HLTH 4913 Module 3 Capstone Cause and Options Analysis Example

Booked Before Discharge Changed More Than the Ride Did: A Capstone Analysis of Causes and Options for Seven-Day Heart Failure Follow-Up

Student Name

American College of Education

HLTH4913: Senior Capstone Experience: Healthcare Administration

Module 3 Assignment

Instructor Name

October 19, 2026

What the Baseline Data Show

The capstone proposal planned to confirm the problem with a year of record data, and the quality department supplied it. Of 762 heart failure patients sent home from the composite community hospital in the past twelve months, 58% had an appointment on their discharge papers when they left, and 55% of those kept it within seven days. Of the 42% who left without a booked appointment, only 21% were seen within the week. Those two groups together produce the hospital's overall figure of 41%. Readmission within 30 days was 19.6% among patients seen within seven days and 26.8% among those who were not, a difference consistent with the national literature, though this simple comparison does not adjust for how sick the two groups were.

The structured phone survey reached 150 patients who missed follow-up. Transportation was named first by 34%, not knowing about or forgetting the appointment by 27%, feeling too unwell or tired to go by 14%, feeling well enough not to need it by 12%, cost by 6%, and other reasons by 7%.

Cause-and-Effect Analysis

The quality improvement course taught the cause-and-effect diagram, and it helps organize these findings. Under methods: appointments are booked only when a unit secretary has time, and there is no rule that every patient leaves with one. Under people: discharge nurses do not ask about transportation, and care coordinators reach only about 60% of patients by phone. Under equipment and information: phone numbers in the record are often outdated, and the discharge paperwork lists the appointment on page four. Under environment: the last bus leaves before dinner, and whole townships have no route at all. Under patients: fatigue after hospitalization, limited understanding of why the visit matters, and no caregiver available on weekdays.

A Pareto view of the survey shows that two causes, transportation and not knowing about the appointment, account for 61% of missed visits. The single strongest lever in the data is not the ride; it is whether the patient walks out the door with an appointment in hand. The second cause is largely a process problem inside the hospital, which makes it cheaper to fix than the first.

Who Faces Which Barrier

Stratifying the data by payer changes the transportation picture. About 14% of the patients are dually eligible for Medicare and Medicaid and so have a Medicaid transportation benefit, but none of the 11 dual-eligible patients in the survey who cited transportation had used it, and most did not know it existed. About 38% have Medicare Advantage plans, several of which include a limited number of rides to medical appointments. The 44% in traditional Medicare have no transportation benefit. Patients living more than 15 miles from the clinic, 29% of the total, missed follow-up at nearly twice the rate of those living closer. A transportation solution therefore needs three routes: activating existing Medicaid and Medicare Advantage benefits, and funding rides for patients who have none.

Stakeholder Views

The options also have to survive the people who would carry them out, so the capstone held short interviews with six stakeholders, applying the stakeholder analysis learned in the management course. Hospitalists supported booking every appointment before discharge but worried about adding steps on busy discharge days; they asked that the rule not delay a patient who is otherwise ready to leave. Discharge nurses said they would ask about transport if the answer went somewhere useful rather than onto a form nobody read. Care coordinators were enthusiastic about a navigator role but noted that their current caseload leaves no room, so it must be a funded position. The cardiology practice manager said the practice could hold two same-week slots a day for hospital discharges if the hospital's schedulers could book them directly. The finance director asked for a cost estimate tied to readmission penalties, which the next module provides. Each view is reflected in how the options are designed and ranked below.

Five Options

Five options emerge from the causes and the literature. Option A is a discharge rule that every heart failure patient leaves with a booked appointment within seven days, shown on the first page of the discharge papers; it requires a change to the electronic record and about 20 hours of informatics work. Option B is a transportation navigator, a half-time care coordinator who asks every patient about transport before discharge and books a ride through the Medicaid broker, the patient's Medicare Advantage plan or a hospital-funded service; it costs about $32,000 a year in staff time plus an estimated $9,100 for about 120 round trips for patients with no benefit. Option C is a nurse home visit within three days for the highest-risk quarter of patients, about 190 visits a year at roughly $180 each, or $34,200. Option D is a video visit alternative for patients who cannot travel, using the practices' existing telehealth platform. Option E is a hospital-based heart failure clinic with guaranteed slots within the week, the most expensive option, requiring a nurse practitioner and space.

Weighing the Evidence

The literature review shapes how the options should be judged. Van Spall et al. (2017) found in a network meta-analysis that nurse home visits reduced all-cause readmissions and deaths after heart failure hospitalization and had the largest pooled cost savings, with disease management clinics also effective. Feltner et al. (2014) similarly found strong evidence for home-visiting programs and multidisciplinary clinics. By contrast, a trial of free rideshare trips for Medicaid primary care patients found low uptake and no change in missed appointments (Chaiyachati et al., 2018). The evidence therefore supports Options C and E most strongly, supports Option B only as part of a broader transition process, and offers no direct trial evidence for A or D, which rest on the hospital's own data and common sense.

Decision Matrix

A weighted decision matrix, a tool from the leadership course, compares the options on five criteria scored from one to five: strength of evidence, weighted 30%; cost, 20%; feasibility within one year, 20%; reach across patients, 15%; and effect on equity, 15%. Option A scored 3.9, high on cost, feasibility and reach but lower on evidence. Option B scored 3.5, with strong equity and reach but moderate evidence. Option C scored 3.8, with the strongest evidence but limited reach because it serves only the highest-risk quarter. Option D scored 3.2, cheap and feasible but untested and unsuited to patients without devices. Option E scored 2.9, well supported by evidence but low on cost and feasibility within a year.

The scores point to a bundle rather than a single choice: Option A for every patient, Option B to connect transport benefits and fill gaps, Option C for the highest-risk patients, and Option D as a backup when travel fails. Option E is deferred as a longer-term goal if the bundle succeeds.

References

Chaiyachati, K. H., Hubbard, R. A., Yeager, A., Mugo, B., Lopez, S., Asch, E., Shi, C., Shea, J. A., Rosin, R., & Grande, D. (2018). Association of rideshare-based transportation services and missed primary care appointments: A clinical trial. JAMA Internal Medicine, 178(3), 383-389. https://doi.org/10.1001/jamainternmed.2017.8336

Feltner, C., Jones, C. D., Cené, C. W., Zheng, Z.-J., Sueta, C. A., Coker-Schwimmer, E. J. L., Arvanitis, M., Lohr, K. N., Middleton, J. C., & Jonas, D. E. (2014). Transitional care interventions to prevent readmissions for persons with heart failure: A systematic review and meta-analysis. Annals of Internal Medicine, 160(11), 774-784. https://doi.org/10.7326/M14-0083

Van Spall, H. G. C., Rahman, T., Mytton, O., Ramasundarahettige, C., Ibrahim, Q., Kabali, C., Coppens, M., Haynes, R. B., & Connolly, S. (2017). Comparative effectiveness of transitional care services in patients discharged from the hospital with heart failure: A systematic review and network meta-analysis. European Journal of Heart Failure, 19(11), 1427-1443. https://doi.org/10.1002/ejhf.765