7 Examples of Health Informatics Coming in the Near Future
Health informatics, which is the intersection of people, technology, and data to improve the safety and quality of patient care, can be found in many forms. A few examples include patient portals, electronic medical records (EMRs), telehealth, healthcare apps, and a variety of data reporting tools. But what comes next? We assembled a list of nine examples of health informatics technologies or advances that are either being explored or improved in the field right now.
1. Voice Dictation
Now that healthcare organizations have moved their medical records to digital systems, health informaticists are diving into the possibilities of improving artificial intelligence voice recognition to digitally transcribe healthcare providers’ notes and medical orders in real time. This could drastically reduce the amount of time spent on data entry and increase the amount of time that healthcare providers can spend interacting directly with their patients.
At the moment, there is still some resistance to incorporating voice transcription due to its error rate of about 7.4%. In a study, this error rate was connected to a lack of proofreading by the clinician. After proofreading, the error rate in the same study fell to 0.3%. (Zhou, Blackley & Kowalski, 2018) Detailed proofreading also takes up a decent amount of time, so it will take insightful and innovative health informaticists to find a voice recognition solution that is both completely accurate and time efficient.
2. EHR Alert Optimization
Instantaneous alerts can act as an incredible useful tool to improve care by notifying a healthcare provider about a number of issues: This may include screenings, drug interactions, chronic disease management, overdue lab tests, prescription recommendations, admission, discharge, transfer (ADT) notifications, and more. However, when everything creates an alert, none of them seem important. “Alert fatigue,” when healthcare providers become desensitized to alerts because there are so many that go off so often, is just as dangerous as not having the alerts in the first place.
Informaticists are working to winnow down the number of EHR alerts to make them more useful. Some proposed approaches include customizing alerts to each patient, tiering alerts by severity, or changing the design of alerts by color or format to be more or less intrusive as needed.
3. Predictive Analytics
In healthcare, predictive analytics studies a massive amount of data to find indications of common symptoms, diagnoses, workflows, and other outcomes. One example is a study done in which an artificial intelligence algorithm analyzed the speech patterns of children, compared their pitch, inflections, and words against data from other clinical interviews and parent questionnaires, and was able to identify diagnoses of depression 80% of the time. (McGinnis et al, 2019)
While this technology is still in its early stages, it is incredibly versatile and could help healthcare professionals optimize their care decisions. Predictive analytics can also be found within our next examples of health informatics technology.
4. Syndromic Surveillance
Using both predictive analytics and EHR alerts, real-time patient surveillance can instantly identify potential adverse events. Instantaneous clinical decision support tools can then take that analyzed surveillance and apply it in real time to signal healthcare professionals to take immediate or precautionary action.
Currently, the implementation of real-time clinical decision support tools is being hampered by poor usability, the aforementioned alert fatigue, and the program’s understanding of different end-users’ needs. (Mann et al, 2019) The latter two factors will likely be addressed as predictive analytics algorithms and EHR alert optimization improve. In the future, these tools may lower health costs and complications through faster, more customized care that can reduce the potential for human error, and even improve public health—for instance, by instantly sharing diagnoses of communicable diseases. (Heekin et al, 2018)
5. Clinical Image Capture
Just like digital cameras can now capture moments in intense detail, medical imaging has improved by leaps and bounds—and the files have similarly increased in size. After a patient goes through an MRI, CAT scan, X-ray, or other procedure, storing or retrieving imaging in the EHR can be difficult. Each image may have a different intent or function, and they may come from different technologies, so they may be saved in different file formats or locations. They also need to be matched to the correct patient, and be saved and accessed only by authorized users.
Informaticists are currently trying to balance these many factors. An ideal imaging system would be able to easily capture any type of image and share it in a single, secure yet easily-accessed file that is also connected to the rest of the patient’s record.
Looking farther into the future, imaging data could be combined with predictive analytics to help healthcare professionals find patterns that could lead to improved diagnoses.
6. Secure Texting
Patient portals have brought a host of accessibility to patients and providers, opening up patients’ access to their own records, prescriptions, and lab results, and creating a new line of communication between the patient and the provider.
However, logging into a portal on a regular basis can be difficult for many patients. Providers have started to look into alternatives to notifying patients through secure texts, which can be automated and thus reduce time that providers spend on the phone or that patients spend on the computer trying to access their portal. Of course, the hard part is making sure those texts remain secure!
7. Shift to the Cloud
It may seem like everyone is moving their data to the “cloud” these days, including photos, music, movies, and now health records. The benefits of cloud computing over an on-site server are fairly straightforward: there’s no hardware or software installation, updates are automatic, and authorized users can access the system anywhere they can get an internet connection. When combined, these benefits can also mean huge cost savings.
Of course, just because the data is in the cloud doesn’t mean it’s automatically perfect. Health informaticists are needed to set up cloud-based systems and monitor them for security, connectivity, correct data input/output, and outages.
Do these health informatics examples sound right up your alley?
Through these examples of health informatics technology, patient health and healthcare providers’ work are being improved little by little. While many technologies have been proposed or implemented to a point, the healthcare field needs more health informatics professionals to bring them to full fruition. For more information:Graduate Programs in Health Informatics | Health Informatics | Master of Science in Health Informatics