Dwindling are the days of printing paper charts, filing massive folders, sorting through Excel sheets, and faxing patient records to compile a person’s health story. For the Medicare population especially, healthcare technology is becoming the primary way to manage patients when they are enrolled in an Accountable Care Organization (ACO), Medicare Advantage (MA) Plan, are members of a Clinically Integrated Network (CIN), or are part of a different provider system.
The transition to shared savings programs has a twofold purpose: mitigate waste in healthcare spending while ensuring that patients receive a high level of care. The technology available today for healthcare providers is only advancing, and leveraging different means of data-sharing can improve not only savings but patient satisfaction in the care they receive. For any organization implementing population health, the following uses of technology to facilitate data-sharing within care teams can lead to upticks in quality and overall satisfaction:
- Composite patient profiles
- Artificial intelligence technology
- Advanced patient engagement
The more data an organization stores, the richer the information set to compile a patient’s history. Whether a patient is high-risk already or on the verge of becoming so, providers want to prevent an episode that leads to hospital admission. Admissions are not only expensive, but the goal in shared savings contracts is to be proactive versus reactive. Utilizing Health Level 7 (HL7) interfaces to convey Admission Discharge Transfer (ADT) data and clinical data from Health Information Exchanges (HIEs), labs, health records, and other sources to its intended location allows a secure, expedited transfer of health information. Providers have access to this information in real-time to act on, and having the entire picture within view can improve the effectiveness of treatment.
Artificial Intelligence and Machine Learning
AI and machine learning technology have made their foray into healthcare, rapidly improving the prediction of condition development and other changes by mimicking neural patterns, a specific concept called deep learning. AI uses algorithms to interpret data, even outside data like climate or weather, for example, to identify possible triggers for a person based on their existing condition(s). The level of clinical data allows AI to determine insights like undiagnosed, potentially chronic conditions, risks if the patient’s current lifestyle practices continue, and even problem-solving to decide on the best treatment options given the patient’s status. Machine learning is part of AI, and functions by applying algorithms to data and learning its different patterns. AI has expanded to different areas of healthcare, like in automating electronic health record (EHR) processes, in medical devices, and in radiology, and it is just the beginning of its capabilities.
Consistent Provider-Patient Communication
Today, providers have automated technology to engage their patients and maintain compliance at scale. Physicians, nurse practitioners, and other providers already have a substantial workload, and the prospect of making phone calls and sending emails steals time away from what they could accomplish in a day. Engagement solutions allow the provider to separate their patients into groups and send communications to them instantaneously. These messages can be appointment reminders, notices to schedule appointments, follow-ups after a procedure or hospital admission, making sure they are adhering to their care plans, and medication information.
What Do These Categories Mean to the Patient?
With advanced data-sharing and AI, the more information an engine has to predict outcomes. A patient on the brink of developing a chronic condition or winding up in the hospital is reason to intervene, and having a technological solution to automate a message not only alerts the patient, but frees up more time in their day to spend with them to address what is going on. Technology improves patient satisfaction because it works hand in hand with physicians, bringing insights to light and improving their experiences and relationships with providers.
For more information on how to improve a patient’s experience and quality while generating a return on investment, watch our webinar “How to Align Clinical Operations with Value-Based Care” with our Clinical Transformation Advisor and in-house nurse, Jessica Scruton, BSN, RN, CCM.
Tammy Ince is an Application Analyst at Lightbeam.