Preventative medicine is all set to make a comeback as hospitals now have the tools that are required to collect, analyze and deliver solutions that map the trajectories of their patient’s health in a sustainable fashion. Telemedicine, as the practice is commonly known was hamstrung by the sheer bulk of the requisite instruments and the lack of interoperability within them.
Telemedicine has now touched a new frontier as mobile applications are proving to be increasingly useful in medicine, especially in pre-emptive and predictive health solutions. As the next phase of telemedicine dawns on us, here are five ways in which hospitals can start delivering predictive health solutions to their customers via mobile telephony:
In the first half of the last decade alone, both physicians and patients began to conduct more and more of their activities on mobile applications. The increasing acceptance of patients liaising with their doctors through mobile applications means that doctors can now mediate most in-person visits via mobile applications. This not only translates to greater convenience for both parties but also facilitates a robust data collection platform that is crucial to delivering predictive health solutions to patients. These have been shown to improve the rate of electronic prescribing and increase the effectiveness of healthcare professionals.
Predictive analytics is proving to be a big draw for hospitals as the average patient now has a digital footprint that provides ample information regarding the patient’s well-being if processed in the right fashion. As of 2015, the average hospital was expected to be generating almost 665 terabytes of data, a goldmine that can finally be leveraged with the use of advanced analytics:
Hospitals seeking to augment their existing practices with predictive health solutions need to unify three key technologies which they have at their disposal: smartphones, predictive analytics, and the wealth of data that they generate on a daily basis. They can also help reduce the cost of re-admissions, as demonstrated in the case of Dr Patricia Newland, who had used it to prevent one of her patients from readmission.
Predictive algorithms, when deployed in tele-ICU settings can give doctors enough insight into patient vitals and alert doctors to signs of impending patient deterioration so they can act on time and save patients from slipping further. In fact, these algorithms can even come in handy in the hospice, as one hospital had demonstrated by implementing an automated early warning scoring system that helped caregivers administer appropriate care and respond early.
There are several anecdotes from around the world as to how the Apple Watch’s state-of-the-art ECG feature helped save lives by alerting the wearer to slight anomalies in their homeostatic process. This can further be extended to patients with chronic diseases who can be equipped with wearable biosensors that collect data at regular intervals. When coupled with smartphones, sensors can be a potent combination for remote patient monitoring as it will allow doctors to set up systems that alert patients in case they display early signs of a severe ailment. This would enable hospitals to unclog their wards and make way for more severe cases that might require in-person care for the patients.
Hospitals can also place comprehensive clinical surveillance systems at home for at-risk patients in their homes. This could effectively reduce 40% of all hospital admissions by bringing healthcare to the homes of those who need it the most, as demonstrated by a study by Partners Healthcare of Boston.
For young hospital chains that still seek to differentiate themselves from older chains, digitizing their operations and making full use of their data and the commoditization of the smartphone can yield staggering results. Over time, they can even create personalized models for individual patients and deliver healthcare with greater success, the likes of which will be received with great fanfare from both customers and non-customers alike.
In 1997, the world watched in awe as IBM’s Deep Blue, a machine designed to…
As healthcare becomes more patient-centric, the demand for efficient and personalized care continues to grow.…
Imagine waking up to an assistant who has already planned your day—rescheduled your meetings to…
When we hear million-dollar AI mistakes, the first thought is: What could it be? Was…
Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it…
Ever wondered what life would be like if the Sun took a day off? Picture…
This website uses cookies.