By Stoltenberg Consulting
In today's era of healthcare reform, organizations face many unique competitive and strategic challenges. Healthcare reform requires leaders to improve access to care and increase the quality and safety of care, while decreasing the cost associated with care delivery — all while thoroughly documenting the improvement. That's a significant undertaking. In order to meet these challenges, no matter where a healthcare organization is in its EHR lifecycle, leaders must find ways to improve efficiencies to solve workflow and data inaccuracies before they hinder productivity and informed patient care decision making. To aid this cumbersome process, below are five areas of consideration for driving true clinical optimization in value-based care transformation.
Defining Optimization
For any hospital's clinical optimization process, leaders must first determine their definition of "optimization" as a guiding principle going forward. Working with an outside resource can help with setting guiding principles, best practices and expectations. Make sure well-defined key performance indicators (KPIs) are in place, and from there set specific benchmarks for future performance and measurement expectations. For example, who will complete the measurement? For which departments does each KPI apply? How often do you measure?
Clinical Assessment
Next, focus on the set area in clinical delivery to assess. Current state mapping will allow your team to see steps, processes, workflows and potential delays in delivering a service to patients to ensure the organization truly offers value-added care. Coordinating with this step, utilize root-cause analysis for problem solving of any current or potential service delays or issues, knowing that more than one root cause can be a hindrance. Arrange identified root causes with higher priority on those causing more issues or delays in patient care.
For the prioritized root cause, focus on optimizing for achieved solutions. Consider industry best practices, including feedback from vendors, EHR user groups, strategic advisors or professional management organizations. With industry best practices in mind, from here map the future state value stream by eliminating any non-value-adding steps from the previous current state value stream. Design and test new workflow pilots to ensure true effectiveness.
Return to KPIs
Even post optimization, continuous monitoring is imperative. Consistently monitor healthcare KPI dashboards for emerging patterns indicating improvement interference. If initial value stream changes don't align with target results, make adjustments and re-measure.
Lasting Results
After testing is complete, take the optimized new future-state value stream across the organization. Not everything goes as smoothly as the pilot. Cross-organizational implementation elicits new challenges, so continue thorough monitoring.
Successful clinical optimization can't occur (and last) without diligent behavioral change. Provide training and reinforce continued proper practice with champions throughout the organization backing, personally demonstrating and enforcing new workflows. Make sure to transition new process ownership to direct operational leadership, so they can apply and monitor new successful workflow daily.
Bringing in Clinical Data Analytics
Clinical data analytics can step in to often identify and solve previously unknown challenges. Clinical healthcare analytics works to bring the optimization process into inherent practice. In a full-circle effort, a smart healthcare data analytics process examines clinical data for conclusions and patterns in efficient care delivery, improves KPIs and works to support an organization's infrastructure. This is when teams begin to observe change, not only in clinical process areas, but also organizational transformation – when the culture of the organization shifts as actionable analytics drives meaningful, measurable change within the clinical setting. Hospitals also start to see clinical areas using their KPIs and trending data to move processes to a more efficient state.
As healthcare facilities begin to realize the benefits of clinical data analytics, behavioral adjustments within the organization occur concurrently. Performance measures trend upward as hospitals see the process begin to repeat itself as it becomes part of the organization's environment. Clinical data analytics becomes the glue between process improvement and optimization, as the driving force to consistently build KPIs in areas such as value based purchasing, patient satisfaction and National Database of Nursing Quality Indicator scores. Both clinical data analytics and clinical optimization will now become a mechanism that generates revenue back to the organization through improving and maintaining high levels and standards within specific performance measures. These are areas that that are increasingly being shifted to for incentive-based payment structures. Beyond this though, the clinical optimization process can directly help with workflow, usability and number of clicks, lessening the everyday EHR burden overwhelming physician and nurses. By adopting a clinical data analytic program that drives optimization, organizations will be hard-wiring a competitive value-based care strategy for success moving forward.