| Course | NUR 650 Care Coordination and Outcomes Management |
|---|---|
| Module | Module 7 |
| Paper type | milestone paper planning the evaluation of a care coordination program |
| Length | About 1,040 words, 6 pages |
| Format | APA 7 student paper |
| School | Southern New Hampshire University |
| Program | MSN |
| Updated | September 2026 |
Free sample paper for NUR 650 Module 7
Milestone Three: Evaluating a Heart Failure Transitional Care Bundle in the Context of National Readmission Policy
[Student Name]
Southern New Hampshire University
NUR 650: Care Coordination and Outcomes Management
Module Seven Milestone Three
[Instructor Name]
[Date]
Milestone Three: Evaluating a Heart Failure Transitional Care Bundle in the Context of National Readmission Policy
The simplest way to evaluate a readmission program is to compare the rate before and after it starts. The simplest way can also be wrong. Readmission rates change for many reasons: national policy, changes in how patients are classified, shifts in the patients a hospital serves and chance. At Brookhaven, the composite regional hospital launching a tiered heart failure bundle, leaders plan to report the change in readmission rate from the year before launch to the year after. This milestone designs a stronger evaluation. It argues that a credible evaluation must account for trends already under way, for patients being placed in observation instead of admitted and for the possibility that fewer readmissions come with more deaths, and that an interrupted time series design with comparison and balancing measures can do this within a hospital's resources.
The Policy Context
Since 2012, the Hospital Readmissions Reduction Program has reduced Medicare payments to hospitals with higher-than-expected readmission rates for targeted conditions, including heart failure. Zuckerman et al. (2016) examined Medicare data from 2007 through 2015 and found that readmission rates for targeted conditions fell from 21.5% to 17.8%, with the steepest decline around the time the program was enacted, while rates for nontargeted conditions fell less, from 15.3% to 13.1%. Over the same period, the use of observation stays increased. The authors did not find that hospitals with larger increases in observation stays had larger decreases in readmissions, but the rise shows that a patient who returns to the hospital may be counted differently depending on classification. For Brookhaven, this means that part of any decline may reflect national pressure and trends rather than the bundle, and that observation returns must be counted alongside readmissions.
The Possibility of Harm
A program that reduces readmissions could, in principle, discourage appropriate admissions. Gupta et al. (2018) analyzed heart failure patients in a national registry linked to Medicare claims and found that the announcement and implementation of the readmission program were associated with lower 30-day and one-year readmission rates, but also with higher 30-day and one-year mortality after discharge. The finding does not prove that the program caused deaths, and later studies have disagreed, yet it makes the case for tracking deaths whenever readmission is the target. Brookhaven's evaluation will report 30-day mortality after discharge next to readmission every month, and any sustained rise will trigger a review of whether patients who needed admission were being sent home.
An Interrupted Time Series Design
Penfold and Zhang (2013) describe interrupted time series analysis as a way to evaluate quality improvement when randomization is not possible. Data are collected at regular intervals before and after an intervention, and the analysis estimates whether the level or slope of the series changed at the point of the intervention, taking the existing trend into account. Its advantage over comparing two annual rates is that it shows whether the change departs from the trajectory already under way. It is strengthened further by a comparison series that is exposed to the same outside forces but not to the intervention.
Brookhaven will use monthly readmission rates for 36 months before and 18 months after launch. The comparison series will be 30-day readmission for patients with pneumonia, another condition targeted by the national program and therefore subject to the same policy pressure, but not included in the bundle. If heart failure readmissions fall more steeply after launch than their prior trend predicts, while pneumonia readmissions continue on their prior course, the case that the bundle caused the change is much stronger. Because monthly counts are small, the analysis will be done with help from the health system's analytics team, and results will be reported with confidence intervals.
What Will Be Measured and Reported
The evaluation will draw on the measurement set from Module Six. Readmission for any cause within 30 days of an eligible heart failure discharge is the main outcome, counted across the regional data exchange. Alongside it will be observation returns within 30 days, 30-day emergency visits without admission and 30-day mortality after discharge, so that a fall in readmissions cannot be credited if it is offset by more observation stays, more emergency visits or more deaths. Process measures, including the all-or-none universal bundle rate, will show whether the bundle was delivered. The evaluation will also compare results for patients in the high-risk tier with those in the universal tier and will examine results by payer, race and rural residence to see whether any group benefits less.
Interpreting Results
The team agreed before launch how results will be read. Credit will be given to the bundle only if heart failure readmissions depart from their prior trend more than the comparison condition does, if observation returns and emergency visits do not rise enough to offset the change, if mortality does not increase and if process measures show that the bundle was delivered to most patients. If readmissions fall but the bundle was poorly delivered, the fall will be attributed to other causes. If the bundle was delivered well but readmissions did not change, the team will review whether the causes identified in Module Three have changed or whether the bundle's components need revision. Writing these rules in advance protects the evaluation from being interpreted to fit what leaders hope to see.
Reporting and Use
Results will be reported quarterly to the quality committee and the heart failure team with run charts for process measures and the time series for outcomes, and annually to the hospital board with a one-page summary of what the evaluation shows and what it cannot show. Financial analysis will estimate the change in readmission penalties and the cost of the bundle, using the same cautious attribution rules.
Conclusion
A readmission rate that falls after a program launches is not proof the program worked. National policy was already pushing rates down, observation stays can change what counts as a readmission and at least one national study raises the possibility of higher mortality. An interrupted time series with a comparison condition, measures of reclassification and harm, process data and decision rules set in advance will let Brookhaven say with more confidence whether its bundle made a difference.
References
Gupta, A., Allen, L. A., Bhatt, D. L., Cox, M., DeVore, A. D., Heidenreich, P. A., Hernandez, A. F., Peterson, E. D., Matsouaka, R. A., Yancy, C. W., & Fonarow, G. C. (2018). Association of the Hospital Readmissions Reduction Program implementation with readmission and mortality outcomes in heart failure. JAMA Cardiology, 3(1), 44-53. https://doi.org/10.1001/jamacardio.2017.4265
Penfold, R. B., & Zhang, F. (2013). Use of interrupted time series analysis in evaluating health care quality improvements. Academic Pediatrics, 13(6, Suppl.), S38-S44. https://doi.org/10.1016/j.acap.2013.08.002
Zuckerman, R. B., Sheingold, S. H., Orav, E. J., Ruhter, J., & Epstein, A. M. (2016). Readmissions, observation, and the Hospital Readmissions Reduction Program. New England Journal of Medicine, 374(16), 1543-1551. https://doi.org/10.1056/NEJMsa1513024
What the NUR 650 Module 7 instructions ask for
The third NUR 650 milestone generally turns to evaluation: how will you know whether the care coordination intervention you designed actually worked? Expect to describe the evaluation design, measures, data sources, analysis and how results will be used and reported. Plan on five to seven pages in APA 7. Choose a design stronger than a simple before-and-after comparison when you can, account for national trends and policy, count reclassification such as observation stays, track mortality or other possible harms, include process measures to show delivery, examine subgroups for equity and write down in advance how you will decide whether the intervention worked. Tailor the reporting to each audience, from frontline staff to the board.
How this NUR 650 Module 7 milestone three example is built
This milestone plans the evaluation of a heart failure bundle at a composite hospital. It summarizes Zuckerman and colleagues' findings on falling readmissions and rising observation stays under the national program and Gupta and colleagues' finding of higher mortality after its rollout. Following Penfold and Zhang, it uses an interrupted time series with 36 months before and 18 after launch and pneumonia as a comparison condition. Measures include observation returns, emergency visits, mortality, process delivery and subgroups. Decision rules set in advance say when the bundle can be credited, and reporting is tailored to each audience. Financial estimates apply the same cautious attribution rules as the clinical results, so savings are not overstated.
Where the NUR 650 Module 7 rubric puts the points
Grading of evaluation plans typically covers the design and its rationale, the choice of measures, data sources and analysis, attention to confounding and bias, plans for reporting and use and APA 7 writing. Top-band papers explain why a simple comparison could mislead and choose a design that addresses existing trends. Graders reward comparison conditions exposed to the same outside forces, balancing measures for reclassification and harm and decision rules written before results are known. Examining whether some groups benefit less, and presenting findings honestly to each audience, shows mature evaluation thinking. Plans that apply the same caution to financial claims as to clinical ones tend to score well, as do plans that name the analytic support they will need.
NUR 650 Module 7 help: the mistakes that cost points
Evaluation plans lose points when they rely on a single before-and-after rate, when national trends and policy are ignored, when observation stays or mortality are not tracked or when the plan does not say how results will be interpreted. Another gap is evaluating outcomes without process data. Choose a stronger design, add a comparison, track reclassification and harm, include process measures, examine subgroups and set decision rules in advance. If your intervention works outside the hospital, such as a clinic-based or community program, send it with your NUR 650 prompt so the evaluation fits. Apply the same caution to any savings you report, and name who will run the analysis.
Get NUR 650 Module 7 written to your instructions
Send the NUR 650 milestone prompt, your intervention and the rubric. Your plan will choose a design stronger than before-and-after, account for trends and reclassification, track harm and set decision rules in advance, within 24 to 48 hours, free the first time. The paper above is an original model document written by our desk, not a submitted student paper and not an official Southern New Hampshire University document.
More NUR 650 papers and related MSN samples
- NUR 650 Module 1 Discussion: What Fragmented Care Costs
- NUR 650 Module 2 Risk Tool Paper: What Readmission Risk Scores Can and Cannot Tell a Care Team
- NUR 650 Module 3 Milestone One: Heart Failure Readmissions: Data, Process Map and Root Causes
- NUR 650 Module 4 Model Comparison Paper: Three Transitional Care Models Compared
- NUR 650 Module 5 Milestone Two: A Discharge and Follow-Up Bundle for Heart Failure
- NUR 650 Module 6 Measures Paper: Measuring Care Coordination With Structure, Process and Outcome
- NUR 640 Module 8 Integrity Paper: Cheating on Clinical Paperwork
- NUR 636 Module 6 SOAP Note: Eczema and Peanut Fear at Four Months
- NUR 508 Module 8 Portfolio Reflection Discussion
- NUR 633 Module 3 Milestone One: Falls on 6 West, Defined With Data
NUR 650 Module 7 questions, answered
Where can I find a free NUR 650 Module 7 Milestone Three sample?
This page carries the full plan: evaluating a heart failure bundle with an interrupted time series, a comparison condition, observation stays and mortality tracking.
What is the Hospital Readmissions Reduction Program?
A Medicare program that reduces payments to hospitals with higher-than-expected readmissions for targeted conditions such as heart failure.
Why count observation stays in a readmission evaluation?
Patients who return may be placed in observation rather than admitted, which lowers the readmission rate without a real improvement.
What is an interrupted time series?
A design that tracks an outcome at regular intervals before and after an intervention and tests whether its level or trend changed at that point.
Why track mortality when reducing readmissions?
A national study found higher post-discharge mortality in heart failure after the readmission program began, so harm must be monitored.