PMI is a $215 million innovative research venture that was started by the US government in 2015 with the purpose of advancing individualized medical treatments. It hopes to develop individualized prevention and treatment strategies for every American citizen. Medical treatments are mostly intended for the average patient, but because of the varying factors among different patients, treatments can be successful in some patients but can have different results or even fail in other patients. Every patient is unique, and doctors have always acknowledged that; even simple techniques such as blood transfusion cannot prove to be efficacious without proper matching. Precision medicine will give doctors the tools that they need to tailor treatments or define the right dosage appropriate for a given patient.
So far, new and powerful discoveries have already been made in treating a variety of cancers (lung, breast and colorectal) as well as leukemias and melanomas. Precision medicine has facilitated this with treatments being designed depending on the specific characteristics of a given patient or the profile of the tumor. Such treatments include Ivacaftor that treats a given form of cystic fibrosis. It is a much superior treatment as compared to the previous treatments that just addressed the symptoms but could not cure the disease. As part of patient care, patients that suffer from such conditions have to undergo molecular testing routinely so as to enable the physicians to choose the treatments that not only diminish exposure to adverse effects but also increase the chances of survival.
With precision medicine, medical professionals will be enabled to design a treatment based on the patient’s health history, microbiome composition (the composition of the microorganisms in a patient’s body), genome sequence, lifestyle, environment, and diet. This innovative approach intends to gather health and genetic data from U.S. participants. It is expected that those that will be enrolled to donate their health information under this project will be more than one million across the nation. With such a massive undertaking, the privacy of the health data submitted by the subjects has been given top priority by the White House including federal agencies and the Department of Health and Human Services in this project. Input from privacy and civil liberties advocates, bioethicists, patient groups and other technology experts is in line to ensure that any technical and legal issues concerning the security and the privacy of the shared data are addressed as stipulated in the Health Insurance Portability and Accountability Act (HIPAA). This HIPAA-compliant project will be implemented by the Harvard Medical School Department of Biomedical Informatics, the National Institutes of Health (NIH) and the Office of the National Coordinator for Health IT (ONC) in collaboration with EHR developers (Cerner, Allscripts, McKesson, Epic, drchrono and athenahealth). From over one million participants expected to take part, 700,000 will be enrolled via their health providers with the rest enrolling independently through S4S. For other EHR vendors willing to take part in this project, one of the first thing that they should do is join the Argonaut’s free, open Implementation Program. It will accelerate the basics of supporting FHIR with SMART’s OAuth profiles. It is expected that as S4S progresses the sample code, UX guidelines and documentation will be openly published for other vendors to build on.
Conventionally, these assessments were administered through paper and pen method used in combination with pagers or electronic wristwatches (Delespaul et al. 1995). With the advancement in technology, electronic devices (PDA’s), and smartphone apps such as Qolty surpassed the traditional pen and paper technique. The surveys are usually short and completed within 1 to 2 minutes. The items are designed for prompt and easy data collection which usually comprise of open-ended questions, checklists or self-report Likert scales, and visual analog scales (Csikszentmihalyi et al. 2013).