WEDNESDAY, OCTOBER 18, 2017
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Industries Healthcare Improving Labor and Delivery Triage Turnaround Time

Improving Labor and Delivery Triage Turnaround Time

Excessive waiting and poor customer service at a hospital’s labor and delivery triage area had existed for years. But with a knowledge of Six Sigma, the hospital’s management knew it did not need to continue unabated. A process improvement project team attacked the problem systematically and began resolving it in a matter of months.

Here is the story:

The original intent when the triage area was set up was to free beds in the labor and delivery area and in antepartum as well as decrease the wait time for patients. Unfortunately, triage became a holding area where patients could wait for hours before disposition of their situation. The patients might wait there because test results were pending, or so they could be observed, or because practitioners would not see patients during the night, or other reasons. This tied up more beds so other waiting patients could not be seen in a timely manner and would sit in the waiting room not having seen anyone unless they were in labor or distress. The hospital had provider and patient dissatisfaction, and had even lost patients to other facilities due to excessive waiting and lack of customer service.

Project Team Finds Extent of Problem

During the project team’s baseline measure, it was discovered that patients waited an average of 147.4 minutes with a standard deviation of 93.7 minutes during the baseline measurement period from June 1 to July 23. A voice of the customer survey from 72 patients, nurses and providers indicated that they would be willing to wait for 120 minutes with an upper specification limit of 180 minutes from the time of presentation to labor and delivery triage to time of disposition. The time of presentation is when the patient arrives and signs in at the triage registration window. Disposition was defined as when a patient is discharged home or transferred to labor and delivery or antepartum units.

Using Mood’s Median and Levene’s Test, the team analyzed 97 patient visits. It found the hospital’s process variations in this area came from radiology, the laboratory, registration and the providers. Of course, another source of variation was the patient’s chief complaint. The results were not surprising since one would expect a patient to be in triage longer if waiting for results or if they had a more complicated chief complaint.

Process Improvements Are Developed

The team came up with these improvements:

  • Standard protocols were developed for seven common complaints with the teamwork of nurses and providers as well as an extensive literature search which included – decreased fetal movement, nausea and vomiting, rule out labor, pregnancy induced hypertension, rule out rupture of membranes, rule out vaginal bleeding, and motor vehicle, fall or other trauma. These protocols can be activated with provider orders upon patient arrival, with provider orders by phone, or if provider fails to contact nurse in a specific amount of time after nurse initiates contact by paging or calling the provider’s office or cell phone.
  • Registration is now completed after the patient is evaluated by triage nurse thus reducing wait time patient experiences upon arrival.
  • The previous pharmacy process caused confusion between nurses and pharmistics as well as delaying medication orders from being processed. The team updated the process so that it is standard throughout the hospital which no longer routinely causes delays and speeds up not only the turnaround time but also reduces delays in medication administration. This also has increased customer satisfaction between nursing and pharmacy.
  • A single call log was implemented where all nurses log in calls to and from providers. This lets the hospital track and monitor if providers are routinely not returning calls in a timely manner. Nurses also are able to easily identify how long it has been since a provider was paged or phoned. Using this documentation allows the initiation of the standard protocols in cases when a provider fails to call within designated time frame.

Evaluating the Hospital’s Pilot Program

The project team analyzed 71 patient visits during the pilot, from Sept. 8 to 22. The mean time was 119.4 minutes with a standard deviation of 71.9 minutes. The sigma score was 2.46 with a yield of 83 percent. The team felt it could accomplish a greater impact, so the team members worked with nurses and addressed a few other issues:

  • The team set up an area for radiology to transmit reports directly from the triage area instead of going to another area of the hospital that has the capability to transmit reports. That avoided the delays that happened when the radiology technician was called to see another patient on their way to another area to post results.
  • Passive visual indicators were used in the form of plastic “we will return” clocks to let staff know when the patient is nearing their target time. Then a nurse could find out what the delay was and take action whether it is a pending test result, waiting for provider to visit or call, or other possible delays.

In and After the Project’s Control Phase

The project team analyzed 248 patient visits during the control phase from Oct. 5 to 24 with a mean of 93.1 minutes with a standard deviation of 53.8 minutes. The sigma score was 3.55 and a yield of 98 percent. The hospital had increased the customer satisfaction for the time it takes to register a patient from 67 percent to 91 percent and the amount of time it takes to triage a patient from 59 percent to 91 percent. The hospital also has had positive feedback from providers on the changes implemented and the turnaround time improvements.

Since the control phase, the hospital has continued to improve. The current sigma score is 3.99 with a 99 percent yield, and the mean time is 72.6 minutes with a standard deviation of 55.7 minutes. The hospital has developed two separate scorecards for nurses and providers that display each individual mean, standard deviation, population and number of defects every month. The labor and delivery nurse manager is strongly supportive of this initiative and has made it a priority for her department. She works with her nurses to meet the goal and keeps her staff informed of how they are performing. With continued vigilance and accountability, there is an anticipation of achieving 6.0 sigma performance by the end of the fiscal year.

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