Systems and methods for optimal health assessment and optimal preventive program development in population health management

A method of identifying patients for assessment, performed by a processor executing software instructions stored in a memory, the method comprising:

• for each patient of a dataset of patients, calculating an evidence-based score (EBS), the calculating the EBS comprising:
• identifying one of more risk factors, and, for a time period t, calculate a risk factor vector Rp,t;
• for each patient, for a time period t+1, collecting a target metric;
• for each patient, determining whether the target metric in the time period t+1 is above a quantile level Q which is a percentile value;
• training a machine learning algorithm to predict a label Lp for a patient p as a function of Rp,t, such that Lp=f(Rpt), where f( ) is the machine learning algorithm, and where Lp is the EBS;
• identifying, from among a list of patients with a simple risk measurement below a quantile M, those patients with an EBS above a threshold value, for assessment;
• automatically generating a list of patients for assessment, the list containing those patients with a simple risk measurement below a quantile M and an EBS above the threshold value;
• and
• transmitting, to one or more healthcare professionals, the list of patients for assessment.