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Why artificial intelligence in health care falls short today and how implementing technology in health care requires integrated workflows to cut costs and improve outcomes.
Health care has spent decades searching for transformation through technology. Electronic health records digitized the medical chart. Analytics gave organizations greater visibility into performance. Cloud infrastructure and interoperability expanded access to information, and now artificial intelligence (AI) promises to automate work, accelerate decisions, and fundamentally change how health care is delivered.
Yet there is a difficult question the industry still needs to confront: Why, after decades of technological progress, does health care remain so difficult and expensive to deliver?
Despite significant investment, technology and productivity have not moved in parallel.
The next era of health care transformation cannot simply be about introducing another generation of technology. It has to be about redesigning the operating environment in which that technology works.
We Digitized Health Care Without Simplifying It
Much of health care’s technology investment has followed a familiar pattern: identify a problem and deploy a tool to solve it. A documentation challenge gets a documentation solution. Scheduling gets a platform. Revenue cycle gets another application. Population health gets a dashboard. Care management gets a workflow tool.