The healthcare sector has been at the forefront of adopting advanced analytics into their daily operations. Healthcare analytics covers a huge swath of the industry, offering insights on both the micro and the macro level.
Healthcare analytics across the financial, operations and clinical areas is expected to touch $29 billion by 2025. As the trend continues to mature across application areas, we examine how it increases the scope for digital service providers to tap in this evergreen market.
Healthcare Financial Management
Given the heavily subsidized nature of healthcare in most countries, healthcare enterprises are actively exploring the full capabilities of today’s analytics solutions to meet the demands of the future. Most of the successful enterprises operating in this sector have managed to monetize their data assets with analytics to extract actionable insights. These insights are also playing an important role in decision-making by clinical analysts.
Financial big data analytics tools used for revenue cycle management, fraud detections, risk adjustment, and claims processing are increasingly finding using among healthcare providers. Fraud and risk management using cognitive analytics and AI will be a huge part of the $10 billion analytics market by 2022.
A report by an industry observer notes that service providers who can inform stakeholders about the performance of quality metrics and financial benchmarks are looking at a $1.15 billion market size waiting to be seized immediately.
However, newcomers into this segment are placing all their bets on even more advanced analytics that leverage machine learning. By 2025, the Machine learning-as-a-service category is expected to drum up business to the tune of $5.5 billion.
As the maturity of AI and advanced analytics tools increases, even more healthcare providers will incorporate these into their infrastructure.
Supporting Clinical Analysts With Advanced Analytics
Healthcare IT is now moving from the realm of descriptive analytics towards predictive insights. Predictive analytics estimate the propensity for future medical conditions based on a patient’s historical data. This allows clinicians to be better prepared.
The hospital bed shortage triggered by the COVID-19 pandemic was predicted well-ahead thanks to predictive modelling techniques.
Healthtech firms like Iquity are using predictive analytics performed on data harvested by wearable technologies to predict the onset of dangerous conditions like multiple sclerosis. Machine learning tools combined with the patient health record data is being used to identify patients on track for septic shock 12 hours before the onset of the condition by researchers at the University of Pennsylvania.
Another area that is seeing widespread use is the realm of personalized healthcare. NLP models like Amazon Comprehend Medical are deployed on medical notes to understand better and strategize a patient’s treatment plan.
Our article on Deep Medicine dives deep into the role of healthcare analytics in clinical diagnosis and how it’s changing the face of the doctor-patient relationship.
Analytics also provides insights on individual behavioral patterns, response to medication etc. thus helping clinicians plan better treatment for their patients in the case of lifestyle diseases like diabetes and hypertension.
Analytics in Day-to-Day Healthcare Operations
Healthcare is an operationally complex behemoth that is almost always operating at full capacity. Investing in new infrastructure often takes a backseat. This means that they must optimize their assets in place.
To become more cost-effective and streamlined, stakeholders need to make optimal operational decisions consistently. These days, analytics is helping massively in this regard.
Offerings like TCS Public Healthcare Solutions leverage the latest in modern tech to enable governments to scale up their healthcare offerings at an affordable cost.
Scaling-up or upgrading involves:
- Automating large hospitals
- Integrating advanced AI/ML-based analytics with existing infrastructure
- Proactively monitor health service quality
- Improve resource and asset utilization
Health care providers lean on service providers for data warehousing, cloud migration/administration, database management, AI/ML-implementation, etc., that makes up a significant portion of healthcare analytics software domain. These solutions are vital to maintain the health of their organization, comply with changing industry guidelines, and optimize both population health and individual patient management.
Major players in the healthcare operations ecosystem include IBM, Vizient Inc, Cerner, and Oracle.
The adoption rate of new-age techs like AI, ML, Analytics in Service operations (45%), Supply chain management (22%) and product development (28%) is rising fast.
This has opened the doors for digital service providers to partner with the healthcare sector and deliver cost-effective, life-saving solutions.
Draup’s account intelligence and real-time sales signals tracking delivers actionable insights based on movements in the healthcare market. Service providers can leverage the industry-specific information to curate their offerings and finetune their bidding proposals. Armed with the right location and industry intelligence data for the healthcare market, Draup empowers service providers with the right toolset to confidently make inroads into untapped markets.
