Thanks to the explosion of Big Data in recent years, physicians now have more clinical decision-making tools than ever before.
Insights derived from machine learning technologies and predictive analytics are helping providers to more easily identify patients at risk for hospital readmission, and to find undiagnosed diabetics in a population based on elevated levels of hemoglobin A1c. The insights also facilitate the adoption of evidence-based care guidelines and can help physicians determine the most cost-effective treatments based on a patient's unique situation.
Physicians are also in the midst of adopting new value-based care models that prioritize quality outcomes and incent providers to track and report on quality initiatives. Quality outcomes benefit patients and reduce the cost of care, but the documentation and reporting requirements for these programs create an administrative burden for physicians and can reduce their productively.
Insights from machine learning technologies and analytics, along with emerging value-based care models hold great promise for improving healthcare – but physicians may be hesitant to take full advantage of their benefits if adoption diminishes productivity. To maximize the health benefits for individual patients without compromising physician productivity, clinicians need relevant data incorporated into their existing workflows at the point of care.
While this might sound like an easy goal to achieve, making the right information available at the right point in time requires the implementation of technology that includes millions of mappings and relationships between clinical concepts. Such mapping facilitates the contextual filtering of data so that physicians can focus on information that is relevant to the current patient and a known or suspected disease state. By eliminating all other "clinical static," clinicians are able to concentrate, and deliver better outcomes more efficiently.
Contextual data at the point of care
Consider how the delivery of care is enhanced when data is appropriately filtered and physicians are only presented with data that is contextually relevant to the patient they are treating. For example, a physician may evaluate a patient with a persistent cough and prescribe a suitable therapy. The recommended therapy might be adjusted, however, if during the documentation process the physician is automatically reminded that the patient is diabetic and that an alternate therapy might be more appropriate. Because the data presented is clinically contextual and incorporated into the doctor's existing workflow, physician productivity does not suffer and the clinical outcome – along with the patient's satisfaction – may even be superior.
Satisfying quality reporting requirements
Value-based care models compensate physicians for high quality scores. Clinicians are thus mindful of applicable performance benchmarks, such as efficient test utilization and avoiding gaps in care. Technology can help physicians meet quality goals by automatically reminding them during the documentation process that the patient in front of them is due for a mammogram or a hemoglobin A1c test. In some cases, the provider can immediately address gaps in care – or at least schedule follow-up testing or procedures before the patient leaves the office.
In addition, if physicians have point-of-care tools to track their progress in meeting quality objectives, quality reporting burdens are minimized. For example, if the system tracks quality measures while a doctor is documenting an encounter, the provider can be advised in real time if certain elements are missing. Physicians don't need to remember which quality-related activities must be documented for proper reimbursement because they are automatically reminded as part of the regular workflow.
The right details at the right time for the right patient
To effectively leverage insights from machine learning and predictive analytics, and to encourage participation in quality-based incentive programs, physicians must have access to the right details at the right time. Unfortunately, a busy doctor documenting at the point of care rarely has time to jump between multiple screens to hunt for critical information – and data that is never accessed provides no clinical value.
Physicians thus need clinically relevant data that is seamlessly presented within their current workflows and integrated into the same clinical workspace. The result is not only better patient care and better outcomes but also higher clinical effectiveness, efficiency, and satisfaction—so that's a win for all of us.
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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