MMHA 6900 Week 3 Readmission Gap Diagnosis Example

From a Public Category to Our Own Discharges: Locating Excess Heart Failure Readmissions Before Diagnosing Their Cause

Student Name

Walden University

MMHA 6900: Healthcare Quality Management

Instructor Name

Month Day, Year

From a Public Category to Our Own Discharges: Locating Excess Heart Failure Readmissions Before Diagnosing Their Cause

Starting Point

Medicare's public reporting site places Cobalt Ridge Medical Center, the fictional hospital at the heart of this quality course, in the "worse than the national rate" category for 30-day heart failure readmissions. The category is a signal, not a diagnosis. It says that, after adjustment for patients' age and illnesses, the hospital's readmission rate is higher than expected compared with hospitals nationally. It does not say which patients are coming back, when or why. This paper works from that public category down to the hospital's own discharge data to locate where the excess readmissions occur. It deliberately stops before diagnosing causes, because a cause found before the problem is located is usually a guess.

What the Public Measure Is

The publicly reported measure is a risk-standardized readmission rate built from Medicare claims. It counts unplanned readmissions for any cause within 30 days of discharge for patients hospitalized with heart failure, and it adjusts for patient factors so that hospitals with sicker patients are not penalized for case mix alone (Keenan et al., 2008). Several features matter for diagnosis. The measure covers only Medicare fee-for-service patients aged 65 and older. It counts readmissions to any hospital, not only Cobalt Ridge. It reflects three years of discharges, so recent changes take time to show. And it does not count observation stays or emergency visits that end without admission.

These features mean the hospital's own data must be built to match the measure before they can explain it. A readmission rate calculated from all heart failure patients, counting only returns to Cobalt Ridge, would describe a different population and miss readmissions elsewhere.

Rebuilding the Measure Internally

The quality department matched the measure's population as closely as its data allowed: Medicare fee-for-service patients aged 65 and older who left alive after a stay coded first for heart failure during the past three years, about 1,900 discharges. Readmissions to other hospitals were identified through a regional health information exchange, which captures most but not all of them. The internal crude rate, an illustrative figure, was 24.8 percent, against an expected rate near 21 percent for patients of this mix.

Table 1

Internal Readmission Rates by Group (Illustrative, Three Years)

Patients discharged home without services carry the highest rate, and two in five readmissions happen within the first week.

Where the Excess Concentrates

Three patterns stand out. First, patients discharged home without home health or other services return at 28 percent, well above other groups. They are also the largest group, so they contribute the most excess readmissions. Second, a large share of readmissions occur within seven days, a period in which events often reflect what happened during the hospital stay and at discharge rather than the later course of disease. Third, about one readmission in six goes to another hospital, which means a purely internal count would understate the problem.

A further cut by follow-up shows that patients who saw a clinician within seven days of discharge were readmitted less often than those who did not. That pattern is consistent with a national study of Medicare heart failure patients, where a hospital's early-visit rate and its 30-day return rate moved in opposite directions (Hernandez et al., 2010). At Cobalt Ridge, only about 38 percent of patients discharged home without services had a documented visit within seven days, an illustrative figure.

Context From the Wider Literature

Readmissions are common across Medicare; Jencks and colleagues counted roughly a fifth of Medicare discharges ending in another admission inside 30 days and that many had no outpatient visit between discharge and readmission (Jencks et al., 2009). Since the Hospital Readmissions Reduction Program began, readmission rates for targeted conditions have fallen nationally, though some of the decline coincided with greater use of observation stays (Zuckerman et al., 2016). Cobalt Ridge's own observation use for returning heart failure patients should therefore be checked, so that any future improvement is not simply a shift from readmission to observation.

Checking the Pattern Against Other Explanations

Before accepting the location, the team tested two other explanations. The first was that the excess came from a few frequent returners, a small group of very sick patients admitted again and again. Removing patients with three or more admissions in the period lowered the rate only slightly, so the excess is spread across many patients. The second was that one attending group or unit accounted for most returns. Rates were similar across the three medical units and across hospitalist groups, which suggests a hospital-wide process rather than a local practice. Both checks strengthen the conclusion that the gap lies in how patients without home services leave and what happens to them in the first days at home.

What This Diagnosis Does Not Yet Say

This paper locates the excess but does not explain it. It does not know whether patients discharged home without services were discharged too early, lacked medications, misunderstood instructions, could not reach a clinician or simply had worse disease than adjustment captured. Those are questions for root cause work, chart review and patient interviews, which the next stage of the project will plan. Naming them here prevents the team from jumping to a favorite solution.

Conclusion

The public category told Cobalt Ridge that its heart failure readmissions were too high. Rebuilding the measure from the hospital's own data shows where: among patients discharged home without services, within the first week and partly at other hospitals, with low rates of early follow-up. That is a located problem, ready for diagnosis. The next step is a structured project that measures and analyzes before it improves.

References

Hernandez, A. F., Greiner, M. A., Fonarow, G. C., Hammill, B. G., Heidenreich, P. A., Yancy, C. W., Peterson, E. D., & Curtis, L. H. (2010). Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure. JAMA, 303(17), 1716-1722. https://doi.org/10.1001/jama.2010.533

Jencks, S. F., Williams, M. V., & Coleman, E. A. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. New England Journal of Medicine, 360(14), 1418-1428. https://doi.org/10.1056/NEJMsa0803563

Keenan, P. S., Normand, S.-L. T., Lin, Z., Drye, E. E., Bhat, K. R., Ross, J. S., Schuur, J. D., Stauffer, B. D., Bernheim, S. M., Epstein, A. J., Wang, Y., Herrin, J., Chen, J., Federer, J. J., Mattera, J. A., Wang, Y., & Krumholz, H. M. (2008). An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure. Circulation: Cardiovascular Quality and Outcomes, 1(1), 29-37. https://doi.org/10.1161/CIRCOUTCOMES.108.802686

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