Faculty Bibliography

There is an active public debate about whether patients' socioeconomic status should be included in the readmission measures used to determine penalties in Medicare's Hospital Readmissions Reduction Program (HRRP). Using the current Centers for Medicare and Medicaid Services methodology, we compared risk-standardized readmission rates for hospitals caring for high and low proportions of patients of low socioeconomic status (as defined by their Medicaid status or neighborhood income). We then calculated risk-standardized readmission rates after additionally adjusting for patients' socioeconomic status. Our results demonstrate that hospitals caring for large proportions of patients of low socioeconomic status have readmission rates similar to those of other hospitals. Moreover, readmission rates calculated with and without adjustment for patients' socioeconomic status are highly correlated. Readmission rates of hospitals caring for patients of low socioeconomic status changed by approximately 0.1 percent with adjustment for patients' socioeconomic status, and only 3-4 percent fewer such hospitals reached the threshold for payment penalty in Medicare's HRRP. Overall, adjustment for socioeconomic status does not change hospital results in meaningful ways.

Programs from the Centers for Medicare and Medicaid Services simultaneously promote strategies to lower hospital admissions and readmissions. However, there is concern that hospitals in communities that successfully reduce admissions may be penalized, as patients that are ultimately hospitalized may be sicker and at higher risk of readmission. We therefore examined the relationship between changes from 2010 to 2013 in admission rates and thirty-day readmission rates for elderly Medicare beneficiaries. We found that communities with the greatest decline in admission rates also had the greatest decline in thirty-day readmission rates, even though hospitalized patients did grow sicker as admission rates declined. The relationship between changing admission and readmission rates persisted in models that measured observed readmission rates, risk-standardized readmission rates, and the combined rate of readmission and death. Our findings suggest that communities can reduce admission rates and readmission rates in parallel, and that federal policy incentivizing reductions in both outcomes does not create contradictory incentives.

Importance: Feasibility, effectiveness, and sustainability of large-scale readmission reduction efforts are uncertain. The Greater New Haven Coalition for Safe Transitions and Readmission Reductions was funded by the Center for Medicare & Medicaid Services (CMS) to reduce readmissions among all discharged Medicare fee-for-service (FFS) patients. Objective: To evaluate whether overall Medicare FFS readmissions were reduced through an intervention applied to high-risk discharge patients. Design, Setting, and Participants: This quasi-experimental evaluation took place at an urban academic medical center. Target discharge patients were older than 64 years with Medicare FFS insurance, residing in nearby zip codes, and discharged alive to home or facility and not against medical advice or to hospice; control discharge patients were older than 54 years with the same zip codes and discharge disposition but without Medicare FFS insurance if older than 64 years. High-risk target discharge patients were selectively enrolled in the program. Interventions: Personalized transitional care, including education, medication reconciliation, follow-up telephone calls, and linkage to community resources. Measurements: We measured the 30-day unplanned same-hospital readmission rates in the baseline period (May 1, 2011, through April 30, 2012) and intervention period (October 1, 2012, through May 31, 2014). Results: We enrolled 10621 (58.3%) of 18223 target discharge patients (73.9% of discharge patients screened as high risk) and included all target discharge patients in the analysis. The mean (SD) age of the target discharge patients was 79.7 (8.8) years. The adjusted readmission rate decreased from 21.5% to 19.5% in the target population and from 21.1% to 21.0% in the control population, a relative reduction of 9.3%. The number needed to treat to avoid 1 readmission was 50. In a difference-in-differences analysis using a logistic regression model, the odds of readmission in the target population decreased significantly more than that of the control population in the intervention period (odds ratio, 0.90; 95% CI, 0.83-0.99; P = .03). In a comparative interrupted time series analysis of the difference in monthly adjusted admission rates, the target population decreased an absolute -3.09 (95% CI, -6.47 to 0.29; P = .07) relative to the control population, a similar but nonsignificant effect. Conclusions and Relevance: This large-scale readmission reduction program reduced readmissions by 9.3% among the full population targeted by the CMS despite being delivered only to high-risk patients. However, it did not achieve the goal reduction set by the CMS.

OBJECTIVE: Recalling a patient to repeat a radiology examination is an adverse and, in certain cases, preventable event. Our objectives were to assess the rate of patient recalls for all imaging performed in the outpatient setting at our institution and to characterize the underlying reasons for the recalls. MATERIALS AND METHODS: We performed a retrospective review of all repeat imaging requests for an inadequate initial imaging study between January 2012 and March 2015. RESULTS: We identified 100 recall requests (mean, 2.6 requests per month), for an overall recall rate of approximately 1 in 8046 ambulatory studies and 1 in 1684 MRI studies. Nearly all recalls (98%) involved adults. A total of 95% of the recalls were for MRI studies. The most common reason for a patient recall request was an incomplete examination, making up 24% of all requests. The other causes were inadequate coverage of the area of interest (22%), protocoling errors (20%), poor imaging quality (15%), additional imaging to clarify a finding (11%), insufficient contrast visualization (7%), and incorrect patient information (1%). CONCLUSION: We found that patient recalls for imaging in the outpatient setting at our institution are not common. When recalls did occur, they were most often related to the acquisition of MR images. Improved technologist education on MRI protocoling and enhanced communication between ordering clinicians and radiologists to clarify the purpose of imaging might reduce the need for repeat ambulatory imaging.