Bed management optimization is critical for efficient functioning of hospitals especially for larger tertiary and quaternary care hospitals. poor bed management can lead to a myriad of problems like increased waiting time for patients, underutilized operation theatres, overcrowded ERs. The need for automated bed management is the need of the hour.
Need to increase face time between clinicians and parents. Clinicians spend considerable amount of time capturing patient information in hospital softwares. Need a technical solution like speech to text option.
Confidentiality of patient medical records is of utmost importance. Access to patient medical records in hospital softwares should be with the treating/admitting clinician and the team. Access to medical records should not be given to everyone in the hospital network.
How can we predict the likelihood of lifestyle diseases early to enable preventive healthcare. This can reduce the cost of treatment significantly. Potential solution: using detailed demographic and vital stats about people who have a particular disease and those who dont, technology companies like Google can create machine learning models to predict specific diseases in an individual during physical checkups.
Supply of doctors is limited in India especially in smaller towns and villages making provision of healthcare difficult to a large number of people. Telemedicine and other solutions in the past have also struggled to scale up due to this problem. Now in the age of digital assistants like Google and Alexa, can we create artificial intelligence based "doctor" that can diagnose everyday acute diseases like common cold, flu, etc, based on simple questions?
For machine learning models to work we needs large amounts of trusted patient data on symptoms of various diseases which can help in diagnosis. How can we make collection of this data easy using technology.
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23rd November , 2018
23rd November , 2018
Healthcare & Biomedical Devices
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