Clinical evidence downloads

Glooko conducted the study to examine remote patient monitoring uptake and diabetes-related outcomes during the COVID-19 pandemic for people with diabetes using a remote care solution.

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Glooko conducted the study to determine if a comprehensive RPM diabetes management program was more effective in reducing HbA1c compared to usual care.

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Glooko conducted this HEOR study to estimate the impact of remote patient monitoring and digital therapeutics technology on diabetes outcomes, healthcare resource use and costs.

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Glooko And Cecelia Health’s Results Suggested Strong Patient Engagement And Clinically Meaningful Reductions In A1C And Above Average Time-In-Range.

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Using secondary analyses to examine whether the comprehensive Glooko remote patient monitoring diabetes management program improved diabetes-related distress compared to usual care in a sample of adults with type 2 diabetes.

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Glooko investigated whether people with type 2 diabetes demonstrated improved glycemia after participating in remote patient monitoring programs.

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In this randomized control trial, Glooko evaluated the short-term efficacy of mobile-enabled RPM implemented in an ambulatory diabetes clinic setting.

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Glooko developed a machine learning algorithm that predicts risk for decreased sensor glucose time in range following a clinic appointment.

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Glooko’s novel algorithm to assess glycemic control performs well compared to clinician assessment and helps clinicians make treatment decisions faster.

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Results of a study using Glooko for remote management of an adult, Type 2 diabetes population experiencing glycemic control issues.

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Glooko developed a machine learning model that predicts risk of declining engagement with its mHealth app that supports diabetes self-management.

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In the study, Glooko evaluated the extent to which an mHealth app for long-acting insulin dose adjustment can help people with type 2 diabetes.

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The purpose of this Glooko study is to evaluate the efficacy of remote patient monitoring pilot programs implemented in endocrinology clinics.

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In the study, Glooko assesses whether the use of an in-app food logging feature corresponded with improved glycemic outcomes.

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This retrospective Glooko study focuses on quantifying the clinical benefit of using a mobile health app to facilitate self-monitoring behavior.

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In the study, Glooko assesses whether the use of reminders features corresponded with improved behavioral and glycemic outcomes in the real world.

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In the study funded by Glooko, mobile-enabled remote patient monitoring (RPM) with weekly monitoring and episodic telephonic coaching led to significantly improved A1C after 24 weeks.

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Clinical evidence downloads

Glooko conducted the study to examine remote patient monitoring uptake and diabetes-related outcomes during the COVID-19 pandemic for people with diabetes using a remote care solution.

Glooko conducted the study to determine if a comprehensive RPM diabetes management program was more effective in reducing HbA1c compared to usual care.

Glooko conducted this HEOR study to estimate the impact of remote patient monitoring and digital therapeutics technology on diabetes outcomes, healthcare resource use and costs.

Glooko And Cecelia Health’s Results Suggested Strong Patient Engagement And Clinically Meaningful Reductions In A1C And Above Average Time-In-Range.

Using secondary analyses to examine whether the comprehensive Glooko remote patient monitoring diabetes management program improved diabetes-related distress compared to usual care in a sample of adults with type 2 diabetes.

Glooko investigated whether people with type 2 diabetes demonstrated improved glycemia after participating in remote patient monitoring programs.

In this randomized control trial, Glooko evaluated the short-term efficacy of mobile-enabled RPM implemented in an ambulatory diabetes clinic setting.

Glooko developed a machine learning algorithm that predicts risk for decreased sensor glucose time in range following a clinic appointment.

Glooko’s novel algorithm to assess glycemic control performs well compared to clinician assessment and helps clinicians make treatment decisions faster.

Results of a study using Glooko for remote management of an adult, Type 2 diabetes population experiencing glycemic control issues.

Glooko developed a machine learning model that predicts risk of declining engagement with its mHealth app that supports diabetes self-management.

In the study, Glooko evaluated the extent to which an mHealth app for long-acting insulin dose adjustment can help people with type 2 diabetes.

The purpose of this Glooko study is to evaluate the efficacy of remote patient monitoring pilot programs implemented in endocrinology clinics.

In the study, Glooko assesses whether the use of an in-app food logging feature corresponded with improved glycemic outcomes.

This retrospective Glooko study focuses on quantifying the clinical benefit of using a mobile health app to facilitate self-monitoring behavior.

In the study, Glooko assesses whether the use of reminders features corresponded with improved behavioral and glycemic outcomes in the real world.

In the study funded by Glooko, mobile-enabled remote patient monitoring (RPM) with weekly monitoring and episodic telephonic coaching led to significantly improved A1C after 24 weeks.