Survey of Potential Disparity Issues Among Minority Stroke Survivors in Central Brooklyn.

Medical data and information are ubiquitous due to internet availability. However, most people persist in using and trusting their healthcare professionals for health information. They are increasingly flooded with health information from diverse sources such as the internet, community-based organizations, and family or friends. It is crucial to understand where stroke patients vary in the use and trust of health information to improve their conditions. This pilot study aimed to better understand the nature of the problems confronted by stroke patients, such as the source of reliable health information, trust in the healthcare system, and technology trend awareness. African American and Afro-Caribbean stroke patients (n=64) residing in Central Brooklyn, New York, participated in a survey. The results showed that physicians remained the most highly trusted information sources for stroke patients, particularly among patients with higher education, irrespective of the available communication sources.

Discontinuity of Stroke Care in a Black Urban Cohort: Insight from EHR Data.

This poster describes the findings from a study that attempts to characterize an underserved Black stroke cohort who are at risk for discontinuities of care using electronic health record (EHR). Preliminary analysis revealed that 90.1% of the patients were Black. After being diagnosed with a stroke, 57% of the population did not return for follow-up. The objective is to understand the factors contributing to discontinuity of care in Black stroke patients.

Do digital health interventions hold promise for stroke prevention and care in Black and Latinx populations in the United States? A scoping review.

BACKGROUND: Black and Latinx populations are disproportionately affected by stroke and are likely to experience gaps in health care. Within fragmented care systems, remote digital solutions hold promise in reversing this pattern. However, there is a digital divide that follows historical disparities in health. Without deliberate attempts to address this digital divide, rapid advances in digital health will only perpetuate systemic biases. This study aimed to characterize the range of digital health interventions for stroke care, summarize their efficacy, and examine the inclusion of Black and Latinx populations in the evidence base. METHODS: We searched PubMed, the Web of Science, and EMBASE for publications between 2015 and 2021. Inclusion criteria include peer-reviewed systematic reviews or meta-analyses of experimental studies focusing on the impact of digital health interventions on stroke risk factors and outcomes in adults. Detailed information was extracted on intervention modality and functionality, clinical/behavioral outcome, study location, sample demographics, and intervention results. RESULTS: Thirty-eight systematic reviews met inclusion criteria and yielded 519 individual studies. We identified six functional categories and eight digital health modalities. Case management (63%) and health monitoring (50%) were the most common intervention functionalities. Mobile apps and web-based interventions were the two most commonly studied modalities. Evidence of efficacy was strongest for web-based, text-messaging, and phone-based approaches. Although mobile applications have been widely studied, the evidence on efficacy is mixed. Blood pressure and medication adherence were the most commonly studied outcomes. However, evidence on the efficacy of the various intervention modalities on these outcomes was variable. Among all individual studies, only 38.0% were conducted in the United States (n = 197). Of these U.S. studies, 54.8% adequately reported racial or ethnic group distribution. On average, samples were 27.0% Black, 17.1% Latinx, and 63.4% White. CONCLUSION: While evidence of the efficacy of selected digital health interventions, particularly those designed to improve blood pressure management and medication adherence, show promise, evidence of how these interventions can be generalized to historically underrepresented groups is insufficient. Including these underrepresented populations in both digital health experimental and feasibility studies is critical to advancing digital health science and achieving health equity.

Black and hispanic patients with movement disorders less likely to undergo deep brain stimulation.

BACKGROUND: DBS is an effective surgical treatment for ET, PD, and dystonia. Racial disparities in DBS utilization in PD have been documented demonstrating that Black patients receive DBS at lower rates than White patients. To our knowledge, no studies have investigated if this pattern of non-use persists in other movement disorders with FDA-approval. OBJECTIVE: To identify racial and ethnic disparities in DBS utilization in those hospitalized for ET, PD, and dystonia. METHODS: The NIS database was queried for US hospitalizations from 2012 to 2018 with a primary diagnosis of ET, PD, or dystonia, and a total of 3,363, 21,963, and 1,835 discharges were recorded, respectively. Within that sample, treatment with DBS was identified. Sex, race, age, payment method, income quartile, year, mortality risk, hospital size, urban/rural setting, teaching status, and geographic region were extracted. A multivariate logistic regression was performed to identify predictors for use and non-use of DBS. RESULTS: Between 2012 and 2018, Black patients with PD, ET, and dystonia were less likely to receive DBS than White patients. Black patients with PD were 7 times less likely to receive DBS (OR = 0.145, CI = 0.111-0.189), and Black patients with ET and dystonia were 5 times less likely to receive DBS than White patients (OR = 0.188, CI = 0.124-0.285; OR = 0.186, CI = 0.084-0.414). Compared to White patients, Hispanic patients with PD (OR = 0.631, OR = 0.539-0.740) and ET (OR = 0.438, CI = 0.277-0.695) were less likely to undergo DBS. When controlling for patient and hospital level characteristics, racial and ethnic disparities remained. CONCLUSIONS: Our data suggest that Black patients with a diagnosis of ET, PD, or dystonia and Hispanic patients with a diagnosis of ET or PD were less likely to be treated with DBS than White patients between 2012 and 2018.

Foundational domains and competencies for baccalaureate health informatics education.

BACKGROUND: Foundational domains are the building blocks of educational programs. The lack of foundational domains in undergraduate health informatics (HI) education can adversely affect the development of rigorous curricula and may impede the attainment of CAHIIM accreditation of academic programs. OBJECTIVE: This White Paper presents foundational domains developed by AMIA's Academic Forum Baccalaureate Education Committee (BEC) which include corresponding competencies (knowledge, skills, and attitudes) that are intended for curriculum development and CAHIIM accreditation quality assessment for undergraduate education in applied health informatics. METHODS: The AMIA BEC used the previously published master's foundational domains as a guide to creating a set of competencies for health informatics at the undergraduate level to assess graduates from undergraduate health informatics programs for competence at graduation. A consensus method was used to adapt the domains for undergraduate level course work and harmonize the foundational domains with the currently adapted domains for HI master's education. RESULTS: Ten foundational domains were developed to support the development and evaluation of baccalaureate health informatics education. DISCUSSION: This article will inform future work towards building CAHIIM accreditation standards to ensure that higher education institutions meet acceptable levels of quality for undergraduate health informatics education.

The Effect of Physicians' Acknowledgement of Clinical Decision Support Systems Generated Alerts on Patient Diabetes Management in a Primary Care Setting.

The purpose of the study is to evaluate whether clinician's acknowledgement and adherence to Clinical Best Practice Advisories (BPA) system's alerts improves the outcome of patients with chronic diabetes. We used deidentified clinical data of elderly (65 or older) diabetes patients with hemoglobin A1C (HbA1C) >= 6.5 that were extracted from the clinical database of a multi-specialty outpatient clinic that also provides primary care services. We performed paired ttest to evaluate whether clinician's acknowledgement and adherence to BPA system's alert has any impact on patients' HbA1C management. Our findings showed that the average HbA1C values improved for patients whose alerts were acknowledged by their clinicians. For the group of patients whose BPA alerts were ignored by their clinicians, we found clinicians' acknowledgement and adherence to BPA alerts for chronic diabetes patient management did not have a significant negative effect on improvement in patient outcome.

Disparities in Breast Cancer Survivors in Rural West Texas.

OBJECTIVES: Breast cancer is the second highest female mortality rate in Texas for all races and ethnicities, except for Hispanics. Interestingly, Hale County is a rural underserved county in West Texas which experiences a lower rate of cancer, has higher age-adjusted mortality rates (26.2/100 000), on average, compared to all of Texas (23.1/100 000). The purpose of this study was to determine the relationship between sociodemographic variables and breast cancer outcomes in underserved Hale County which contributed to the highest mortality rate in Texas. METHODS: Hale County breast cancer data (1995-2014) were obtained from the Texas Cancer Registry. Statistical methods independent samples t-test, Kaplan-Meier curve, and Cox proportional hazard were used to describe the significant relationship between survival time, sociodemographic, and prognostic variables. RESULTS: Women with breast cancer in Hale County were more likely to be White non-Hispanics (n = 266, 65.5%) and had the highest longevity (2753.6 ± 2073.5 days). White Hispanics experienced the worst survival (2369.6 ± 2060.2 days) and were more likely to develop a serious grade of cancer. Significant relationships were found between the stage of cancer and insurance status with survival time for both White non-Hispanics and White Hispanics (P < .001). Patients in grades II and III were found to be significantly (P < .01) associated with breast cancer death, and grades II and III which had around five-fold and eleven-fold increased risk of death, respectively, compared with the referent group, grade I. CONCLUSION: Determining the impact of sociodemographic variables on breast cancer outcome is essential to addressing issues of geographic disparities and integrating such variables may guide relevant policy interventions to reduce breast cancer's incidence in rural underserved communities in West Texans.

Sex Differences in Cardiovascular Disease and Cognitive Dysfunction in Rural West Elderly Texans.

BACKGROUND: The prevalence of cognitive dysfunction increases in elderly due to cardiovascular disease related risk factors in rural communities like West Texas. OBJECTIVE: The purpose of this study was to find risk factors of cardiovascular disease (CVD) related to cognitive dysfunction and their impact on elderly adults in rural West Texans. METHODS: Statistical methods such as Pearson's chi-squared and a multinomial logistic regression were utilized to analyze data. We used SPSS software to detect and understand the nature of the risk factors. RESULTS: A summary of statistics was obtained by using Pearson's chi-squared test for categorical variables. CVD, diabetes mellitus, and depression were significantly associated with cognitive dysfunction for both males and females (p = 0.0001), whereas anxiety was found to be significantly associated with cognitive dysfunction for females (p = 0.0001). Age group and race/ethnicity were significantly associated with cognitive dysfunction for both males and females (p = 0.0001). By performing a multinomial logistic regression method and controlling for confounders, the significant risk factors (p <  0.05)- age (65- 84 years), diabetes, and memory loss for age-associated cognitive impairment; diabetes for cognitive impairment no dementia; age (65- 84, ≥85 years), CVD, diabetes, depression, memory loss, non-Hispanic Whites, and Black/African-Americans for mild cognitive impairment; and age, memory loss, non-Hispanic Whites, Black/African-Americans, and male gender were found for dementia. CONCLUSION: CVD related risk factors in developing cognitive dysfunction exist and integrating such risk variables may guide relevant policy interventions to reduce Alzheimer's incidence or dementia in rural communities in West Texans.

Disparities in the Use of Intravenous t-PA among Ischemic Stroke Patients: Population-based Recent Temporal Trends.

OBJECTIVE: To explore a 5-year comparison of disparities in intravenous t-PA (IV t-PA) use among acute ischemic stroke (AIS) patients based on race, gender, age, ethnic origin, hospital status, and geographic location. METHODS: We extracted patients' demographic information and hospital characteristics for 2010 and 2014 from the New York Statewide Planning and Research Cooperative System (SPARCS). We compared disparities in IV t-PA use among AIS patients in 2010 to that in 2014 to estimate temporal trends. Multiple logistic regression was performed to compare disparities based on demographic variables, hospital designation, and geographic location. RESULTS: Overall, there was approximately a 2% increase in IV t-PA from 2010 to 2014. Blacks were 15% less likely to receive IV t-PA compared to Whites in 2014, but in 2010, there was no difference. Patients aged 62-73 had lower odds of receiving IV t-PA than age group ≤61 in both 2010 and 2014. Designated stroke centers in the Lower New York State region were associated with reduced odds of IV t-PA use in 2010 while those located in the Upper New York State region were associated with increased odds of IV t-PA use in both 2010 and 2014, compared to their respective nondesignated counterparts. Gender, ethnic origin, and insurance status were not associated with IV t-PA utilization in both 2010 and 2014. CONCLUSION: Overall IV t-PA utilization among AIS patients increased between 2010 and 2014. However, there are evident disparities in IV t-PA use based on patient's race, age, hospital geography, and stroke designation status.

Ischemic Stroke Predictors in Patients Presenting with Dizziness, Imbalance, and Vertigo.

OBJECTS: To identify predictors of acute ischemic stroke (AIS) among patients presenting to the Emergency Department (ED) with dizziness, imbalance, or vertigo (DIV) based on demographic and clinical characteristics. METHODS: We identified patients admitted to the hospital after presenting to the ED with DIV from the Statewide Planning and Research Cooperative System database of New York from 2010 to 2014. Demographic and clinical characteristics were systematically collected. Multivariable logistic regression was used to determine predictors of a discharge diagnosis of AIS. RESULTS: Among 77,993 patients with DIV, 3857 (4.9%) had a discharge diagnosis of AIS. Admission presentation of imbalance, African-American race, history of hypertension, diabetes mellitus, hypercholesterolemia, tobacco use, atrial fibrillation, and prior AIS due to extracranial artery atherosclerosis were each positively associated with an AIS diagnosis independently. Factors negatively associated with an AIS discharge diagnosis included: admission presentation of vertigo, female sex, age > 81, history of anemia, coronary artery disease, asthma, depressive disorders, and anxiety disorders. CONCLUSIONS: Multiple potential positive and negative predictive AIS risk factors were identified. Combining with currently available centrally-caused dizziness prediction tools, these newly identified factors could provide more accurate AIS risk stratifying method for DIV patients.

Evaluation of a Cyber Security System for Hospital Network.

Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time. On an evaluation using real-world hospital network data consisting of incoming network connections collected for a 24-hour period, the proposed system detected 15 unusual connections which were undetected by a commercial intrusion prevention system for the same network connections. Evaluation of the proposed system shows a potential to secure protected patient health information on a hospital network.