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Individuals suffering from Serious Mental Illnesses (SMI) are at risk for serious adverse health and social outcomes compared to the general population due to a high prevalence of chronic physical health disorders such as cardiovascular disease, hypertension, and Type II Diabetes, along with consequences of mental distress such as suicide, substance abuse, and acute stress.While pharmacological treatments exist for these conditions, they have limited effectiveness in SMI populations because: (1) up to 60% of individuals with SMI do not take their psychiatric or somatic medications as prescribed, (2) individuals with SMI have poorer clinical outcomes and experience high rates of hospitalizations, and (3) individuals with SMI experience worse care. Challenges in the management of these complex chronic health and mental health conditions have led to the development of intensive community-based service delivery programs. However, as currently structured these intensive in-person interventions have only had limited impact optimizing service delivery, and consequently on adherence to treatment and health outcomes. While in-person clinical contact in select situations is important, telehealth may serve as an effective and nimble intervention to help meet the high need for clinical intervention for SMI populations and particularly those with geographically limited-service access. Although research exists regarding the efficacy of telehealth with SMI populations, most of the existing interventions with this population have been designed for institutional settings, not community settings, because of barriers to adoption of telehealth such as limited access to digital technology, technical support difficulties and cost of necessary technology. The COVID-19 pandemic has underscored the need for developing effective telemedicine and telemonitoring technologies to serve the unique needs of this vulnerable population in community settings. This project builds on a successful Phase I SBIR project and ongoing Phase II clinical trial of the Medherent medication management platform. This study will test an expanded set of telehealth care-coordination services that can be used to address the broad health needs of individuals diagnosed with SMI living in community settings and supported by community mental health agencies. The study team will recruit 300 individuals, including 200 individuals currently using the device and 100 new users of the device. The study will test the existing Medherent platform and a set of extended services. Our key outcomes include acute service use, receipt of preventive and other health screenings, health outcomes and costs of services. The study will use a Stepped Wedge Design approach with a matched comparison group to identify potential benefits of the intervention.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Usual Care | No Intervention | Usual Care: no intervention elements. | |
| Existing Medherent | Active Comparator | Group using the Medherent Device with no added intervention components. |
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| New Medherent | Experimental | Group using Medherent Device with added interventional components. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Medherent | Other | Medherent is a telehealth adherence intervention platform designed for individuals with Serious Mental Illness living in the community. It is currently being used to dispense medication and monitor consumer adherence. It is a fully supported digital hub that is always on network connection and provides a cost- effective mechanism for increased care coordination through the Electronic Medication Record (EMR). The enhanced intervention will add collection of health data though Bluetooth connected devices, Telehealth medical visits and integrated algorithms that provide feed back to providers and consumers about health status. |
| Measure | Description | Time Frame |
|---|---|---|
| Health Service Utilization | The study team will use medical records and claims data to calculate monthly counts of outpatient/ambulatory care events, inpatient hospitalization, and Emergency Room or urgent care visits. The Healthcare Effectiveness Data and Information Set (HEDIS) tool will be used to identify preventable hospitalization or emergency room visits, follow up care after hospitalizations or emergency room visits. | Two years prior to study enrollment to at least one year after study enrollment. |
| Consumer Satisfaction STAR-P | Consumers self reports of services satisfaction with agency services. Scale is between 12 and 60. Higher scores are associated with higher satisfaction with services. | Change from Baseline to 6 months to 12 Months |
| Diabetes control as reported hemoglobin A1c levels | Reported hemoglobin A1c will be use to assess adherence to medication by modeling individual change change over time. A1C levels between 5.7 and less than 6.5% will be conferred as prediabetes range. A1C level of 6.5% or higher are considered in the diabetes range. | Two years prior to study enrollment to at least one year after study enrollment. |
| Reported Low-density lipoprotein (LDL)/High-density lipoprotein (HDL) | Reported Low-density lipoprotein (LDL)/High-density lipoprotein (HDL) will be use to assess adherence to medication by modeling individual change change over time. Normal HDL is 45 to 70 mg/dL for men and 50 to 90 mg/dL for women. The cutoff for good total cholesterol to HDL ratio is 5:1. Lower ratios are better than higher ratios. | Two years prior to study enrollment to at least one year after study enrollment. |
| High blood pressure. | Reported blood pressure will be use to assess adherence to medication by modeling individual change change over time. Scores will be considered normal if systolic is less than 120 mm Hg and diastolic less than 80 mm Hg. Scores will be considered elevated if systolic is 120-129 mm Hg and diastolic is less than 80 mm Hg. Scores will be considered evidence of hypertension if systolic is greater than 130 mm Hg and diastolic is more than 80 mm Hg. |
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Inclusion Criteria:
Exclusion Criteria:
• Unable to have the Medherent device in residence
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| Name | Affiliation | Role |
|---|---|---|
| George Unick | University of Maryland | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Maryland | Baltimore | Maryland | 20201 | United States |
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| ID | Term |
|---|---|
| D001523 | Mental Disorders |
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To test our research aims we will use a stepped wedge cluster randomized design (SWD) and matched control group. All enrolled individuals will be grouped into a rollout unit. This unit could be comprised of individuals living in a group home or multiple group homes, a group of clients served by a case manager at an agency or a division of an agency. We anticipate that units will have approximately 10 - 15 clients and that we will have approximately 25 units across participating agencies. This design allows the study team to address problems with the rollout of the machines facilitating a good phase-in of the intervention for each unit. Third, this design addresses issues associated with the diffusion of the intervention within agencies that would occur with individual randomization while maintaining strong internal validity and assessment of the treatment effect.
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| Two years prior to study enrollment to at least one year after study enrollment. |
| Change in Health Service Costs | Costs of health services and mental health agency care will be calculated from Medicaid Claims data. These costs will be calculated for outpatient care, emergency room/urgent care, and inpatient hospitalization care by summing up all the costs of medical claims in each of these categories by month. | Two years prior to study enrollment to at least one year after study enrollment. |