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Data Science Helps UCHealth Improve Infusion Center and Hospital...
Steve Hess, CIO, UCHealth
Increasing Value To Patients With Data And Analytics
By Charlton Park, CAO, University Of Utah Hospitals & Clinics
Truly understanding the costs of patient care at an individual case level isn’t as easy as an outsider to healthcare might think. Hospitals are complicated business environments that are able to provide an extraordinarily large range of services. The number of conditions treated and the uniqueness of each patient’s care make accurately accounting for the cost of patient care at the patient encounter level a difficult task. Timely, detailed, accurate cost-accounting data is a key component of the data foundation and all hospital systems must have to support value improvement work. Hospital systems must invest in sophisticated cost accounting systems/ processes that provide accurate, “believable” encounter-level cost data that will support the value work. Relying on generalized costing data that is driven largely by cost-to-charge ratios or work relative value units (wRVU) simply won’t provide the detail necessary to understand costs and drive change. All costing data is not created equal. Engaging busy physicians, clinicians, and administrators in understanding true patient care costs will require investment in high quality costing data that provides transparency to actual clinical costs.
Developing the Metrics
Similar to the investments in developing accurate cost accounting data, hospital systems must continue to develop quality, outcomes, and process metrics. Unlike costing data, which relate to every patient encounter, these metrics don’t necessarily apply broadly and can change over time. For example, measuring mortality rates makes a lot of sense when analyzing outcomes for heart transplant cases, but measuring mortality rates are not as meaningful for joint replacement patients. The differences in what are important in the measurement of one population or condition compared to another requires the development of specific metrics for each population or condition. With the large number of conditions treated in most hospital systems, the development of meaningful, quality outcomes and process metrics is no simple task. That is a lot of metrics!
Truly understanding the costs of patient care at an individual case level isn’t as easy as an outsider to healthcare might think
We define value as the best quality and satisfaction at the lowest cost. When measuring value for any specific condition, it will comprise several quality, outcomes, and process metrics. Hospital systems need to engage physicians, process improvement specialists, IT professionals, and others in identifying and building these metrics. Over the past decade, hospital systems have made significant investments in electronic medical record (EMR) systems that facilitate electronic capture and exchange of clinical data. EMRs collect an astonishing amount of information that is incredibly useful to the value improvement work.
When identifying the right metrics to measure, remember the purpose is to create a foundation of meaningful data that will support value improvement work. Nobody is more critical to the value improvement work than physicians. Physicians know what impacts the care and outcomes of their patients and long for transparency of that information. They are able to provide great insight into which metrics are the most meaningful. Regulatory bodies, including CMS, have identified specific metrics they believe are important. Process measurements that ask questions like “Do joint-replacement patients have physical therapy on the same day as surgery?” and “Were antibiotics given within six hours of ED admission for a community-acquired pneumonia patient?” help to measure adherence to adopted clinical care pathways. Patient-reported outcomes, when collected, provide a unique, patient perspective to the value of care. Quality, outcomes, and process metrics, whatever their source, are critical to support value improvement work, but they must be specific and meaningful to a condition or population.
The hard work of building a foundation of data to support value improvement work is the first step,. The next critical task is creating transparency to the information. Transparency, in this sense, doesn’t simply mean including cost and quality data in a report that is shared broadly. To support value improvement work, organizations need to create a culture that is accepting of transparent data and embraces the concept that transparency is a tool that allows physicians and others to learn from each other. When coupled with a supportive culture, transparency created by physician-to-physician comparisons in both cost and quality can be one of the most effective tools for understanding variation and creating dialogue around process improvement. Without a culture that embraces transparency, even the best costing and quality data will be undermined, disputed and disregarded. Developing a culture accepting of transparency starts from the top and requires the engagement and support of the top physician and administrative leaders.
Improving value is a team effort and, to do it well in any hospital system, will require engaging physicians and administrators and surrounding them with the tools and talent to support the work. This will include knowledgeable business analysts, process engineers, quality specialists, IT analysts and project managers who are familiar with data, and the complexities of healthcare. Each value improvement effort will be different and require a different mix of resources. However, each effort will be heavily reliant on data to support each project. Surrounding physicians with the talented resources they need as well as access to transparent cost information and quality, outcomes, and process measurements will create the environment needed to truly increase value to patients.
Data Science Helps UCHealth Improve Infusion Center and Hospital Efficiency
Steve Hess, CIO, UCHealth