Six Ways Artificial Intelligence is Transforming Medication Management

 Artificial intelligence, a phenomenon by which machines are destined to work with the human intelligence, is making its mark with every new passing year. Artificial intelligence is playing a major role in almost all fields of life, may it be educational field, social, travelling, business, healthcare etcetera. 

If we talk about healthcare sector specifically, artificial intelligence has showed prevailing marks, ranging from robotic surgery to clinical research. Artificial intelligence has benefited mankind in healthcare sector by not only increasing reliability of diagnosis and treatment but also by reducing treatment cost. It has shown its triumph in replacing labor and decreasing chances of error by introducing computerized data collection to ensure proper and secure storage of data. Hence artificial intelligence is transforming medication management and definitely in a positive direction. 

As we discussed earlier, artificial intelligence is working its level best in healthcare sector, let us now throw light on the types of artificial intelligence technologies that are behind this success. Machine learning and natural language processing are those two artificial intelligence technologies that have highlighted its victory in the field of healthcare.

Machine learning, the most common kind of artificial intelligence technology, uses heuristic techniques for speeding up problem solving methods. It is of great use for handling large datasets or in areas where statistical methods are ambiguous.

On the other hand, natural language processing, as the name tells, is a technology that works to communicate computer language to easily understandable language for mankind. It helps in making clinical notes, organizing them into specific data form and supporting decision. Generating clinical notes is the greatest contribution of natural language processing in Health Information Technology (health IT).

Besides these two, artificial neural networks and deep learning technology are also showing their mark in healthcare sector. Taken together, artificial intelligence is transforming medication management in various ways, some of which are discussed next. 

Improve Medication Safety

Artificial intelligence has excelled in improving medication safety by making diagnosis and treatment processes more reliable and effective. Artificial intelligence can efficiently work to reduce data collection errors by investigating large datasets and organizing them in a particular order, for example reviews regarding drug utilization. Machine learning approach is a group of members working to reduce errors and omissions by predicting and removing outliers from a data. This helps in detection of medication errors and is a best tool that could be used for screening process. A group of people at Brigham and Women’s Hospital worked at this approach. It has been found that screening done through this approach can be helpful for getting alerts that could have been missed without screening. 

Reliably and Cost Effectively Predict Health Risks and Outcomes across Large Populations

Artificial intelligence has also benefited humans by enhancing reliability of diagnosis and intervention, and by decreasing cost of treatment. Artificial intelligence works to prevent drug abuse. A team in Michigan is working to elicit any chances of drug abuse in patients. For this purpose they have collected the history of present and previous illness, as well as history of present and past medical prescriptions of their patients from different available sources, for example through electronic health records (EHRs) and managed prescription drug monitoring programs in a algorithms to evaluate ‘overdose risk scores’ and predetermine the chances of drug abuse by using a prescribed opioids. Once the risks are calculated, the patients with high risks are prescribed interventions. Therefore it won’t be wrong to say that artificial intelligence has successfully transformed medication management by making decision making more reliable and effective.

Reduce Time and Expense

Artificial intelligence has proved to be an excellent technology for not only increasing reliability and accuracy of an intervention but also for reducing time and cost of intervention. The chances of errors have reduced due to the invention of artificial intelligence enabled dosage error reduction application. It is one of the top 10 artificial intelligence applications in the field of healthcare that has an ability to save expense of intervention. 

Streamline the Prior Authorization Process

Although electronic prior authorization (ePA) is excessively being used for approving drug usage such as those used in therapies, errors in data and delay of relevant piece of information is a limiting factor for this technology. Natural language processing has a great contribution in extracting and transforming structured data to provide health practitioners with clinical data of their clients. Furthermore, natural language processing performs this task as soon as the request for data is sent to electronic prior authorization (ePA). With the help of evidence based algorithms ePA programs and machine learning extract the information which is required by the clinician. Artificial intelligence has eased the process of extracting clinical data and also aids in decision making process by providing the health practitioner, the medical reports and health status of their clients as well as by giving them an idea of outcomes of certain therapies or drugs on patients with similar cases, to help them prescribe best therapies for their clients. When the health practitioners choose from the recommended therapies, the automatic approval of the prior authorization is approved. It is expected that prior authorization will become more advanced and reliable in coming future.

Monitor Medication Adherence

Once the doctor has prescribed medicines to the patient, it is patient’s responsibility to adhere to the intervention plan so he could get well soon. Patient adherence is a very significant factor in treating their illness therefore artificial intelligence can be utilized for the wellbeing of patients. Artificial intelligence can notify the health practitioners about the right time to initiate treatment. Natural language processing and machine learning has reduced the cost and labor. It has decreased the time required by the clinician to diagnose and recommend intervention to the patient. Thus, it won’t be wrong to say that artificial intelligence has saved lives and well as money. It has improved medical adherence and minimized the number of deaths. 

A Medicare Advantage Plan has proved to be useful in making medical compliance more efficient. This plan makes people aware of the outcomes of their medical non-adherence and notifies the patients to help them stick to the intervention plans recommended to them by their health practitioners. The better the communication with patients about their health conditions, the greater is patient’s medical compliance. 

The use of artificial intelligence is not only confined to this, but it also gives information about the outcomes of medical non-adherence of patients. Then according to the outcomes, it recommends best interventions, in terms of efficiency, reliability and cost, for tackling those issues. It has been unveiled that presence of a virtual assistant can aid in predicting patient’s risk failures and recommend interventions for dealing with those failures. Moreover, the virtual assistant monitors the need for a follow up session or a checkup session with the doctor by keeping in view the number of health practitioners the client is consulting, the role of caretakers of patients, the severity of disease and the amount of medicine the client is taking.  

Schedule Follow-Up Visits to Assess Therapy Progress

The shortage of time and busy routines of both health practitioners and patients makes it difficult to schedule follow up sessions. Artificial intelligence can perform this task for the doctors. It can schedule follow up sessions of the patients to save the time of both parties. Machine learning is used in this process to avoid any clashes in appointments. It schedules follow up sessions by keeping in mind the doctor’s working hours as well as patient’s attributes.

Thus, it is clear from the above discussed transformation in medication management that artificial intelligence is a driving force behind the progress of healthcare sector.