Find out what data-driven analytics is and what its trends in healthcare are.
Today, the healthcare industry generates approximately thirty percent of the world’s data. The amount of healthcare data grows exponentially. RBC Capital Markets sets the bar at thirty-six percent for the compound annual data growth rate in the healthcare industry. Moreover, this bar is expected to be conquered by 2025. In comparison, the volume of data in other industries grows more slowly. In manufacturing, it is thirty percent. In financial services — twenty-six percent. In media and entertainment — twenty-five percent.
As an expert in HealthTech, I could name the major types of healthcare data. These are electronic health records, patient behavioral data, claims, wearable data, administrative data, and research and development data.
Imagine the situation. A healthcare organization receives a lot of complaints from patients about long wait times to see an ear, nose, and throat (ENT) specialist. The provider collects info about the clinic’s «peak hours». It turns out that the heaviest influx of patients occurs between five p.m. and seven p.m. How can the healthcare organization use this data? There are several options. For example, they can hire an additional ENT specialist for the busiest time. Another option is to offer a different appointment time to patients who want to see the doctor between five p.m. and seven p.m. The key steps to make data-driven decisions in this situation are to collect and analyze info.
What Is Data-Driven Analytics?
It uses data to make strategic decisions based on it. A healthcare organization that uses a data-driven approach operates with the help of complex data analysis tools and reliable facts.
I closely study the business strategies of the healthcare industry and have noticed that today many healthcare organizations value the data-driven approach as an important measure. A provider can use this approach to make effective clinical decisions faster, prescribe the right treatment, and establish smooth hospital workflows.
In early 2023, a team of analysts from the Harvard Business Review surveyed more than seven hundred representatives of the healthcare industry or an industry that is somehow related to healthcare. According to the survey, ninety-four percent of participants agree that data-driven healthcare creates new opportunities for clinicians and patients. It allows them to benefit from more personalized approaches to healthcare.
What Are the Trends in Analytics-Driven Healthcare?
Predictive Analytics
Until recently, business intelligence (BI) was synonymous with dashboards and statistical reports. It offered vendors and providers historical insights into metrics that were recorded in the past. Such tools are valuable, but real-time decision-making requires new capabilities from data analytics.
Next-generation BI goes beyond simple reports to deliver actionable, dynamic insights in real time. Artificial intelligence (AI) and machine learning (ML) tools enable companies that have adopted next-generation healthcare business intelligence to identify opportunities and anticipate trends. These companies use predictive and prescriptive analytics tools to help them extract meaningful insights from diverse and complex data sets.
First, analytics tools help identify the reasons why an event occurred. For example, they analyze the genetic data of an individual patient or a focus group and can infer why the «owners» of this genetic data became ill. Then, analytics can make a prediction based on human genetics about whether a patient will develop a certain disease. For this purpose, researchers use Next Generation Sequencing (NGS) based on Python. Unlike traditional sequencing, where only one fragment of DNA is tested, NGS testing analyzes millions of DNA fragments. Algorithms look for genetic mutations that a person has inherited. If these mutations are present and are predicted to trigger a disease, the provider can use the analytics reports as a basis for early intervention and prevention.
By the way, a healthcare technology company may not look for a Python programmer to complement its engineering team. It can outsource Python development projects. This strategy helps the company reduce administrative costs.
Personalized Patient Care
With data-driven analytics, healthcare companies can offer personalized care to patients. CVS Health is the world’s 2nd largest medical organization. It has proposed many initiatives which aim to improve the personalized customer strategy. For example, CVS Health has begun to deliver prescription drugs to patients’ homes much more often. It has also invested in platforms based on Microsoft Azure Databricks. These platforms track how likely patients are to buy a certain drug or remind them to pick up their medication. Leveraging solutions like Databrick ETL can streamline the integration and transformation of complex healthcare data, ensuring that actionable insights are delivered effectively.
Insurance companies offer another option for personalized care. This point applies not only to an individual approach to medical care but also to healthcare insurance. For example, data analytics allows insurance companies to select a plan for the needs of each patient. The insurer doesn’t wait for the patient to understand the complex and varied insurance plans. They study analytics reports that show that the patient has chosen a plan with low coverage but uses it very often. The insurer can offer the patient a comprehensive insurance plan more likely to meet the client’s needs.
Telemedicine (Not Confuse with Telehealth)
First, let me briefly explain the terms. Telehealth is not a synonym for telemedicine. This term is more general and includes all remote clinical (telemedicine) and non-clinical services (virtual providers’ meetings, tele-education of providers, etc.). Telemedicine includes processes and technologies that enable providers to treat patients remotely.
Telemedicine took off in the spring of 2020 during the coronavirus pandemic. That’s when the US Congress rolled back many telemedicine regulations because people needed remote medical care.
Today, telemedicine uses digital communication technologies such as mobile apps, video conferencing, and remote access devices to connect patients with providers at their convenience from any location. Children’s National Hospital has integrated telemedicine solutions into its services. It has used phone, video, and text messages for a variety of medical needs (e.g., for patients with immunology and endocrinology diagnoses).
According to the Mott Poll Report, ninety-two percent of parents whose children received telemedicine care were satisfied with the experience and had their questions answered.
A data-driven approach to telemedicine allows the analytics software to collect patient data, claims data, and the types of care provided. Analytics tools are useful to find out what major diagnoses doctors give their patients during these video calls. For example, during the coronavirus pandemic, an analysis of the use of telemedicine was conducted. It turns out that telemedicine was used more often to treat behavioral health conditions than common physical ailments during this period. Online visit rates remained consistently high even as the pandemic subsided. The study shows that telemedicine visits to improve behavioral health are in demand by patients and providers. It could provide an incentive to include this service in the benefit packages that employers offer their employees.
To End Off
Although healthcare organizations are more data-driven now, only sixteen percent consider their position mature. They use analytics tools to acquire and analyze information from multiple sources and make decisions quickly. This process is still full of difficulties and white spots for other healthcare vendors. With twenty years of experience in the HealthTech industry, I’m sure custom software with advanced business analytics tools and methods is a great solution. It helps healthcare companies use all the possibilities of modern forecasting and make data-driven decisions.
About the author:
Dmitry Baraishuk is a partner and Chief Innovation Officer at the software development company Belitsoft (a Noventiq company) with 20 years of expertise in digital healthcare, custom e-learning software development, and Business Intelligence (BI) implementation.
