The clinician-patient encounter is the crucial interaction in care delivery. However, current clinical technologies, in the form of electronic health record (EHR) screens and claims processes can create friction between physicians and patients. The current clinical environment and supporting technology infrastructure is exposing physicians to stress and burnout, while patients feel like mere objects to be processed as quickly and efficiently as possible.
The cure for bad technology can be better technology — if it focuses on the relationship between clinician and patient. While patients are generating increasing amounts of data, care teams can improve care and reclaim their patient relationships with the support of advanced technologies. Artificial intelligence (AI), intelligent information filtering and voice recognition all serve to make the trove of patient generated data intelligible and useful, leading to better patient outcomes. The race is on to better connect patients and providers with data that can elevate the wellbeing of us all.
While technology has overpromised in the past, the next generation of intelligent assistants is poised to remove the burden of administration from physicians. At the same time, these assistants are giving them increased power to find and apply available knowledge and, concurrently, help patients understand and manage their health.
Information management for the busy clinician
The healthcare industry generates 30% of the world’s data volume, and its rate of growth will only increase. Methods for managing and integrating those data flows will need to dramatically improve.
Patient data is already contained in systems of record that include medical histories, lab results, clinical images and outcomes, as well as recorded health habits and shared personal circumstances. The addition of genomic and other data will enable the development and delivery of targeted treatments based on a patient’s specific physiology and disease state.
Increasingly, data is generated from connected sensors, whether wearable, implanted, or in the patient’s therapeutic equipment that generate real-time and real-world data. The clinician can have a contextual, longitudinal and real-time view of a patient’s vital signs, including heart rate, blood pressure, blood sugar and sleep patterns.
Additional data from research and population data in the form of clinical practice guidelines, randomized clinical trials (RCTs), journal articles and real-world data (RWD) further enhance individualized understanding. However, the volume of data generated from patients and clinical activities can easily overwhelm the most dedicated clinician. Natural language processing (NLP) and other methods will extract essential clinical insights converting those insights into real-world evidence, which in turn enhances clinical decision-support tools powered by NLP and AI.
Understanding workflows
Information from connected sensors supports clinical workflows at every point. Sensors at the bedside and in the bed aid in identifying at-risk patients, by monitoring vital signs and detecting the early signs of an upcoming problem.
The need to enter encounter data into EHRs is a time-consuming workflow that clinicians desperately want to automate. The most workable solution to documenting exams as they occur, rather than requiring hours of later work, has been to rely on a human medical scribe — an expensive solution with limited scalability. Increasingly, though, voice-driven computerized virtual assistants, such as Dragon Ambient eXperience from Nuance Health and 3M™ M*Modal Fluency Direct are finally delivering scalable solutions for clinical environments.
Remote presence technologies, including telehealth, increase the range of possible clinical encounters and scale it suitably for the treatment regimen. Remote care demonstrated its value during the pandemic. Sometimes a longer in-person visit is necessary, but often the best solution is a quick video chat supported by data from sensors, or even a quick set of questions from an app and a clickthrough to a prescription.
Healthcare is increasingly a team enterprise — including not only physicians, nurses, allied health staff and technicians but also increasingly capable AI-enabled equipment. Connected sensors enable every member of the team to have access to real-time data relevant to their task. Well-functioning communication between clinical and consumer sensors along with data aggregation, security, compliance and analytics that facilitate team communication during crucial care handoffs can significantly improve outcomes. Communication errors, particularly during handoffs, contribute to 50% to 80% of significant adverse events.
The most important member of the care team is the patient, who can be in charge of their own health outcomes. Progressively capable apps can guide patients through symptoms and issues, taking them step by step through self-checks that increase their understanding of their health status and enable the physician to focus directly on whatever issues are most important.
