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1.
J Am Coll Emerg Physicians Open ; 3(1): e12678, 2022 Feb.
Article in English | MEDLINE | ID: mdl-35224551

ABSTRACT

OBJECTIVES: Examining the social risks that influence the health of patients accessing emergency care can inform future efforts to improve health outcomes. The optimal modality for screening in the emergency department (ED) has not yet been identified. We conducted a mixed methods evaluation of the impact of screening modality on patient satisfaction with the screening process. METHODS: Patients were enrolled at a large urban academic ED and randomized to verbal versus electronic modalities following informed consent. Participants completed a short demographic survey, a brief validated health literacy test, and a social need and risk screening tool. Participants were purposively sampled to complete qualitative interviews balanced across 4 groups defined by health literacy scores (high vs limited) and screening modality. Quantitative outcomes included screening results and satisfaction with the screening process; qualitative questions focused on experience with the screening process, barriers, and facilitators to screening. RESULTS: Of 554 patients assessed, 236 were randomized (115 verbal, 121 electronic). Participants were 23% Hispanic, 6% non-Hispanic Black, 58% non-Hispanic White, 38% publicly insured, and 57% privately insured. Two-thirds (67%) identified social needs and risks and the majority (81%) reported satisfaction with the screening. Screening modality was not associated with satisfaction with screening process after adjustment for language, health literacy, and social risk (adjusted odds ratio, 0.74; 95% confidence interval, 0.32, 1.71). CONCLUSION: Screening modality was not associated with overall satisfaction with screening process. Future strategies can consider the advantage of multimodal screening options, including the use of electronic tools to streamline screening and expand scalability and sustainability.

2.
J Telemed Telecare ; : 1357633X211070725, 2022 Jan 24.
Article in English | MEDLINE | ID: mdl-35072550

ABSTRACT

BACKGROUND: With the rapid increase in telehealth use during the COVID-19 pandemic, concerns have been raised about the potential for exacerbating existing healthcare disparities in marginalized populations. While eliminating barriers such as transportation and time constraints, telehealth may introduce barriers related to technology access. With little known about the patient experience accessing telehealth during the COVID-19 pandemic, this study seeks to understand the barriers and facilitators to telehealth use as well as interventions that may address them. METHODS: We conducted qualitative interviews with parents of pediatric patients of a primary care clinic in a diverse community during the study period of March-May 2021. The interviews explored barriers and facilitators to telehealth during the COVID-19 pandemic. Interviews were balanced across language (Spanish and English) as well as across visit type (in-person vs. telehealth). Recruitment, collection of demographic information, and interviews were conducted by telephone. The conversations were recorded and transcribed. Once thematic saturation was achieved, the data were analyzed using a modified grounded theory approach. RESULTS: Of the 33 participants, 17 (52%) spoke English and 16 (48%) spoke Spanish. A total of 17 (52%) had experienced a telehealth encounter as their first visit during the study period while 16 (48%) had an in-person visit. Five themes were identified: (1) a recognition of differences in technological knowledge and access, (2) situational preferences for telehealth versus in-person visits, (3) avoidance of COVID-19 exposure, (4) convenience, and (5) change over time. English-speaking patients expressed greater ease with and a preference for telehealth, while Spanish-speaking participants expressed more technological difficulty with telehealth and a preference for in-person visits. Suggested interventions included informational tutorials such as videos before the visit, technical support, and providing families with technological devices. CONCLUSION: In this study, we examined patient and family perspectives on pediatric telehealth during the COVID-19 pandemic. Implementation of the suggested interventions to address barriers to telehealth use is essential to prevent further exacerbation of health disparities already experienced by marginalized populations.

3.
West J Emerg Med ; 22(6): 1283-1290, 2021 Oct 27.
Article in English | MEDLINE | ID: mdl-34787552

ABSTRACT

INTRODUCTION: Prevention quality indicators (PQI) are a set of measures used to characterize healthcare utilization for conditions identified as being potentially preventable with high quality ambulatory care. These indicators have recently been adapted for emergency department (ED) patient presentations. In this study the authors sought to identify opportunities to potentially prevent emergency conditions and to strengthen systems of ambulatory care by analyzing patterns of ED utilization for PQI conditions. METHODS: Using multivariable logistic regression, the authors analyzed the relationship of patient demographics and neighborhood-level socioeconomic indicators with ED utilization for PQI conditions based on ED visits at an urban, academic medical center in 2017. We also used multilevel modeling to assess the contribution of these variables to neighborhood-level variation in the likelihood of an ED visit for a PQI condition. RESULTS: Of the included 98,522 visits, 17.5% were categorized as potentially preventable based on the ED PQI definition. On multivariate analysis, age < 18 years, Black race, and Medicare insurance had the strongest positive associations with PQI visits, with adjusted odds ratios (aOR) of 1.41 (95% confidence interval [CI], 1.29, 1.56), 1.40 (95% CI, 1.22, 1.61), and 1.40 (95% CI, 1.28, 1.54), respectively. All included neighborhood-level socioeconomic variables were significantly associated with PQI visit likelihood on univariable analysis; however; only level of education attainment and private car ownership remained significantly associated in the multivariable model, with aOR of 1.13 (95% CI, 1.10, 1.17) and 0.96 (95% CI, 0.93, 0.99) per quartile increase, respectively. This multilevel model demonstrated significant variation in PQI visit likelihood attributable to neighborhood, with interclass correlation decreasing from 5.92% (95% CI, 5.20, 6.73) in our unadjusted model to 4.12% (95% CI, 3.47, 4.87) in our fully adjusted model and median OR similarly decreasing from 1.54 to 1.43. CONCLUSION: Demographic and local socioeconomic factors were significantly associated with ED utilization for PQI conditions. Future public health efforts can bolster efforts to target underlying social drivers of health and support access to primary care for patients who are Black, Latino, pediatric, or Medicare-dependent to potentially prevent emergency conditions (and the need for emergency care). Further research is needed to explore other factors beyond demographics and socioeconomic characteristics driving spatial variation in ED PQI visit likelihood.


Subject(s)
Emergency Service, Hospital , Medicare , Adolescent , Aged , Child , Geography , Humans , Residence Characteristics , Socioeconomic Factors , United States
4.
J Am Coll Emerg Physicians Open ; 2(4): e12502, 2021 Aug.
Article in English | MEDLINE | ID: mdl-34278377

ABSTRACT

OBJECTIVE: Given the variability in crisis standards of care (CSC) guidelines during the COVID-19 pandemic, we investigated the racial and ethnic differences in prioritization between 3 different CSC triage policies (New York, Massachusetts, USA), as well as a first come, first served (FCFS) approach, using a single patient population. METHODS: We performed a retrospective cohort study of patients with intensive care unit (ICU) needs at a tertiary hospital on its peak COVID-19 ICU census day. We used medical record data to calculate a CSC score under 3 criteria: New York, Massachusetts with full comorbidity list (Massachusetts1), and MA with a modified comorbidity list (Massachusetts2). The CSC scores, as well as FCFS, determined which patients were eligible to receive critical care under 2 scarcity scenarios: 50 versus 100 ICU bed capacity. We assessed the association between race/ethnicity and eligibility for critical care with logistic regression. RESULTS: Of 211 patients, 139 (66%) were male, 95 (45%) were Hispanic, 23 (11%) were non-Hispanic Black, and 69 (33%) were non-Hispanic White. Hispanic patients had the fewest comorbidities. Assuming a 50 ICU bed capacity, Hispanic patients had significantly higher odds of receiving critical care services across all CSC guidelines, except FCFS. However, assuming a 100 ICU bed capacity, Hispanic patients had greater odds of receiving critical care services under only the Massachusetts2 guidelines (odds ratio, 2.05; 95% CI, 1.09 to 3.85). CONCLUSION: Varying CSC guidelines differentially affect racial and ethnic minority groups with regard to risk stratification. The equity implications of CSC guidelines require thorough investigation before CSC guidelines are implemented.

5.
West J Emerg Med ; 22(2): 218-224, 2021 Mar 04.
Article in English | MEDLINE | ID: mdl-33856303

ABSTRACT

INTRODUCTION: Unmet health-related social needs (HRSN) are among the drivers of disparities in morbidity and mortality during public health emergencies such as the novel coronavirus 2019 (Covid-19) pandemic. Although emergency departments (ED) see a high volume of patients with HRSN, ED providers have limited time to complete detailed assessments of patients' HRSN and are not always able to provide up-to-date and comprehensive information to patients on available community resources. Electronic, geographically indexed resource database systems have the potential to provide an efficient way for emergency physicians to rapidly identify community resources in settings where immediate social work consultation is not accessible. METHODS: We conducted a systematic review of papers examining the use of geographically indexed resource database systems in healthcare to better understand how these services can be used in emergency care. We then conducted simulated, standardized searches using two nationally available databases (211 and Aunt Bertha), applied to a single metropolitan area (Boston). RESULTS: Our systematic review found that most public health and screening interventions using nationally available databases have focused on chronic care needs. A small subset of publications demonstrated that these databases were mobilized during disasters to successfully aid vulnerable populations during Hurricanes Katrina and Rita. A total of 408 standardized searches were conducted to identify community resources related to four domains of social needs (food, transportation, housing, and utilities). Although 99% of the resources identified by both databases were relevant to the search domains queried, a significant proportion of the resources identified by each database were restricted to a specific demographic (eg, veterans). CONCLUSION: Our findings demonstrate that geographically indexed referral databases may be an effective tool to help ED providers connect patients to nearby community resources during public health emergencies. We recommend that EDs select a referral database based on the greatest number of resources that are not demographically restricted.


Subject(s)
Databases, Factual , Emergency Service, Hospital , Needs Assessment , Referral and Consultation , Health Services Needs and Demand , Humans
6.
Public Health Rep ; 136(3): 368-374, 2021 05.
Article in English | MEDLINE | ID: mdl-33729070

ABSTRACT

OBJECTIVE: Understanding the pattern of population risk for coronavirus disease 2019 (COVID-19) is critically important for health systems and policy makers. The objective of this study was to describe the association between neighborhood factors and number of COVID-19 cases. We hypothesized an association between disadvantaged neighborhoods and clusters of COVID-19 cases. METHODS: We analyzed data on patients presenting to a large health care system in Boston during February 5-May 4, 2020. We used a bivariate local join-count procedure to determine colocation between census tracts with high rates of neighborhood demographic characteristics (eg, Hispanic race/ethnicity) and measures of disadvantage (eg, health insurance status) and COVID-19 cases. We used negative binomial models to assess independent associations between neighborhood factors and the incidence of COVID-19. RESULTS: A total of 9898 COVID-19 patients were in the cohort. The overall crude incidence in the study area was 32 cases per 10 000 population, and the adjusted incidence per census tract ranged from 2 to 405 per 10 000 population. We found significant colocation of several neighborhood factors and the top quintile of cases: percentage of population that was Hispanic, non-Hispanic Black, without health insurance, receiving Supplemental Nutrition Assistance Program benefits, and living in poverty. Factors associated with increased incidence of COVID-19 included percentage of population that is Hispanic (incidence rate ratio [IRR] = 1.25; 95% CI, 1.23-1.28) and percentage of households living in poverty (IRR = 1.25; 95% CI, 1.19-1.32). CONCLUSIONS: We found a significant association between neighborhoods with high rates of disadvantage and COVID-19. Policy makers need to consider these health inequities when responding to the pandemic and planning for subsequent health needs.


Subject(s)
COVID-19/epidemiology , Ethnicity/statistics & numerical data , Medically Uninsured/statistics & numerical data , Poverty/statistics & numerical data , Residence Characteristics , Vulnerable Populations/statistics & numerical data , Adult , Aged , Female , Food Assistance/statistics & numerical data , Geographic Mapping , Humans , Incidence , Male , Massachusetts/epidemiology , Middle Aged , Socioeconomic Factors
7.
West J Emerg Med ; 21(6): 152-161, 2020 Oct 06.
Article in English | MEDLINE | ID: mdl-33207161

ABSTRACT

INTRODUCTION: Social risks, or adverse social conditions associated with poor health, are prevalent in emergency department (ED) patients, but little is known about how the prevalence of social risk compares to a patient's reported social need, which incorporates patient preference for intervention. The goal of this study was to describe the relationship between social risk and social need, and identify factors associated with differential responses to social risk and social need questions. METHODS: We conducted a cross-sectional study with 48 hours of time-shift sampling in a large urban ED. Consenting patients completed a demographic questionnaire and assessments of social risk and social need. We applied descriptive statistics to the prevalence of social risk and social need, and multivariable logistic regression to assess factors associated with social risk, social need, or both. RESULTS: Of the 269 participants, 100 (37%) reported social risk, 83 (31%) reported social need, and 169 (63%) reported neither social risk nor social need. Although social risk and social need were significantly associated (p < 0.01), they incompletely overlapped. Over 50% in each category screened positive in more than one domain (eg, housing instability, food insecurity). In multivariable models, those with higher education (adjusted odds ratio [aOR] 0.44 [95% confidence interval {CI}, 0.24-0.80]) and private insurance (aOR 0.50 [95% CI, 0.29-0.88]) were less likely to report social risk compared to those with lower education and state/public insurance, respectively. Spanish-speakers (aOR 4.07 [95% CI, 1.17-14.10]) and non-Hispanic Black patients (aOR 5.00 [95% CI, 1.91-13.12]) were more likely to report social need, while those with private insurance were less likely to report social need (private vs state/public: aOR 0.13 [95% CI, 0.07-0.26]). CONCLUSION: Approximately one-third of patients in a large, urban ED screened positive for at least one social risk or social need, with over half in each category reporting risk/need across multiple domains. Different demographic variables were associated with social risk vs social need, suggesting that individuals with social risks differ from those with social needs, and that screening programs should consider including both assessments.


Subject(s)
Emergency Service, Hospital/statistics & numerical data , Health Services Accessibility/statistics & numerical data , Adult , Cross-Sectional Studies , Female , Housing/statistics & numerical data , Humans , Male , Mass Screening , Middle Aged , Prevalence , Socioeconomic Factors , Surveys and Questionnaires
8.
J Am Coll Emerg Physicians Open ; 1(5): 852-856, 2020 Oct.
Article in English | MEDLINE | ID: mdl-33145531

ABSTRACT

Emergency medicine has increasingly focused on addressing social determinants of health (SDoH) in emergency medicine. However, efforts to standardize and evaluate measurement tools and compare results across studies have been limited by the plethora of terms (eg, SDoH, health-related social needs, social risk) and a lack of consensus regarding definitions. Specifically, the social risks of an individual may not align with the social needs of an individual, and this has ramifications for policy, research, risk stratification, and payment and for the measurement of health care quality. With the rise of social emergency medicine (SEM) as a field, there is a need for a simplified and consistent set of definitions. These definitions are important for clinicians screening in the emergency department, for health systems to understand service needs, for epidemiological tracking, and for research data sharing and harmonization. In this article, we propose a conceptual model for considering SDoH measurement and provide clear, actionable, definitions of key terms to increase consistency among clinicians, researchers, and policy makers.

9.
West J Emerg Med ; 21(5): 1170-1174, 2020 Aug 20.
Article in English | MEDLINE | ID: mdl-32970571

ABSTRACT

INTRODUCTION: With recent healthcare policy changes, including the creation of accountable care organizations, screening for social risks such as food and housing insecurity has become increasingly common in the healthcare system. However, the wide variety of different tools used for screening makes it challenging to compare across systems. In addition, the majority of tools used to measure social risks have only been tested in primary care settings and may not be optimal for emergency department (ED) use. Therefore, the goal of this study was to create a brief social screening tool for use in EDs. METHODS: We developed an initial tool using publicly available questions corresponding to the five core categories of the Centers for Medicare & Medicaid Services' Accountable Health Communities Screening Tool. Iterative cycles of cognitive interviews with purposively sampled participants were performed using a hybrid model of think-aloud and verbal probing to understand/experience answering questions and potential comprehension challenges. After thematic saturation was reached in one cycle, the tool was changed per participant input; cycles were completed until thematic saturation was reached overall. RESULTS: A total of 16 participants (six patient guardians and 10 patients) completed cognitive interviews throughout three cycles. Participant feedback included suggestions for further clarification and simplification of survey questions for improved comprehension. The survey was thus reduced and simplified from 16 questions concerning five domains to 10 questions concerning four domains. CONCLUSION: We used an iterative cognitive interviewing process to develop a social screening tool for use in EDs. This process demonstrates the importance of patient input to refine questionnaires, and provides a brief screening tool for ED use.


Subject(s)
Emergency Service, Hospital , Mass Screening/methods , Psychological Distance , Social Determinants of Health , Surveys and Questionnaires , Emergency Service, Hospital/organization & administration , Emergency Service, Hospital/standards , Humans , Needs Assessment , Risk Assessment/methods , Risk Factors , United States/epidemiology
10.
West J Emerg Med ; 21(4): 964-973, 2020 Jun 24.
Article in English | MEDLINE | ID: mdl-32726271

ABSTRACT

INTRODUCTION: Social risks adversely affect health and are associated with increased healthcare utilization and costs. Emergency department (ED) patients have high rates of social risk; however, little is known about best practices for ED-based screening or linkage to community resources. We examined the perspectives of patients and community organizations regarding social risk screening and linkage from the ED. METHODS: Qualitative interviews were conducted with a purposive sample of ED patients and local community organization staff. Participants completed a brief demographic survey, health literacy assessment, and qualitative interview focused on barriers/facilitators to social risk screening in the ED, and ideas for screening and linkage interventions in the ED. Interviews were conducted in English or Spanish, recorded, transcribed, and coded. Themes were identified by consensus. RESULTS: We conducted 22 interviews with 16 patients and six community organization staff. Three categories of themes emerged. The first related to the importance of social risk screening in the ED. The second category encompassed challenges regarding screening and linkage, including fear, mistrust, transmission of accurate information, and time/resource constraints. The third category included suggestions for improvement and program development. Patients had varied preferences for verbal vs electronic strategies for screening. Community organization staff emphasized resource scarcity and multimodal communication strategies. CONCLUSION: The development of flexible, multimodal, social risk screening tools, and the creation and maintenance of an accurate database of local resources, are strategies that may facilitate improved identification of social risk and successful linkage to available community resources.


Subject(s)
Emergency Service, Hospital/statistics & numerical data , Patient Acceptance of Health Care/statistics & numerical data , Social Determinants of Health/statistics & numerical data , Adult , Community Health Services/methods , Community Health Services/standards , Female , Health Services Needs and Demand , Humans , Male , Mass Screening/methods , Massachusetts/epidemiology , Qualitative Research , Quality Improvement , Socioeconomic Factors
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