Artificial Intelligence: Improved Outpatient Workflow Thanks To Electronic Patient-Reported Outcome Systems – Gyaani Mind

Artificial Intelligence

Artificial Intelligence: Improved Outpatient Workflow Thanks To Electronic Patient-Reported Outcome Systems – Gyaani Mind


Artificial Intelligence: According to an analysis published in The Royal Society of Medicine Journals, the adoption of electronic patient-reported outcome systems, or ePROs, decreased outpatient wait times without decreasing outcomes or patient satisfaction with care.

The effective use of the data and successful integration of ePROs into current health systems are essential, according to Olalekan Lee Aiyegbusi, MBChB, PhD, an associate professor at the University of Birmingham’s Centre for Patient-Reported Outcome Research.

Research points to the possibility of improving workflow efficiency and time savings when ePRO results are routinely and actively used by physicians to choose the subject and direct clinical consultations.

Aiyegbusi and colleagues describe patient-reported outcomes as reports of condition status that come from the patient directly, without any outside interpretation.

Numerous studies have shown that the collection of ePROs in routine clinical practise is both acceptable and feasible, with patients increasingly expressing a preference for an electronic mode of administration, thanks to doctors’ growing interest in patient-reported outcomes and technological advancements within the practise setting.

Artificial Intelligence, The researchers looked at 18 articles on the usage of ePRO solutions in outpatient settings in order to compile an overview of potential ePRO advantages and disadvantages.

Overall, the researchers found a number of noteworthy advantages, especially in terms of outpatient management, doctor-patient communication, and physician interventions.

Patient triaging was made easier by ePROs’ remote administration. The researchers discovered that clinically stable patients who did not require outpatient appointments were given symptom care while those who did were given appointments and were seen more quickly.

The rapid delivery of therapies across a range of therapeutic specialties as well as a considerable drop in outpatient consultations resulted from this.

The following specific outcomes were enhanced as a result of using ePRO:

  • less in-person visits for troubling symptoms in lung cancer patients;
  • decreased inflammatory bowel disease patients’ outpatient visits and hospital stays;
  • reduced requirement for a follow-up examination after breast reconstruction.

According to the researchers, the usage of ePROs also resulted in a 7.4% lower risk of treatment discontinuation in cancer immunotherapy patients.

Hand pointing at glowing digital brain. Artificial intelligence and future concept. 3D Rendering

Artificial Intelligence, Clinicians who were questioned for one of the articles discovered ePROs to be “useful rather than burdensome,” according to Aiyegbusi.

According to data, PRO collection may increase physicians’ satisfaction who are skilled in using PROs for routine patient management.

Furthermore, according to the researchers, “clinicians reported that ePRO data facilitated their understanding of patients’ general health status and symptoms, identification of low-grade and high-grade symptomatic adverse events.

They also noted a number of obstacles for ePROs, including inadequate computer and health literacy among some populations.

Those with socioeconomic disadvantages and a majority of Black people may be less likely to be given consideration for ePRO-based follow-up, they said. Hence, if the benefits of ePROs are not also accessible to patients who are already disadvantaged, their successful application in clinical care could worsen health disparities.

In order to assess the effects of ePRO systems on patient safety, patient and clinician satisfaction, impact on clinical workflow, and establish if they support cost-effective delivery of care, Aiyegbusi stated that “additional research is required.”

Focus of EY report is on transition to intelligent health ecosystem

Artificial Intelligence, Leading professional services company Ernst & Young (EY) recently released a paper titled “Shaping the next generation of digital and data-driven healthcare and sustainability practises.” The paper emphasises important facets of digital technology, data, and sustainability in defining the future generation of humanised healthcare given that the healthcare and life sciences industries have experienced a significant transformation over the past few years.

The report discusses a transition to an intelligent health ecosystem that will provide individualised health experiences. Artificial intelligence (AI) offers a way to link, combine, and examine data in new ways to uncover useful insights as the world of healthcare data continues to grow.

Healthcare algorithms will continuously advance in value and intelligence as a result of the application of AI into care delivery.

Artificial Intelligence, The walls between care locations may be broken down, and decision-making throughout the patient journey can be optimised, thanks to this data-driven smart system. Most significantly, it will give a way to provide care that is really human-centric.

The clinicians of the future may change into medical engineers and receive training in robots, big data, artificial intelligence, and other cutting-edge fields.

The paper also highlights how technology may revolutionise the whole pharmaceutical value chain. To ensure the safety and calibre of medicines, AI and machine learning (ML) can monitor in-line manufacturing operations.

A digital twin can simulate the complete manufacturing process in real time. Companies may be able to track operations in real time, foresee and predict future errors, maximise quality and efficiency, and provide therapies to patients much more quickly with the help of such a “digital factory.”

According to Suresh Subramanian, Partner & National Life Sciences Leader, EY India, “the accessibility of data and analytics is offering new opportunities for life sciences enterprises and health care service providers to rethink innovation and generate personalised health results.” Platforms that connect, gather, and share data will be the primary enablers of this future wealth creation.

As Indian businesses prepare to transition from supplying commodities to delivering ideas, the role of new technology will become even more crucial in the development of this integrated ecosystem.

Individuals with severe allergies may be helped by modifying a peanut protein using artificial intelligence.

How may the treatment environment and schedule for individuals with peanut (and other) allergies be altered by artificial intelligence (AI)?

We believe that this is an optimistic period for patients, which is fantastic. There weren’t many efforts being made at the time we established Ukko. Several of them, in my opinion, were being started, but not so much was said about them. And it’s been wonderful to observe how many initiatives are emerging and startups are beginning to assist patients.

One of the difficulties has been that, generally speaking, when treating allergies, we typically use the real dangerous allergen itself. Yet, there is a problem: the therapeutic substance is also the harmful substance (what you are reacting to).

Because it restricts what you can do with patients, it effectively puts you in an impasse. You are continuously making a choice between safety and effectiveness. “I can’t choose the best path… I have to use little doses if it’s too risky. It truly makes it difficult to develop a sort of treatment that is efficient, secure, and patient-centered.

Where does artificial intelligence (AI) fit into this, then? I’m going to generalize, but especially for Ukko, AI is used for specialized protein designers like micro-engineering, which enables us to ask ourselves, “What qualities do we genuinely want this protein to have?” How can we sort of get rid of the undesirable components that the protein shouldn’t have?

They might be harmful or hazardous. How can we preserve the components—call let them the good, for brevity—that might truly be healing, beneficial, or immunogenic for the patients? Hence, in the case of food allergies, it actually enables us to modify how the immune system interacts with the protein.

In a manner, the allergy itself can be advantageous, [and] play out the advantageous aspects without being hazardous overall. That is the plan. Can we create them with the features we desire?

The plan is to use our therapy to modify the immune system’s response to natural allergens while still being safe (and effective) for patients.

Thus, while the treatment will be simpler for patients to undergo, we should be able to achieve the same results as possible immunotherapy today in the sense that you could move around safely and not worry about incidental exposures. And this is what we will soon have to demonstrate in human experiments.

How can pharmacists assist patients with peanut allergies in their quest for knowledge?

Artificial Intelligence, I believe that pharmacists will always play a crucial role in healthcare since they frequently serve as the human interface between patients and potential treatments. So, I believe that they can effectively inform patients about both potentially fatal features of allergies.

Some patients urge patients to visit an allergist and kind helps them go through the various processes from the moment they’re trying to recognize whether what they’re experiencing could be an allergy and how to think about it. Other patients are unaware that this can truly be life-threatening.

where they should go to ask questions and attempt diagnoses up to, say, the point where they receive a certain therapy and work with a particular team who can help them ensure that they’re doing it safely, respond to queries, and so on. I believe that pharmacists may actually play a crucial and key part in this, as they do in all situations.