There are numerous potential benefits to technology in healthcare. Across all industries, technology is developed mainly to speed up, improve the quality and accuracy, and cut the costs of a variety of processes, while automating mundane tasks to free people to do higher-level work. Where healthcare differs from other industries is these marginal—and not-so-marginal—gains can be the difference between life and death.
Improved efficiency is also felt within hospitals relating to staff and equipment. By collecting and analyzing data that suggests when busy periods are likely to occur, for example, weekend evenings for ERs, hospitals can help ensure that they have the appropriate number and type of staff on hand. Similarly, if there are times that are generally less busy, organizations can make sure they don’t overstaff. Also, by monitoring bed occupancy, hospitals will know if they have spare capacity and when they can assign maintenance services to clean a room that’s just been vacated so that it’s readily available for the next occupant.
Online patient portals let people access their test results and prescriptions anytime they wish, as well as set up notifications about upcoming appointments or payments due. They also give patients another way to contact their medical team if they have questions about tests, prescriptions, appointments, sudden health maladies, or anything else.
These portals give people a greater sense of autonomy, while freeing up admin staff to take urgent calls and freeing doctors to deal with emergencies and spend more face time with patients.
Consider the simple example of a patient complaining of excessive thirst and urination. A clinician would run a blood test to check for glucose levels and factor in the patient’s weight, eating habits, and family medical history to assess whether the patient has prediabetes. They would then decide whether preventative measures, such as reducing carbohydrate intake and exercising more frequently, could forego the onset of Type 2 diabetes. More complex diagnoses require more sophisticated, often genetics-based data analysis.
AI also has a huge role to play in advanced diagnostics, as it can model massive amounts of data that could take human specialists months or years to assemble and analyze.
The most sophisticated form of precision medicine involves sequencing an individual’s genome, now easier and more affordable than ever before. Such analyses could lead a clinician to prescribe drug X instead of drug Y or dosages that are more likely to be effective for that particular patient.
At a presentation at an Oracle conference some years ago, a noted physician told the story of an 18-month-old girl suffering from debilitating neck, leg, and arm weakness who was incorrectly diagnosed to have an autoimmune disease. Her condition (predictably) worsened. Only after the toddler’s blood was drawn and her exome was sequenced was it revealed that she was missing a gene that transports Vitamin B2 (Riboflavin), a lack of which can cause progressive neurological weakness and, eventually, death. Treated with a high dosage of off-the-shelf B2, the girl recovered fully within eight weeks. The outcome would have been very different had it not been for the personalized treatment.
It’s not only in the management and treatment of conditions where technology has benefited patients. The whole experience—scheduling appointments, accessing test results, getting answers to basic health questions—has become less frustrating thanks to various technologies.
It could be in the form of computerized provider order entry (CPOE), where all treatment instructions are entered into a single system that anyone involved in the process can access, helping them know what actions have been taken—such as drug dispensation—and which are still to take place so that stages aren’t repeated or missed completely. Clinical decision support (CDS) can sit within systems to prompt clinicians if something about their actions appears unusual, such as failing to undertake a part of the diagnostic process. Often, it will be for a specific reason in that scenario—for example, blood samples were taken yesterday, so they don’t need to be taken again—so the alert can be overridden. But it can also act as a checkbox in case a process or order has slipped a clinician’s mind.
Even on the most basic level, healthcare technology advancement can help to reduce the likelihood of medical errors. It has become a joke that doctors have bad handwriting, but when that handwriting means that a pharmacist provides the incorrect dosage or an incorrect treatment is performed, the benefits of having everything rendered electronically cannot be underestimated.
Technology platforms let researchers assemble clinical trials more quickly by enabling them to build their own studies when they need them rather than having to rely on third parties. They also let researchers add all the elements they need and make mid-study changes if required.
Once it’s time to involve patients in studies, technology allows for a decentralization of clinical trials in cases where patients and doctors don’t need to meet in person. Data can be collected anytime, and the study will be more reflective of real-life conditions, as participants are monitored during their day-to-day tasks.
Telemedicine (more on this subject later) lets patients consult with their clinicians without having to take time off work or pay to travel and park at a venue of care, while reducing unnecessary and expensive emergency room visits. Likewise, remote patient monitoring (more later)—whereby glucose and heart rate monitors and other wearables regularly stream patient data to care providers—is known to reduce hospital visits by improving care coordination and making it more likely patients will consistently take their meds and do other preventative measures.
EHRs help medical practices avoid printing, filing, paper storage, and other administrative costs. As with the example of the 18-month-old patient cited earlier in this article, genome sequencing and advanced diagnostic systems remove a degree of costly trial and error when diagnosing and treating patients.
Automating routine administrative tasks (more on this later), such as scheduling appointments, sending reminders, filling out forms, entering patient notes, and billing for services also reduces costs. Data analytics augmented by AI can help hospitals and practices avoid ordering too many or too few supplies by reducing forecasting errors.
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