Digital Health Systems Design

Thrust Leads

Goals: Thrust 4 is developing new data-driven clinical workflows that seamlessly integrate new devices, like Lab-on-your-Wrist and Lab-in-your-Palm into clinical workflows in healthcare systems serving underserved communities. These novel clinical workflows have to meet multiple goals simultaneously – improve patient health outcomes while reducing care burden for providers and decreasing costs for the insurers. Thrust 4 is unique in its approach and has a multi-disciplinary team of engineers, behavioral scientists and clinicians working with healthcare system partners. The research in Thrust 4 is divided into three coupled projects to develop bio-behavioral models of new forms of LoyW and LiyP data (Project 4.1), develop interventions that are suited to the context of underserved communities (Project 4.2) and develop platforms for translating the new interventions for adoption in healthcare systems (Project 4.3).

Project 4.1: Bio-behavioral modeling of health data from wearables and point-of-care devices

PATHS-UP platforms, LoyW and LiyP, present new opportunities for disease management. In this project, our goal is to convert data from the advanced devices into clinically-interpretable models that capture both biological and behavioral insights about the patient health condition.

This requires modeling patient health and behavior in free-living environments, using data to understand and identify actions, environments, and nutrition. This project looks to understand “what” is being collected, “where” it is being monitored, and “when” these actions take place to best personalize modeling. Using continuous glucose monitors, wearable activity trackers, and gathering ecological momentary assessments, we understand the “why” and “how” of healthy decision-making.

Ashu Sabharwal

Rice (Thrust Co-Lead)

Farzan Sasangohar

TAMU (Thrust Co-Lead)

Bobak Mortazavi

TAMU

New biometrics from continuous glucose monitoring in underserved populations

THRUST 4.1 RESEARCH HIGHLIGHTS

Proposed breakfast CGM measures. Annotated breakfast start and peak shown with a red and green circle respectively in a participant with T2D. g1: starting glucose (SG) value, t1: start time of breakfast response, g2: glucose value at breakfast response peak, t2: time at breakfast response peak. (g2- g1) represents the maximum glucose rise (Max GR) and (t2- t1) represents the time to glucose peak (TTP). The purple hatched region represents the incremental area under the glucose curve (Glucose iAUC).

Lancet EClinicalMedicine (2021)

The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes – PubMed (nih.gov)

Souptik Barua, Ashutosh Sabharwal, Namino Glantz, Casey Conneely, Arianna Larez, Wendy Bevier, and David Kerr

Standardized CGM measures for n = 100 participants stratified by HbA1c. Boxplots shown as median (red), interquartile range (blue edges) and total range (black tails). Outliers shown as red dots. P-values for pairwise comparisons computed using Tukey's HSD criterion (ns: not significant, *:p

Lancet EClinicalMedicine (2021)

Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring – PubMed (nih.gov)

Souptik Barua, Ashutosh Sabharwal, Namino Glantz, Casey Conneely, Arianna Larez, Wendy Bevier, and David Kerr

Sensors (2022)

Food Habits: Insights from Food Diaries via Computational Recurrence Measures (mdpi.com)

Amruta Pai and Ashutosh Sabharwal

THRUST 4.1 NEWS HIGHLIGHTS

https://www.univision.com/local/houston-kxln/conoce-los-beneficios-de-los-dispositivos-portatiles-que-miden-los-niveles-de-azucar-en-la-sangre-video

https://beyondtype2.org/glucose-monitors-type-2-diabetes-hispanic/

https://news.rice.edu/news/2021/wearable-glucose-monitors-shed-light-progression-type-2-diabetes-hispaniclatino-adults

Project 4.2: Novel interventions for self-management of chronic diseases

Underserved communities face multiple simultaneous challenges that influence health outcomes, e.g., food insecurity is commonplace in many underserved populations who also often happen to have lower socioeconomic status (SES). We are developing culturally and contextually-relevant interventions which aim to address simultaneous overlapping challenges affecting underserved communities. This project includes several tasks focused on the development and validation of 1) interventions to address food insecurity, 2) identifying self-relevant strategies for managing blood glucose among those with pre-diabetes and type 2 diabetes and 3) identifying and addressing self-relevant barriers to physical activity among those with low-SES.

Ashu Sabharwal

Rice (Thrust Co-Lead)

Farzan Sasangohar

TAMU (Thrust Co-Lead)

Sherecce Fields

TAMU

THRUST 4.2 RESEARCH HIGHLIGHTS

BMJ Nutrition, Prevention & Health (2020)

Farming for life: impact of medical prescriptions for fresh vegetables on cardiometabolic health for adults with or at risk of type 2 diabetes in a predominantly Mexican-American population

Kerr, David, Souptik Barua, Namino Glantz, Casey Conneely, Mary Kujan, Wendy Bevier, Arianna Larez, and Ashutosh Sabharwal

Project 4.3: Advanced platforms for cost-effective telemonitoring of chronic diseases for the underserved

Telemonitoring has the potential to provide quick identification and resolution of emerging problems before they result in costly, life-altering complications, such as heart attack and stroke. Future adoption of telemonitoring technologies require interactions that are intuitive, effective, affordable, and usable. This project includes three tasks focused on 1) evaluate advanced mobile health and digital therapeutics platforms for telemonitoring, 2) understand the opportunities and barriers related to adoption, implementation, and integration of telemonitoring technologies, and 3) investigate the cost effectiveness of telemonitoring services in underserved communities.