Hostname: page-component-848d4c4894-p2v8j Total loading time: 0.001 Render date: 2024-05-30T22:29:38.109Z Has data issue: false hasContentIssue false

Reducing readmissions following paediatric cardiothoracic surgery: a quality improvement initiative

Published online by Cambridge University Press:  13 August 2014

Brian Kogon*
Affiliation:
Department of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, Georgia, United States of America
Kim Woodall
Affiliation:
Department of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, Georgia, United States of America
Kirk Kanter
Affiliation:
Department of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, Georgia, United States of America
Bahaaldin Alsoufi
Affiliation:
Department of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, Georgia, United States of America
Matt Oster
Affiliation:
Sibley Heart Center Cardiology, Children’s Healthcare of Atlanta, Atlanta, Georgia, United States of America
*
Correspondence to: B. E. Kogon, Department of Cardiothoracic Surgery, Emory University, Children’s Healthcare of Atlanta, 1450 Clifton Road NE, Atlanta, GA 30033, United States of America. Tel: +404 785 6319; Fax: +404 785 6266; Email: Bkogon@emory.edu

Abstract

Background: We have previously identified risk factors for readmission following congenital heart surgery – Hispanic ethnicity, failure to thrive, and original hospital stay more than 10 days. As part of a quality initiative, changes were made to the discharge process in hopes of reducing the impact. All discharges were carried out with an interpreter, medications were delivered to the hospital before discharge, and phone calls were made to families within 72 hours following discharge. We hypothesised that these changes would decrease readmissions. Methods: The current cohort of 635 patients underwent surgery in 2012. Demographic, preoperative, operative, and postoperative variables were evaluated. Univariate and multivariate risk factor analyses were performed. Comparisons were made between the initial (2009) and the current (2012) cohorts. Results: There were 86 readmissions of 77 patients during 2012. Multivariate risk factors for readmission were risk adjustment for congenital heart surgery score and initial hospital stay >10 days. In comparing 2009 with 2012, the overall readmission rate was similar (10 versus 12%, p=0.27). Although there were slight decreases in the 2012 readmissions for those patients with Hispanic ethnicity (18 versus 16%, p=0.79), failure to thrive (23 versus 17%, p=0.49), and initial hospital stay >10 days (22 versus 20%, p=0.63), they were not statistically significant. Conclusions: Potential risk factors for readmission following paediatric cardiothoracic surgery have been identified. Although targeted modifications in discharge processes can be made, they may not reduce readmissions. Efforts should continue to identify modifiable factors that can reduce the negative impact of hospital readmissions.

Type
Original Articles
Copyright
© Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Clinical Advisory Board – Preventing unnecessary readmissions, Clinical Advisory Board interviews and analysis. Retrieved 12 December 2013, from http://www.advisoryboardcompany.com Google Scholar
2. Kogon, B, Jain, A, Oster, M, Woodall, K, Kanter, K, Kirshbom, P. Risk factors associated with readmission after pediatric cardiothoracic surgery. Ann Thorac Surg 2012; 94: 865873.Google Scholar
3. Jenkins, KJ, Gauvreau, K, Newburger, JW, Spray, TL, Moller, JH, Iezzoni, LI. Consensus-based method for risk adjustment for surgery for congenital heart disease. J Thorac Cardiovasc Surg 2002; 123: 110118.Google Scholar
4. Kripalani, S, Theobold, CN, Anctil, B, Vasilevskis, EE. Reducing hospital readmission rates: current strategies and future directions. Annu Rev Med 2014; 65: 471485.Google Scholar
5. Bradley, EH, Curry, L, Horwitz, LI, et al. Hospital strategies associated with 30-day readmission rates for patients with heart failure. Circ Cardiovasc Qual Outcomes 2013; 6: 444450.Google Scholar
6. Gil, M, Mikaitis, DK, Shier, G, Johnson, TJ, Sims, S. Impact of a combined pharmacist and social worker program to reduce hospital readmissions. J Manag Care Pharm 2013; 19: 558563.Google Scholar
7. Hansen, LO, Young, RS, Hinami, K, Leung, A, Williams, MV. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med 2011; 155: 520528.CrossRefGoogle ScholarPubMed
8. Hesselink, G, Schoonhoven, L, Barach, P, et al. Improving patient handovers from hospital to primary care: A systematic review. Ann Intern Med 2012; 157: 417428.Google Scholar
9. Koehler, BE, Richter, KM, Youngblood, L, et al. Reduction of 30-day postdischarge hospital readmission of emergency (ED) visit rates in high-risk elderly medical patients through delivery of a targeted care bundle. J Hosp Med 2009; 4: 211218.Google Scholar
10. Yam, CH, Wong, E, Chan, FW, et al. Avoidable readmission in Hong Kong – clinician, patient, or social factor? BMC Health Serv Res 2010; 10: 311.CrossRefGoogle ScholarPubMed
11. Mackie, AS, Gauvreau, K, Newburger, JW, Mayer, JE, Erickson, LC. Risk factors for readmission after neonatal cardiac surgery. Ann Thorac Surg 2004; 78: 19721978.Google Scholar
12. Halfon, P, Eggli, Y, Melle, G, Chevalier, J, Wasserfallen, JB, Burnand, B. Measuring potentially avoidable hospital readmissions. J Clin Epidemiol 2002; 55: 573587.CrossRefGoogle ScholarPubMed
13. Frankl, S, Breeling, JL, Goldman, L. Preventability of emergent hospital readmission. Am J Med 1991; 90: 667674.Google Scholar
14. Oddone, EZ, Weinberger, M, Horner, M, et al. Classifying general medicine readmissions. Are they preventable? Veterans Affairs Cooperative Studies in Health Services Group on Primary Care and Hospital Readmissions. J Gen Intern Med 1996; 11: 597607.Google Scholar
15. Gautam, R, Macduff, C, Brown, I, Squair, J. Unplanned readmissions of elderly patients. Health Bull 1996; 54: 449457.Google ScholarPubMed
16. Maurer, PP, Ballmer, PE. Hospital readmissions – are they predictable and avoidable? Swiss Med Wkly 2004; 134: 606611.Google Scholar
17. Baillie, CA, VanZandbergen, C, Tait, G, et al. The readmission risk flag: using the electronic health record to automatically identify patients at risk for 30-day readmission. J Hosp Med 2013; 8: 689695.Google Scholar
18. Tang, N. A primary care physicians ideal transitions of care – where’s the evidence. J Hosp Med 2013; 8: 472477.Google Scholar