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Improving post-stroke health outcomes: Can facilitated care help?

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  • Kucukyazici, Beste
  • Verter, Vedat
  • Nadeau, Lyne
  • Mayo, Nancy E.

Abstract

Objectives The objectives of this study were (1) identifying the patterns of post-stroke care, (2) determining the care-provider and patient characteristics associated with optimal management of post-stroke care and (3) estimating the potential influence of various facilitated care policies on outcomes.Methodology The 3946 subjects included in the study were admitted to one of Quebec's acute-care hospitals with confirmed diagnosis of stroke and subsequently discharged to their home. The records related to fee-for-service billings of this sample were obtained for the 3 months following discharge and used to define the care-provider path for each stroke survivor. These paths were analyzed and the potential impact of various facilitated care interventions was estimated via a Markov model.Results The rate of mortality for this sample was 3.2% during the first 3 months after discharge. For the patients who were re-hospitalized, however, the mortality rates were up to 10.3% depending on the care-provider visited prior to re-hospitalization. Our analyses indicate that by avoiding such critical sub-paths via facilitated care, it is possible to achieve improvements in health outcomes as well as cost.Discussion There is a window of opportunity for improving community-based post-stroke care. Facilitated care policies concerning planned visits upon discharge from hospital or following ER visits can improve the outcomes.

Suggested Citation

  • Kucukyazici, Beste & Verter, Vedat & Nadeau, Lyne & Mayo, Nancy E., 2009. "Improving post-stroke health outcomes: Can facilitated care help?," Health Policy, Elsevier, vol. 93(2-3), pages 180-187, December.
    • Handle: RePEc:eee:hepoli:v:93:y:2009:i:2-3:p:180-187
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    1. Peter Doubilet & Colin B. Begg & Milton C. Weinstein & Peter Braun & Barbara J. McNeil, 1985. "Probabilistic Sensitivity Analysis Using Monte Carlo Simulation," Medical Decision Making, , vol. 5(2), pages 157-177, June.
    2. Nicky J. Welton & A. E. Ades, 2005. "Estimation of Markov Chain Transition Probabilities and Rates from Fully and Partially Observed Data: Uncertainty Propagation, Evidence Synthesis, and Model Calibration," Medical Decision Making, , vol. 25(6), pages 633-645, November.
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    1. Carole L White & Tracy L Brady & Laura L Saucedo & Deb Motz & Johanna Sharp & Lee A Birnbaum, 2015. "Towards a better understanding of readmissions after stroke: partnering with stroke survivors and caregivers," Journal of Clinical Nursing, John Wiley & Sons, vol. 24(7-8), pages 1091-1100, April.

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