DDHA 9500 Week 6 Literature Summary Example

Course	DDHA 9500 DHA Project Prospectus
Week	Week 6
Paper type	Literature summary by claim
Length	About 1,020 words, 6 pages
Format	APA 7 student paper
School	Walden University
Program	Doctor of Healthcare Administration (DHA)
Updated	October 2026

Free sample paper for DDHA 9500 Week 6

Three Claims the Offload Project Rests On and the Sources Behind Each: A Literature Summary Organized by Argument, With the Disagreements Kept Beside the Agreements

Student Name

Walden University

DDHA 9500: DHA Project Prospectus

Instructor Name

Month Day, Year

What this page is doingThe title signals a summary organized by the claims the argument needs rather than by author, which is the version that survives into a short prospectus.

Three Claims the Offload Project Rests On and the Sources Behind Each: A Literature Summary Organized by Argument, With the Disagreements Kept Beside the Agreements

Purpose of This Summary

This summary supports a prospectus on the association between emergency department boarding and ambulance patient offload time at three hospitals of a composite regional health system. It is organized around the three claims the argument depends on, not around individual articles. Each source is described by what it measured, where and how recently, so that a reader can judge how well it fits this project. Sources that disagree are discussed in the same section as those they disagree with.

Claim 1: Offload Delay Is Common and Varies Widely Between Hospitals

The project assumes that offload delay is a real and widespread problem, not a local anomaly. Three sources support this. Feldmeier et al. (2024) analyzed ambulance patient offload times reported across California's local emergency medical services agencies, using data from the state's reporting system, and found wide variation between agencies and hospitals. This is the most recent and largest source, but it covers one state, whose reporting rules and hospital capacity differ from those of the project's setting. Cooney et al. (2013) measured offload intervals at a single university hospital emergency department in the United States, showing that delays occurred there as well. It is older and from one site, so it establishes that the problem exists in a U.S. hospital rather than how common it is. Li et al. (2019) reviewed the published literature on offload delay, drawing on studies from Canada, Australia, the United Kingdom and the United States, and found the problem reported across many health systems. Together, the sources support the claim that offload delay is common and variable, while none measures it in the project's state.

Claim 2: Offload Delay Arises Mainly From Conditions Inside the Hospital

The project's purpose rests on the claim that hospital conditions, especially boarding, are the main driver of offload delay, so that examining boarding is the right place to look. Li et al. (2019) are the central source: most studies in their review linked offload delay to emergency department crowding and to access block, meaning admitted patients who cannot leave the department because no ward bed is ready. Asplin et al. (2003), in a widely used conceptual model of emergency department crowding, place boarding of admitted patients in the output component and describe how blocked output backs up through the department to its front door, which is where ambulances arrive. Hoot and Aronsky (2008), in a systematic review of emergency department crowding, identify inpatient boarding as one of the most consistently reported causes of crowding.

Not all sources place the cause entirely inside the hospital. Greaves et al. (2017), evaluating a dedicated ambulance offload nurse role at an Australian emergency department, found offload performance changed after the role was introduced, which suggests that how the department organizes the handover itself, not only boarding, affects offload time. Li et al. (2019) also note that some interventions move the delay from the ambulance bay to inside the department rather than removing it. The disagreement matters for this project: if the handover process explains much of the delay, the association with boarding may be weaker than expected, and the approach should record whether each hospital had a dedicated offload role during the study period.

Claim 3: Offload Time Must Be Measured as a Defined Interval

The project's outcome depends on measuring offload time consistently. Cooney et al. (2011), in the resource document for a national emergency medical services physicians' position statement, discuss offload delay as the interval during which a patient remains in the care of the ambulance crew after arrival at the hospital, and describe the hospital's responsibility for that patient. Feldmeier et al. (2024) used a defined offload interval from arrival to transfer of care, as reported under California's rules. Carter et al. (2014) tested turnaround time, the interval until the ambulance drives away, as a stand-in for offload time, and their results argue against the substitution, since turnaround also covers cleaning, restocking and paperwork after the handover. This claim supports defining the outcome as arrival to transfer of care, using time stamps from both the hospital and the ambulance service, rather than relying on the ambulance service's turnaround data alone.

What These Sources Do Not Cover

Four gaps matter for this project. First, the large recent analyses come from California, and no comparable published data exist for the project's state, so the local prevalence of delay must be established by the project itself. Second, none of the sources examines the association between boarding and offload time hour by hour; most link offload delay to crowding in general or describe it at the level of days or hospitals. Third, the sources say little about the effect of offload delay on response times in the communities served, which the project's significance section mentions but will not measure. Fourth, the recent study by Shteyler et al. (2025), which found offload times differing with the race and income profile of the patients hospitals serve, raises an equity question that this project's design could examine only partly, by comparing the three hospitals. These gaps define the project's contribution and its limits.

How the Sources Were Found

The sources were located through searches of PubMed and the CrossRef database using combinations of "ambulance offload," "offload delay," "ambulance patient offload time" and "emergency department crowding," limited to English-language publications, with reference lists of the review by Li et al. (2019) checked for additional studies. Conference abstracts were excluded because they rarely report enough method to judge fit. The search will be repeated before the final prospectus is submitted, since the California work suggests the field is active.

How the Summary Will Be Used

The three claims map onto three parts of the prospectus. Claim 1 supports the problem and significance sections. Claim 2 supports the choice of boarding as the exposure in the purpose statement, while the disagreement in that section shapes a control variable in the approach. Claim 3 supports the outcome definition and the data plan.

References

Asplin, B. R., Magid, D. J., Rhodes, K. V., Solberg, L. I., Lurie, N., & Camargo, C. A. (2003). A conceptual model of emergency department crowding. Annals of Emergency Medicine, 42(2), 173-180. https://doi.org/10.1067/mem.2003.302

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

Cooney, D. R., Wojcik, S., Seth, N., Vasisko, C., & Stimson, K. (2013). Evaluation of ambulance offload delay at a university hospital emergency department. International Journal of Emergency Medicine, 6, Article 15. https://doi.org/10.1186/1865-1380-6-15

Feldmeier, M., Reyes, K. P., Chen, C., Sporer, K. A., Konik, Z., Garzón, H., & Hsia, R. Y. (2024). Patterns in California ambulance patient offload times by local emergency medical services agency. JAMA Network Open, 7(12), Article e2451022. https://doi.org/10.1001/jamanetworkopen.2024.51022

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

Hoot, N. R., & Aronsky, D. (2008). Systematic review of emergency department crowding: Causes, effects, and solutions. Annals of Emergency Medicine, 52(2), 126-136. https://doi.org/10.1016/j.annemergmed.2008.03.014

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

Shteyler, V. M., Feldmeier, M., Bagay, R. J. G., Ballard, D., Colwell, C., & Hsia, R. Y. (2025). Racial and socioeconomic disparities in California ambulance patient offload times. JAMA Network Open, 8(5), Article e2510325. https://doi.org/10.1001/jamanetworkopen.2025.10325

DDHA 9500 Week 6 instructions, in plain terms

Literature summaries in a prospectus are usually short, and the strongest ones are organized around the claims your argument depends on. Identify those claims, typically two to four, and write each as a sentence. Under each, discuss the two or three sources that support it, describing what each measured, in what setting and how recently, so readers can judge fit. Keep sources that disagree in the same section as those they contradict, since separating them hides the disagreement a reader most needs to see. Add a paragraph on what the sources do not cover, because that defines your contribution. Close by showing where each claim will be used in the prospectus. Explain briefly how the sources were found.

Inside the DDHA 9500 Week 6 example

The summary opens by explaining its claim-based organization. The first section describes the California analysis, a single-site U.S. study and an international review, noting the limits of each for this setting. The second presents the review's link to access block, the conceptual model of crowding and a crowding review, then discusses the offload nurse study and the possibility of moving delay inside the department, explaining how this shapes a control variable. The third discusses defining offload as arrival to transfer of care and why turnaround time is a poor substitute. A gaps section lists four missing pieces, including the equity question. A short search section describes databases and limits, and a final section maps each claim to a part of the prospectus.

Reading the DDHA 9500 Week 6 rubric

Literature summaries are graded on synthesis. Organization by claim rather than by article is expected at this level and earns substantial credit. Each source should be characterized by what it measured, where and when, which lets readers judge relevance. Keeping disagreements with the claims they challenge shows intellectual honesty. A section on what the literature does not cover is often decisive, since it justifies the project. Links between claims and later sections of the prospectus show coherence. Sources should be current where the field moves quickly and should be cited accurately in APA style. Graders also notice whether recency matters to the claim and whether the writer says so.

DDHA 9500 Week 6 help from the desk

The most common mistake is an annotated bibliography in paragraph form, one article after another. Decide what claims your argument needs and organize around them. Describe each source by setting, measure and date rather than praising it. Put contradicting evidence next to the evidence it contradicts. Be honest about gaps; they are your opportunity. Say how you searched. If you have collected articles but cannot see how to organize them, we can build a claim-based summary from your reading list. Before submitting, check that each claim heading is a full sentence your argument actually uses. If a claim would not be missed from the prospectus, cut it and its sources. Then confirm that every source in your list is discussed somewhere under a claim.

Get a DDHA 9500 Week 6 example written to your instructions

Send over the prompt, the rubric and the claims the document has to support, and a summary organized by claim, with each source characterized and the gap stated plainly, comes back to you. Nothing is charged for the first, and it takes 24 to 48 hours. Reading lists come from the classroom, and no unpublished internal report is requested to fill them.

More DDHA 9500 papers and DHA samples

DDHA 9500 Week 6 questions, answered

Where can I find a free DDHA 9500 Week 6 sample paper?

The claim-based literature summary for the offload project is free to read on this page.

What three claims does the DDHA 9500 Week 6 example support?

That offload delay is common and variable, that it arises mainly inside hospitals and that it must be measured as a defined interval.

Which source partly disagrees with the second claim?

A study of an offload nurse role, suggesting the handover process itself also affects offload time.

What gaps does the summary identify?

No hour-by-hour analysis of boarding and offload, no data for the project's state and limited work on community response times and equity.

Why keep disagreeing sources together?

Separating them would hide the disagreement a reader most needs to see.