Healthcare Solutions
Enhance Your Healthcare solution With AI
There may be no more challenging environment that could benefit from AI decision support than healthcare where the number of variables to consider, the sometimes urgent need to make decisions when seconds matter, and with so much on the line. Qualetics’ blends the responsiveness of our AI Management System with expertise in AI and Machine Learning to solve challenging patient care challenges. Consider the examples below and how Qualetics can apply to deliver decision support to healthcare professionals and improve patient outcomes.
Healthcare Solutions
Enhance Your Healthcare solution With AI
There may be no more challenging environment that could benefit from AI decision support than healthcare where the number of variables to consider, the sometimes urgent need to make decisions when seconds matter, and with so much on the line. Qualetics’ blends the responsiveness of our AI Management System with expertise in AI and Machine Learning to solve challenging patient care challenges. Consider the examples below and how Qualetics can apply to deliver decision support to healthcare professionals and improve patient outcomes.
Improve Patient Data Quality
Minimize Distractions while Enhancing Critical Decision-Making
Deliver Better Patient Outcomes
IMPROVE PATIENT DATA QUALITY
Enhanced Patient Screening for Symptoms
Patient intake typically relies on the patient’s ability to recall symptoms relevant to their condition. An experienced professional may know to ask specific follow-up questions about symptoms the patient may not have mentioned, providing answers that can greatly improve the speed or accuracy of a diagnosis.
Following the NLP symptom example where symptoms provided are accurately interpreted we can use AI to enhance the screening process. Prompting more complete symptom feedback can prove critical to diagnostic accuracy allowing some conditions to be excluded while confirming others.
ENHANCING CRITICAL DECISION-MAKING
AI-Generated Health Risk Indicator
A patient’s appearance may belie the health risks they represent. In a busy clinical setting, it can be easy to miss the contributing factors to a patient’s condition overlooking aspects of risk. Providing decision support that assesses factors like a patient’s age, medical history, vital signs, and symptoms would be helpful if it provided a clear high, medium, and low-risk assessment with preliminary diagnostic information and key health indicators for the Doctor’s consideration.
In this example, a 25-year-old with pre-existing conditions arrives at a clinic with symptoms that may suggest Covid-19 (elevated temperature, hypertension beyond the patient’s already elevated range, headaches, body aches, shortness of breath).
Qualetics HealthCare Body of Work
Qualetics’ field of work in healthcare includes experience in a broad range of settings including remote healthcare delivery, clinical and hospital settings as well as the dental field.
The AI technologies we’ve employed include detailed Descriptive, Diagnostic, and Predictive Analytics, Deep Learning model development and training, Natural Language Processing and Image Analysis of the chest and dental X-rays applying complex logic and ML processes.
Below is a summary of our Healthcare Experience:-
Patient Risk Prediction – Clinical Intake Screening
Objective: To improve decision support for doctors, to analyze a patient’s demographics, history, and symptoms to deliver a health risk prediction.
Patient Audience: Patients in remote areas where healthcare outreach efforts are essential, as well as in support of clinics for healthcare screenings.
Analyzed Result: An AI-generated patient risk diagnosis providing the status as well as any likely risks associated due to pre-existing conditions. Example: “The initial assessment suggests pre-existing cardiovascular & diabetes diseases, along with current conditions of novel coronavirus disease that may need further evaluation of risk and treatment. The patient is predicted to be at medium risk as per risk assessment.”
Patient Re-Admission Risk Prediction – Clinical Discharge Screening
Objective: To predict the likelihood of a patient being readmitted to a hospital for a recurring problem based on an evaluation of the patient's condition at the time of hospital discharge.
Patient Audience: Patients being discharged from a hospital after treatment.
Analyzed Result: An AI-generated patient readmission risk diagnosis indicated by a score designed to the specification of the healthcare customer to indicate the level of risk on a numeric scale or a LIKERT scale (Ex. High, Low, Medium, Likely, Unlikely etc.)
Dental Image Analysis for Orthodontic Evaluation
Objective: Where a patient’s alignment issues may call for dental treatment and there was a need to apply the dental industry’s PAR index scoring measure (Peer Assessment Rating, a commonly accepted measure of orthodontic treatment) to determine the level of dental irregularity or malocclusion and assess relative improvement throughout treatment.
Patient Audience: Dental patients with alignment issues receiving corrective dental services
Analyzed Result: Scores measuring alignment and spacing of patient’s dental conditions over time.
Chest X-Ray for Chest Related Disease Conditions
Objective: To provide color-coded image decision support for doctors evaluating chest X-rays. The analyzed result provides color-coded shading associated with such chest-related diseases as viral and bacterial pneumonia, tuberculosis, Covid-19, and other conditions.
Patient Audience: The algorithm was trained to provide the intended result for any human chest X-ray.
Analyzed Result: Initial training resulted in the algorithm achieving model accuracy of 85% with a 20% false positive rate and 19% false negative rate.
Diabetes Treatment Assessment - Clinical Setting
Objective: To analyze the success of two different diabetes treatments on an extensive patient population to understand treatment effectiveness relative to patient factors.
Patient Audience: Patients treated by a diabetes clinic network operated by a major Indian hospital network.
Analyzed Result: Presents treatment effectiveness on a time series graph correlating the duration of the treatment, treatments used, and changes in the condition of patients over time.
AI-based Cardiac Risk Prediction - Early Warning for Hospital Setting
Objective: To provide a predictive early warning for incoming hospital patients.
Patient Audience: In support of hospital or emergency room intake procedures this is designed to provide predictive insight providing staff early warning of a pending cardiac event before cardiac arrest occurs.
Analyzed Result: A Cardiac Risk prediction score designed to the specifications of the healthcare customer indicating the level of risk a patient has concerning heart disease.
Symptom Screening AI - Intake for Remote Care Appointments
Objective: To facilitate more accurate, and productive screening processes for a follow-on visit with the doctor, this algorithm is meant to predict disease possibilities and respond to the symptoms presented selectively prompting for other symptoms that would effectively exclude some disease conditions and narrow the possible diagnosis for the doctor’s attention.
Patient Audience: Underserved populations in remote locations where the patient rarely if ever can be evaluated or treated by medical professionals.
Analyzed Result: The models have been built and data is currently being collected to initiate the training and testing process.
Other Platform Features
API Based Integration
Integrate Analytics and AI outcomes like Content Recommendations, Adaptive Learning Journeys, Learner History and Real-Time Learner Competence and Confidence insights with our API based integration simplifying the process of enhancing your solution with AI.
Collaborative Insights
Improve decision-making and alignment across your organization and in client communication by democratizing the insights in curated dashboards with a full set of sharing and collaboration features.
Subscriptions
No need to monitor the constant flow of new insights to know when key behaviors and details are happening. Let Qualetics work for you by making it easy to define scenarios you want to be informed of immediately and the system will reach out and notify you when it happens, as it happens.