Lehigh Valley Health Network Reduces Length of Stay with Minitab

FEATURE - Industry Innovation Article - Minitab

Lehigh Valley Health Network (LVHN) has achieved Quality Milestones throughout its 100+ year history. Its quality journey has recently added Lean Six Sigma tools and Minitab statistical analysis software to help achieve improvements in patient-centred care.

A project team including the Chief Medical Officer, VP of Patient Care Services, Director of Care Management, Director of Medical Surgical Services, two units of Nurse Managers, front-line unit nurses, Care Management staff and a Black Belt from the Organizational Effectiveness team used Minitab in their improvement effort.

The Challenge
Two adjacent hospitals merged and grew patient volume by 40% in their Medical/Surgical and Cardiac units. To manage the increase, the project team at LVHN investigated opportunities to improve patient flow and staff satisfaction. About 550 patients per month were discharged between the two units.

How Minitab Helped
The LVHN project team discovered a constant challenge during similar hours of the day when they examined their data over 14 months. With Minitab's Dotplot shown in Figure 1 below, they could see that 95% of discharges and 57% of admissions happened between 10 am and 8 pm.

Figure 1: A Minitab Dotplot for Time of Day for Admissions & Discharges (over 14 months of patients) showed a crucial 10-hour window.

You show this to any nurse in the world, and they'll probably say, 'So what? We know this. We live this,'" said Paul Kelly, the Black Belt on the project team. "But it was a turning point for us because they saw the data I was seeing, and visually they could confirm, 'Wow, this is a vital part of our day where we have to be at our most efficient. We've got a lot of traffic coming in these 10 hours. We're not only discharging 95% of patients. We're doing over half our admissions during those hours, and on top of that, we're caring for patients.'"

What could the team deploy to better manage these "rush hours" for unit staff? Initially, Length of Stay (LOS) data was presented for 57 different discharge locations, as shown in Figure 2 below, with the length of stay on the y-axis and discharge codes on the x-axis. The team wanted to simplify this, and Minitab's recoding functionality made the LOS data much easier to interpret.

Figure 2: Fifty-seven different discharge locations LOS.

When they recoded the 57 discharge locations into three groups, as seen in Figure 3 below, the team asked themselves: Should they focus on the higher LOS discharge locations or where more patients were being discharged to? More patients were discharged to their homes, but their LOS was the lowest of the three groups so it may have less impact overall. The highest LOS were discharged to Skilled Nursing Facilities (SNF), but the number of patient discharges to Skilled Nursing Facilities was lower.

Figure 3: Minitab's recoding of 57 discharge locations, reduced to three (for two units shown), provided a simpler, more easily understood view of LOS by discharge locations.

Results
LVHN's solution targeted all discharge locations because they thought a once-deployed solution in the past could be helpful again. Nursing management deployed two Admission/Discharge Registered Nurses (RNs) to assist nurse colleagues with direct patient care responsibility with their admissions and discharges.

Over 13 months, the Admission/Discharge RNs performed 30% of all admissions and discharges on two units. This off-loading of value-added work allowed admissions and discharges to occur earlier for patients.

Minitab's Histogram was the primary visual method to keep track of progress and if gains were sustained. The latest discharge times, from 6 pm to midnight, were of most interest to the team to reduce. Recoding 24 hours in the day to four 6-hour groups allowed the team to track the change in earlier-in-the-day discharges (see Figure 4).

Figure 4: Discharges to Home (top row), Other (middle row) and Skilled Nursing Facilities (bottom row), 13 months before (left column) A/D RNs use and 13 months after (right column) A/D RNs use. NOTE: Y-axis is the number of patients discharged in that hour of the day, and the x-axis is the hour of the day for discharges.

They observed the most significant improvement – 13.6% – with discharges to SNFs during the last 6 hours of the day coming down from 42.7% to 29.1%. Home and Other discharge categories also saw reductions in late discharges:

Minitab's quality tools, including the Dotplot, Boxplot, Interval Plot and Histogram, all contributed to the LVHN team's selecting an area for improvement and validation of the solution's effectiveness over time.

For more Minitab information including free trails, please visit: https://www.sofsol.co.nz/minitab/

If you would like to provide feedback on the above feature article please contact the editor Rebecca McBeth.

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