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| Name | Class |
|---|---|
| PJSC VimpelCom | UNKNOWN |
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DIALOG is a study to assess the efficacy and safety of remote patient monitoring using virtual operator voice technologies and a business intelligence (BI) system for timely detection, prevention of early complications, worsening of the condition, and other adverse events in patients who have been discharged from the hospital.
After ensuring that the patient's characteristics meet the inclusion and exclusion criteria and confirming the patient's ability to use the "voice assistant", as provided in the research protocol, patients who have completed the briefing will be able to use the voice assistant at home. During the month, robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system will be conducted for five groups of patients (CHF, DM, AH, LPD, and patients who underwent total knee replacement) who have been discharged from the hospital. The system developed allows for quick surveys, collection of data on patient conditions, and convenient transfer of this data to the physician. The physician will receive information on patient status in a graphical form using a traffic light system. In the event of any red flags, the physician will contact the patient for further discussion on treatment strategies. The study will evaluate the efficacy and safety of utilizing the "voice assistant" by assessing the achievement of target values for controlled parameters, evaluating patient satisfaction and adherence to treatment, reducing the number of repeat hospitalization, and reducing overall mortality and cardiovascular-related mortality.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Heart Failure | Experimental | Patients with chronic heart failure who was hospitalized due to decompensation of their condition. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight) related to heart failure. |
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| Diabetes mellitus | Experimental | Patients with diabetes mellitus who was hospitalized with unstable glucose level. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight, glucose) related to diabetes mellitus. |
|
| Arterial hypertension | Experimental | Patients with arterial hypertension who was hospitalized with unstable arterial pressure. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, hypotension sings, signs of damage to target organs). |
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| Lymphoproliferative diseases |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Voice assistant | Device | Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands on the "question-answer" principle. It allows us to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate, weight) depending on disease. Follow-up and management of disease provided by specialists at participating institutions. |
| Measure | Description | Time Frame |
|---|---|---|
| cardiovascular mortality | mortality rate | an average, 1 month after randomization |
| all-cause mortality | mortality rate | an average, 1 months after randomization |
| complications, decompensations | rate of complications and exacerbations of the main disease | an average, 1 month after randomization |
| Measure | Description | Time Frame |
|---|---|---|
| achievement target or maximally tolerated doses | achievement target or maximally tolerated doses for CHF, DM and AH | an average, 1 month after randomization |
| satisfaction | satisfaction of patients and doctors with the robotic speech questionnaire |
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Inclusion Criteria:
Non-inclusion criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Maria Kozhevnikova, Professor | Contact | +79265605019 | kozhevnikova_m_v@staff.sechenov.ru | |
| Aleksei Emelianov, Assistant | Contact | +79998305785 | emelyanov_a_v@staff.sechenov.ru |
| Name | Affiliation | Role |
|---|---|---|
| Maria Kozhevnikova, Professor | The Sechenov First Moscow State Medical University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), University Clinical Hospital No.1 | Moscow | 119048 |
According to the Local Ethics Committee's rules, we are not allowed to provide this data.
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Patients with any lymphoproliferative disease who is undergoing chemotherapy. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (blood pressure, heart rate) related to chemotherapy complications. |
|
| Total knee replacement | Experimental | Patients who underwent total knee replacement. Their condition should be stabilized before discharge. Robotic remote monitoring of patients using unique algorithms developed for virtual operator speech technology and a BI system by voice commands to automate data collection and obtain information about the patient's well-being and his vital signs (pain, fever) related to replacement complications. |
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| an average, 1 month after randomization |
| changes in medical adherence | change in amount of taking drugs and doses | an average, 1 month after randomization |
| Russia |
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| ID | Term |
|---|---|
| D006333 | Heart Failure |
| D003920 | Diabetes Mellitus |
| D006973 | Hypertension |
| D008232 | Lymphoproliferative Disorders |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
| D014652 | Vascular Diseases |
| D008206 | Lymphatic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
| D007160 | Immunoproliferative Disorders |
| D007154 | Immune System Diseases |
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