The most powerful computer in any healthcare enterprise is the one between the clinician's ears. Given the current frenzy about artificial intelligence (AI), cognitive computing, and machine learning, we might be among the few who still believe in the primacy of doctors in providing quality care to patients.
Unfortunately, physicians face a number of distractions that prevent them from focusing solely on the delivery of quality patient care. Government regulations, poorly designed clinical user interfaces, and inefficient hospital information systems (HIS) slow doctors down and impede the care process. The large HIS platforms were designed to track patients and facilitate billing and reimbursement - and never to support the clinical thought process of physicians at the point of care. It's not the fault of the HIS vendors, who have simply been responding to the needs of their customers and creating solutions to capture billable transactions, instead of developing clinically-focused solutions that provide actionable views of patient data.
Today's systems take a transaction-centric approach and organize clinical data for each type of transaction into different "buckets" for active problems, laboratory results, medications, orders, etc. To find data relevant for a particular problem, a user must click between different tabs, which interrupts the clinical thought process and leads to user frustration.
Clinical quality measure (CQM) requirements under MACRA add another impediment to usability. Approximately 190 of the CQMs require clinical decisions that are best made at the point of care. Most systems treat CQMs as just another set of transactions that must be addressed for reporting requirements, rather than integrating the CQMs at the point of care and in support of the physician's thought process.
Many of the leading HIS vendors are hoping that new technologies will make things easier for physicians. Specifically, vendors are hoping that one day doctors will be able to dictate, have the dictation converted to free-text, have the free-text analyzed through natural language processing (NLP), and finally apply AI techniques and machine learning to the data to provide clinical decision support and ultimately improve the quality of care. STOP. Read that sentence again. There is a lot of "hoping" involved in that one long sentence – and today those hopes are not backed up with a lot of reality.
However, there is a better way.
Today's current systems can be made more usable for physicians at the point of care by adding a clinical engine and a user interface that supports physician thought processes. Such a clinician-friendly user interface must include:
1. A single workspace with an actionable patient summary showing all clinically relevant information for any problem. The workspace should be integrated with point-of-care documentation and quality measures should be part of the workflow and not a separate task.
2. A clinical data engine that supports problem-oriented views and documentation and automatically shows a physician what is new, different, or unchanged about the patient. A quality compliance engine should also determine potential care gaps for each patient at the point of care and for every encounter.
3. The proven ability to see more patients in the same amount of time (or less), and allow users to complete all documentation and quality, compliance, and billing requirements at the time of the encounter.
If your organization's existing systems are standing in the way of your physicians' ability to deliver quality patient care, perhaps it's time to consider proven technologies that allow doctors to return to the practice of medicine.
AUTHOR BIO: David Lareau is the Chief Executive Officer of Medicomp Systems. Lareau joined Medicomp in 1995 and is responsible for operations, strategy, customer success, and product management.
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