In the context of population health, data is essential for identifying high-risk patients who may benefit from targeted interventions.
Here's why:
Targeted Interventions:
Identifying high-risk patients allows healthcare providers to allocate resources more efficiently and design interventions that are specifically tailored to those most in need, improving overall population health outcomes.
Preventive Care:
By focusing on high-risk patients, the organization can implement preventive measures that reduce the likelihood of adverse health outcomes, which is a key objective in population health management.
Data-Driven Decision Making:
Data enables the identification of patterns and trends within the population, helping to stratify patients based on risk and prioritize care for those at the highest risk of complications or poor outcomes.
Resource Optimization:
Identifying high-risk patients helps in optimizing the use of healthcare resources by focusing efforts on those who require the most attention, leading to more effective management of the population's health.
While determining the voice of the customer, identifying high-risk low-volume processes, and determining high-cost procedures are valuable, the primary use of data in population health is to identify high-risk patients for targeted interventions.
Reference: NAHQ Guide to Population Health Management
NAHQ Healthcare Quality Competency Framework: Data Analytics and Risk Stratification