MedAware provides an innovative solution to the need for detecting and eliminating prescription errors. MedAware’s patent-pending technology uses big data analytics and machine learning algorithms to analyze large scale data of Electronic Medical Records (EMRs). By deploying MedAware’s proprietary algorithms to mine the data gathered via millions of EMRs, MedAware’s engine builds a mathematical model which represents real-world treatment patterns. A prescription largely deviating from the standard treatment spectrum is likely to be erroneous.
The underlying assumption behind this solution is that most physicians perform well most of the time. Consequently, prescription patterns of thousands of physicians treating millions of patients can be used to determine the “normal” treatment spectrum. A prescription largely deviating from this spectrum is likely to be erroneous. One can find many similarities between this approach and the one successfully employed for fraud detection at the point of sale. Both apply cutting edge big data analytic capabilities to identify outliers from a trend or practicein order to identify suspicious or erroneous transactions.
MedAware provides the following decision support and risk management tools targeted at improving patient safety and healthcare quality:
MedAware Alerting System (MedAS) – Real time alerts for eliminating prescription errors
Whenever a physician enters a new prescription through the computerized physician order entry system, MedAware’s software performs a real-time evaluation of the prescribed drug against the specific and up-to-date patient profile. When it identifies a deviation from the normal treatment spectrum of similar patients, it sends an alert to the physician, highlighting the potentially hazardous error. The physician may respond by accepting or dismissing the alert. The system also keeps track of all active medications and provides additional alerts if new incoming data (such as blood tests, procedures, diagnoses, etc.) renders one of the active medications hazardous.
MedAware’s system is self-learning. Based on the physician’s response to the alert, it automatically fine-tunes the model so that an alert, which has been repetitively rejected, will not be repeated, thus avoiding alert fatigue.
MedAware Risk Management (MedRIM) decision support tool
MedRIM offers hospitals and caregivers a reporting tool that enables better risk management, quality control, and essential feedback to clinicians on potentially erroneous prescriptions. The tool runs as an independent analytical task that can be activated either upon request or periodically, at an interval that can be decided by the caregiver.
The MedRIM tool gathers patient data and prescription data and compares them to historical norms for the institution. Outliers are flagged for further analysis by the prescribing clinician or by another selected professional.
MedRIM reports include the following information:
- Institutional Risk Mapping – departments with exceptionally high rates of prescription errors and the most commonly misprescribed medications
- Patient Risk Mapping – patients with medication errors
- Physician Risk Mapping – physicians who tend to have a high rate of errors
- Medication Risk Mapping- medications which are more frequently misprescribed
With a simple installation, and without any changes to the institution’s EMR, MedRIM ensures better care, improvements in safety performance and safety training, and risk reduction.
MedAware Quality Control (MedQC) decision support tool
MedQC provides clinicians with a powerful tool to compare treatment and outcome patterns for similar patients with complex diseases. This tool provides answers to the following questions of interest to any healthcare provider, and which could not be previously answered:
- Are similar patients treated differently?
- What have other physicians prescribed to similar patients in similar clinical scenarios?
- What was the treatment outcome of similar patients in similar clinical scenarios?
- What diagnoses emerge from the patient’s profile which are not on his list of diagnoses?
MedAware Reducing Alert Fatigue (MedRAF) decision support tool
MedRAF is a decision support tool that identifies the rules that are most likely causing the “alert fatigue.” It is up to the healthcare provider to remove these rules, or present the alerts generated by these rules in a different manner, in order to distinguish them as potential false alarms.