Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Ari B. Friedman is active.

Publication


Featured researches published by Ari B. Friedman.


PLOS Medicine | 2008

The reversal of fortunes: trends in county mortality and cross-county mortality disparities in the United States.

Majid Ezzati; Ari B. Friedman; Sandeep C. Kulkarni; Christopher J. L. Murray

Background Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends. Methods and Findings We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each countys life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration. Conclusions There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.


Population Health Metrics | 2009

Diabetes Prevalence and Diagnosis in US states: Analysis of Health Surveys

Goodarz Danaei; Ari B. Friedman; Shefali Oza; Christopher J L Murray; Majid Ezzati

BackgroundCurrent US surveillance data provide estimates of diabetes using laboratory tests at the national level as well as self-reported data at the state level. Self-reported diabetes prevalence may be biased because respondents may not be aware of their risk status. Our objective was to estimate the prevalence of diagnosed and undiagnosed diabetes by state.MethodsWe estimated undiagnosed diabetes prevalence as a function of a set of health system and sociodemographic variables using a logistic regression in the National Health and Nutrition Examination Survey (2003-2006). We applied this relationship to identical variables from the Behavioral Risk Factor Surveillance System (2003-2007) to estimate state-level prevalence of undiagnosed diabetes by age group and sex. We assumed that those who report being diagnosed with diabetes in both surveys are truly diabetic.ResultsThe prevalence of diabetes in the U.S. was 13.7% among men and 11.7% among women ≥ 30 years. Age-standardized diabetes prevalence was highest in Mississippi, West Virginia, Louisiana, Texas, South Carolina, Alabama, and Georgia (15.8 to 16.6% for men and 12.4 to 14.8% for women). Vermont, Minnesota, Montana, and Colorado had the lowest prevalence (11.0 to 12.2% for men and 7.3 to 8.4% for women). Men in all states had higher diabetes prevalence than women. The absolute prevalence of undiagnosed diabetes, as a percent of total population, was highest in New Mexico, Texas, Florida, and California (3.5 to 3.7 percentage points) and lowest in Montana, Oklahoma, Oregon, Alaska, Vermont, Utah, Washington, and Hawaii (2.1 to 3 percentage points). Among those with no established diabetes diagnosis, being obese, being Hispanic, not having insurance and being ≥ 60 years old were significantly associated with a higher risk of having undiagnosed diabetes.ConclusionDiabetes prevalence is highest in the Southern and Appalachian states and lowest in the Midwest and the Northeast. Better diabetes diagnosis is needed in a number of states.


JAMA Internal Medicine | 2014

Primary Care Access for New Patients on the Eve of Health Care Reform

Karin V. Rhodes; Genevieve M. Kenney; Ari B. Friedman; Brendan Saloner; Charlotte C. Lawson; David Chearo; Douglas Wissoker; Daniel Polsky

IMPORTANCE Current measures of access to care have intrinsic limitations and may not accurately reflect the capacity of the primary care system to absorb new patients. OBJECTIVE To assess primary care appointment availability by state and insurance status. DESIGN, SETTING, AND PARTICIPANTS We conducted a simulated patient study. Trained field staff, randomly assigned to private insurance, Medicaid, or uninsured, called primary care offices requesting the first available appointment for either routine care or an urgent health concern. The study included a stratified random sample of primary care practices treating nonelderly adults within each of 10 states (Arkansas, Georgia, Illinois, Iowa, Massachusetts, Montana, New Jersey, Oregon, Pennsylvania, and Texas), selected for diversity along numerous dimensions. Collectively, these states comprise almost one-third of the US nonelderly, Medicaid, and currently uninsured populations. Sampling was based on enrollment by insurance type by county. Analyses were weighted to obtain population-based estimates for each state. MAIN OUTCOMES AND MEASURES The ability to schedule an appointment and number of days to the appointment. We also examined cost and payment required at the visit for the uninsured. RESULTS Between November 13, 2012, and April 4, 2013, we made 12,907 calls to 7788 primary care practices requesting new patient appointments. Across the 10 states, 84.7% (95% CI, 82.6%-86.8%) of privately insured and 57.9% (95% CI, 54.8%-61.0%) of Medicaid callers received an appointment. Appointment rates were 78.8% (95% CI, 75.6%-82.0%) for uninsured patients with full cash payment but only 15.4% (95% CI, 13.2%-17.6%) if payment required at the time of the visit was restricted to


Environmental Health Perspectives | 2010

Within-Neighborhood Patterns and Sources of Particle Pollution: Mobile Monitoring and Geographic Information System Analysis in Four Communities in Accra, Ghana

Kathie L. Dionisio; Michael S. Rooney; Raphael E. Arku; Ari B. Friedman; Allison F. Hughes; Jose Vallarino; Samuel Agyei-Mensah; John D. Spengler; Majid Ezzati

75 or less. Conditional on getting an appointment, median wait times were typically less than 1 week (2 weeks in Massachusetts), with no differences by insurance status or urgency of health concern. CONCLUSIONS AND RELEVANCE Although most primary care physicians are accepting new patients, access varies widely across states and insurance status. Navigator programs are needed, not only to help patients enroll but also to identify practices accepting new patients within each plans network. Tracking new patient appointment availability over time can inform policies designed to strengthen primary care capacity and enhance the effectiveness of the coverage expansions with the Patient Protection and Affordable Care Act.


Science of The Total Environment | 2012

Spatial and temporal patterns of particulate matter sources and pollution in four communities in Accra, Ghana

Michael S. Rooney; Raphael E. Arku; Kathie L. Dionisio; Christopher J. Paciorek; Ari B. Friedman; Heather Carmichael; Zheng Zhou; Allison F. Hughes; Jose Vallarino; Samuel Agyei-Mensah; John D. Spengler; Majid Ezzati

Background Sources of air pollution in developing country cities include transportation and industrial pollution, biomass and coal fuel use, and resuspended dust from unpaved roads. Objectives Our goal was to understand within-neighborhood spatial variability of particulate matter (PM) in communities of varying socioeconomic status (SES) in Accra, Ghana, and to quantify the effects of nearby sources on local PM concentration. Methods We conducted 1 week of morning and afternoon mobile and stationary air pollution measurements in four study neighborhoods. PM with aerodynamic diameters ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) was measured continuously, with matched global positioning system coordinates; detailed data on local sources were collected at periodic stops. The effects of nearby sources on local PM were estimated using linear mixed-effects models. Results In our measurement campaign, the geometric means of PM2.5 and PM10 along the mobile monitoring path were 21 and 49 μg/m3, respectively, in the neighborhood with highest SES and 39 and 96 μg/m3, respectively, in the neighborhood with lowest SES and highest population density. PM2.5 and PM10 were as high as 200 and 400 μg/m3, respectively, in some segments of the path. After adjusting for other factors, the factors that had the largest effects on local PM pollution were nearby wood and charcoal stoves, congested and heavy traffic, loose dirt road surface, and trash burning. Conclusions Biomass fuels, transportation, and unpaved roads may be important determinants of local PM variation in Accra neighborhoods. If confirmed by additional or supporting data, the results demonstrate the need for effective and equitable interventions and policies that reduce the impacts of traffic and biomass pollution.


The New England Journal of Medicine | 2015

No Place to Call Home — Policies to Reduce ED Use in Medicaid

Ari B. Friedman; Brendan Saloner; Renee Y. Hsia

Sources of air pollution in developing country cities include transportation and industrial pollution, biomass fuel use, and re-suspended dust from unpaved roads. We examined the spatial patterns of particulate matter (PM) and its sources in four neighborhoods of varying socioeconomic status (SES) in Accra. PM data were from 1 week of morning and afternoon mobile and stationary air pollution measurements in each of the study neighborhoods. PM(2.5) and PM(10) were measured continuously, with matched GPS coordinates. Data on biomass fuel use were from the Ghana 2000 population and housing census and from a census of wood and charcoal stoves along the mobile monitoring paths. We analyzed the associations of PM with sources using a mixed-effects regression model accounting for temporal and spatial autocorrelation. After adjusting for other factors, the density of wood stoves, fish smoking, and trash burning along the mobile monitoring path as well as road capacity and surface were associated with higher PM(2.5). Road capacity and road surface variables were also associated with PM(10), but the association with biomass sources was weak or absent. While wood stoves and fish smoking were significant sources of air pollution, addressing them would require financial and physical access to alternative fuels for low-income households and communities.


JAMA Internal Medicine | 2016

Urgent Care Needs Among Nonurgent Visits to the Emergency Department

Renee Y. Hsia; Ari B. Friedman; Matthew Niedzwiecki

Medicaid expansion alone may not reduce emergency-department use among new enrollees. Rather than making the ED more costly for patients to use, a promising alternative approach is to provide more robust alternatives to the ED, in keeping with the medical home model.


Statistical Methods in Medical Research | 2017

Estimating negative likelihood ratio confidence when test sensitivity is 100%: A bootstrapping approach.

Keith A. Marill; Yuchiao Chang; Kim F. Wong; Ari B. Friedman

Letters Obtained funding: Both authors. Administrative, technical, or material support: Prather. Study supervision: Prather. Conflict of Interest Disclosures: Dr Prather is a paid consultant for Posit Science on an unrelated project. No other disclosures were reported. Funding/Support: Dr Prathers involvement was supported by grant K08HL112961 from the National Heart, Lung, and Blood Institute. Dr Leung’s involvement was supported by grant K99HD084758 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. 1. Extent and health consequences of chronic sleep loss and sleep disorders. In: Colten HR, Altevogt BM, eds. Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem. Washington, DC; National Academies Press; 2006:55-136. 2. Prather AA, Janicki-Deverts D, Hall MH, Cohen S. Behaviorally assessed sleep and susceptibility to the common cold. Sleep. 2015;38(9):1353-1359. 3. Cohen S, Doyle WJ, Alper CM, Janicki-Deverts D, Turner RB. Sleep habits and susceptibility to the common cold. Arch Intern Med. 2009;169(1):62-67. 4. Patel SR, Malhotra A, Gao X, Hu FB, Neuman MI, Fawzi WW. A prospective study of sleep duration and pneumonia risk in women. Sleep. 2012;35(1):97-101. 5. Bryant PA, Trinder J, Curtis N. Sick and tired: does sleep have a vital role in the immune system? Nat Rev Immunol. 2004;4(6):457-467. 6. Buysse DJ. Sleep health: can we define it? does it matter? Sleep. 2014;37(1): Urgent Care Needs Among Nonurgent Visits to the Emergency Department The goal of triage is to prioritize patients who need to be seen most urgently; it is essential for providing the highest quality of care to the sickest patients. 1 We sought to determine whether a triage determination of non- urgent status in the emer- Editors Note page 854 gency department (ED) effec- tively ruled out the possibility of serious pathologic conditions, as indicated by visits result- ing in diagnostic screening, procedures, hospitalization, or death, and compared these findings with visits deemed as urgent from triage. Methods | The National Hospital Ambulatory Medical Care Survey is a national multistage probability sample survey of patient visits to the ED. These data contain triage scores for each ED visit as assessed by a triage nurse on arrival based on a scale of 1 to 5, with 1 being immediate, 2 emergent, 3 urgent, 4 semi- urgent, and 5 nonurgent. 2 We compared characteristics and outcomes of visits from January 1, 2009, to December 31, 2011, labeled as nonurgent (category 5) with characteristics and out- comes of visits with all other labels (categories 1-4), which we labeled as urgent visits. We focused on nonelderly adults aged 18 to 64 years and excluded visits for which triage scores were missing or where the patient left before triage or medical screening. This study was deemed exempt from human subjects review at the University of California San Francisco. Results | We analyzed 59 293 observations from 2009 to 2011, representing 240 million visits. A total of 218.49 million vis- its (92.5%) were deemed urgent at triage and 17.76 million vis- its (7.5%) as nonurgent. A total of 33.82 million visits (15.5%) deemed urgent arrived by ambulance, compared with 1.19 million visits (6.7%) considered nonurgent. Diagnostic ser- vices, such as blood tests, electrocardiograms, and imaging, were provided in 8.45 million nonurgent visits (47.6%) (any blood tests: weighted, 18.8% [95% CI, 15.5%-22.1%]; electro- cardiograms: 5.8% [95% CI, 4.3%-7.2%]; and any imaging: 28.5% [95% CI, 24.9%-32.0%]), and procedures, such as in- travenous fluids, casting, and splinting, were performed in 5.76 million nonurgent visits (32.4%) (intravenous fluids: weighted, 12.6% [95% CI, 9.7%-15.6%]; casting: 0.6% [95% CI, 0.2%- 1.0%]; and splinting: 6.2% [95% CI, 5.2%-7.3%]). In compari- son, diagnostic services were provided in 163.49 million ur- gent visits (74.8%) (any blood tests: weighted, 46.2% [95% CI, 44.7%-47.6%]; electrocardiograms: 18.7% [95% CI, 17.8%- 19.6%]; and any imaging: 49.0% [95% CI, 47.7%-50.3%]), and procedures were performed in 107.89 million urgent visits (49.4%) (intravenous fluids: weighted, 31.7% [95% CI, 30.2%- 33.3%]; casting: 0.3% [95% CI, 0.2%-0.3%]; and splinting: 5.6% [95% CI, 5.3%-5.9%]) (P < .001 for all comparisons) (Table 1). A total of 776 000 nonurgent visits (weighted, 4.4% [95% CI, 3.1%-5.7%]) resulted in admissions and of these, 126 000 (16.2%; weighted, 0.7% (95% CI, 0.1%-1.3%]) were admis- sions to critical care units. A total of 27.86 million urgent vis- its (weighted, 12.8% [95% CI, 11.7%-13.8%]) resulted in admis- sions (P < .001), of which only 2.91 million (10.5%; weighted, 1.3% (95% CI, 1.2%-1.5%]) (P = .32) were admissions to criti- cal care units. Overall, 1.01 million nonurgent visits (weighted, 5.7% [95% CI, 4.2%-7.1%]) resulted in admission or transfer, compared with 32.49 million urgent visits (weighted, 14.9% [95% CI, 13.8%-15.9%]) (P < .001) (Table 2). When we examined the chief symptoms reported at non- urgent visits, 6 of the top 10 reasons—back symptoms, ab- dominal pain, sore throat, headache, chest pain, and low back pain—were also in the top 10 symptoms reported at urgent vis- its. In addition, when the top 10 diagnoses from nonurgent visits were analyzed, 5 were identical to those at urgent visits (backache, lumbago, acute upper respiratory infection, cellulitis, and acute pharyngitis). Discussion | Our study found that a nontrivial proportion of ED visits that were deemed nonurgent arrived by ambu- lance, received diagnostic services, had procedures per- formed, and were admitted to the hospital, including to criti- cal care units. Certainly, not all of these data necessarily indicate that these services were required, and they could signal overuse or a lack of availability of primary care physicians. 3 However, to some degree, our findings indicate that either patients or health care professionals do entertain a degree of uncertainty that requires further evaluation before diagnosis. That half of the top 10 diagnoses, among over 14 000 International Classification of Diseases, Ninth Revision codes, are found in both nonurgent and urgent vis- its shows that 50% of these visits are virtually indistinguish- able from each other. There are certain limitations to this study. Specifically, while the National Hospital Ambulatory Medical Care Survey uses a 5-level triage score, not all hospitals do. The National Hospital Ambulatory Medical Care Survey therefore rescales visits to hospitals that do not use a 5-level triage score, and also JAMA Internal Medicine June 2016 Volume 176, Number 6 (Reprinted) Copyright 2016 American Medical Association. All rights reserved. Downloaded From: http://jamanetwork.com/ by a UCSF LIBRARY User on 11/18/2016 jamainternalmedicine.com


Medical Care Research and Review | 2015

Primary Care Appointment Availability and Preventive Care Utilization: Evidence From an Audit Study

Brendan Saloner; Daniel Polsky; Ari B. Friedman; Karin V. Rhodes

Objectives Assessing high-sensitivity tests for mortal illness is crucial in emergency and critical care medicine. Estimating the 95% confidence interval (CI) of the likelihood ratio (LR) can be challenging when sample sensitivity is 100%. We aimed to develop, compare, and automate a bootstrapping method to estimate the negative LR CI when sample sensitivity is 100%. Methods The lowest population sensitivity that is most likely to yield sample sensitivity 100% is located using the binomial distribution. Random binomial samples generated using this population sensitivity are then used in the LR bootstrap. A free R program, “bootLR,” automates the process. Extensive simulations were performed to determine how often the LR bootstrap and comparator method 95% CIs cover the true population negative LR value. Finally, the 95% CI was compared for theoretical sample sizes and sensitivities approaching and including 100% using: (1) a technique of individual extremes, (2) SAS software based on the technique of Gart and Nam, (3) the Score CI (as implemented in the StatXact, SAS, and R PropCI package), and (4) the bootstrapping technique. Results The bootstrapping approach demonstrates appropriate coverage of the nominal 95% CI over a spectrum of populations and sample sizes. Considering a study of sample size 200 with 100 patients with disease, and specificity 60%, the lowest population sensitivity with median sample sensitivity 100% is 99.31%. When all 100 patients with disease test positive, the negative LR 95% CIs are: individual extremes technique (0,0.073), StatXact (0,0.064), SAS Score method (0,0.057), R PropCI (0,0.062), and bootstrap (0,0.048). Similar trends were observed for other sample sizes. Conclusions When study samples demonstrate 100% sensitivity, available methods may yield inappropriately wide negative LR CIs. An alternative bootstrapping approach and accompanying free open-source R package were developed to yield realistic estimates easily. This methodology and implementation are applicable to other binomial proportions with homogeneous responses.


JAMA | 2014

Economic Incentives and Use of the Intensive Care Unit

Ari B. Friedman

Insurance expansions under the Affordable Care Act raise concerns about primary care access in communities with large numbers of newly insured. We linked individual-level, cross-sectional data on adult preventive care utilization from the 2011-2012 Behavioral Risk Factor Surveillance System to novel county-level measures of primary care appointment availability collected from an experimental audit study conducted in 10 states in 2012 to 2013 and other county-level health service and demographic measures. In multivariate regressions, we found higher county-level appointment availability for privately insured adults was associated with significantly lower preventive care utilization among adults likely to have private insurance. Estimates were attenuated after controlling for county-level uninsurance, poverty, and unemployment. By contrast, greater availability of Medicaid appointments was associated with higher, but not statistically significant, preventive care utilization for likely Medicaid enrollees. Our study highlights that the relationship between preventive care utilization and primary care access in small areas likely differs by insurance status.

Collaboration


Dive into the Ari B. Friedman's collaboration.

Top Co-Authors

Avatar

Majid Ezzati

Imperial College London

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Michael S. Rooney

Massachusetts Institute of Technology

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge