Hypothesis Testing + Time Series

Analysis of health clinic KPIs to measure patient engagement and adherence

Time series analysis and statistical comparisons of health clinic KPIs to answer patient and business impact questions
The challenge

Our client has a telehealth software platform that seeks to streamline client interactions, scheduling, and inventory management. They wanted to determine what the patient and business impacts were for health clinics after they were on-boarded onto their software platform. Many of the health clinics were on-boarded around the time of COVID-19 which meant the analysis was at times skewed by macroeconomic, seasonal, and environmental factors, meaning the impact on KPIs were difficult to analyze and interpret.

Our Solution

Our team explored their SQL databases to extract relevant time series metrics relating to business and patient KPIs. Using various time series and statistical techniques like forecast modeling and hypothesis testing, while controlling for seasonality, noise and existing trends, we were able to quantify and present the impact their software platform had on health clinics while accounting for external macro factors like COVID-19. Our findings showed increased patient engagement, higher prescription adherence, fewer appointment cancellations, and positive economic impact. These findings supported our client’s sales initiatives and strategic collaborations.

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