Vulnerable and underserved populations such as ethnic and racial minorities, the poor, the LGBTQ communityand those with physical or intellectual disabilities, often suffer the greatest health risks while facing significantbarriers to receiving healthcare. While biological and clinical risks influence outcomes, sociocultural andsocioeconomic factors also create major barriers to receiving healthcare services, at an individual, communityand population level for these populations. These social determinants of health (SDOH), such as transportation,literacy, and finances can severely limit participation in health programs designed for the general population.Diabetes Prevention Programs are a good example of a lifestyle change protocol that is proven to reduce therisk of type 2 diabetes by half for pre-diabetics patients at risk by encouraging weight-loss. But, despite theeffectiveness of the program, more than 50% of participants drop out before completing this year-long lifestylechange program, severely limiting the program's success. This is in part due to the fact that programs like DPPtake little account of the limitations faced by underserved and vulnerable populations that it is meant to help.This lack of support at the individual and community level combined with the fact that healthcare institutions arenot designed for, nor economical, in supporting patient health outside the medical facility where it is most needed.This creates a gap in healthcare service that current systems cannot overcome.Viora is closing this health services gap with a system that interfaces between the health care system, theunderserved patient, and underutilized community-based resources and providers, to facilitate better outcomesin programs like DPP. By using risk stratification based on SDOH factors, each DPP participant can have tailoredinterventions that consider their socioeconomic and sociocultural characteristics. The Viora Health systemconnects patients to local resources using simple communication between the patient, health providers, andcommunity services, facilitating patient completion of the DPP program, thereby improving health outcomes. InPhase I, Viora will evaluate a larger set of pre-diabetes and SDOH risk factors across 5000 minority andunderserved subjects to select the most relevant variables for risk assessment and personal prevention plandevelopment. The system will automatically screen pre-diabetic participants who are eligible, ready and able toadhere to DPP, and will create a personalized intervention plan that is the most impactful in reducing their riskbut is also doable. The system's communication network will be expanded to provide direct communicationbetween the patient, DPP coach, health providers and community resources, to support the participant towardmaintaining their DPP goals. Finally, the project will assess the basic function of the system, preferences andhuman interaction in a human subject study with underserved subjects and community-based partners.Completion of Phase I will demonstrate feasibility of our software system incorporating major components of theVIORA SYSTEM, which will inform the development of a minimum viable product to be tested in Phase 2.
Public Health Relevance Statement: Narrative
Vulnerable and underserved populations often suffer the greatest health risks while facing
significant barriers, largely due to social and behavioral factors that hinder continued participation
in disease prevention and management protocols. Viora Health's system will have significant
public health impact in scaling evidence- based protocols by using technology to identify such
factors and leverage existing community based resources to support patients in mitigating these
factors.
Project Terms: Algorithms ; Automation ; Felis catus ; Cats ; Cats Mammals ; Domestic Cats ; Feline Species ; Felis domestica ; Felis domesticus ; Felis sylvestris catus ; Centers for Disease Control and Prevention (U.S.) ; CDC ; Centers for Disease Control ; Centers for Disease Control and Prevention ; United States Centers for Disease Control ; United States Centers for Disease Control and Prevention ; Communication ; Communities ; Community Services ; comorbidity ; co-morbid ; co-morbidity ; Confidential Information ; Non-Insulin-Dependent Diabetes Mellitus ; Adult-Onset Diabetes Mellitus ; Ketosis-Resistant Diabetes Mellitus ; Maturity-Onset Diabetes Mellitus ; NIDDM ; Non-Insulin Dependent Diabetes ; Noninsulin Dependent Diabetes ; Noninsulin Dependent Diabetes Mellitus ; Slow-Onset Diabetes Mellitus ; Stable Diabetes Mellitus ; T2 DM ; T2D ; T2DM ; Type 2 Diabetes Mellitus ; Type 2 diabetes ; Type II Diabetes Mellitus ; Type II diabetes ; adult onset diabetes ; ketosis resistant diabetes ; maturity onset diabetes ; type 2 DM ; type II DM ; type two diabetes ; Environment ; Face ; faces ; facial ; Family ; Feasibility Studies ; Feedback ; Focus Groups ; Goals ; Health ; Healthcare Systems ; Health Care Systems ; Health Personnel ; Health Care Providers ; Healthcare Providers ; Healthcare worker ; health care personnel ; health care worker ; health provider ; health workforce ; healthcare personnel ; medical personnel ; treatment provider ; Health Promotion ; Salutogenesis ; promoting health ; Health Services ; Recording of previous events ; History ; Human ; Modern Man ; Health Insurance ; health insurance plan ; Life Style ; Lifestyle ; literacy ; Minority Groups ; Minority People ; Minority Population ; Patient Monitoring ; Patients ; Philadelphia ; Probability ; Program Effectiveness ; Public Health ; Research ; Resources ; Research Resources ; Risk ; Risk Factors ; Socioeconomic Factors ; socio-economic factors ; Computer software ; Software ; Surveys ; Survey Instrument ; Technology ; Testing ; Transportation ; Body Weight decreased ; Weight Loss ; Weight Reduction ; body weight loss ; wt-loss ; Woman ; Work ; Measures ; Cost Savings ; Health Care Costs ; Health Costs ; Healthcare Costs ; Healthcare ; health care ; physically handicapped ; physical disability ; physically disabled ; Risk Assessment ; Socioeconomic Status ; Socio-economic status ; socio-economic position ; socioeconomic position ; Underinsured ; Data Set ; Dataset ; base ; human subject ; improved ; Phase ; Biological ; Medical ; Ensure ; Individual ; Databases ; Data Bases ; data base ; Development Plans ; Disease Progression ; Prediabetes ; Prediabetic State ; pre-diabetes ; pre-diabetic ; prediabetic ; Prediabetes syndrome ; Disorder Management ; Disease Management ; programs ; Side ; Protocol ; Protocols documentation ; System ; Intellectual disability ; Intellectual limitation ; intellectual and developmental disability ; Intellectual functioning disability ; meetings ; preference ; experience ; Performance ; success ; hospital re-admission ; re-admission ; re-hospitalization ; readmission ; rehospitalization ; hospital readmission ; Participant ; disease prevention ; disorder prevention ; member ; Study Subject ; General Public ; General Population ; Prevention ; social ; Social Support System ; Support System ; Modeling ; Intervention Strategies ; interventional strategy ; Intervention ; vulnerable group ; Vulnerable Populations ; Drops ; CPT Codes ; Current Procedural Terminology Codes ; Risk Reduction ; Provider ; Institution ; Health system ; Data ; Collection ; Characteristics ; Process ; follow-up ; Active Follow-up ; active followup ; follow up ; followed up ; followup ; Text ; socioeconomics ; socio-economic ; socio-economically ; socioeconomically ; Development ; developmental ; Behavioral ; Diabetes prevention ; Output ; diabetes prevention program ; cost ; software systems ; Underserved Population ; under served group ; under served people ; under served population ; underserved group ; underserved people ; design ; designing ; Minority ; Outcome ; Population ; innovation ; innovate ; innovative ; ethnic minority population ; ethnic minority ; racial and ethnic ; ethnoracial ; usability ; prototype ; commercialization ; evidence base ; diabetic patient ; social health determinants ; Institutional Review Boards ; IRB ; IRBs ; clinical risk ; cloud based ; Emergency department visit ; ED visit ; ER visit ; Emergency care visit ; Emergency hospital visit ; Emergency room visit ; personalized intervention ; precision interventions ; racial minority ; health care service ; healthcare service ; risk stratification ; stratify risk ; recruit ; Text Messaging ; short message service ; texting ; service gap ; barrier to care ; barrier to health care ; barrier to healthcare ; barrier to treatment ; obstacle to care ; obstacle to healthcare ; insurance plan ; Lesbian Gay Bisexual Transgender Queer ; LGBTQ ; Lesbian Gay Bi-sexual Transgender Queer ; social culture ; socio-cultural ; sociocultural ; data de-identification ; data deidentification ; de-identified data ; deidentified data ; machine learning method ; machine learning methodologies ; Home ;
