Healthcare organizations have long relied on traditional benchmarking to compare their performance to others and determine where they can do better; however, to identify the highest ROI improvement opportunities and understand how to take action, organizations need more comprehensive data.
Next-generation opportunity analysis tools, such as Health Catalyst® Touchstone™, use machine learning to identify projects with the greatest need for improvement and the greatest potential ROI. Because Touchstone determines prioritization with data from across the continuum of care, users can drive improvement decisions with information appropriate to their patient population and the domains they’re addressing.
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To thrive in today’s improvement-focused healthcare environment and achieve sustainable transformation, healthcare organizations must prioritize improvement projects with analytics-driven processes and technologies. By strategically prioritizing healthcare projects, health systems can focus on opportunities that optimize their ROI while working within their individual resource constraints. Otherwise, organizations risk devoting time, money, and skills in areas where they’re unlikely to realize quality or financial gains.
Health Catalyst® Touchstone™ is an artificial intelligence-powered next-generation opportunity analysis and prioritization tool that helps health systems determine which projects represent the greatest ROI for patients and for the bottom line. Touchstone leverages two key capabilities to identify opportunities and prioritize projects:
Healthcare benchmarking is a practice that compares an organization’s performance metrics to a standard developed using data from similar organizations. Benchmarking shows healthcare leaders how their organizations are performing compared to similar health systems; it also shows them where they can improve.
According to 2018 survey conducted by Health Catalyst, 72 percent of healthcare leaders consider benchmarking important or extremely important in identifying and prioritizing improvement projects. Of these executives, 22 percent say that an organization’s performance against benchmarks is the most influential factor in determining which improvement initiatives to launch; benchmarking followed regulatory/reporting requirements (25 percent) and improvement team priorities (24 percent).
Even though many leaders consider benchmarking a critical tool in improvement project prioritization, benchmarks still don’t support highly data-driven strategic planning and fall short when it comes to identifying the greatest opportunity for an organization to improve. Benchmarking data tends to be limited to specific domains (e.g., inpatient), may not be truly compatible with an organization’s patient population (due to factors such as age and socioeconomic status), and rarely captures performance across the continuum of care (e.g., both inpatient and ambulatory settings).
Benchmarks may tell leaders limited quantitative data (e.g., that an opportunity exists), but don’t necessarily tell them where and how to strategically improve to achieve the best ROI. And, even when they do find an improvement opportunity, benchmarks don’t include the critical qualitative data that helps organizations understand if they’re ready to take on a project (e.g., whether there’s a team in place to execute on improvement, whether that team wants to be data driven, and if they have the right mindset to improve processes).
To carry out data-driven improvement, health systems need more comprehensive processes than traditional benchmarking; processes that run on data from across the continuum of care (e.g., clinical claims, cost accounting, and patient satisfaction) and make informed, automated improvement recommendations.
In traditional benchmarking, analysts manually identify improvement opportunities using repeated processes of slicing and dicing data to look for cohorts with the greatest opportunity to improve. Touchstone automates these repeatable tasks and uses machine learning algorithms to drive prioritization. Similar to Netflix movie recommendations, Touchstone further automates prioritization by using machine learning to recognize the users’ main focus areas, based what type of data they tend to look up (e.g., if health system users search frequently for diabetes, the tool will recommend more improvements around diabetes).
Healthcare is currently experiencing a data explosion, in which it’s constantly flooded with more sources of information. Ideally, improvement leaders want to incorporate as many data and comparison sources as possible in improvement opportunity assessment and prioritization. Many health systems have dozens, and sometimes hundreds, of data sources flowing into their EDW. To fully leverage this overflow of data, health systems need tools, such as Touchstone, that look across all healthcare data sources, not just the EMR, to identify opportunities for improvement.
Touchstone uses risk-adjusted benchmarks for dozens of utilization and outcomes metrics. The data starts at the encounter level (the lowest grain of data), allowing users to slice and dice their metrics by any dimension and see a corresponding risk-adjusted benchmark. This process yields thousands of comparisons and, with data across the full continuum of care, achieves more ROI-driven prioritization than traditional benchmarking.
To succeed in improvement, health systems must start with a clear understanding of their most impactable improvement opportunities, including which of those opportunities promises the biggest ROI. If organizations don’t prioritize areas where they’ve identified the greatest need for improvement, they will see little ROI.
With effective improvement project prioritization, organizations can devote time and resources to the more complex, yet critical, qualitative aspects of transforming care, such as understanding their readiness to tackle improvement. Qualitative improvement opportunity analysis is equally important as identifying the best opportunities for improvement and prioritizing them, as it shows organizations whether they have the capacity to carry out and sustain improvement work.
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