A Learning EHR for a Learning Healthcare System

Can the health care system survive the adoption of electronic health records? When the HITECH act mandated the installation of EHRs in 2009, we all hoped they would propel hospitals and clinics into a 21st-century consciousness. Instead, EHRs threaten to destroy those who have adopted them: the doctors whose work environment they degrade and the hospitals that they are pushing into bankruptcy. But the revolution in artificial intelligence that’s injecting new insights into many industries could also create radically different EHRs. Here I define AI as software that, instead of dictating what a computer system should do, undergoes a process of experimentation and observation that creates a model to control the system, hopefully with far greater sophistication, personalization, and adaptability. Breakthroughs achieved in AI over the past decade now enable things that seemed impossible a bit earlier, such as voice interfaces that can both recognize and produce speech. AI has famously been used by IBM Watson to make diagnoses. Analyses of big data (which may or may not qualify as AI) have saved hospitals large sums of money and even–finally, what we’ve been waiting for!–make patients healthier. But I’m talking in this article about a particular focus: the potential for changing the much-derided EHR. As many observers have pointed out, current EHRs are mostly billion-dollar file cabinets in electronic form. That epithet doesn’t even characterize...
Source: EMR and HIPAA - Category: Information Technology Authors: Tags: EHR Electronic Health Record Healthcare AI AI EHR Artificial Intelligence EHR Virtual Assistants Learning EHR Learning Health Care System Machine Learning Source Type: blogs