ObesityNCT03386773
Reporting Patient Generated Health Data and Patient Reported Outcomes With Health Information Technology
A study testing 16-week program and Patient generated health data in people with Obesity, run by Denver Health and Hospital Authority at 1 site in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Obesity
- What is being tested?
- 16-week program and Patient generated health data
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 300 participants
- Where
- 1 siteUnited States
- Study dates
- 2 Nov 2018to 31 Aug 2020
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- Does not meet inclusion criteria
Trial locations and contacts
1 site in 1 country.
United States1 site
Denver Health and Hospital Authority
Denver, Colorado, 80204
About this study
Official title: 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.
Read the 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.
- Conditions
- Obesity
- Being tested
- 16-week program, Patient generated health data
- Keywords
- patient generated health data, patient reported outcome measures, health information technology, mobile health, consumer health informatics
- Medical subject headings
- Obesity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
16-week programBehavioural
16-week program where patients will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity.
Patient generated health dataBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Intervention | Experimental | 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. Receives: Behavioral: 16-week program; Behavioral: Patient generated health data |
| Control | Active comparator | 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. Receives: Behavioral: 16-week program |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Baseline, Post-Intervention
Secondary outcomes (4)
Weight Loss
Change in absolute percent weight
Measured: 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.
Measured: 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.
Measured: 16 weeks
Number of Patients Who Responded to Text Messages
Text message response to prompts for weight data.
Measured: 16 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Dec 2017
- Study start2 Nov 2018
- Primary completion19 Jul 2019
- Study completion31 Aug 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for ObesityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Recruited participants will be randomized to one of two arms, intervention or control. Both intervention and control groups 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 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. Intervention patients will also be asked to provide answers to patient-reported outcomes measures on a weekly basis. If intervention patients do not have a fitness tracker, a low-cost option will be provided for them. Both iOS and Android phone options will be supported. The app will be selected from a limited set of well-established options such as LoseIt!, MyFitnessPal, Apple Health, or Google Fit.
- Masking
- None (open label)
- Enrolment
- 300 participants (actual)
Sponsor and investigators
- Lead sponsor
- Denver Health and Hospital Authority
- Sponsor type
- University, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Responsible party
- Principal investigator, Susan Moore, Colorado School of Public Health
- Investigators
- Susan L Moore, PhD, MSPH, Principal investigator, Colorado School of Public Health
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03386773
- Sponsor's protocol ID
- 17-1082
- Status last verified
- Sep 2022
- First submitted
- 14 Dec 2017
- Last updated
- 26 Sep 2022
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: 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.
Study at a glance
From the registry record, last updated by the sponsor on 26 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Engaging Disadvantaged Patients in Sharing Patient Generated Health Data and Patient Reported Outcomes Through Health Information Technology
- ClinicalTrials.gov ID
- NCT03386773
- Acronym / sponsor ID
- 17-1082
- Conditions
- Obesity
- Keywords
- patient generated health data, patient reported outcome measures, health information technology, mobile health, consumer health informatics
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 300 participants (actual)
- Lead sponsor
- Denver Health and Hospital AuthorityUniversity, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Study start
- 2 Nov 2018 (actual)
- Primary completion
- 19 Jul 2019 (actual)
- Study completion
- 31 Aug 2020 (actual)
- First posted
- 29 Dec 2017 (actual)
- Results
- Posted 26 Sep 2022
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Recruited participants will be randomized to one of two arms, intervention or control. Both intervention and control groups 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 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. Intervention patients will also be asked to provide answers to patient-reported outcomes measures on a weekly basis. If intervention patients do not have a fitness tracker, a low-cost option will be provided for them. Both iOS and Android phone options will be supported. The app will be selected from a limited set of well-established options such as LoseIt!, MyFitnessPal, Apple Health, or Google Fit.
| Arm | Type | Receives |
|---|---|---|
| Intervention | Experimental | Behavioral: 16-week program, Behavioral: Patient generated health dataIntervention 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. |
| Control | Active comparator | Behavioral: 16-week programControl 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (1 listed)
- Does not meet inclusion criteria
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| 16-week program16-week program where patients will receive regular health promotion messaging about (a) food, nutrition, and diet; and (b) exercise and physical activity. | Behavioural | Control, Intervention |
| Patient generated health dataIntervention 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. | Behavioural | Intervention |
Primary outcome
Patient Engagement (Patient Activation Measure)
Time frame: Baseline, Post-Intervention
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.
4 secondary outcomes
Weight Loss
Time frame: 16 weeks
Healthy Days HRQOL-4 Measure
Time frame: 16 weeks
Healthy Days Symptoms Measure
Time frame: 16 weeks
Number of Patients Who Responded to Text Messages
Time frame: 16 weeks
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Sep 2022.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: No. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Susan L Moore, PhD, MSPH principal investigator
Colorado School of Public Health
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing 16-week program and Patient generated health data in people with Obesity, run by Denver Health and Hospital Authority at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Sep 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 26 Sep 2022). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient Engagement (Patient Activation Measure) (time frame: Baseline, Post-Intervention). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Sep 2022; AzTrials last refreshed its copy on 6 Nov 2026.