| Course | PHLT 8064 Dissertation Seminar III |
|---|---|
| Week | Week 10 |
| Paper type | Feasibility memo |
| Length | About 1,010 words, 6 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | PhD in Public Health |
| Updated | October 2026 |
Free sample paper for PHLT 8064 Week 10
Feasibility Memo: Three Versions of One Drive-Time Registry Project on Infant Hearing Follow-Up, Each With the Approval Delay That Would Trigger It and the Claim That Would Survive
Student Name
Walden University
PHLT 8064: Dissertation Seminar III
Instructor Name
Month Day, Year
Feasibility Memo: Three Versions of One Drive-Time Registry Project on Infant Hearing Follow-Up, Each With the Approval Delay That Would Trigger It and the Claim That Would Survive
Why Three Versions
A registry study looks fast on paper because the data already exist. In practice it waits on approvals from several offices, each with its own calendar, and a dissertation that has only one version of the study has no answer when one of them runs late. This memo lays out what waits on what, then describes three versions of the same study and the specific delay that would move the work from one to the next. Bowen et al. (2009) list practicality and implementation among the questions a feasibility assessment should answer, and for secondary data the practical question is mostly about access.
What Waits on What
The review board step is the most predictable. Secondary research on identifiable information already collected for other purposes may qualify for exemption under the federal Common Rule when the investigator records data so that individuals cannot be identified (45 C.F.R. § 46.104), and the analytic file will be built that way. The data use agreement will specify a limited data set, which under the federal privacy rule may contain dates and geographic detail below the state level but not names or street addresses (45 C.F.R. § 164.514). Because drive time requires street addresses, geocoding must happen inside the state's secure environment before the limited data set is created, which is why it waits on vital records.
Table 1
Dependencies Between Approval and Analysis Steps
| Step | Office responsible | Waits on | Expected time | |
|---|---|---|---|
| Review board determination | University institutional review board | Final proposal approval | Four to six weeks | |
| Data use agreement | State screening program and its legal counsel | Review board determination | Two to four months | |
| Vital records approval for linkage | State vital records office | Data use agreement and its own review | Two to five months | |
| Geocoding and drive time | State secure computing environment | Vital records approval for addresses | Four weeks | |
| Analysis | Candidate, inside the secure environment | Geocoded analytic file | Three months | |
Note. Times are estimates from program staff for comparable recent requests; the two longest steps run partly in parallel once the data use agreement is signed.
The Full Version
The full version links every registry record to the birth certificate, geocodes the birth address, computes drive time and answers both research questions: whether longer drives go with fewer recorded evaluations by three months, and whether that association differs by payer. It uses the six birth years from 2017 through 2022 and the full covariate set, including maternal education and payer from the birth certificate.
Trigger
None; this is the plan if all approvals arrive by the end of March of the analysis year.
Claim That Survives
Everything in the purpose statement.
The Reduced Version
If vital records approval has not arrived by the end of March, linkage is dropped and the study runs on registry fields alone. The registry holds the infant's birth date, birth hospital, screening results, follow-up status and the address the program uses for contact, which can be geocoded inside the program's own environment. It does not hold maternal education, and its payer field is completed inconsistently. Harron et al. (2017) describe how losing a linked source can remove the very variables needed for confounding control, and that is what happens here.
Trigger
Vital records approval delayed past March 31.
Claim That Survives
The first research question, with weaker adjustment and an E-value reported prominently. The payer question weakens to a descriptive comparison among infants with a recorded payer, and the limitations will say so.
The Narrowed Version
If the data use agreement itself stalls, the cohort shrinks rather than the variables. The registry changed software in mid-2018, and records from before the change require a separate extraction and recoding that program staff estimate adds six weeks. In the narrowed version, births before July 2018 are dropped, leaving about four and a half birth years.
Trigger
Data use agreement unsigned by the end of January.
Claim That Survives
Both research questions, over a shorter period with less power. The sampling plan's sensitivity calculation will be rerun for the smaller cohort and the new smallest detectable odds ratio reported.
The Candidate's Own Position
The author works inside the screening program, which helps and complicates feasibility. It helps because the author knows the registry's fields, codes and staff. It complicates because a program employee requesting program data for a dissertation must keep the two roles separate. The data use agreement will name the author as an outside researcher under university oversight, the analysis will be done on the de-identified file rather than through the author's work access, and the program's director rather than the author will approve the request. Those steps add time but protect both the study and the program.
Risks Outside the Approvals
Approvals are the largest risk but not the only one. The secure computing environment limits each outside user to a set number of sessions a week, and the routing software must be installed by state information technology staff, which program staff say takes about a month to schedule. The request for installation will be filed with the data use agreement so the two run together. A second risk is that the facility list changes during the study period, as sites open or close. The list for each birth year will be fixed from the program's annual reports, and drive time will be computed against the sites operating in the infant's birth year rather than today's list. A third risk is the author's own time. Analysis is planned for the months when the program's annual federal report is not due, and the chair has agreed to monthly meetings during that period.
Decision Dates
The dates above are written into the timeline so that switching versions is a scheduled decision rather than a reaction. On each trigger date the author and chair will review the status of the relevant approval and record which version proceeds.
References
Bowen, D. J., Kreuter, M., Spring, B., Cofta-Woerpel, L., Linnan, L., Weiner, D., Bakken, S., Kaplan, C. P., Squiers, L., Fabrizio, C., & Fernandez, M. (2009). How we design feasibility studies. American Journal of Preventive Medicine, 36(5), 452-457. https://doi.org/10.1016/j.amepre.2009.02.002
Exempt research, 45 C.F.R. § 46.104 (2024).
Harron, K., Dibben, C., Boyd, J., Hjern, A., Azimaee, M., Barreto, M. L., & Goldstein, H. (2017). Challenges in administrative data linkage for research. Big Data & Society, 4(2), 1-12. https://doi.org/10.1177/2053951717745678
Other requirements relating to uses and disclosures of protected health information, 45 C.F.R. § 164.514 (2024).
The Walden PHLT 8064 Week 10 instructions
The tenth week calls for a feasibility memo assessing whether the dissertation can be completed as planned within the program timeline. Faculty expect the memo to identify the approvals, data access steps and resources the study depends on, estimate how long each takes and show how they depend on one another. Candidates using secondary data should address data use agreements, review board determinations and any linkage or geocoding that requires secure environments. Strong memos plan for things going wrong, naming fallback versions of the study and the point at which each would be adopted. Any conflict between the candidate's employment and the research should be disclosed and managed. Three to five pages with a timeline or dependency table is common, and the memo should cite feasibility frameworks and the relevant regulations.
How this PHLT 8064 Week 10 example is built
The memo opens by explaining why a registry study needs more than one version, citing Bowen and colleagues on feasibility questions. Table 1 lays out the dependencies between approvals and analysis steps, and the text explains the exemption category under the Common Rule and the limited data set rules under the privacy regulations, noting why geocoding must precede de-identification. Three versions follow under matching headings, each with a description, a trigger and the claim that survives; Harron and colleagues are cited on what losing a linked source removes. A section on the author's position separates program employment from research access. Risks beyond approvals, including software installation, a changing facility list and the author's workload, are addressed. The memo closes by fixing decision dates on the timeline so switching versions is planned.
Where the marks sit in the PHLT 8064 Week 10 rubric
Graders look for realism. A feasibility memo that assumes every approval arrives on schedule earns less than one that names the likely delays and plans for them. The sample scores by attaching a concrete trigger date and a surviving claim to each version, which turns contingency into a scheduled decision. Accuracy about regulatory pathways is checked, so exemption categories and limited data set rules must be described correctly and cited. Disclosing and managing the author's employment by the program earns credit under ethics criteria. Attention to nonregulatory risks, such as software and staffing, shows thoroughness. The dependency table is judged on clarity. The final points cover use of feasibility literature, the logical order of sections and APA style, including correct citation of federal regulations.
PHLT 8064 Week 10 help: mistakes that cost marks
Feasibility memos lose credibility when they treat approvals as formalities. Data use agreements, vital records requests and secure environment access each run on their own calendars, and a dissertation built on one optimistic timeline has no plan when the first one slips. Write down each dependency and its likely duration. Decide in advance what version of the study you will run if a step is late, and what claim that version supports. Candidates who work for the data owner face an extra issue, separating work access from research access, and committees notice when it is not addressed. Remember practical risks too, from software installation to your own workload in busy months. If your study relies on surveys or partner sites instead of records, we can prepare a free custom feasibility memo matched to those risks.
Get a PHLT 8064 Week 10 example written to your instructions
Describe every approval, data source and person your study depends on, and include the Week 10 memo instructions and rubric. The memo charts the dependencies, writes design variants in parallel with dated triggers and says what each can still claim. The first memo is free, ready inside 24 to 48 hours. Approvals remain yours to seek, and the program described is invented.
More PHLT 8064 papers and PhD in Public Health samples
- PHLT 8064 Week 1: Research Question Reading Post
- PHLT 8064 Week 2: Purpose Statement Rebuild
- PHLT 8064 Week 3: Design Comparison Paper
- PHLT 8064 Week 4: Method Defense Paper
- PHLT 8064 Week 5: Registry Sampling Plan
- PHLT 8064 Week 6: Measurement Memo
- PHLT 8064 Week 7: Alignment Table Check
- PHLT 8064 Week 8: Analysis Plan
- PHLT 8064 Week 9: Peer Design Critiques
- PHLT 8064 Week 11: Chapter 3 Method Draft
- PHLT 8062 Week 10: Narrowed Gap Statement
- PHLT 8060 Week 10: Problem-Question Alignment Check
- PHLT 8048 Week 10: Falsifiable Prediction Memo
- PHLT 8046 Week 10: Resubmission Response to Review
PHLT 8064 Week 10 questions, answered
Why plan several versions of the study instead of one?
Because approvals for linked administrative data often take longer than a dissertation calendar allows, and a plan with no alternative stalls entirely when one approval is late. The example writes three versions in advance, each with a trigger, so the decision to switch is made now, calmly, rather than later under pressure. Committees generally read that as preparedness. Keep every version answering a recognizable form of the original question.
How does a data use agreement differ from review board approval?
A data use agreement is a contract with the data owner, here the state screening program, setting out what data will be shared, how they will be protected and how they may be used. Review board approval, or a determination that review is not required, comes from your university and concerns the protection of the people in the data. The example needs both, plus a separate vital records approval for linkage.
Can I use data I already have access to at work?
Not for research without the approvals research requires. Access granted for program operations does not extend to a dissertation, even when the records are the same. The example routes every record through the formal agreement and says so in the memo. Discuss your position with your committee and your employer early; the approvals themselves are steps only you and your institution can take.
Where can I find a free PHLT 8064 Week 10 sample paper?
The entire Week 10 feasibility memo is on this page: three versions of one registry project about travel time and diagnostic hearing visits, each with the approval delay that triggers it and the claim it keeps. The dependency table and the regulatory citations are included.
What is a limited data set?
Under the federal privacy rule, a limited data set strips direct identifiers such as names and street addresses while allowing dates and geography finer than the state level. It can be shared for research under a data use agreement. The sample computes drive time from street addresses inside the secure environment before creating one.