On the significance of reducing the need for stroke patients to visit the emergency department.
We studied the care-provider paths followed by 3,946 patients in Quebec in 2001. We showed that the patients flow during the three months preceding discharge from hospital can be represented by a Markov model with memory. This model enables study of four major scenarios to improve health outcomes, workloads and cost efficiency in the overall community-based care delivery system. Based on the field data, we establish that increasing the availability of specialists, family physicians and general practitioners to mitigate the need for ER visits would be an effective strategy for improvement. A comprehensive policy to support stroke patients needs to incorporate both hospital-based and community-based care delivery processes. The seamless flow of patients through the healthcare providers in such an integrated system is crucial for achieving successful outcomes. Emergency rooms (ER) have a crucial role in this context, since in many cases ER acts as the hospital's "gate keeper", determining if a patient needs to be (re)admitted. In this paper, we establish (based on field data) that mitigating the ER visits of stroke patients improves health outcomes, distribution of workload across the healthcare system as well as associated costs. To this end, we make use of a Markov modeling framework, where the aggregate patient flow information is represented in a compact form through the use of a transition-probability matrix. This allows us to investigate the system-wide impact of several plausible scenarios with regards to the delivery of community-based care to stroke patients who are recently discharged from hospital.
Verter
Vedat
V
Desautels Faculty of Management, McGill University, Montreal, Quebec, Canada. vedat.verter@mcgill.ca
Kucukyazici
Beste
B
Mayo
Nancy E
NE
D003151:Community Health Centers; D003365:Costs and Cost Analysis; D004636:Emergency Service, Hospital; D006801:Humans; D008390:Markov Chains; D008954:Models, Biological; D015233:Models, Statistical; D020380:Needs Assessment; D010043:Outcome and Process Assessment, Health Care; D010361:Patients; D020521:Stroke; D016526:Workload