Real-time data (or just in time information) to the end-user can provide enormous value to improving patient care, clinician time, workflow solutions and reducing healthcare costs. All healthcare organizations need robust electronic health record (EHR) systems for all clinical data in order to provide a complete picture of the patient’s condition and predict patient outcomes.
Improving healthcare information systems with real-time data is transforming the healthcare of tomorrow. An advanced degree in health informatics can equip healthcare professionals with the necessary knowledge in health information systems to excel.
What Is Real-Time Data in Healthcare?
Real-time data can refer to various tools to collect, store, share and analyze health data as quickly as possible to provide information to the user. These tools might include:
- Electronic health record (EHR)
- Electronic prescription services (E-prescribing)
- Patient portals
- Artificial intelligence monitoring
- Master patient index (MPI) or Master client index (MCI)
- Virtual health
- Health-related smartphone apps
EHRs both contain and compute information. Predictive analytics uses historical and real-time data to forecast future events. For example, healthcare analytics prevent a patient’s readmission, gauge their risk for chronic conditions or suicide and predict missed appointments or non-compliance.
What Are Some of the Benefits of Real-Time Data?
Real-time data in healthcare can help predict patient outcomes and save the cost of medical treatment. There are many pros of health informatics for healthcare organizations, including the following:
- Care coordination. Integrated systems not only communicate across departments but also interface with other care facilities to provide seamless, coordinated care. Shared intelligence helps eliminate delays in care, repeat tests and medication errors, reducing costs.
- Safety. Data analytics help manage drug therapy in real time to identify possible side effects, drug interactions and toxicities, as well as reduce overall costs. Orders go directly into the HER that communicates with the pharmacy. ATM-like machines dispense drugs following rigorous safety checks. Nurses scan the patient’s armband and medication for a match and documentation, while data monitoring flags any problems.
- Saving lives. Artificial intelligence (AI) and predictive analytics can identify high-risk patients for certain complications and extract meaningful data for effective decision-making processes. For example, HCA Healthcare uses S-P-O-T (Sepsis Prediction and Optimization of Therapy) AI to quickly identify sepsis by using clinical data points to alert clinicians for early intervention.
- Managing costs. Healthcare organizations rely on real-time data to improve productivity and control costs. For example, real-time documentation can save hours of charting at the end of a nurse’s 12-hour shift and reduce overtime costs as a result. Knowing which patients might miss appointments can reduce lost income and staffing costs. In addition, real-time data maximize reimbursements models while minimizing insurance fraud.
What Are Some of the Current Challenges?
Many challenges relate to fragmented data and consumer expectations with overarching concerns regarding privacy and cybersecurity. Below are three major challenges facing real-time data systems:
- System integration. Instead of one master system throughout the United States, each organization can choose its system and tailor it to its needs. With over a dozen EHR systems that do not necessarily “talk to each other” or interface, patients and clinicians suffer the consequences. Patients are frustrated at having to repeat their medical history, carry lab reports or scans on a CD-ROM or coordinate their own care. Clinicians practicing at different facilities must learn the various nuances of that EHR. Providing a seamless digital exchange of information is critical to improving care and minimizing costs.
- EHR burnout. The EHR was designed mainly for billing and coding compliance with screens focusing on content that improves financial coverage to control costs instead of improving patient care. Many physicians and nurses report feelings of frustration with the busy work of documentation. Studies now suggest that EHR fatigue contributes to stress and burnout. User-friendliness is a critical concern, especially given the severe nursing and physician shortage. Several organizations have a call to action for improvements in reducing documentation and administrative burden for clinicians.
- Real interaction. Computers improve our lives but can also limit our interactions. Particularly in the outpatient setting, many providers focus on the computer screen instead of the patient-provider human interaction. This situation creates providers who are out of touch with the reason they went into healthcare and dissatisfied patients who suffer from a lack of human connection. Tomorrow’s real-time data will need to create optimization strategies solutions that re-focus on what matters most: the relationship between the patient and their care team member.
Healthcare is a business with many stakeholders — patients, payers and healthcare professionals. More than ever before, these participants rely on data to make healthcare decisions. All expect continuous access to each other. Real-time data is quickly adding value to healthcare organizations’ ability to meet consumer demands. Continuously improving real-time data performance is critical to providing the best care at the right cost.
Be part of the solution by learning the science, system and software behind the emerging technologies for real-time data.