EMR-based prediction models developed and deployed in the HIV care continuum: a systematic review

Study findings and insights
1. The Role of EMRs in HIV Care
Using electronic medical records (EMRs) to predict patient outcomes is an exciting development in HIV care. EMRs are digital records with information about a patient's medical history, treatments, and test results. By analyzing this data, healthcare providers can identify patterns and predict when patients might be at risk of missing appointments, stopping treatment, or facing other challenges.
2. Benefits of EMR-Based Predictions
This approach has already shown promise. For example, some hospitals have used EMR-based models to increase the number of people being tested for HIV and to ensure those who test positive get connected to care faster. In some cases, EMR tools have helped increase monthly HIV screenings from a few people to hundreds and improve the number of patients staying in care.
3. Challenges of Implementing EMR Models
However, there are still challenges to making these models work well. For instance, missing information in a patient’s record can lead to biased predictions. Also, most of the current studies have been done in high-income countries, so it’s not yet clear how well these models will work in other settings.
4. Future Potential of EMR-Based Tools
Despite these hurdles, the potential of EMR-based prediction models is significant. With ongoing improvements and wider testing, these tools could transform HIV care, making it more personalized and efficient. By understanding when and where patients need the most support, healthcare providers can help more people stay engaged in their treatment, reduce the spread of HIV, and ultimately improve the quality of life for those living with the virus.
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