How Healthcare Analytics Improves the Quality of Patient Care

Healthcare analytics is used in the healthcare industry to collect data from claims, pharmaceuticals, cost data, R&D, data from EHR’s, and behavioral data. These data are used to understand the patterns from the healthcare perspective to improve the quality of care given to the patients and reduce healthcare costs.

How Healthcare Analytics Can Improve Patient Care- Healthcare analytics helps to improve patient care in the following manner:

Streamline Process – The healthcare industry is creating analytics data by using machine learning, AI, and advanced tools which helps to reduce the time spent manually preparing these documents. Hospitals are also using mobile apps that provide real-time data about the availability of beds, quality and safety measures, census details, discharge summary. This helps to reduce the patient wait times as they can book an appointment from the app, emergency cases are handled with faster response time and elimination of creating and maintaining manual records. This app can also be used to make a strategic decision by the hospital department heads.

Reduced Admissions – Hospitals are using predictive analysis data to administer patients with chest pains and assess which patient needs to be hospitalized and which patients can be treated at home safely. This helps the hospitals to efficiently use their hospital staff, more free hospital beds to admit only the emergency patients, shorter wait times for the patients at the hospital, and reduced cost. These healthcare analytics data have helped to reduce the overall mortality and the emergency department(ED) returns by 10 %.

Reduced Costs – Healthcare systems are using data integration engines to achieve the quality of care for their patient with minimal costs. It helps to alert the hospital case managers to identify the high utilizer patients. These are the patients who use the emergency department for getting primary care and are also charged very less, they enter the emergency departments because they are not aware of how to use the other hospital service lines. Based on the analytical data, the patients are guided by the hospital case managers to the correct department depending on their illness.

Shorter ICU Stays – In the ICU is it important to know when to put the patient on ventilators and when to remove them. For this purpose, the hospitals are using data-driven dashboards that alert their ICU staff when the patient needs a ventilator and when they can be weaned from it. This application has helped the hospitals to reduce the time the patient spends on using the ventilators.

Predictive Analysis For The Healthcare Workforce – In 2017, the Society of Actuaries claims that 89% of healthcare providers are currently using predictive analysis for planning their healthcare activities. The HR department in any healthcare organization needs to maintain vast and sensitive data about the people, their jobs, personal information which are important from a business point of view. So many healthcare organizations are using predictive analytics that provides accurate data about a job applicant even before he/she is interviewed. The analytical data gives a list of high-performing candidates, their performance and productivity detail in the previous jobs, their leadership qualities, and also the leave and attendance details! (2017).

Using the right healthcare analytics and helps to not only improve the quality of patient care but also reduce the costs of treatment.

References