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Population Health Analytics

Population Health analytics is an approach to identify and resolve healthcare issues of the whole population. It segments the needs of the patients and provides them with the best services to meet their needs. The local population is dividing into several groups depending on their health risk identification and various aspects such as health behaviors, health status and use, and quality of available services. <br>

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Population Health Analytics

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  1. THE IMPACT OF POPULATION HEALTH ANALYTICS ON THE QUALITY OF PATIENT SERVICES Healthcare organizations worldwide with a large amount of patient population are fast-growing. It depends on the tried and tested or evidence-based theory to safeguard the patients' health and safety. Back when the traditional principle was following called "Fee-for-service," which only aimed at dealing with the patients' sickness and not with health outcomes, leading to less attention and engagement towards the patient's health. Many healthcare providers highly use ​population healthcare management​ to improve patients' health by tracking and monitoring the clinical and health outcomes while estimating costs. The need for​​population health analytics arises due to various challenges faced, such as pharmaceutical costs, risk stratification, proper patient identification, etc. The communication gap between doctors and the patients was the central issue where the patients hesitated or did not centralize an exact conversation with their healthcare providers. Tan exactly overcame all challenges due to population health solutions. It engaged more and more patients beyond the shorter timeframes and helped identify high-risk patients via an easy patient identification strategy. The healthcare industry has initiated various​ population health management strategies that provide positive health outcomes. The local population's data is collected as a whole and later transformed into a single patient's record depending on the patient's health status and the best quality of services available for him/her. Proper patient identification makes it easier to ensure the adequate delivery of the patients' benefits, hence improving their health and safety. After collecting data from the local population, they identify and evaluate improvement opportunities based on care variation. Due to this digital revolution, healthcare organizations have switched from a fee-for-service model to a value-based model, which brings about positive health outcomes. It optimizes care management processes and products to support individuals across the continuum of care. Conclusion:​​Population Health Analytics​ rewards healthcare providers to promote wellness and offer additional funding to improve workflow and technology. These changes make it easier for them to balance evidence-based practices and focus on preventative care, improving care quality.

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