What have you done for me lately? That’s the question many healthcare executives are asking these days as they search for meaningful ROI from their heavy IT investments made over the past decade. Executives and board members need to validate that enterprise priorities successfully address their strategic agenda. Leaders struggle to evaluate the best way to allocate shrinking investment capital. Operations managers strive to optimize staffing efficiency and patient flow without sacrificing effectiveness. Clinical leaders are trying to deliver high quality care at the lowest cost, while also managing transitions of care and preventing readmissions. Wasn’t the information technology in which we invested supposed to help?
There’s no doubt that the healthcare industry has achieved tremendous gains through Electronic Medical Records (EMRs) and budding business intelligence (BI) capabilities. However, many organizations are now struggling to translate the vast storehouses of clinical and operational data into actionable information. Healthcare leaders who realize that their best insights may result from asking “why” (Why are we experiencing a 21% readmission rate?), and exploring the “what if” (What’s our new penalty exposure if readmissions from our largest physician group were reduced 10%?), know that their analytics programs should answer these questions.
This need for concurrency—the “why” and “what if”—is the direct result of the convergence in BI technologies and reimbursement models that increasingly emphasize care accountability and transparency, as well as healthcare leaders’ evolving sophistication in the use of dynamic analytic tools. Once an organization equips executive stakeholders with relevant and meaningful analytics, the collective desire for healthcare analytics capabilities that support real-time decision-making can become insatiable. The analytics leader of a healthcare organization I recently worked with called their leaders’ response to their new enterprise performance analytics and reporting tool “nothing less than shock and awe.” Decision-makers across clinical, operational, and strategic functions immediately moved from resisting transparency to clamoring for more – more performance visibility, more drill-down capability to investigate relationships between measures, and ever-more depth of granularity to reveal useful insights into performance gaps.
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New intelligence demands and capabilities are self-perpetuating. Healthcare decision-makers in organizations with strong BI capabilities naturally move from asking “why,” to asking “what if?” For example, “what if”:
- Clinical leaders could concurrently stratify their own patient data by clinical, economic, and psycho-social factors to clearly understand provider and patient behaviors that contribute to effective care transitions and prevent readmissions?
- Nursing managers could forecast the impact of closing a unit, changing bed allocation, or changing the staffing pattern for next week, next month, and next year?
- Planners could forecast demand for inpatient and ambulatory services by zip code and population demographics?
- Care managers could predict patient flow bottlenecks, patient discharge needs, and could receive real-time alerts of variations from protocols and best practices throughout an episode of care?
- Scheduling blocks in the operating room, interventional radiology, and advanced imaging could be arranged to achieve 80% utilization and ensure adequate access for urgent cases?
Healthcare leaders are just beginning to understand the potential for healthcare analytics to transform decision making through use of predictive algorithms and accurate forecasts. There is little doubt that other industries have used the power of predictive analytics to power strategic growth and margin enhancement, and that healthcare needs to keep up. How should healthcare leaders prepare to leverage this potential?
- Recognize that your organization’s analytics capability is a strategic asset, and develop a plan to enhance your analytics assets, including their people, processes and technology. Comprehensive assessment of the organization’s current analytics capability is a complex undertaking, and obtaining expert assistance from an external resource to establish baseline performance and create a roadmap for enhancing value is a wise investment.
- Assess baseline performance for critical enterprise capacity functions. Capacity equates to currency, and patient flow is the leading driver of margin. Is your current capacity plan aligned with your strategy for profitable growth? How well are your daily capacity management and staffing plans aligned with that strategy? For instance, how many hours are patients held in ED, PACU, or ICU while waiting for a bed at the appropriate level of care? In a recently conducted analysis, we discovered a $9.3 million opportunity for a hospital with an average daily census of 400. Applying predictive analytics to questions such as these separates top performers from the pack.
- Invest in the talent needed to develop a healthcare analytics program that concurrently illuminates the drivers of current performance gaps, provides real-time support for clinical and operational decisions, and drives development of predictive algorithms and accurate forecasting.
It’s time for healthcare enterprise leaders and their analytics partners and vendors to work together to address these challenges and deliver higher care quality at a sustainable cost. It’s time to become concurrent.
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