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Transform Care Infographics September 02, 2015

POV: The Impact of Automation on Medical Decision Making

Principal, Health and Life Sciences, Oliver Wyman
Key Takeaway
Automated diagnosis will push care out of traditional settings

IBM recently announced its planned $1 billion acquisition of Merge Healthcare, a medical imaging company. Through this acquisition, IBM will gain access to millions of medical images that it will use to further develop its advanced analytics platform known as Watson in the hopes of eventually supporting physicians as they make treatment decisions. To what extent could “intelligent” analytic tools, such as IBM’s Watson, impact healthcare providers in the future? Oliver Wyman’s Frank Roberts explores this question:

Today, companies developing “intelligent” analytic capabilities are focused on supporting physicians as they make medical decisions. In the future, however, these capabilities could form the basis for automated diagnostic tools that might eliminate the need for a physician in many situations. Such tools would inevitably disrupt the physician-patient relationship and, in so doing, transform healthcare.

How will patient care be impacted? The impact of automated diagnostic tools on patient care will depend on two factors: the degree of required physical patient contact and the degree of medical decision making complexity associated with an episode of care. Patient care that requires a high degree of physical contact, such as drawing blood, or involves a high degree of complex decision making, such as behavioral therapy, are less likely to be affected by automation than those episodes of patient care which require minimal patient contact and are not medically complex. Our Automation Impact Matrix shows how new medical devices will reduce the need for direct patient contact (see chart above).

How big could the impact be? As the infographic below illustrates, “low complexity” codes represented 140 million of the approximately 250 million Medicare Part B enrollee physician office visits in 2013:

In the not too distant future, some of the medical issues associated with these visits could be resolved without any provider input. A patient who has a rash could be diagnosed with contact dermatitis through diagnostic software and image processing technology. The example of a rash is not just a convenient one – per a recent study by the Mayo Clinic, the most common reason for a visit to U.S. healthcare providers is for skin disorders.

This trend towards automated diagnosis of simple medical issues will push care delivery out of traditional care settings and will be a part of the new “front door” to medical care. Here’s how a treatment pathway of the future might look:

When will this impact be realized? While it might be tempting to assume that healthcare’s complexity and its unique patient-provider relationship will protect it from the dramatic transformations that have occurred in other industries as a result of automation, recent history illustrates the risk in making such assumptions. Few would have predicted that the widespread adoption of smartphones, for example, would lead to significant disruption of the taxi industry just a decade later.

There will, of course, be barriers to adoption. An automated medical diagnostic tool will require approval from the U.S. Food & Drug Administration. The safety of a tool that does not require a provider’s input will inevitably raise concerns and slow its adoption. Also, many providers will be reluctant to accept tools that they may see as “replacing” them, but will likely warm to the idea when they realize that such tools give them more time to build relationships with patients through longer, higher-value visits. Ultimately the drive towards lower costs and higher quality in healthcare is expected to lead physicians, health systems, payers, and the government to push for the implementation of automated diagnostic tools.

What can organizations do today? Automated medical diagnostic tools will not be an immediate concern for most healthcare organizations. This does not mean, however, that companies should not begin to think about their role in a future where many medical decisions are made autonomously. The transition to this future world of automation has already begun. New hardware is able to support medical diagnosis and treatment through remote monitoring. Telemedicine is redefining patient expectations in terms of when and where care should be delivered. Technology companies are embedding decision support tools in EHRs.

These tools and processes will provide a solid competitive foundation for many companies as the industry continues its transition towards automated care delivery, and some of these remarkable innovations will be shared as experiential exhibits at the upcoming Oliver Wyman Health Innovation Summit. As companies evaluate potential investments to support growth and remain competitive in this transitional period, they must also consider how these investments will position themselves in a future where fewer and fewer medical needs require a provider’s input.

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