Reporting Patient Generated Health Data and Patient Reported Outcomes With Health Information Technology

Engaging Disadvantaged Patients in Sharing Patient Generated Health Data and Patient Reported Outcomes Through Health Information Technology

This study will assess the feasibility of using patient-centered, commercial off-the-shelf (COTS) health information technology (IT) solutions to collect patient generated health data (PGHD) and patient-reported outcomes (PROs) from diverse, low-income disadvantaged populations. These data will then be mapped and reported in a way that will allow them to be made actionable and used to improve health care quality and delivery. The data mapping will be designed for data collection through technology such as mobile apps and wearables, and will be intended to support integration into interoperable electronic health records (EHRs), clinical information systems, and big data infrastructures.

Study Overview

• Status: Completed
• Conditions: Obesity
• Intervention / Treatment: Behavioral: 16-week program; Behavioral: Patient generated health data

Detailed Description

Patient engagement is particularly critical to achieving good chronic disease self-management. This is especially important for disadvantaged patients, who are disproportionately affected by chronic disease. A key component of chronic disease self-management is the ability for patients to record and monitor their ongoing performance on indicator measures. While health IT solutions have been shown to improve chronic disease self-management, adoption and use of costly, specialized technologies among disadvantaged patients is lower than among higher-income populations. In contrast, COTS technologies such as mobile phones are more accessible to and widely adopted by disadvantaged patients, thus bridging the gap of the digital divide.

The central research hypothesis posits that 1) low-income, disadvantaged patients both can and will provide high quality PGHD and PROs through COTS-based health IT solutions, and 2) these data can be integrated into clinical systems and used to improve health care quality and delivery. PGHD can be collected through patient interaction with COTS health IT solutions such as mobile health apps and fitness trackers. PROs can be collected via patient response to questionnaire-based PROs measures, or PROMs. These data can be transmitted to clinical information systems, integrated into clinical workflows and used by providers to improve health care quality and delivery. Using a sequential integrated mixed-methods approach, we propose to test the central hypothesis through three specific aims, as follows:

Aim 1: To assess the needs and preferences of disadvantaged patients and safety net health care providers regarding the use of health IT for communicating PGHD and PROs.

Aim 1 Research Questions: What specific features in COTS solutions meet the needs and preferences of disadvantaged patients for communicating PGHD and PROs to their providers? What PGHD and PROs are deemed most important by providers and patients for improving health care and health outcomes?

Answering these questions will inform health IT solution selection, design, usability, and utility; assist with prioritizing PGHD and PROs collection by data element and measure type; and identify potential discrepancies between patients' and providers' perceptions of PGHD and PROs importance.

Aim 2: To demonstrate the feasibility of PGHD and PROs collection through COTS health IT solutions in a patient-centered pilot intervention for weight management among disadvantaged patients.

Aim 2 Hypothesis: Providing PGHD and PROs through COTS solutions will improve engagement among disadvantaged patients. Secondary outcomes include improving key health indicators (e.g., weight, physical activity) and PROMs (e.g., quality of life, mental health symptoms).

Weight management is important in delaying, averting, and reducing the effects of multiple chronic diseases, including diabetes, hypertension, and obesity. A weight management-related intervention also serves as an effective test of PGHD and PROMs collection, due to the existence of numerous COTS solutions which use different methods for tracking common data elements related to weight, physical activity, and fitness.

Aim 3: To create an ontology mapping and set of interoperability resources which can be used to support integration of PGHD and PRO into clinical information systems.

Aim 3 Hypothesis: PGHD and PROs can be characterized by distinct types, elements, and structures which, once described, may be modeled and mapped to existing vocabularies for health data management.

In order to make PGHD and PROs actionable, these data must be integrated into clinical information systems such as electronic health records (EHRs) where it can be used by clinicians in their practice. Creating a "translation" by matching PGHD and PROs data elements to comparable ones in existing clinical vocabularies will provide a tool to support future data integration into the EHR. Creating a resource set which can be used with multiple EHRs will improve the generalizability and broad usability of the ontology mapping tool.

• Study Type: Interventional
• Enrollment (Actual): 300
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Colorado
    • Denver, Colorado, United States, 80204
      • Denver Health and Hospital Authority

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• BMI of 25.0-39.9,
• Has a smartphone
• English or Spanish as primary language
• assessed at "medium health risk" according a risk stratification algorithm based on clinical criteria, diagnostic scoring, and health care utilization

Exclusion Criteria:

• Does not meet inclusion criteria

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Intervention; Intervention patients will engage in a 16-week program where they will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity. Intervention patients will be asked to track patient generated health data (PGHD) elements related to weight management through a mobile health app loaded on their phones and/or through using a fitness tracker, depending on patient preference, and to share that information with the research team. Patient-reported outcomes (PRO) measures will be collected pre-and-post-intervention. Intervention patients will also be asked to provide answers to patient-reported outcomes measures on a weekly basis.	Behavioral: 16-week program; 16-week program where patients will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity.; Behavioral: Patient generated health data; Intervention patients will be asked to track patient generated health data and patient reported outcomes. PGHD elements related to weight management will be collected through a mobile health app loaded on their phones and/or through using a fitness tracker, depending on patient preference, and to share that information with the research team. Patient-reported outcomes (PRO) measures will be collected pre-and-post-intervention. Intervention patients will also be asked to provide answers to patient-reported outcomes measures on a weekly basis.
Active Comparator: Control; Control patients will engage in a 16-week program where they will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity. Patient-reported outcomes measures will be collected pre-and-post-intervention.	Behavioral: 16-week program; 16-week program where patients will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Patient Engagement (Patient Activation Measure)	Patient Engagement will be measured by participant performance on the Patient Activation Measurement (PAM)-13 tool. This validated instrument helps to show patients' motivation for being an active participant in managing their health. Each of the 13 items on the tool is rated on a four-point per-item scale, then converted to a total PAM score. The total PAM score is transformed into a scale score with values that range from 0 to 100 based on the calibration tables for the instrument, with higher numbers reflecting better scores and indicative of increased engagement. The scale score is reported here.	Baseline, Post-Intervention

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Weight Loss	Change in absolute percent weight	16 weeks
Healthy Days HRQOL-4 Measure	Healthy days will be measured by participant performance on the Health Related Quality of Life Scores (HRQOL)-4 questionnaire. This questionnaire is scored based on participant reported number of days experiencing poor physical or mental health. The scale ranges from 1-30, with lower scores being better in that they indicate fewer poor health days.	16 weeks
Healthy Days Symptoms Measure	Patient Reported Outcomes Measures, Healthy Days Symptoms Score - lower scores are better, save for Energy where a higher score is better. Minimum value is 0, maximum value is 30.	16 weeks
Number of Patients Who Responded to Text Messages	Text message response to prompts for weight data.	16 weeks

Collaborators and Investigators

• Sponsor: Denver Health and Hospital Authority
• Collaborators: Agency for Healthcare Research and Quality (AHRQ)
• Investigators: Principal Investigator: Susan L Moore, PhD, MSPH, Colorado School of Public Health

Study record dates

Study Major Dates

• Study Start (Actual): November 2, 2018
• Primary Completion (Actual): July 19, 2019
• Study Completion (Actual): August 31, 2020

Study Registration Dates

• First Submitted: December 14, 2017
• First Submitted That Met QC Criteria: December 21, 2017
• First Posted (Actual): December 29, 2017

Study Record Updates

• Last Update Posted (Actual): September 26, 2022
• Last Update Submitted That Met QC Criteria: September 6, 2022
• Last Verified: September 1, 2022

More Information

Terms related to this study

• Keywords: mobile health; patient reported outcome measures; health information technology; patient generated health data; consumer health informatics
• Other Study ID Numbers: 17-1082

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No
• IPD Plan Description: An enhanced entity-relationship (EER) model will be created for the PGHD elements and PROMs used in the study. Knowledge representation techniques will be utilized to describe the model in ontological terms. Concepts from the UMLS Metathesaurus will be used to create a mapping to the SNOMED-CT clinical vocabulary. Modeled information will be structured using Fast Healthcare Interoperability Resource (FHIR) standards and packaged as a set of FHIR resources. Each FHIR resource includes: 1) common definitions and representations; 2) a common metadata set; and 3) a human-readable part to aid user interpretation. Products will include a detailed EER schema, an interface and requirements assessment, an ontology, and a list of UMLS concepts and SNOMED-CT terms used in ontology mapping.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No