stated that, “The healthcare industry generates vast amounts of data. To leverage the power of data, India’s healthcare sector is gearing up for digitalization. With the help of cloud technologies and data analytics, the potentials to improve overall patient care and collaboration and research are immense.”
“Migrating to cloud platforms offers the flexibility and storage capacity needed to house such large volumes of data and enable healthcare organizations to derive insights that positively impact patient care and hospital operations.”
“Also, with access to real-time information, healthcare professionals and executives are empowered to make informed decisions that improve overall care. By analyzing data sets, healthcare professionals and researchers will be able to recommend steps to create disease-control strategies,” he adds.
According to a recent report by Research and Markets, the healthcare analytics market in India is anticipated to reach INR 47.04 billion by 2025. Factors such as the growing focus on collection and analysis of data from various healthcare sources for improved customer service and technological advancements and growing adoptions of EHRs are responsible for the growth of this market in India.
“Data security is critical when handling Personally identifiable information (PII) and patients’ records. Healthcare institutions and medical professionals should have clearly defined policies and procedures in handling, storing, and sharing patient data. Moreover, records should be kept in a secure and reliable environment where data can be easily and safely accessed by authorized users,” explains Vimal Venkatram.
According to reports, it is predicted that in India, close to 4300 people die daily owing to poor diagnosis and inaccurate treatment of the diseases. Therefore, Healthcare analytics is anticipated to reduce this patient death rate by implementing more and more advanced tools for diagnosis and planning out proper treatment procedures.
