After Medicare, Medicaid, managed care and commercial health plans, the remainder of a hospital or health system’s revenue comes from patients. Those balances already comprise more than 30 percent of a large health system’s revenues and are rising rapidly. An analysis released last year found an 88 percent increase from 2012 to 2017 in total hospital revenue attributed to patient balances after insurance reimbursement.

Today’s mostly paper-dependent clinical trials pose fundamental challenges to the pharmaceutical industry. Such trials can be prohibitively expensive, struggle to enroll and retain a sufficient number of participants, and have difficulty maintaining compliance and data reliability. But with the advent of virtual and partially virtual trials using digital tools and devices, we have the opportunity to substantially improve efficiency by deploying the same design principles that make consumer apps so successful.

A few years ago, a technologist in a healthcare organization’s IT group would view data in the cloud skeptically, if at all. Today, that position is fading fast, with data to support it: IDC estimates that the healthcare industry’s spending on cloud technologies would surge to $13.6 billion in 2019[1].

The health system revenue cycle is a complex process, starting with registration and scheduling, and ending with claims submitted and processed and payments received. Removing bottlenecks that prevent faster receivables has been a constant challenge facing revenue cycle leaders. Missing providers in EHRs is a major root cause of bottlenecks and rework. The advent of promising new digital provider enrollment workflows may, someday soon, eliminate them.

In October of 2018, President Trump signed into law the “SUPPORT for Patients and Communities Act,” a comprehensive bill designed to address the opioid abuse epidemic. This landmark legislation presents a unique opportunity for the healthcare IT community: we now have a real chance to position electronic prescribing of controlled substances (EPCS) as a crucial technology component of the national fight against opioid abuse.

Visionary pundits have already painted pictures of futuristic healthcare scenarios with robots strolling through hospital corridors in place of doctors – examining patients, making diagnoses, and prescribing medications. A lot of hype surrounds artificial intelligence (AI) and its application in healthcare resulting in questions about its usability, safety, and practical value– and for good reason. We’re still a long way off from completely replacing human medical practitioners, and perhaps we never will. The objective for healthcare today is to move past the hype and chart a course for AI that balances its opportunities and liabilities, while understanding its current limitations and finding areas where it can create real value and solutions.