Lean Six Sigma Data Analysis Quantifies Patient Benefits & Justifies Growth Plans in Cardiac Rehabilitation Services

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Lean Six Sigma Data Analysis Quantifies Patient Benefits, Justifies Growth Plans in Cardiac Rehabilitation Services

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Client: A full-service hospital in Colorado with 286 beds
Industry: Healthcare
Service: Lean Six Sigma

Challenge:

Patient volume was rising and clients had a high level of satisfaction, but the client could not quantify the positive impact that rehabilitation services had on their patients

Solutions:

Used Lean Six Sigma data analysis and implementation tools to evaluate the outcomes of patients who participate in the cardiac rehabilitation program versus those who did not

Results:

The average length-of-stay for patients in the rehabilitation program, over a two-year period, was 30% lower than patients who did not participate following an acute medical or surgical event
Justified investment in growing the program

The cardiac rehabilitation staff of this 286-bed tertiary hospital in Colorado knew that their programs were effective and that client satisfaction was high, but they didn’t have any indicators in place to measure the overall impact of their work. They needed hard data to justify increased patient participation and the investment in the rehabilitation program to support that growth. Such data could also help justify cardiac rehabilitation coverage with insurers when negotiating future contracts.

A team of clinical and non-clinical staff members used Lean Six Sigma tools, over a 10-week period, to determine exactly how their services were helping patients. The team included nurses, cardiac rehabilitation technicians, physical therapists, administrators and marketing staff. They evaluated two patient groups, one that had received Phase II cardiac rehabilitation services and one that had not. For each group they looked at length-of-stay, readmission rates, severity of illness upon readmission, and the costs of readmission.

The project team followed the “plan-do-check-act” framework to move in a structured way from gathering raw data to asking the right questions, identifying root causes and presenting their conclusions. Following a “just-in-time” training approach, Guidon advisors introduced analytical tools as they were needed. These tools included cause and effect diagrams, pareto analysis, data charting and segmentation, surveying and interviewing techniques, and best practices research.

The team discovered that the average length of stay for patients in the cardiac rehabilitation program over a two-year period was 30% lower than for patients who had not participated in cardiac rehabilitation after an acute medical or surgical event. More importantly, the cardiac rehabilitation patient had a severity score—a measure of the heart’s overall strength—that was 15% better than the other group. Patients who participated in the program, as one example, would not have to be re-admitted for cardiac catheterization as frequently as those who didn’t go through rehab. For such reasons, the overall cost for a rehabilitation program patient was 27% lower (a savings of $4,672 per inpatient stay) than for those patients who did not participate in the program.

With this data in hand the team was able to move forward with their plans to grow the cardiac rehabilitation program. Their recommendations based on the data analysis included:

Increase marketing efforts to capture more patients for the Phase II cardiac rehab program
Initiate formal negotiations with insurance companies that did not cover rehabilitation services
Present specific data to cardiologists and primary care physicians on the benefits of the rehabilitation program
Educate patients regarding the superior outcome of those who participated in the cardiac rehabilitation program