3 Important Keys to Move from Reactive Care to Proactive Care
The challenges impacting healthcare systems requires transformation to proactive population health management
Summary
The drive for high-value care is shifting from acute, reactive care towards a proactive preventative outlook.
Innovation is not only about technology, but also processes and workflow changes.
Proactive care requires addressing care variability, incorporation of predictive analytics and early awareness of patient/disease trajectory.
A collaborative system wide approach is needed to move from quantity to quality to align with organization goals.
Review
There is general agreement the current framework of healthcare delivery is ineffective.
If we are to shift from a reactive to a largely proactive model, there are 3 key considerations we must address.
Item 1: Care Variability
By definition care variability implies a group of patients have a poorer clinical outcome with the same level of healthcare resources and expenses.
There are 2 broad types of variability
Knowledge Variability
Poses the greatest threat to quality and cost effective care
Clinicians are not aware of pieces of knowledge or data elements (missing or unaware).
Operational Variability
Variations in outcome due to differing levels of care delivery
EHR’s can reduce some operational variability
Limitation is they only serve as a vehicle to deliver previously and currently available data.
Item 2: Clinical Decision Support-Predictive Analytics (CDS-PA)
·We are in the early stages of CDS-PA
Few health systems effectively use CDS-PA to influence care
CDS-PA alone is not enough – integration into clinical systems to help in decision making and track quality are also needed.
Still requires clinical judgement to be exercised.
Item3: 4 Stages of Patient/Disease Trajectory
Stage A: Apparently Healthy – Physiologic changes begin
Stage B: Early Disease Precursors & Dysfunction – Usually asymptomatic
Stage C: Traditional Clinical Expression – outward symptoms
Stage D: Requiring Care Intervention to manage disease
PROACTIVE CARE MODEL:
Dysfunction detection in Stage B allows for proactive interactions
A collaborative-systems based approach should be used to detect the emergence of risk factors of dysfunction without signs or symptoms to better assess overall patient status.
Technology can be leveraged to integrate a variety of data from various sources as well as identification of missing data.
This requires moving from the traditional “Threshold value” evaluation and response to a slope of decline in function and physiologic status.
Innovations not only in technology but process and structures as well
·Shift activity from “Being Busy” to “Being productive and effective”
This implies abandoning rounding to “catch up” without a plan, to clinical evaluation to support therapeutic plans
Conclusions
Proactive care involves:
a. A collaborative system change emphasizing quality over quantity which align with organizational goals.
b. Rounding on every patient can lead to a “Checklist” mentality
c. Process change should leverage technology to be both more efficient and effective
d. Decrease in care variability, incorporation of clinical decision support and monitoring for early signs of disease trajectory are key to proactive care.
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