DDHA 9500 Week 7 Approach Outline Example

Approach Outline for the Offload Project: A Retrospective Design Sized to Its Question, Existing Data Set Against the Little That Must Be Gathered, and What the Design Cannot Show

Student Name

Walden University

DDHA 9500: DHA Project Prospectus

Instructor Name

Month Day, Year

Approach Outline for the Offload Project: A Retrospective Design Sized to Its Question, Existing Data Set Against the Little That Must Be Gathered, and What the Design Cannot Show

Design

The project will use a quantitative, retrospective observational design. It matches the verb in the purpose statement, "examine the association," because it can show whether offload times are longer when more admitted patients are boarding, without claiming to show that boarding causes the delay. No intervention is introduced, and no patient or staff member is contacted.

Data That Already Exist

Most of the data are produced in the ordinary course of operating. From the health system's emergency department records come arrival time, the time the triage nurse accepted the patient from the ambulance crew, the hospital, and patient age, for every adult arriving by ambulance over 24 months. From the same records comes an hourly count of admitted patients still in each emergency department, already calculated for the system's operations dashboard. From the county ambulance service's electronic patient care records come the crew's recorded arrival at the hospital and the crew's recorded transfer of care. The two sources will be linked by hospital, date and arrival time within a short window, a method the system's analytics team already uses for other ambulance reports.

Data That Must Be Gathered

Only two items must be gathered on purpose. The first is a list of the periods during which each hospital had a dedicated ambulance offload nurse or similar role, to be obtained from the emergency department managers, because the literature suggests such roles affect offload time (Greaves et al., 2017). The second is a validation sample: for 100 randomly selected arrivals, a chart review comparing the hospital's transfer-of-care time with the ambulance service's, to estimate how closely the two sources agree.

Unit of Analysis

The unit of analysis is the individual adult ambulance arrival. Each arrival has one offload time, measured from the crew's arrival at the hospital to transfer of care, and one exposure value, the number of admitted patients boarding in that department during the hour of arrival. Carter et al. (2014) caution against using ambulance turnaround time in place of offload time, so the outcome uses the two time stamps that bracket the handover itself.

Comparison

The central comparison is between offload times during hours with different boarding counts, within each hospital. Hours will be grouped by boarding count, and offload times compared across groups, adjusting for hour of day, day of week, month and whether an offload role was in place. Comparing within hospitals avoids confusing differences between hospitals, such as size and layout, with the effect of boarding. A secondary comparison will describe how offload times differ among the three hospitals.

Analysis in Brief

Offload times are typically skewed, with a long tail of very long waits, so results will be reported as medians and as the share of arrivals exceeding 30 minutes, the interval used in emergency medical services guidance (Cooney et al., 2011). The association will be estimated with regression models suited to skewed times and to a yes-or-no outcome for exceeding 30 minutes, with standard errors that account for arrivals in the same hour.

What the Approach Cannot Show

The design can show whether offload times are longer when boarding is higher. It cannot show that reducing boarding would shorten offload times, because other conditions that rise with boarding, such as overall emergency department volume, may explain part of the association even after adjustment. It cannot measure the effect of offload delay on ambulance response times in the community or on patient outcomes. And it cannot explain why one hospital performs differently from another beyond the variables recorded. Li et al. (2019) note that offload delay has many contributing factors, so a single exposure will not account for all of it. These limits will be stated in the prospectus so that reviewers judge the project against what it can deliver.

References

Carter, A. J. E., Overton, J., Terashima, M., & Cone, D. C. (2014). Can emergency medical services use turnaround time as a proxy for measuring ambulance offload time? The Journal of Emergency Medicine, 47(1), 30-35. https://doi.org/10.1016/j.jemermed.2013.08.109

Cooney, D. R., Millin, M. G., Carter, A., Lawner, B. J., Nable, J. V., & Wallus, H. J. (2011). Ambulance diversion and emergency department offload delay: Resource document for the National Association of EMS Physicians position statement. Prehospital Emergency Care, 15(4), 555-561. https://doi.org/10.3109/10903127.2011.608871

Greaves, T., Mitchell, M., Zhang, P., & Crilly, J. (2017). The impact of an emergency department ambulance offload nurse role: A retrospective comparative study. International Emergency Nursing, 32, 39-44. https://doi.org/10.1016/j.ienj.2016.12.005

Li, M., Vanberkel, P., & Carter, A. J. E. (2019). A review on ambulance offload delay literature. Health Care Management Science, 22(4), 658-675. https://doi.org/10.1007/s10729-018-9450-x