Digestive Diseases and Sciences

, Volume 60, Issue 12, pp 3563–3569 | Cite as

An Automated Telephone Monitoring System to Identify Patients with Cirrhosis at Risk of Re-hospitalization

  • Mary Thomson
  • Michael Volk
  • Hyungjin Myra Kim
  • John D. Piette
Original Article


Background and Aims

Hospitalizations for cirrhosis are costly and associated with increased mortality. Disease management outside of clinic, such as the use of interactive voice response (IVR) calls, may identify signs to prevent hospitalization. The aim of this study was to investigate whether IVR monitoring can predict hospitalization and mortality in cirrhosis.


One hundred patients with decompensated cirrhosis were enrolled in this observational study, of which 79 patients were included in the final analysis. Participants were followed until death, transplant, or last clinical follow-up (range 7–874 days). Analysis focused on potential predictors identified during the first month of IVR calls: presence of jaundice, abdominal/leg swelling, weakness, paracentesis requirement, medication changes, and weight change. The primary outcome was time to first hospital admission; secondary outcomes included hospitalization and time to death. Potential predictors with a p value <0.1 were further analyzed after adjustment for covariates (Model for End-stage Liver Disease score, serum sodium, number of medications).


Twenty (25 %) patients died, and 49 (62 %) were hospitalized at least once. Fifty-six (70 %) patients completed >80 % of their IVR calls. After adjustment for covariates, weakness was associated with an increased risk of first hospitalization (HR 2.14, CI 1.13–4.05, p = 0.02) and hospitalization rate (HR 2.1, CI 1.0–4.3, p = 0.048). Weight change of ≥five pounds (2.3 kg) in a week increased the rate of hospitalization by 2.7 (CI 1.0–7.1, p = 0.045). No variable predicted death after covariate adjustment.


These results suggest IVR calls can be used to predict hospitalization in cirrhosis.


Telemedicine Cirrhosis Patient care management Hospitalization 



This work was supported in part by K23DK085204 (Volk) and P30DK092926 (Piette, National Institute of Diabetes, Digestive and Kidney Diseases).

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical standard

All procedures performed in studies involving human participants were in accordance with the ethical standard of the institutional research committee (University of Michigan Human Subjects Committee) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Heron M. Deaths: leading causes for 2010. Natl Vital Stat Rep. 2013;62:1–96.PubMedGoogle Scholar
  2. 2.
    Volk ML, Tocco RS, Bazick J, Rakoski MO, Lok AS. Hospital readmissions among patients with decompensated cirrhosis. Am J Gastroenterol. 2012;107:247–252.PubMedCentralCrossRefPubMedGoogle Scholar
  3. 3.
    Holland R, Battersby J, Harvey I, Lenaghan E, Smith J, Hay L. Systematic review of multidisciplinary interventions in heart failure. Heart. 2005;91:899–906.PubMedCentralCrossRefPubMedGoogle Scholar
  4. 4.
    Wigg AJ, McCormick R, Wundke R, Woodman RJ. Efficacy of a chronic disease management model for patients with chronic liver failure. Clin Gastroenterol Hepatol. 2013;11:e1–e4.CrossRefPubMedGoogle Scholar
  5. 5.
    Morando F, Maresio G, Piano S, et al. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59:257–264.CrossRefPubMedGoogle Scholar
  6. 6.
    Piette JD, Rosland AM, Marinec NS, Striplin D, Bernstein SJ, Silveira MJ. Engagement with automated patient monitoring and self-management support calls: experience with a thousand chronically ill patients. Med Care. 2013;51:216–223.PubMedCentralCrossRefPubMedGoogle Scholar
  7. 7.
    Aharonovich E, Hatzenbuehler ML, Johnston B, et al. A low-cost, sustainable intervention for drinking reduction in the HIV primary care setting. AIDS Care. 2006;18:561–568.CrossRefPubMedGoogle Scholar
  8. 8.
    Helzer JE, Rose GL, Badger GJ, et al. Using interactive voice response to enhance brief alcohol intervention in primary care settings. J Stud Alcohol. 2008;69:251–258.CrossRefGoogle Scholar
  9. 9.
    Kobak KA, Taylor LH, Dottl SL, et al. Computerized screening for psychiatric disorders in an outpatient community mental health clinic. Psychiatr Serv. 1997;48:1048–1057.CrossRefPubMedGoogle Scholar
  10. 10.
    Kim H, Bracha Y, Tipnis A. Automated depression screening in disadvantaged pregnant women in an urban obstetric clinic. Arch Womens Ment Health. 2007;10:163–169.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Internal MedicineUniversity of Michigan Medical SchoolAnn ArborUSA
  2. 2.Division of Gastroenterology and HepatologyUniversity of Michigan Medical SchoolAnn ArborUSA
  3. 3.Loma Linda University Medical Center Transplantation InstituteLoma LindaUSA
  4. 4.Center for Statistical Consultation and ResearchUniversity of MichiganAnn ArborUSA
  5. 5.Health Services Research and Development Center for Clinical Management ResearchDepartment of Veterans AffairsAnn ArborUSA
  6. 6.Health Behavior and Health Education, School of Public HealthUniversity of MichiganAnn ArborUSA

Personalised recommendations