Improving Adherence and Outcomes by Artificial Intelligence-Adapted Text Messages (AIM@BP)

April 7, 2017 updated by: Karen Farris, PhD., University of Michigan
Uncontrolled hypertension is a major cause of morbidity and mortality and many patients fail to take their antihypertensive medication as prescribed. The investigators propose to use artificial intelligence (AI) to allow short message service (SMS or text messages) interventions to adapt to patients' adherence needs and substantially improve medication taking. The aims of the study are to: (1) develop AI methods for adaptive decision-making in human-centered environments and demonstrate the feasibility of the resulting AI-enhanced SMS medication adherence intervention, (2) demonstrate that the intervention can "learn" by adapting the SMS message stream according to patients' medication taking over time, and (3) examine potential intervention impact as measured by improvements in medication adherence and systolic blood pressures. The investigators will recruit 100 patients with uncontrolled hypertension and antihypertensive medication non-adherence. Adherence and other covariates will be measured via surveys at baseline, 3- and 6 months; blood pressures will be measured at baseline and 6 months. Participants will be given an electronic pill-bottle adherence monitor. Participants will receive SMS messages designed to motivate antihypertensive medication adherence. Message content and frequency will adapt automatically using AI algorithms designed to automatically optimize expected pill bottle opening. For Aim 1, the first 25 patients will be enrolled to develop and test alternative RL algorithms and fine-tune the system parameters. For Aim 2, the investigators will examine changes in the probability distribution over message-types and compare that distribution with patients' reasons for non-adherence reported at baseline. For Aim 3, the investigators will examine changes in self-reported medication non-adherence and blood pressure and automatically-reported pill bottle openings. This pilot study will establish the feasibility and potential impact of this novel approach to mobile health messaging for self-management support. The results will be used to support an R01 application for a larger and more definitive trial of intervention impacts.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

Self-management of chronic conditions involves complex behaviors, and patients vary in their adherence to these behaviors. The focus of this proposal is medication adherence because patients' failure to take their medications as prescribed is a major cause of excess morbidity and mortality and increased health care costs. Studies suggest that 33-50% of patients do not take their medications properly, contributing to nearly 100,000 premature deaths each year and $290 billion in health care costs. Adherence to antihypertensive medications is of particular importance in its own right, and hypertension can serve as an important tracer condition to better understand and improve medication adherence more generally. Uncontrolled hypertension is a major cause of stroke, coronary heart disease, heart failure and mortality, and medication non-adherence is a major cause of uncontrolled hypertension. For example, in a one-year study of ~5,000 hypertensive patients, most patients took their medications only intermittently with half of patients eventually discontinuing their medications against medical advise.

Improving medication adherence requires addressing multiple challenges because patients typically have a variety of reasons for not taking their medication as prescribed, such as beliefs about their disease and its treatment, organizational challenges, and cost barriers. Moreover, as patients' regimens, health status, and social context change over time, adherence support interventions need to adapt, but most services lack the flexibility to do so.

Mobile health (mHealth) services such as patient text messaging or SMS have shown some promise in improving medication adherence. However, since almost all mHealth services are based on simplistic, deterministic protocols, these interventions lack the capacity to meet patients' complex changing needs. As a consequence, these rudimentary systems have demonstrated only modest effects that tend to decrease over time. The investigators propose to apply artificial intelligence (AI) methods, specifically Reinforcement Learning (one type of AI), to develop a model medication adherence system that can automatically adapt SMS communication to improve individual medication taking.

The proposed project is the result of a new multidisciplinary collaboration between UM experts from the College of Pharmacy, College of Engineering, and School of Medicine. Our long-term goal is to improve health outcomes using artificial intelligence (AI) enhanced mobile health tools. The objective in the proposed pilot study is to develop a Reinforcement Learning-based mHealth program focused on medication adherence among patients with poorly controlled hypertension. Our central hypotheses are that a SMS system that uses Reinforcement Learning (RL) will: be acceptable to patients, adapt to hypertension patients' unique adherence-related needs and preferences and changes in these needs over time, and improve medication adherence and blood pressure control. The specific aims are:

  1. Develop RL methods for adaptive decision-making in human-centered environments and demonstrate the feasibility of the resulting RL-based adaptive SMS medication adherence intervention,
  2. Demonstrate "learning" by the RL-base adaptive system using data showing adaptation of the SMS message stream according to variation across patients and over time in the reasons for non-adherence, and
  3. Examine the potential efficacy of the RL-based adaptive SMS intervention with respect to improvements in medication adherence and systolic blood pressure.

The results of this pilot project will include a novel AI/RL technology and evidence regarding its real-world use based on experience with a sample of adults with poorly controlled hypertension. These results will be used to support an R01 application for a larger and more definitive study of the intervention's impact on patients' health and long-term adherence behaviors. Over the longer term, this AI-enhanced mHealth self-management support infrastructure and unprecedented collaboration between investigators in Pharmacy, Medicine, and Computer Science will lay the foundation for a larger program of NIH-funded research using similar AI approaches to addressing behavior change challenges in a large number of health and healthcare problems.

Study Type

Interventional

Enrollment (Actual)

49

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • Michigan
      • Ann Arbor, Michigan, United States, 48109
        • University of Michigan College of Pharmacy
      • Grand Rapids, Michigan, United States, 49503
        • Spectrum Health

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

21 years and older (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Patient must have Priority Health Care Health Insurance Coverage
  • Patient must have PDC of < 0.5 for anti-hypertensive medications

Exclusion Criteria:

  • No hypertension medicine currently taken
  • Patient doesn't text message (no cell phone) in an average week
  • No access to the internet
  • Patient has heart failure which makes it difficult to catch breath and move around
  • Patient uses artificial oxygen to breathe
  • Patient is currently under treatment for cancer
  • Patient currently has kidney disease that requires dialysis
  • Patient self reports a mental health diagnosis (from a health professional)
  • Patient reports having schizophrenia
  • Patient reports currently being treated bipolar disorder or manic-depressive illness or schizophrenia
  • Patients reports ever been diagnosed with dementia or Alzheimer's disease

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: PREVENTION
  • Allocation: RANDOMIZED
  • Interventional Model: PARALLEL
  • Masking: SINGLE

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: SMS (Text messaging)
This group will receive text messages during their entire enrollment period in the study.
Behavioral: SMS (Text messages)
Up to 1 text message a day. The artificial agent will determine whether to send a message each day. If it sends a message, it will also determine which of five message types to send.
No Intervention: No SMS (No text messages)
This group will not receive text messages during their entire enrollment period in the study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Medication Adherence (Proportion Days Covered (PDC)) assessed by administrative insurance records
Time Frame: 2 years
A measure of Proportion Days Covered (PDC) and is assessed administrative insurance records
2 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Self-reported medication adherence assessed via a questionnaire
Time Frame: baseline, 3 months and 9 months
Medication adherence is collected at these time points and assessed via a questionnaire.
baseline, 3 months and 9 months
Pill bottle openings (how often medication was taken) assessed by records from pill bottle caps (MEMS readers)
Time Frame: 9 months
proxy measure of how often medication was taken, assessed by records from pill bottle caps (MEMS readers)
9 months
Medication Beliefs assessed via a questionnaire
Time Frame: baseline, 3 months and 9 months
A measurement of the patients beliefs about the medication they take will be collected at these time points and assessed via a questionnaire.
baseline, 3 months and 9 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Michigan

Collaborators

Agency for Healthcare Research and Quality (AHRQ)

Investigators

  • Principal Investigator: Karen Farris, PhD, Univerity of Michigan, College of Pharmacy

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 1, 2015

Primary Completion (Actual)

November 4, 2016

Study Completion (Actual)

November 4, 2016

Study Registration Dates

First Submitted

May 12, 2015

First Submitted That Met QC Criteria

May 26, 2015

First Posted (Estimate)

May 27, 2015

Study Record Updates

Last Update Posted (Actual)

April 11, 2017

Last Update Submitted That Met QC Criteria

April 7, 2017

Last Verified

March 1, 2017

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • 1R21HS022336-01A1 (U.S. AHRQ Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Medication Non-adherence

Clinical Trials on SMS (Text messages)

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Bahrain

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe