Original article
Impact of Average Patient Acuity on Staffing of the Phase I PACU

https://doi.org/10.1016/j.jopan.2006.07.007Get rights and content

The authors consider methods for determining staffing requirements for a Phase I PACU. Given that the total number of nursing hours per day is limited by budgetary constraints, PACU staffing can be adjusted to minimize the percentage of days that the PACU is full and cannot accept additional patients from the OR. Except for very small PACUs, the number of staffing options is so large that computer optimization methods must be used. In addition, patient acuity must be incorporated into the staffing plan. Methods are described for adjusting staffing requirements when some patient acuities differ from 1 nurse:2 patients, when patients transition from one acuity to another, and when acuity is not known for all patients.

Section snippets

Background

The number of nurses in the Phase I PACU should be chosen to ensure that the PACU meets staffing guidelines and accommodates all patients from the ORs on the majority of days (95%-99%). The frequency of delays must be balanced against the relative costs of an hour of OR time and an hour of PACU staffing. Prevention of all delays is not cost-effective and is virtually impossible to achieve without a large excess in the number of nurses staffing the PACU.

For smaller PACUs (ie, with less than 4

Patient Acuity

What the preceding section does not describe, and the existing literature does not consider, is how to incorporate patient acuity into the staffing plan. A recent article reported disturbing results that some PACUs may have staffing that is inadequate to care for existing patients, given their physiologic condition.4

According to the ASPAN guideline for Phase I PACU care,5 a minimum of two licensed nurses should be present at all times when patient care is provided, even if the number of

Example of PACU Staffing Optimization

A 28-OR facility had 205 staffed PACU hours per workday. A delay in PACU admission occurred on 59% of 96 consecutive workdays in 2004.

Nurses worked 8-, 10-, and 12-hour shifts starting at 6 am, 7 am, 8 am, 9 am, 10 am, 11 am, 12 pm, 1 pm, 3 pm, 4 pm, 9 pm, and 11 pm. A prospective survey of patient acuity was performed. Using the previous methods, average patient acuity was 1:1.77, representing a mixture of 1:1 and 1:2 patients.

The analysis described in the Background was performed using these

Conclusions

Because the total number of PACU nursing hours per day is limited by budget constraints, delays in admission from the OR cannot be eliminated entirely. PACU staffing can be adjusted so that 5% is the maximum percentage of days that the PACU is full and cannot accept additional patients from the OR. Optimal staffing options attempt to achieve this goal with a minimum of PACU nursing hours. Except for very small PACUs, these options cannot be determined manually because potential combinations of

Franklin Dexter, MD, PhD, is Director, Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, IA, USA and Professor, Departments of Anesthesia and Health Management & Policy, University of Iowa, Iowa City, IA

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Franklin Dexter, MD, PhD, is Director, Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, IA, USA and Professor, Departments of Anesthesia and Health Management & Policy, University of Iowa, Iowa City, IA

Ruth E. Wachtel, PhD, MBA, is Associate Professor, Department of Anesthesia, University of Iowa, Iowa City, IA

Richard H. Epstein, MD, is Professor, Department of Anesthesiology, Jefferson Medical College, Philadelphia, PA, and President, Medical Data Applications, Ltd., Jenkintown, PA.

1

F.D. is Director of the Division of Management Consulting, which is a Division of the Department of Anesthesia at the University of Iowa. He receives no funds personally other than his salary from the State of Iowa, including no travel expenses or honoraria, and has tenure with no incentive program.

2

R.H.E. is President of Medical Data Applications, Ltd., which developed the CalculatOR™ software that was used to perform one of the analyses described in this article.

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