Healthcare practices and providers have access to more data today than ever before. Real-time data housed in electronic health records (EHRs) and software with robust reporting capabilities has changed how we approach patient care in numerous ways, from helping identify vulnerable, high-risk individuals, to operating more efficiently and proactive population health management.
Additionally, patients are becoming more willing to share their personal health data with providers. Interest in patient data sharing rose from 71 to 73 percent in the COVID-19 era, spotlighting a shift in attitudes regarding privacy concerns. According to a report by Deloitte, healthcare consumers are becoming increasingly active and engaged in their care, with more and more accessing medical data and using it to guide decision-making.
Patients’ willingness to share healthcare data—not to mention the sheer abundance of it that’s available today—can help providers be more proactive in health management. Ultimately, with the right strategy (and the technology to support it), your practice can use data to improve patient outcomes and deliver the best care possible.
Leveraging Data to Guide Clinical Decision-Making
Real-time data (collected from real-world sources) plays an important role in quality improvement, enabling practices and providers to recommend evidence-based treatment plans rather than taking a shot in the dark, so to speak. Making decisions supported by real patient data can have a significant impact on both your quality of care and subsequent outcomes.
Your practice can (and should) leverage health data to guide clinical decision-making and improve patient outcomes. By making smart use of aggregated real-world data and patient-reported insights, you can gain a better idea of patient needs, as well as the staffing, supplies, and resources you need in place to consistently deliver quality care.
Making Predictions to Deliver More Timely Treatments
A high percentage of the factors that impact health outcomes—or what we refer to as the social determinants of health (SDOH)—are technically unrelated to traditional healthcare. Predictive analytics can help identify patients who have a higher risk of developing a chronic disease based on a number of different factors, such as medical history, health habits and behaviors, socio-economics, demographics, and comorbidities.
Throughout the COVID-19 pandemic, data has proven even more useful than it already was. Healthcare leaders have relied on real-time data to predict who’s at risk of progressing towards a more severe version of the virus, ultimately enabling them to act quickly and adequately.
Practices can leverage the power of predictive analytics paired with real-time data to arrange for early intervention in higher-risk patients, before problems develop that could have been avoided. Proactive population health management ultimately results in better, more targeted care delivered to the right patients, in the right way, at the right time.
Reducing Medical Errors to Improve Patient Safety
Data is just as beneficial for reducing medical errors as it is for delivering timely, top-quality care. Patient safety has long remained a concern in the healthcare industry, with adverse and preventable events making medical error the third leading cause of death in the U.S., before the pandemic occurred.
Providers can review data on a number of safety-related concerns, ranging from hospital-acquired infections and incorrect diagnosis or treatment, to emergency department visits and readmissions. Tracking these adverse events and acting accordingly can help improve patient safety, outcomes, and care quality all at once.
Using Connected Medical Devices for Patient Care
Wearables, digital therapeutics, smart pill bottles, and home health monitors are just a few examples of the connected devices that make up the Internet of Things (IoT). As an increasing number of medical devices become connected to the internet, more and more healthcare practices are exploring and embracing them as a way of monitoring patients virtually and between office visits.
These devices generate enormous amounts of clinical data, making them an integral component in healthcare today. As artificial intelligence (AI) and machine learning continue to advance, it’s likely more practices will begin embracing connected devices to deliver quality, data-driven patient care.
These are just a few of countless examples of how health data can be used to drive quality improvements and better patient outcomes. Looking ahead, we’ll only continue seeing real-world examples of how powerful clinical data can be when it’s harnessed in the right ways. Is your practice ready?