Find out what data-driven analytics is and what its trends are in healthcare.
Currently, the healthcare industry generates approximately 30% of the world’s data. The amount of healthcare data is growing exponentially. RBC Capital Markets has set a benchmark for the healthcare industry’s compound annual data growth rate of 36%. Moreover, this benchmark is expected to be reached by 2025. In comparison, other industries are seeing slower data volume growth: 30% for manufacturing, 26% for financial services, and 25% for media and entertainment.
As a health tech professional, I can list the main types of healthcare data: Electronic Health Records, Patient Behavior Data, Claims, Wearable Data, Administrative Data, and R&D Data.
Imagine this scenario: A healthcare organization is receiving a lot of complaints from patients about long wait times to see an ENT specialist. The organization collects information about the “peak hours” of the clinic. It finds that the highest influx of patients occurs between 5 PM and 7 PM. How can the organization use this data? There are several options. For example, the organization could hire additional ENT specialists for the busiest hours. Another option could be to offer alternative appointment times to patients who want to be seen between 5 PM and 7 PM. A key step in making data-driven decisions in situations like this is to collect and analyze information.
What is Data-Driven Analytics?
Use data to make strategic decisions. Healthcare organizations that take a data-driven approach operate with complex data analysis tools and trusted facts.
I have been closely studying the business strategies of the healthcare industry and have noticed that many healthcare organizations today are focusing on a data-driven approach as a key measure, which can help healthcare providers make effective clinical decisions faster, prescribe appropriate treatments, and establish smooth hospital workflows.
In early 2023, a team of analysts at Harvard Business Review surveyed more than 700 representatives from the healthcare industry or industries somehow related to healthcare. According to the survey, 94% of participants agreed that data-driven medicine opens new opportunities for clinicians and patients, who can benefit from a more personalized approach to healthcare.
What are the trends in analytics-driven healthcare?
Predictive analytics
Until recently, business intelligence (BI) was synonymous with dashboards and statistical reports. BI provided vendors and providers with historical information on metrics recorded in the past. While such tools are valuable, real-time decision making requires new capabilities from data analytics.
Next-gen BI goes beyond simple reports to deliver actionable, dynamic insights in real time. Artificial intelligence (AI) and machine learning (ML) tools enable organizations with next-gen healthcare business intelligence to identify opportunities and forecast trends. They are using predictive and prescriptive analytics tools to extract meaningful insights from diverse and complex data sets.
First, analytical tools help determine why an event occurred. For example, genetic data of individual patients or focus groups can be analyzed to infer why the “owners” of this genetic data became ill. Second, the analysis can predict whether a patient will develop a certain disease, based on human genetics. For this purpose, researchers use Python-based next-generation sequencing (NGS). Unlike traditional sequencing, which tests only one fragment of DNA, NGS tests analyze millions of DNA fragments. Algorithms look for genetic mutations that a person inherited. If these mutations are present and predicted to cause disease, providers can use the analytical report as a basis for early intervention and prevention.
By the way, healthcare technology companies don’t need to look for Python programmers to complement their engineering teams. They can outsource their Python development projects. This strategy allows companies to reduce management costs.
Tailored care
Data-driven analytics enable healthcare companies to provide personalized care to patients. CVS Health is the second largest healthcare organization in the world. It has proposed many initiatives aimed at improving its personalized customer strategy. For example, CVS Health has significantly increased the frequency of delivering prescription drugs to patients’ homes. It has also invested in platforms based on Microsoft Azure Databricks. These platforms track the likelihood of patients purchasing certain drugs and remind patients to pick up their drugs.
Insurance companies offer another option for personalized care. This point applies not only to individualized approaches to medicine, but also to health insurance. For example, data analytics allows insurance companies to select plans that fit the needs of each patient. Insurance companies do not wait for patients to understand complex and diverse insurance plans. Insurance companies study analytical reports that show that patients have chosen plans with low coverage but use them frequently. Insurance companies can offer patients comprehensive insurance plans that are more likely to meet their client’s needs.
Telehealth (not to be confused with telemedicine)
First, a quick word on terminology: Telehealth is not a synonym for telehealth. The term is more general and includes all remote clinical (telehealth) and non-clinical services (virtual provider meetings, distance education for providers, etc.). Telehealth includes the processes and technologies that allow providers to treat patients remotely.
Telehealth took off during the coronavirus pandemic in the spring of 2020. At the time, people needed telehealth so much that the U.S. Congress lifted many of the regulations regarding it.
Today, telehealth uses digital communications technologies like mobile apps, video conferencing, and remote access devices to connect patients and healthcare providers from wherever the patient is most comfortable. Children’s National Hospital has integrated telehealth solutions into its services, using phone, video, and text messaging to address a variety of healthcare needs (such as patients with immunology and endocrinology diagnoses).
The Mott Poll report found that 92% of parents whose children received telehealth care were satisfied with the experience and had their questions answered.
A data-driven approach to telehealth allows analytics software to collect patient data, billing data, and the type of care provided. Analytics tools can help examine what primary diagnoses doctors give patients during these video calls. For example, an analysis was conducted on the use of telehealth during the coronavirus pandemic. It was found that during this period, telehealth was used more frequently to treat behavioral health conditions than common physical illnesses. Even after the pandemic subsided, online visit rates remained consistently high. The survey indicates that telehealth visits to improve behavioral health are in demand by patients and healthcare providers. This may provide an incentive for employers to include this service in the benefits packages they offer to their employees.
lastly
Healthcare organizations are now becoming more data-driven, but only 16% consider their position to be mature. These organizations use analytical tools to obtain and analyze information from multiple sources to make decisions quickly. This process is still full of difficulties and shortcomings for other healthcare vendors. With 20 years of experience in the HealthTech industry, I am convinced that custom software with advanced business analytics tools and methods is a better solution. This software helps healthcare companies leverage all the latest predictive possibilities and make data-driven decisions.
About the author:
Dmitry Baraishuk is Partner and Chief Innovation Officer at software development company Belitsoft (a subsidiary of Noventiq) and has 20 years of experience in digital healthcare, custom e-learning software development, and business intelligence (BI) implementation.
