# Predictive Medicine Predictive medicine involves predicting the probability of disease and implementing measures to either prevent the disease altogether or significantly decrease its impact upon the patient. The outcomes of predictive medicine are often applied to the care of individual patients, but may also inform the deployment of resources to entire populations at high risk. The goal of predictive medicine is to predict the probability of future disease so that healthcare professionals and the patient themselves can be proactive in implementing lifestyle modifications and increased physician surveillance, such as regular skin exams, mammograms, or colonoscopies. Predictive medicine changes the paradigm of medicine from being reactive to being proactive, and has the potential to significantly extend the duration of health and to decrease the incidence, prevalence and cost of diseases. Much attention has been focused on the availability of genetic makers of vulnerability to specific illnesses. However the accurate capture of phenotypic (e.g. height and weight, blood pressure), environmental factors (e.g. smoking, alcohol consumption) and other lifestyle factors (e.g. exercise, nutrition, quality of life) is not to be overlooked. For example: 1. Patient is a smoker and has ischemic heart disease ? predict excess risk of myocardial infarction 2. Patient has BRCA1 gene and is a 40 year old woman ? predict (excess) risk of breast cancer SNOMED CT can help to support predictive medicine by: * Helping to identify clinical trial candidates * Helping to analyze clinical data, such as family history, lifestyle and environmental findings, to improve predictive capabilities * Providing a link between patient data and risk assessment rules, so that rules can be triggered based on subsumption of codes recorded in clinical data. For example, matching against patient records could be improved by defined the above rules as: Risk: 22298006 |myocardial infarction|\ 2\. Criteria: 412734009 |BRCA1 gene mutation positive|\ Risk: 254837009 |breast cancer| *** Provide Feedback --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.snomed.org/snomed-ct-practical-guides/snomed-ct-data-analytics-guide/7-task-oriented-analytics/7.3-clinical-research/7.3.2-predictive-medicine.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.