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Efficacy of Post-discharge Interventions on Preventing Hospital Readmissions in Stroke Patients

2018
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Project Description

More than 795,000 people in the United States have a stroke every year. Some 610,000 of them are first or new strokes, and 185,000 of these are recurrent strokes (Centers for Disease Control and Prevention, 2016). Studies show that anywhere from 17.4% to 66% of patients discharged from a healthcare facility following an acute stroke are readmitted within 30 days (Zhong et al., 2016; Lahiri et al., 2015; Strowd et al., 2015; Bjerkreim, Thomassen, Waje-Andreassen, Selvik, & Naess, 2016; Burke, Skolarus, Adelman, Reeves, & Brown, 2014; Kilkenny, Longworth, Pollack, Levi, & Cadilhac, 2013; Lichtman, Leifheit-Limson, Jones, Wang, & Goldstein, 2012; Li, Yang, & Chung, 2011). Hospital readmissions are costly both to the healthcare system and to patients. In 2016, the average hospital cost for each admission that resulted in a live patient discharge was $17,500, and that figure has been projected to increase in 2017 and 2018 (U.S. Department of Health and Human Services and the Agency for Healthcare Research and Quality, 2016, p. 16). All the conclusions in the reviewed literature recommend the use of multiple or bundled interventions versus the use of just one intervention (Poston, Dumas, & Edlund, 2014; Verhaegh et al., 2014; Wong, Chow, Chan, & Tam, 2014). The objectives of this program improvement project were, 1) to examine whether specific discharge interventions, as a group, helped reduce hospital readmissions; and 2) to develop an understanding of the effectiveness of these discharge interventions based on readmission risk stratification for stroke patients. Data was analyzed using retrospective chart analysis. This data was used to compare preintervention and postintervention readmission rates for patients discharged from the hospital after their first stroke. All three of the Fischer’s Exact Tests revealed no significant differences in the relationship of the sample prior to the intervention and that of the sample after implementation (two-tailed p values of 0.42 for all data, 1.00 for medium risk, and 0.23 for high risk). Postintervention analyses revealed organizational systemic barriers that might have affected the results.

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