Difference between revisions of "ANLY482 AY2016-17 T2 Group18"

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<div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Project Description</font></div>
 
<div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Project Description</font></div>
 
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Hospital X is a pioneer tertiary hospital that provides a comprehensive range of medical and rehabilitative services for children, adolescents, adults and the elderly. Patients can be categorised according to their appointments with a doctor, a psychologist or even both. This project plans to make use of the dataset to analyse if there is any relationship between the variables and to create a predictive model for likelihood of a patient in defaulting appointments.
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Hospital X is a pioneer tertiary hospital that provides a comprehensive range of medical and rehabilitative services for children, adolescents, adults and the elderly. Patients can be categorised according to their appointments with a doctor, a psychologist or even both. Our project sponsor is a medical consultant working for Hospital X. He specialises in tending to younger patients from the age of 18 years old and below. He hopes to tap into the under-utilised administrative data that is collected by the hospital daily.
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Patients are usually referred to Hospital X by other medical institutions or they booked an appointment directly. Currently, Hospital X experiences high no-show  appointments rate of about 21% for first visits and 19% for review visits. Our project sponsor is keen on improving productivity for the doctors and psychologists as missed appointments lead to longer appointment lead times, idle time and overall lower quality of care.
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Freeing up the time wasted by patients’ no-show would improve utilisation of slots, and even reduce appointment wait time for other patients.  
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Revision as of 11:28, 14 January 2017


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Project Description


Hospital X is a pioneer tertiary hospital that provides a comprehensive range of medical and rehabilitative services for children, adolescents, adults and the elderly. Patients can be categorised according to their appointments with a doctor, a psychologist or even both. Our project sponsor is a medical consultant working for Hospital X. He specialises in tending to younger patients from the age of 18 years old and below. He hopes to tap into the under-utilised administrative data that is collected by the hospital daily.

Patients are usually referred to Hospital X by other medical institutions or they booked an appointment directly. Currently, Hospital X experiences high no-show appointments rate of about 21% for first visits and 19% for review visits. Our project sponsor is keen on improving productivity for the doctors and psychologists as missed appointments lead to longer appointment lead times, idle time and overall lower quality of care.

Freeing up the time wasted by patients’ no-show would improve utilisation of slots, and even reduce appointment wait time for other patients.