Improving Adherence and Outcomes by Artificial Intelligence-Adapted Text Messages
Trial ID: NCT02454660
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2015-05
Completion date: 2016-11-04
Sponsor: University of Michigan
Collaborators: Agency for Healthcare Research and Quality (AHRQ)
Conditions: Medication Non-adherence
Interventions: SMS (Text messages)
Locations: University of Michigan College of Pharmacy; Spectrum Health
Countries: United States; United States
Enrollment: 49
Age range: 21 Years - None
Sex: ALL

Summary:
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.

Eligibility criteria:
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

Outcomes:
Medication Adherence (Proportion Days Covered (PDC)) assessed by administrative insurance records