Search

We investigated the role of both individual-level social needs and community-level social determinants of health (SDOH) in explaining emergency department (ED) utilization rates. We also assessed the potential synergies between the two levels of analysis and their combined effect on patterns of ED visits. We extracted electronic health record (EHR) data between July 2016 and June 2020 for 1,308,598 unique Maryland residents who received care at Johns Hopkins Health System, of which 28,937 (2.2%) patients had at least one documented social need. There was a negative correlation between median household income in a neighborhood with having a social need such as financial resource strain, food insecurity, and residential instability (correlation coefficient: -0.05, -0.01, and − 0.06, p = 0, respectively). In a multilevel model with random effects after adjusting for other factors, living in a more disadvantaged neighborhood was found to be significantly associated with ED utilization statewide and within Baltimore City (OR: 1.005, 95% CI: 1.003–1.007 and 1.020, 95% CI: 1.017–1.022, respectively). However, individual-level social needs appeared to enhance the statewide effect of living in a more disadvantaged neighborhood with the OR for the interaction term between social needs and SDOH being larger, and more positive, than SDOH alone (OR: 1.012, 95% CI: 1.011–1.014). No such moderation was found in Baltimore City. To our knowledge, this study is one of the first attempts by a major academic healthcare system to assess the combined impact of patient-level social needs in association with community-level SDOH on healthcare utilization and can serve as a baseline for future studies using EHR data linked to population-level data to assess such synergistic association. [ABSTRACT FROM AUTHOR]

Patients enrolled in Medicaid have significantly higher social needs (SNs) than others. Using claims and electronic health records (EHRs) data, managed care organizations (MCOs) could systemically identify high-risk patients with SNs and develop population health management interventions. Impact of SNs on models predicting health care utilization and costs was assessed. This retrospective study included claims and EHRs data on 39,267 patients younger than age 65 years who were continuously enrolled during 2018–2019 in a Medicaid-managed care plan. SN marker was developed suggesting presence of International Classification of Diseases, 10th revision codes in any of the 5 SN domains. Impact of SN marker was compared across demographic and 2 diagnosis-based (ie, Charlson and Adjusted Clinical Groups risk score) prediction models of emergency department (ED) visit and hospitalizations, and total, medical, and pharmacy costs. After combining data sources, prevalence of documented SN marker increased from 11% and 13% to 18% of the study population across claims, EHRs, and both combined, respectively. SN marker improved predictions of demographic models for all utilization and total costs outcomes (area under the curve [AUC] of ED model increased from 0.57 to 0.61 and R2 of total cost model increased from 10.9 to 12.2). In both diagnosis-based models, adding SN marker marginally improved outcomes prediction (AUC of ED model increased from 0.65 to 0.66). This study demonstrated feasibility of using claims and EHRs data to systematically capture SNs and incorporate in prediction models that could enable MCOs and policy makers to adjust and develop effective population health interventions. [ABSTRACT FROM AUTHOR]

We aimed to empirically measure the degree to which there is a "digital divide" in terms of access to the internet at the small-area community level within the State of Maryland and the City of Baltimore and to assess the relationship and association of this divide with community-level SDOH risk factors, community-based social service agency location, and web-mediated support service seeking behavior. To assess the socio-economic characteristics of the neighborhoods across the state, we calculated the Area Deprivation Index (ADI) using the U.S. Census, American Community Survey (5-year estimates) of 2017. To assess the digital divide, at the community level, we used the Federal Communications Commission (FCC) data on the number of residential fixed Internet access service connections. We assessed the availability of and web-based access to community-based social service agencies using data provided by the "Aunt Bertha" information platform. We performed community and regional level descriptive and special analyses for ADI social risk factors, connectivity, and both the availability of and web-based searches for community-based social services. To help assess potential neighborhood linked factors associated with the rates of web-based social services searches by individuals in need, we applied logistic regression using generalized estimating equation modeling. Baltimore City contained more disadvantaged neighborhoods compared to other areas in Maryland. In Baltimore City, 20.3% of neighborhoods (defined by census block groups) were disadvantaged with ADI at the 90th percentile while only 6.6% of block groups across Maryland were in this disadvantaged category. Across the State, more than half of all census tracts had 801–1000 households (per 1000 households) with internet subscription. In contrast, in Baltimore City about half of all census tracts had only 401–600 of the households (per 1000 households) with internet subscriptions. Most block groups in Maryland and Baltimore City lacked access to social services facilities (61% of block groups at the 90th percentile of disadvantage in Maryland and 61.3% of block groups at the 90th percentile of disadvantage in Baltimore City). After adjusting for other variables, a 1% increase in the ADI measure of social disadvantage, resulting in a 1.7% increase in the number of individuals seeking social services. While more work is needed, our findings support the premise that the digital divide is closely associated with other SDOH factors. The policymakers must propose policies to address the digital divide on a national level and also in disadvantaged communities experiencing the digital divide in addition to other SDOH challenges. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has impacted communities differentially, with poorer and minority populations being more adversely affected. Prior rural health research suggests such disparities may be exacerbated during the pandemic and in remote parts of the U.S. Objectives: To understand the spread and impact of COVID-19 across the U.S., county level data for confirmed cases of COVID-19 were examined by Area Deprivation Index (ADI) and Metropolitan vs. Nonmetropolitan designations from the National Center for Health Statistics (NCHS). These designations were the basis for making comparisons between Urban and Rural jurisdictions. Method: Kendall's Tau-B was used to compare effect sizes between jurisdictions on select ADI composites and well researched social determinants of health (SDH). Spearman coefficients and stratified Poisson modeling was used to explore the association between ADI and COVID-19 prevalence in the context of county designation. Results: Results show that the relationship between area deprivation and COVID-19 prevalence was positive and higher for rural counties, when compared to urban ones. Family income, property value and educational attainment were among the ADI component measures most correlated with prevalence, but this too differed between county type. Conclusions: Though most Americans live in Metropolitan Areas, rural communities were found to be associated with a stronger relationship between deprivation and COVID-19 prevalence. Models predicting COVID-19 prevalence by ADI and county type reinforced this observation and may inform health policy decisions. [ABSTRACT FROM AUTHOR]

Traditionally, risk-adjustment models do not address the characteristics of minority populations, such as race or socioeconomic status. This study aimed to evaluate the added value of place-based social determinants on risk-adjustment models in explaining health care costs and utilization. Statewide commercial claims from the Maryland Medical Care Database were used, including 1,150,984 Maryland residents aged 18 to 63 with ≥6 months enrollment in 2013 and 2014. Area Deprivation Index (ADI) was assigned to individuals through zip code. The authors examined the addition of ADI to predictive models of concurrent and prospective costs and utilization; linear regression was adopted for costs and logistic regression for utilization markers. Performance measures included R2 for costs (total, pharmacy, and medical costs) and the area under the curve (AUC) for utilization (being top 5% top users, having any hospitalization, having any emergency room [ER] visit, having any avoidable ER visit, and having any readmission). All performance measures were derived from the bootstrapping analysis with 200 iterations. Study subjects were ∼48% male with a mean age of ∼41 years. Adding ADI to the demographics or claims-based models generally did not improve performance except in predicting the probability of having any ER or any avoidable ER visit; for example, AUC of avoidable ER visits increased significantly from.610 to.613 when using ADI rank deciles in claims-based models. Future research should focus on patients with a higher need for social services, assess more granular place-based determinants (eg, Census block group), and evaluate the added value of individual social variables. [ABSTRACT FROM AUTHOR]

As the US health care system moves to expand access to and quality of medical care, the importance of addressing patient-level social needs and community-level social determinants of health (SDOH) is increasingly being recognized. This study evaluates individual- and community-level needs of housing (one of the SDOH domains) across the patient population of an academic medical center and explores how the level of housing needs impacts health care utilization. The authors performed a descriptive analysis of housing issues identified in both structured and unstructured (eg, clinical notes) data extracted from the electronic health record (EHR) and compared this to community-level characteristics of patients' neighborhood as measured by the Area Deprivation Index. Multivariate analyses were performed to assess the association between these and other factors on the frequency of service encounters. Among the 1,034,683 study participants, 59,703 (5.8%) had at least 1 housing issue identified in their EHR from structured or unstructured data combined. After adjusting for other factors, patients with housing instability and homelessness had 49% and 34% more encounters with the health care system compared to patients without housing issues (P < 0.00001). Patients living in the most disadvantaged neighborhoods had 55% more encounters with the health care system compared to those living in the most advantaged neighborhoods (P < 0.00001). This data collection approach and findings can inform health care systems aiming to make use of their EHRs and community-level SDOH information to provide a full assessment of patients' social needs and challenges. [ABSTRACT FROM AUTHOR]

There is growing recognition that social and behavioral risk factors impact population health outcomes. Interventions that target these risk factors can improve health outcomes. This study presents a review of existing literature and proposes a conceptual framework for the integration of social and behavioral data into population health analytics platforms. The authors describe several use cases for these platforms at the patient, health system, and community levels, and align these use cases with the different types of prevention identified by the Centers for Disease Control and Prevention. They then detail the potential benefits of these use cases for different health system stakeholders and explore currently available and potential future sources of social and behavioral domains data. Also noted are several potential roadblocks for these analytic platforms, including limited data interoperability, expense of data acquisition, and a lack of standardized technical terminology for socio-behavioral factors. [ABSTRACT FROM AUTHOR]

The premise of this project was that social and behavioral determinants of health (SBDH) affect the use of healthcare services and outcomes for patients in an integrated healthcare system such as the Veterans Health Administration (VHA), and thus individual patient level socio-behavioral factors in addition to the neighborhood characteristics and geographically linked factors could add information beyond medical factors mostly considered in clinical decision making, patient care, and population health. To help VHA better address SBDH risk factors for the veterans it cares for within its primary care clinics, we proposed a conceptual and analytic framework, a set of evidence-based measures, and their data source. The framework and recommended SBDH metrics can provide a road map for other primary care-centric healthcare organizations wishing to use health analytic tools to better understand how SBDH affect health outcomes. [ABSTRACT FROM AUTHOR]

Introduction: This study aims to assess the effect of individual and geographic-level social determinants of health on risk of hospitalization in the Veterans Health Administration primary care clinics known as the Patient Aligned Care Team.Methods: For a population of Veterans enrolled in the primary care clinics, the study team extracted patient-level characteristics and healthcare utilization records from 2015 Veterans Health Administration electronic health record data. They also collected census data on social determinants of health factors for all U.S. census tracts. They used generalized estimating equation modeling and a spatial-based GIS analysis to assess the role of key social determinants of health on hospitalization. Data analysis was completed in 2018.Results: A total of 6.63% of the Veterans Health Administration population was hospitalized during 2015. Most of the hospitalized patients were male (93.40%) and white (68.80%); the mean age was 64.5 years. In the generalized estimating equation model, white Veterans had a 15% decreased odds of hospitalization compared with non-white Veterans. After controlling for patient-level characteristics, Veterans residing in census tracts with the higher neighborhood SES index experienced decreased odds of hospitalization. A spatial-based analysis presented variations in the hospitalization rate across the Veterans Health Administration primary care clinics and identified the clinic sites with an elevated risk of hospitalization (hotspots) compared with other clinics across the country.Conclusions: By linking patient and population-level data at a geographic level, social determinants of health assessments can help with designing population health interventions and identifying features leading to potentially unnecessary hospitalization in selected geographic areas that appear to be outliers. [ABSTRACT FROM AUTHOR]

Community health records (CHRs) are defined as "a curated set of population-level indicators that describe the health and quality of life of a geographic community". CHRs encompass clinical, social determinants of health (SDOH), and public health data aggregated at the neighborhood level. If developed and deployed across communities, CHRs provide an opportunity to track and enhance population health on a regional or national level. Electronic Health Records (EHRs), if linked across providers, can document certain indicators of SDOH in addition to capturing clinical data for residents of a community. Moreover, EHR-derived patient-level SDOH information could be collated with geographic level public health and social services information to create the basis for neighborhood-specific CHRs. An EHR-derived CHR - relative to current survey-based assessments used by public health agencies in the United States and other countries - could dramatically increase the scope, quality, and timeliness of data available for planning interventions targeted at SDOH factors at both the consumer and small-area levels. EHR-derived CHRs, if assembled across neighborhoods, could also offer a significant value to the society by providing population-level SDOH data across various regions and eventually nationwide. [ABSTRACT FROM AUTHOR]

Population health is one of the pillars of the Triple Aim to improve US health care. The authors developed a framework for population health measurement and a proposed set of measures for further exploration to guide the population health efforts in Maryland. The authors searched peer-reviewed, expert-authored literature and current public health measures. Using a semi-structured analysis, a framework was proposed, which consisted of a conceptual model of several domains and identified population health measures addressing them. Stakeholders were convened to review the framework and identified the most feasible population health measures considering the underlying health information technology (IT) infrastructure in Maryland. The framework was organized based on health system factors, determinants of health, and population-based and clinical outcomes. Measurement specifications were developed that addressed different aspects of selected measures and assessed various national and local data sources for selected measures. Data sources were identified based on their key characteristics, challenges, opportunities, and potential applicability to the proposed measures, as well as the issue of interoperability of data sources among different organizations. The proposed framework and measures can act as a platform to quantify the determinants of health and the state overall population health goals. Key considerations for developing a population health measures framework include health IT infrastructure, data denominators, feasibility, health system environment, and policy factors. Measurement development and progression using the framework will largely depend on the users' focus areas and availability of data. The authors believe that the proposed framework and road map can serve as a model for communities elsewhere. [ABSTRACT FROM AUTHOR]

CONTEXT: Digital retinal imaging with the application of telemedicine technology shows promising results for screening of diabetic retinopathy in the primary care setting without requiring an ophthalmologist on site. AIMS: We assessed whether the establishment of telemedicine technology was an effective and efficient way to increase completion of annual eye examinations among underserved, low-income (Medicaid) diabetic patients. SETTINGS AND DESIGN: A cross-sectional study in a primary care setting. SUBJECTS AND METHODS: Health care claims data were collected before the establishment of telemedicine technology in 2010 and after its implementation in 2012 for Medicaid patients at East Baltimore Medical Center (EBMC), an urban health center that is part of Johns Hopkins Health System. STATISTICAL ANALYSIS USED: The primary outcome measure was the compliance rate of patients with diabetic eye examinations; calculated as the number of diabetic patients with a completed telemedicine eye examination, divided by the total number of diabetic patients. RESULTS: In 2010, EBMC treated 213 Medicaid diabetic patients and in 2012 treated 228 Medicaid patients. In 2010, 47.89% of patients completed their annual diabetic eye examination while in 2012 it was 78.07% (P < 0.001). After adjustment for age, gender, HgBA1C, disease severity, using resource utilization band score as a proxy, and medication possession ratio; telemedicine technology significantly increased the compliance (odds ratio: 4.98, P < 0.001). CONCLUSIONS: Adherence to annual eye examinations is low in the studied Medicaid diabetic population. Telemedicine technology in a primary care setting can increase compliance with annual eye examinations. [ABSTRACT FROM AUTHOR]

Purpose: The disability‑adjusted life‑years (DALYs) lost due to eye diseases and trends in DALYs in Iran has not been previously reported. The object of this study is to report the burden of eye diseases in Iran and to compare changes from 1990 to 2010 based on age and gender. Methods: Data from the Global Burden of Disease Study 2010 (GBD 2010) are used to report DALYs for cataract, refraction/accommodation (functional) disorders, macular degeneration, and glaucoma. Results: Cataract, refraction/accommodation (functional) disorders, macular degeneration, and glaucoma were the 84th, 87th, 138th, and 151st causes of DALY in 1990 and the 89th, 72nd, 99th, and 137th in 2010, respectively. Cataract accounted for 0.085% of national DALY in 1990 and 0.09% in 2010, refraction/accommodation (functional) disorders accounted for 0.42% in 1990 and 0.47% in 2010, macular degeneration accounted for 0.017% in 1990 and 0.071% in 2010 and glaucoma accounted for 0.0099% in 1990 and 0.025% in 2010. There was a steady increase in DALY with age for each eye disease for both genders and dichotomized for males and females from 1990 to 2010. Conclusions: Epidemiologic transition is reflected in major ophthalmic and blinding diseases in the GBD data for Iran. The burden of macular degeneration is rising, followed by glaucoma. The burden of presbyopia affected individuals past their middle age. The burden of cataract manifested as a slower increase that could be attributable to better access to treatment. [ABSTRACT FROM AUTHOR]

Research Objective: International Classification of Diseases (ICD) coding system have codes for recording of social determinants of health (SDOH); however, documentation of non‐clinical issues in electronic health records (EHRs) is infrequent compared to medical conditions. ICD codes in EHRs for SDOH identification, therefore, may under‐report patients with social needs and risks, which makes it difficult for healthcare systems to target "high risk" patients for interventions addressing social needs. SDOH may be discussed with healthcare providers during visits and, therefore, recorded in EHR free‐text notes (a.k.a, providers' notes). These notes might provide a more accurate accounting of SDOH; however, traditional approaches for review and abstraction of patient information from medical record notes is laborious, expensive, and slow. Recent developments in text mining and natural language processing (NLP) of digitized text allows for reliable, low cost, and rapid extraction of information from EHRs. In this pilot project we evaluated whether an NLP algorithm could extract valid measures of SDOH from Epic‐based EHRs in three healthcare systems: Johns Hopkins Health System (JHHS), Kaiser Permanente Mid‐Atlantic States (KPMAS), and KP Southern California (KPSCcal). The focus of our study was residential instability (i.e., homelessness and housing insecurity). Study Design: The study was conducted independently, in a parallel and coordinated framework across sites. The validation assessment and NLP algorithm logic were identical across sites; however, the "gold standard" for assessment of algorithm validity differed according to data availability. Using the EntityRuler module of spaCy 2.3 Python toolkit, we created a rule‐based NLP system made up of 61 expert‐developed patterns that, if present, would represent residential instability. Our patterns included word 'lemmas' and base forms to account for morphological variations (e.g., singular and plural forms) as well as substitutions of different prepositions (e.g., about and for), and synonym words (e.g., house, apartment, and home). We calibrated and then validated the algorithm using a split sample approach. Validity was assessed at each site by measures of sensitivity and specificity. Population Studied: Beneficiaries ≥18 years of age during 2016 through 2019 who received care at JHHS, KPMAS, KPSCal. Principal Findings: The following table presents the characteristics of the study population and performance of the NLP algorithm at each study site. JHHSKPMASKPScalStudy Population (Patient No.)~1,200,000~1,600,000~4,700,000NLP ValidationGold Standard MethodSDOH QuestionnaireSDOH QuestionnaireSDOH ICD codes Manual AnnotationSample SizePatients/ Response No. (with/without residential Instability)1000(500+/ 500‐)8197(833+,7364‐)300(150+/150‐)Clinical Note No.134,06278,8259575NLP Algorithm PerformanceSensitivity0.840.610.96Specificity0.960.870.97 Conclusions: The consistent performance of this NLP algorithm to identify residential instability in three different healthcare systems suggests the algorithm is generalizable. The consistent and relatively high sensitivity and specificity demonstrates the algorithm's validity. Implications for Policy or Practice: Development of generalizable NLP algorithms with promising performance will enhance the value of EHRs to identify at risk patients across different health systems, to improve patient care and outcomes, and to mitigate socioeconomic disparities across individuals and communities. Primary Funding Source: Johns Hopkins and Kaiser Permanente Research Collaboration Committee Pilot Awards. [ABSTRACT FROM AUTHOR]

Research Objective: International Classification of Diseases (ICD) coding system have codes for recording of social determinants of health (SDOH); however, documentation of non‐clinical issues in electronic health records (EHRs) is infrequent compared to medical conditions. ICD codes in EHRs for SDOH identification, therefore, may under‐report patients with social needs and risks, which makes it difficult for healthcare systems to target "high risk" patients for interventions addressing social needs. SDOH may be discussed with healthcare providers during visits and, therefore, recorded in EHR free‐text notes (a.k.a, providers' notes). These notes might provide a more accurate accounting of SDOH; however, traditional approaches for review and abstraction of patient information from medical record notes is laborious, expensive, and slow. Recent developments in text mining and natural language processing (NLP) of digitized text allows for reliable, low cost, and rapid extraction of information from EHRs. In this pilot project we evaluated whether an NLP algorithm could extract valid measures of SDOH from Epic‐based EHRs in three healthcare systems: Johns Hopkins Health System (JHHS), Kaiser Permanente Mid‐Atlantic States (KPMAS), and KP Southern California (KPSCcal). The focus of our study was residential instability (i.e., homelessness and housing insecurity). Study Design: The study was conducted independently, in a parallel and coordinated framework across sites. The validation assessment and NLP algorithm logic were identical across sites; however, the "gold standard" for assessment of algorithm validity differed according to data availability. Using the EntityRuler module of spaCy 2.3 Python toolkit, we created a rule‐based NLP system made up of 61 expert‐developed patterns that, if present, would represent residential instability. Our patterns included word 'lemmas' and base forms to account for morphological variations (e.g., singular and plural forms) as well as substitutions of different prepositions (e.g., about and for), and synonym words (e.g., house, apartment, and home). We calibrated and then validated the algorithm using a split sample approach. Validity was assessed at each site by measures of sensitivity and specificity. Population Studied: Beneficiaries ≥18 years of age during 2016 through 2019 who received care at JHHS, KPMAS, KPSCal. Principal Findings: The following table presents the characteristics of the study population and performance of the NLP algorithm at each study site. JHHSKPMASKPScalStudy Population (Patient No.)~1,200,000~1,600,000~4,700,000NLP ValidationGold Standard MethodSDOH QuestionnaireSDOH QuestionnaireSDOH ICD codes Manual AnnotationSample SizePatients/ Response No. (with/without residential Instability)1000(500+/ 500‐)8197(833+,7364‐)300(150+/150‐)Clinical Note No.134,06278,8259575NLP Algorithm PerformanceSensitivity0.840.610.96Specificity0.960.870.97 Conclusions: The consistent performance of this NLP algorithm to identify residential instability in three different healthcare systems suggests the algorithm is generalizable. The consistent and relatively high sensitivity and specificity demonstrates the algorithm's validity. Implications for Policy or Practice: Development of generalizable NLP algorithms with promising performance will enhance the value of EHRs to identify at risk patients across different health systems, to improve patient care and outcomes, and to mitigate socioeconomic disparities across individuals and communities. Primary Funding Source: Johns Hopkins and Kaiser Permanente Research Collaboration Committee Pilot Awards. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the public health and preventive medicine (PHPM) physicians' career paths in the U.S. It provides an analysis of the Johns Hopkins PHPM Residency Program-trained physicians' career paths. It also reveals evaluation of the characteristics of physicians' PHPM jobs, including working for international nongovernmental organizations and public health agencies such as the World Health Organization.

Purpose. To evaluate macular thickness, agreement, and intraclass repeatability in three optical coherence tomography (OCT) devices: the time domain (TD) Stratus OCT and two spectral domain (SD) OCTs, Spectralis and Cirrus SD-OCT, in eyes with macular edema secondary to diabetic retinopathy (DR) and retinal vein occlusion (VO). Methods. In a prospective observational study at a university-based retina practice, retinal thickness tomography was performed simultaneously for fifty-eight patients (91 eyes) with DR and VO employing a time domain and two spectral domain OCTs. Agreement in macular measurements was assessed by constructing Bland-Altman plots. Intraclass repeatability was assessed by intraclass correlation coefficients (ICCs). Results. Based on the Bland-Altman plots for central macular thickness, there was low agreement between the measurements of Cirrus SD-OCT and Stratus OCT, Spectralis OCT and Stratus OCT, as well as Spectralis OCT and Cirrus SD-OCT among DR and RVO patients. All three devices demonstrated high intraclass repeatability, with ICC of 98% for Stratus OCT, 97% for Cirrus SD-OCT, and 100% for Spectralis OCT among DR patients. The ICC was 97% for Stratus OCT, 79% for Cirrus SD-OCT, and 91% for Spectralis OCT among RVO patients. Conclusion. There are low agreements among interdevice measurements. However, intraclass repeatability is high in both TD and SD-OCT devices. [ABSTRACT FROM AUTHOR]

Purpose: Corticosteroids (CS) are the only approved drug class for treatment of noninfectious uveitis by the U.S. Food and Drug Administration. Serious side effects are associated with chronic use of systemic CS; established guidelines recommend the use of steroid-sparing agents if control of uveitis cannot be achieved with ≤10 mg/day of prednisone (or equivalent) within 3 months. This study evaluated the treatment patterns among physicians who routinely manage patients with noninfectious uveitis to determine how treatment guidelines are followed. Design: Cross-sectional, multicenter study conducted across the United States. Participants: Sixty ophthalmologists and 3 rheumatologists were recruited using payer reimbursement International Classification of Diseases, Ninth Revision codes. Methods: Patient data were reported using a study-specific questionnaire. Physicians were also asked if they were aware of or used recommended treatment guidelines. Main Outcome Measures: Uveitis treatment patterns were compared with guidelines. Results: Physicians managed a mean of 5555 patients; patients with uveitis who required systemic CS treatment comprised approximately 5% of each physician''s practice. A total of 580 patients with noninfectious uveitis were randomly selected for analyses. Anterior uveitis requiring systemic therapy was diagnosed in 168 patients (29%), intermediate uveitis was diagnosed in 140 patients (24%), posterior uveitis was diagnosed in 150 patients (26%), and panuveitis was diagnosed in 122 patients (21%); 199 patients (34%) had active disease. The mean time interval from the diagnosis of uveitis to the time of survey was 3.1 to 4.5 years. A systemic disorder was associated with uveitis in 16% to 54% of patients; 57% to 100% of patients received systemic immunosuppressive therapy. In all, 360 of 580 patients (62%) received systemic CS, with a mean initial daily dose of 44 mg, tapered to 34 mg prednisone (or equivalent) as maintenance dose. Among physicians surveyed, 75% did not use or were not aware of treatment guidelines for uveitis. Conclusions: The study reveals that the majority of physicians surveyed are not familiar with or do not adhere to currently recommended guidelines for management of uveitis. High CS doses are used to maintain control of disease, and there is a low level of awareness of recommended guidelines to treat noninfectious uveitis. The finding underscores the need to place further emphasis on educating the medical community and reinforcing treatment guidelines to improve the care of patients with uveitis. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. [Copyright &y& Elsevier]

Purpose: To determine the prevalence of lens opacities and cataract surgical coverage among Tehran citizens 40 years of age and older. Methods: The Tehran Eye Study was a population-based survey, with random sampling from Tehran household clusters. Those 40 years of age and older from that survey were included in this analysis. All participants underwent full optometric, slit lamp, and fundoscopic examinations. Lens opacity was assessed after pupil dilation using the modified Lens Opacities Classification System III (LOCS III). The main indices for prevalence of cataract were any lens changes, defined as the presence of a gradable cataract in one or both eyes, and all lens changes, defined as any lens changes plus a history of cataract surgery. Results: A total of 1434 participants were included in this analysis; 305 of which met the criteria for all lens changes resulting in an adjusted prevalence of 22.7% (CI95%: 20.2%-25.3%). The prevalence was 21.2% among men and 24.5% among women. The prevalence of any lens changes was 19.1% (CI95%: 16.6%-21.6%) and the prevalence was higher in women. The prevalence for both indices increased with age. Considering their better eyes, 39 people (2.7%) were shown to have low vision because of cataract and another 12 (0.8%) were classified as blind. Conclusions: Cataract has affected approximately one-fifth of the Tehran population aged 40 years and over, women more than men, and has severely affected the vision of approximately 3.5% of this population. We found that access to cataract surgery facilities was not an issue. [ABSTRACT FROM AUTHOR]

Purpose : To determine the prevalence of astigmatism and its epidemiological risk factors in Tehran via a population-based study. Methods : By means of a stratified random cluster sampling, 6497 citizens representing a cross-section of the population of Tehran were selected from 160 clusters. Eligible people were recruited through a door-to-door household survey in the selected clusters and transferred to a clinic for an extensive eye examination and interview. The refractive status was determined with manifest refraction. Astigmatism was defined as cylinder worse than or equal to 0.5 D. High astigmatism was defined as a manifest cylinder ≥1.5 D. Results : Between August and December 2002, 4565 of the 6497 eligible individuals in the sample attended the interview and ophthalmic examination (a participation rate of 70.3%). The age- and gender-standardized prevalence of astigmatism was 50.2% (95% CI, 48.4% to 51.9%) on manifest refraction. High astigmatism was found in 490 right eyes (11.1%; 95% CI, 10.1% to 12.0%). Of 2532 participants with ametropia, 59.6 (95% CI, 57.6–61.5) had astigmatism. The percentages of with-the-rule, against-the-rule and oblique astigmatism were 33.6%, 36.9% and 29.3%, respectively. The proportion of type of astigmatism was significantly related to age (p [ABSTRACT FROM AUTHOR]

This study aimed to assess the impact of coronavirus disease (COVID-19) prevalence in the United States in the week leading to the relaxation of the stay-at-home orders (SAH) on future prevalence across states that implemented different SAH policies. We used data on the number of confirmed COVID-19 cases as of August 21, 2020 on county level. We classified states into four groups based on the 7-day change in prevalence and the state's approach to SAH policy. The groups included: (1) High Change (19 states; 7-day prevalence change ≥50th percentile), (2) Low Change (19 states; 7-day prevalence change <50th percentile), (3) No SAH (11 states: did not adopt SAH order), and (4) No SAH End (2 states: did not relax SAH order). We performed regression modeling assessing the association between change in prevalence at the time of SAH order relaxation and COVID-19 prevalence days after the relaxation of SAH order for four selected groups. After adjusting for other factors, compared to the High Change group, counties in the Low Change group had 33.8 (per 100,000 population) fewer cases (standard error (SE): 19.8, p < 0.001) 7 days after the relaxation of SAH order and the difference was larger by time passing. On August 21, 2020, the No SAH End group had 383.1 fewer cases (per 100,000 population) than the High Change group (SE: 143.6, p < 0.01). A measured, evidence-based approach is required to safely relax the community mitigation strategies and practice phased-reopening of the country. [ABSTRACT FROM AUTHOR]

Background: The spread of COVID-19 has highlighted the long-standing health inequalities across the U.S. as neighborhoods with fewer resources were associated with higher rates of COVID-19 transmission. Although the stay-at-home order was one of the most effective methods to contain its spread, residents in lower-income neighborhoods faced barriers to practicing social distancing. We aimed to quantify the differential impact of stay-at-home policy on COVID-19 transmission and residents' mobility across neighborhoods of different levels of socioeconomic disadvantage.Methods: This was a comparative interrupted time-series analysis at the county level. We included 2087 counties from 38 states which both implemented and lifted the state-wide stay-at-home order. Every county was assigned to one of four equally-sized groups based on its levels of disadvantage, represented by the Area Deprivation Index. Prevalence of COVID-19 was calculated by dividing the daily number of cumulative confirmed COVID-19 cases by the number of residents from the 2010 Census. We used the Social Distancing Index (SDI), derived from the COVID-19 Impact Analysis Platform, to measure the mobility. For the evaluation of implementation, the observation started from Mar 1st 2020 to 1 day before lifting; and, for lifting, it ranged from 1 day after implementation to Jul 5th 2020. We calculated a comparative change of daily trends in COVID-19 prevalence and Social Distancing Index between counties with three highest disadvantage levels and those with the least level before and after the implementation and lifting of the stay-at-home order, separately.Results: On both stay-at-home implementation and lifting dates, COVID-19 prevalence was much higher among counties with the highest or lowest disadvantage level, while mobility decreased as the disadvantage level increased. Mobility of the most disadvantaged counties was least impacted by stay-at-home implementation and relaxation compared to counties with the most resources; however, disadvantaged counties experienced the largest relative increase in COVID-19 infection after both stay-at-home implementation and relaxation.Conclusions: Neighborhoods with varying levels of socioeconomic disadvantage reacted differently to the implementation and relaxation of COVID-19 mitigation policies. Policymakers should consider investing more resources in disadvantaged counties as the pandemic may not stop until most neighborhoods have it under control. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Population Health: Curriculum Framework for an Emerging Discipline" by D. Harris and colleagues in the 2016 issue.

Purpose: To investigate relationship between macular sensitivity and retinal thickness in diabetic macular edema (DME). Design: Prospective observational study. Methods: settings: University-based retina practice. patients: Twenty-two eyes of 11 patients with DME. procedure: Fundus microperimetry and retinal thickness tomography were performed simultaneously using an automatic fundus perimetry/tomography system. main outcome measures: Quantification of macular sensitivity, fixation pattern, and relationship between macular sensitivity and retinal thickness. Results: Fixation stability revealed that 21 eyes (95.4%) had stable fixation (>75% within central 2 degrees of point of fixation) and 1 eye (4.5%) had relatively unstable fixation (<75% of fixation points located within 2 degrees, >75% located within 4 degrees). Evaluation of fixation location revealed that 15 eyes (68.2%) had central (>50% of fixation points within 0.5 mm of fovea), 3 eyes (13.6%) pericentral (25% to 50% within 0.5 mm of fovea), and 4 eyes (18.2%) eccentric (<25% of fixation points within 0.5 mm of fovea) fixation location. Macular sensitivity increased by an average of 0.03 decibel (dB) (95% confidence interval [CI]: 0.00, 0.06) per 1-micron (μm) increase in retinal thickness for thickness values ≤280 μm measured with the OPKO/OTI spectral-domain OCT. The macular sensitivity decreased by an average 0.05 dB (95% CI: −0.08, −0.02) per 1-μm increase in thickness for thickness values >280 μm. Conclusions: In this pilot study, the majority of eyes with DME had stable, central fixation. Macular sensitivity varied depending on the thickness of the retina. Additional studies are needed to determine the role of microperimetry in eyes with DME. [ABSTRACT FROM AUTHOR]

The article presents a study which explored innovative interventions in which Maternal Mortality Review Committees (MMRCs) actively engaged physician trainees, enhancing their understanding of maternal population health. Topics discussed include evaluation method and findings, challenges to the training model, and analysis of integrating trainees into local and state MMRCs.

Purpose: To describe the clinical spectrum and severity of eye injuries sustained during the Persian Wednesday Eve Festival “Charshanbe-Soori” and to identify the fireworks devices involved. Methods: Prospectively, consecutive patients treated for fireworks-related eye injuries in the emergency room at Farabi Eye Hospital, Tehran, over 3 days around the occasion in 2000, 2001, and 2002 were studied. Results: Four hundred thirty-seven cases of eye injuries with an age range of 2–74 (median 17; SD 11.1) years were studied: 84.6% were male; 18.6% of the injuries were bilateral; 79.9% of the injured were bystanders or passersby. Eleven types of devices were involved, of which seven were explosives and eight were homemade. “Narenjaks,” homemade grenades, were involved in 62.2%, firecrackers in 14.8%, and sparklers in 6.2% of the events. Injuries were categorized as severe in 49% of cases, and 45 (10.4%) people were hospitalized. Five eyes with no light perception and/or enucleation, 33 cases of monocular blindness, 54 (12.3%) cases of open globe (including intraocular foreign bodies) were observed. Grenades, bystander and passerby roles, outdoor context, a relatively older age, lower socioeconomic status, and male gender in the subset of passive roles were the determinants of more severe injuries (all p values < 0.05). Lid injuries (67.7%), corneal abrasions (51.6%), hyphema (48.1%), superficial foreign bodies (32.5%), and corneal contusions (13.8%) were the five leading injuries. Conclusions: In Iran, fireworks cause frequent and diverse injuries during the Wednesday Eve Festival and are a leading cause of severe eye injuries and monocular blindness. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the relationship between retinal sensitivity and the photoreceptor inner segment/outer segment (IS/OS) layer status in patients with diabetic macular edema (DME). Design: Cross-sectional study. Participants: Twenty-five adult patients (37 eyes) diagnosed with DME and managed at the Wilmer Eye Institute, Johns Hopkins University (Baltimore, MD). Methods: We obtained simultaneous fundus microperimetry (MP) and optical coherence tomography (OCT) of patients with DME using a combined MP/OCT system. The device recorded retinal sensitivity and retinal thickness on a 3-dimensional tomography map, and we performed a point-by-point analysis of the IS/OS layer integrity at every MP point. We also reviewed OCT scans to determine the type of DME, cystoid macular edema, or diffuse macular edema (absence of any cysts). In addition, fixation stability and fixation location were analyzed. Main Outcome Measures: Retinal point sensitivity measured by MP. Results: Twenty-five patients (37 eyes: 29 male and 8 female; mean age, 64.16 years) with DME were enrolled. Fixation was centric in 30 eyes (81%), paracentric in 3 eyes (8%), and eccentric in 4 eyes (11%). Twenty-seven eyes had cystoid macular edema, and 10 eyes had diffuse macular edema. Mean central subfield thickness was 325 μm. We analyzed a total of 1036 individual MP points. Mean point sensitivity was 10.51 dB. A total of 793 points (76.5%) had IS/OS layer present, and 243 points (23.5%) had IS/OS layer disrupted. A mixed linear model, constructed to adjust for potential confounders and account for dependence between retinal points, revealed that the absence of the IS/OS junction was significantly associated with a 3.28-dB decrease in retinal point sensitivity (P<0.001). Conclusions: This novel index study demonstrates that disruption of the IS/OS junction is correlated with a significant decrease in point sensitivity in eyes with DME. Further studies are indicated to confirm and validate this relationship. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. [Copyright &y& Elsevier]

Purpose: To compare the frequencies of attacks before and after immunomodulatory therapy (IMT) with mycophenolate mofetil (MMF) in recurrent punctate inner choroidopathy (PIC) and to report fundus autofluorescence (FAF) findings. Methods: Eight patients who had at least two recurrent episodes of increased activity before MMF and 12 months of documented clinical course before and after MMF were included. The frequencies of attacks before and after MMF were compared. FAF images evaluated. Results: Before MMF, the 8 patients experienced 19 attacks of recurrent disease activity; during MMF therapy, 3 (38%) patients experienced 6 recurrent episodes. The attack frequencies were 1.09 ±± 0.75 before and 0.23 ±± 0.32 during treatment ( p == .036). Among the 6 patients who had FAF, surrounding hyperautofluorescent halo was detected in 4 and recurrence occurred in 2 who did not show any changes on the intensity during treatment. Conclusion: In the index study, the employment of MMF has decreased frequency of attacks in recurrent PIC. FAF may be employed to monitor and predict the response to treatment. [ABSTRACT FROM AUTHOR]

Objectives: To determine the long-term effects of ranibizumab (RBZ) in patients with diabetic macular edema (DME). Design: Prospective, randomized, interventional, multicenter clinical trial. Participants: One hundred twenty-six patients with DME. Methods: Subjects were randomized 1:1:1 to receive 0.5 mg RBZ at baseline and months 1, 3, and 5 (group 1), focal or grid laser photocoagulation at baseline and month 3 if needed (group 2), or a combination of 0.5 mg RBZ and focal or grid laser at baseline and month 3 (group 3). Starting at month 6, if retreatment criteria were met, all subjects could be treated with RBZ. Main Outcome Measures: The mean change from baseline in best-corrected visual acuity (BCVA) at month 24. Results: After the primary end point at month 6, most patients in all groups were treated only with RBZ, and the mean number of injections was 5.3, 4.4, and 2.9 during the 18-month follow-up period in groups 1, 2, and 3, respectively. For the 33 patients in group 1, 34 patients in group 2, and 34 patients in group 3 who remained in the study through 24 months, the mean improvement in BCVA was 7.4, 0.5, and 3.8 letters at the 6-month primary end point, compared with 7.7, 5.1, and 6.8 letters at month 24, and the percentage of patients who gained 3 lines or more of BCVA was 21, 0, and 6 at month 6, compared with 24, 18, and 26 at month 24. The percentage of patients with 20/40 or better Snellen equivalent at month 24 was 45% in group 1, 44% in group 2, and 35% in group 3. Mean foveal thickness (FTH), defined as center subfield thickness, at month 24 was 340 μm, 286 μm, and 258 μm for groups 1, 2, and 3, respectively, and the percentage of patients with center subfield thickness of 250 μm or less was 36%, 47%, and 68%, respectively. Conclusions: Intraocular injections of RBZ provided benefit for patients with DME for at least 2 years, and when combined with focal or grid laser treatments, the amount of residual edema was reduced, as were the frequency of injections needed to control edema. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. [Copyright &y& Elsevier]

Purpose: To describe the bioactivity of an intercellular adhesion molecule inhibitor (efalizumab) in a patient with refractory uveitic macular edema. Methods: A 55-year-old man presented with idiopathic autoimmune uveitis and associated macular edema, which could not be controlled by regional and systemic corticosteroid and selected immunomodulatory therapy. Efalizumab was administered as subcutaneous injections. Results: After 37 weekly injections of efalizumab, the uveitic macular edema was successfully eliminated. Six months following discontinuation of efalizumab, there were no signs of recurrent inflammation. Conclusion: Further investigation of the role of intercellular adhesion molecule inhibitors in the management of uveitic macular edema is indicated. [ABSTRACT FROM AUTHOR]

Purpose: Perifosine is a novel alkylphospholipid with antiproliferative properties attributed to protein kinase B inhibition. The authors describe a form of ulcerative keratitis in 5 patients with advanced gastrointestinal stromal tumor (GIST) enrolled in a phase I/II trial of perifosine in combination with imatinib. Design: Interventional case series. Participants: Five patients (1 man, 4 women) with imatinib-resistant metastatic GIST who received a combination of imatinib and perifosine orally. Methods: The medical records were reviewed retrospectively. Main Outcome Measures: Ocular toxicity and ulcerative keratitis associated with perifosine. Results: The ocular symptoms included redness, irritation, tearing, photophobia, and a gradual decrease in vision. Slit-lamp biomicroscopy in each case revealed a peripheral, paralimbal, ring-shaped, superficial corneal stromal infiltration and ulcerative keratitis, reminiscent of the autoimmune keratitis in conditions such as rheumatoid arthritis. The ulcerative keratitis was unilateral in 3 and bilateral in 2 patients; it was National Cancer Institute grade II (symptoms interfering with function but not interfering with activities of daily living) in all patients. All 5 patients had imatinib-resistant metastatic GIST and had continued on the highest dose of imatinib tolerated and initiated therapy with perifosine 100 mg daily or 900 mg weekly. A combination of topical steroids, topical antibiotics, and lubricating drops were used to manage ulcerative keratitis. In the first 3 patients, ulcerative keratitis initially was treated with topical antibiotics without improvement, but subsequently they improved significantly after topical steroids were added. Conclusions: A vision-threatening form of ulcerative keratitis may occur in patients taking perifosine. It is possible that imatinib in combination with perifosine contributes to this corneal toxicity; however, the authors are unaware of this ocular toxicity having been reported for imatinib when used without perifosine. The visual loss associated with perifosine may be reversible if detected and treated early and with judicious early use of topical steroids, topical antibiotic coverage, and lubrication. [Copyright &y& Elsevier]

Introduction: Integrative medicine (IM) is by its very definition patient centric: "It reaffirms the importance of the relationship between practitioner and patient, focuses on the whole person, is informed by evidence, and makes use of all appropriate therapeutic approaches." Best methods for teaching IM in residency have not been well described.Methods: An IM curriculum for preventive medicine (PM) residents was thoughtfully developed and iteratively revised using Kern's six-step approach. The centerpiece of this curriculum was to have learners work collaboratively within teams on projects that would facilitate IM-focused care within primary care practices. Before embarking on specific IM-related projects, residents immersed themselves within the practices to understand the needs of the community.Results: Forty-eight PM residents have participated in the curriculum in the last 3 years, and 27 unique physician preceptors served as mentors for the projects. Both residents and preceptors enjoyed working on the projects, and both groups considered the work to be a valuable educational pursuit. Common IM content areas covered by the projects dealt with interprofessional collaboration, health promotion, and population-based prevention. Although there were challenges associated with implementation of the projects, overcoming these enhanced the PM residents' confidence and ability to serve as agents of change.Conclusions: An IM curriculum was successfully incorporated into a PM residency program. The focus on serving the community, or a population health approach, may not be the most common approach in IM, but it worked effectively to enhance the IM knowledge and skills of PM residents. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether the use of ultra wide-field imaging changes the management or determination of disease activity in patients with noninfectious posterior uveitis. Design: Prospective, observational case series. Methods: setting: Divisions of Retina and Ocular Immunology at single academic medical center. patient population: Total of 43 patients with noninfectious posterior uveitis seen by 4 investigators at the Wilmer Eye Institute. procedures: Each patient underwent standard clinical examination, followed by ultra wide-field scanning laser ophthalmoscope (SLO) imaging and angiography. Investigators successively determined disease activity and management decisions based on clinical examination, examination plus simulated 30- or 60-degree fluorescein angiography (FA) (obtained by physically narrowing the field of view of the wide-field images), examination plus ultra wide-field SLO images, and examination plus wide-field FA. main outcome measures: The primary outcome was the percentage of patients whose management changed based on the availability of wide-field imaging, compared with standard examination and imaging. The secondary outcome was detection of disease activity with and without wide-angle imaging. Results: Management was altered in 7 of 43 patients (16%) based on examination and limited FA, whereas 21 of 43 patients (48%) had management change with the use of the ultra wide-field imaging and angiography (P < .001). Disease activity was detected in 22 of 43 patients (51%) based on examination and simulated conventional imaging, and in 27 of 43 (63%) with wide-field imaging (P = .27). Conclusions: The index study, with several design limitations, has suggested that ultra wide-field imaging may alter management decisions compared to standard-of-care imaging and clinical examination. Additional studies, including longitudinal evaluations, are needed to determine whether these findings, or the subsequent management alterations, may improve patient outcomes. [Copyright &y& Elsevier]