By Leslie Swanson, president and CEO, eXalt Solutions.
We are quickly moving to a patient-centric world in healthcare where treatment is coming to the patient, the patient is treated more like a customer, and medical facilities of all types must use technology from the business sector. Business sector software designed to improve the customer experience can now be used to improve the patient experience. No technology is driving this shift faster than artificial intelligence (AI). AI is propelling us into an increasingly digital medical experience where patients expect personalized experiences that take into account their individual needs and values, and empower them to get information fast and accurately.
Prescription drugs are ground zero for AI innovation
Although AI has been touted for everything from diagnosis to automating medical imaging to drug discovery, we believe that ground zero for AI innovation in patient-centric healthcare is prescription medicine. Prescribers and patients are suffering in countless ways from the complexity and associated errors in prescriptions.
A single drug has hundreds of factors that must be considered by a doctor or a pharmacist when prescribing or dispensing a drug to a patient. We examined 50 of the most popular drugs and found that the average number of considerations for a single drug is enormous:
- Adverse Reactions/Prescribed Drug = 40 Average
- Contra Indications/Prescribed Drug = 32 Average
- Drug Interactions/Prescribed Drug = 76 Average
- Demographic Considerations/Drug = 2-10
Currently, doctors must painstakingly examine each and every one of these considerations manually, and they usually must consider several drugs for a given condition which compounds the effort required to make even the most simple prescription.
Prevalence of prescription errors and economic impact
This complexity has resulted in dangerous error rates which have accelerated from .5 percent in 1990 to 1.5-9.9 percent in 2005:
- Prescribing error rates ranging from 0.6 to 53 per 1,000 orders
- Prescribing error rates from 1.5 to 9.9 per 100 opportunities
- About 30 percent of hospitalized patients have at least one discrepancy on discharge medication reconciliation.
The human mind is not suited to sift through each and every adverse reaction, contraindication, drug interaction, and demographic consideration manually. Unfortunately, these medication errors are a significant burden that adversely affects patients, providers, and the economy:
- Adverse drug events (ADEs) account for more than 3.5 million physician office visits and 1 million emergency department visits each year.
- It is believed that preventable medication errors impact more than 7 million patients and cost almost $21 billion annually across all care settings.
AI agents in prescription medicine
The issues in prescription medicine are 100 percent analogous to those in customer interaction management in other industries where companies need to engage with customers through self-service channels to be able to influence demand upfront and close the sale. AI-based knowledge bots provide customers a personalized self-service adviser giving them the same guidance and assistance they would get from a team of the world’s best experts.
These knowledge bots literally read the contents of several drug databases and automatically create a set of AI-Based Agents from this combined knowledge base:
- AI advisor: It can act to either
- Recommend prescriptions: AI knowledge bots can perform an entire intake for the demographic profile, pre-existing conditions, and existing prescriptions and recommend the best drugs for the condition to be treated.
- Check and validate prescriptions: AI knowledge bots can perform an entire intake for a patient capturing their demographic profile, pre-existing conditions, and existing prescriptions and validate that the drugs prescribed do not conflict with patient data captured in the intake.
- AI administrator: Creates a low friction experience by taking take over time consuming manual work for
- Retrieval of information from EHR: AI knowledge bots can retrieve patient information automatically.
- Submission of Information to EHR: AI knowledge bots can send patient information automatically to EHR or external pharmacy.
- AI analyst: Can collect patient feedback and identify patterns if there are unexpected adverse reactions or dissatisfaction with a drug. Consumers can get proactive notifications if there are changes in medication considerations.
AI agents critical to creating a patient-centric world
These AI prescription agents can be used across the entire health care ecosystem to create a patient-centric world with customer interaction management:
- Patient: The world will now be “the patient will see you now.” Patients armed with their own health profiles including information from personal devices, DNA and EHR will be empowered to get immediate answers and personalized drug treatments. They will be able to check prescriptions automatically and prevent many of the errors that occur today. They can compare their experiences with fellow patients and contribute information.
- Physicians and hospitals: It will be easier for physicians to identify the right drug treatment to cut the time and error of prescribing. The AI agent will not be a substitute for the doctor but it will remove all the manual work of collecting intake information and give an additional validation to remove potential prescription errors.
- Pharmacies: Using AI, pharmacies can ensure that they dispense prescription drugs with the assistance of AI agents that check and limit the potential for error that exists today.
- Pharmaceutical industry: Pharma companies can now craft a customer experience like other industries to create a patient-centered world where medicine comes to the individual rather than the other way around. These same AI Agents can proactively and promptly reach out to patients to provide a streamlined, personalized treatment experience.
It is time that health care adopt AI technology that is being used successfully in other industries without delay.