Transforming MedTech with Data Intelligence

Transforming MedTech with Data Intelligence

Over the past couple of years, the rapid implementation of digital transformation initiatives and advances in digital technologies have taken the entire MedTech industry by storm. This new era of healthcare is based on technology as a key enabler. Digital technologies have advanced to such an extent that huge volumes of data, like patient information, can be analyzed in a flash, utilized to derive patterns, and used to suggest methods for efficiently planning, managing, and addressing a specific business challenge and resulting in significant cost savings. In fact, the McKinsey Global Institute estimates the cost saved could be anywhere between $1.5 trillion and $3 trillion a year by 2030.

The power of technology coupled with innovation can tackle and assist in solving problems in both business and healthcare. Data science in MedTech is a valuable intelligence asset that not only helps improve quality of life, forecast pandemics, and reduce treatment costs but also assists in tailoring healthcare to the specific requirements of each individual. Here are a few scenarios where this technology is helping decision-makers, providers, caregivers, and patients in the real world:

Enhancing diagnosis and treatment

Electronic medical records, or EHRs, are the most prevalent medical application of data. Each individual has a computerized record containing demographic information, medical history, allergies, laboratory test results, and other data. EHRs make medical history readily accessible, thus promoting quicker, more precise, and better-informed treatments.

Improving patient engagement

Smart devices such as fitness bands, ECG monitors, and spirometers continuously monitor the steps, heart rates, and sleeping patterns of individuals. Combining this critical information with other trackable data points can generate actionable insights that indicate trends to avoid a certain health problem much more quickly, thereby reducing possible expenses and delays.

Aiding in effective strategic planning

Utilizing data intelligence in MedTech enables providers to exercise strategic planning with a deeper understanding of patients’ motivations. Care managers can examine check-up data from various demographic groups to determine what factors discourage individuals from seeking care, enabling them to take preventative action.

For instance, if a provider wants to optimize the way they provide their services to patients, they will need to define certain KPIs to achieve the desired optimization. As a result of advances in the Internet of Things (IoT), tracking and measurement may now be carried out without the need for physical presence. The obtained data can then be structured and analyzed to measure KPIs and ensure alignment.

Integrating with medical imaging

Every healthcare organization conducts multiple imaging screenings every year, but manually processing and archiving these images is expensive and time-consuming. Leveraging data analytics alters how images are interpreted – algorithms are developed by analyzing hundreds of images, discovering specific pixel patterns, and converting them into numbers to aid in diagnosis.

Predictive Analytics and Alerts

Meaningful predictions derived from historic and real-time patient data can be leveraged for prognosis, designing treatment courses, clinical decision support, designing remote monitoring, and fraud detection. Predictive analytics also helps in better patient engagement,  satisfaction, efficient resource planning, and supply chain management.

Predictive analytics also aims at notifying and alerting providers and care partners about the likelihood of events before the occurrence, providing the opportunity to take corrective action.

Due to the versatility and maturity of data science, healthcare stakeholders can now focus on the “what” rather than the “how” to achieve their goals. It allows them to simultaneously collect and analyze structured and unstructured data. For instance, in oncology, using cutting-edge technologies like AI/ML on data helps reduce the time between diagnosis and treatment, which is crucial to patient outcomes.

Data analytics in MedTech is positioned to deliver significant efficiencies to all the stakeholders in the chain – from business managers, healthcare providers, insurance providers, caregivers, and hospitals to the patients. The impressive integration of structured and unstructured data is the significant differentiator that enables sound decision-making and better predictability of a business or healthcare.

Zimetrics is a data technology company that has helped multiple MedTech companies leverage data assets, gain profound insights, and scale rapidly. Talk to our experts to learn more about how we can help you embark on a data-driven journey for your business.


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January 25, 2024