DDHA 9500 Week 8 Feasibility Memo Example

Memorandum

To: Doctoral Project Committee Chair

From: DHA Student, Riverbend Health Project

Date: October 20, 2026

Re: Feasibility of the ambulance offload and boarding project

Finding in Brief

The project is feasible within three terms, provided a data use agreement with the county ambulance service is signed by the end of the first term. That agreement is the only permission outside the health system's control and is the main risk to the schedule. Every other element, the hospital data, the internal approvals and the analysis, can be completed with resources already available.

Data

Finding: the data exist, and the roles that control them have been identified.

The emergency department data, arrival times, triage acceptance times, patient age and hourly boarding counts, sit in the health system's enterprise data warehouse. Access is controlled by the director of enterprise analytics, who has confirmed that the boarding counts are already calculated for the operations dashboard and that a de-identified extract can be prepared once approvals are in place.

The ambulance data, the crew's arrival and transfer-of-care times, sit in the county ambulance service's electronic patient care record system. Access is controlled by the service's medical director and its privacy officer. The medical director has expressed interest, since the service has its own concerns about crews being held at hospitals, a concern the published literature shows is widely shared (Li et al., 2019), but has said that a written agreement is required.

The two items to be gathered on purpose, the dates of dedicated offload roles and a 100-arrival validation sample, depend on the three emergency department managers and on one health information management analyst for the chart review. All four have agreed in principle.

Permissions

Finding: five permissions are needed, in this order, and the external one takes longest.

First, the project's quality improvement or research determination from the health system's institutional review board office, usually two to three weeks for a retrospective review of de-identified data.

Second, approval from the emergency services executive director to use the departments' data and staff time, usually one to two weeks after the review board's determination.

Third, a data use agreement with the county ambulance service, specifying the fields shared, de-identification, storage and publication rights. Agreements of this kind between the health system and county agencies have taken six to ten weeks, because they pass through the county attorney's office.

Fourth, a data request to enterprise analytics, fulfilled within three weeks once the first two approvals are in hand.

Fifth, approval from the doctoral program for the prospectus itself, which the program requires before any data are analyzed.

The first, second and fourth can proceed while the third is negotiated.

Time

Finding: the work fits three eleven-week terms, with data access in the first and analysis in the second.

In the first term, the prospectus is completed and approved, the internal permissions are obtained and the data use agreement is negotiated. In the second term, the two data sources are extracted and linked, the validation sample is reviewed and the analysis is run. In the third term, results are written and the project is presented. If the ambulance agreement slips past the first term, the second term can begin with the hospital data alone, describing offload times recorded at triage and the boarding counts, and the linked analysis can follow when the agreement arrives, compressing the third term.

Support Needed

Finding: the project needs little beyond what the program and the health system already provide. Enterprise analytics will spend about twelve hours preparing and linking the extracts. The chart review for the validation sample will take a health information management analyst about two days. Statistical consultation is available through the program's methods support, which I will book for the start of the second term. No funding is required.

Risks to Completion

Finding: one risk is serious, and it has a fallback.

The serious risk is that the county ambulance service declines or delays the agreement. The fallback is to use the hospital's own record of when the triage nurse accepted the patient, together with the ambulance arrival time recorded at registration. That measure is weaker, because registration may occur after the ambulance arrives, and the validation sample would no longer be possible. Since a stand-in for the defined offload interval can mislead (Carter et al., 2014), the fallback would be reported as a limitation rather than presented as equivalent. A minor risk is linkage error between the two sources; the validation sample is designed to measure it. Cooney et al. (2011) emphasize that offload delay concerns both hospitals and ambulance services, which is also why the county service is likely to see value in the project and agree.

Recommendation

The committee chair is asked to approve proceeding with the prospectus and to support an early request to the county ambulance service, so that the agreement can be negotiated while the internal approvals are obtained.

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

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