Steven J Atlas

Massachusetts General Hospital, Boston, Massachusetts, United States

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Publications (93)418.96 Total impact

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    ABSTRACT: BACKGROUND Improving the ability to risk-stratify patients is critical for efficiently allocating resources within healthcare systems. OBJECTIVE The purpose of this study was to evaluate a physician-defined complexity prediction model against outpatient Charlson score (OCS) and a commercial risk predictor (CRP). DESIGN Using a cohort in which primary care physicians reviewed 4302 of their adult patients, we developed a predictive model for estimated physician-defined complexity (ePDC) and categorized our population using ePDC, OCS and CRP. PARTICIPANTS 143,372 primary care patients in a practice-based research network participated in the study. MAIN MEASURES For all patients categorized as complex in 2007 by one or more risk-stratification method, we calculated the percentage of total person time from 2008-2011 for which eligible cancer screening was incomplete, HbA1c was ≥ 9 %, and LDL was ≥ 130 mg/dl (in patients with cardiovascular disease). We also calculated the number of emergency department (ED) visits and hospital admissions per person year (ppy). KEY RESULTS There was modest agreement among individuals classified as complex using ePDC compared with OCS (36.7 %) and CRP (39.6 %). Over 4 follow-up years, eligible ePDC-complex patients had higher proportions (p HbA1c ≥ 9 % (15.6 % vs. 8.1 % for OCS; 15.9 % vs. 6.9 % for CRP); and LDL ≥ 130 mg/dl (12.4 % vs. 7.9 % for OCS; 11.8 % vs 9.0 % for CRP). ePDC-complex patients had higher rates (p CONCLUSION Our measure for estimated physician-defined complexity compared favorably to commonly used risk-prediction approaches in identifying future suboptimal quality and utilization outcomes.
    Journal of General Internal Medicine 06/2015; DOI:10.1007/s11606-015-3357-8 · 3.42 Impact Factor

  • The American journal of emergency medicine 05/2015; 33(9). DOI:10.1016/j.ajem.2015.05.042 · 1.27 Impact Factor
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    ABSTRACT: Identifying individuals at high risk for suboptimal outcomes is an important goal of healthcare delivery systems. Appointment no-shows may be an important risk predictor. To test the hypothesis that patients with a high propensity to "no-show" for appointments will have worse clinical and acute care utilization outcomes compared to patients with a lower propensity. We calculated the no-show propensity factor (NSPF) for patients of a large academic primary care network using 5 years of outpatient appointment data. NSPF corrects for patients with fewer appointments to avoid over-weighting of no-show visits in such patients. We divided patients into three NSPF risk groups and evaluated the association between NSPF and clinical and acute care utilization outcomes after adjusting for baseline patient characteristics. A total of 140,947 patients who visited a network practice from January 1, 2007, through December 31, 2009, and were either connected to a primary care physician or to a primary care practice, based on a previously validated algorithm. Outcomes of interest were incomplete colorectal, cervical, and breast cancer screening, and above-goal hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) levels at 1-year follow-up, and hospitalizations and emergency department visits in the subsequent 3 years. Compared to patients in the low NSPF group, patients in the high NSPF group (n=14,081) were significantly more likely to have incomplete preventive cancer screening (aOR 2.41 [2.19-.66] for colorectal, aOR 1.85 [1.65-.08] for cervical, aOR 2.93 [2.62-3.28] for breast cancer), above-goal chronic disease control measures (aOR 2.64 [2.22-3.14] for HbA1c, aOR 1.39 [1.15-1.67] for LDL], and increased rates of acute care utilization (aRR 1.37 [1.31-1.44] for hospitalization, aRR 1.39 [1.35-1.43] for emergency department visits). NSPF is an independent predictor of suboptimal primary care outcomes and acute care utilization. NSPF may play an important role in helping healthcare systems identify high-risk patients.
    Journal of General Internal Medicine 03/2015; 30(10). DOI:10.1007/s11606-015-3252-3 · 3.45 Impact Factor
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    ABSTRACT: BACKGROUND Improving colorectal cancer (CRC) screening rates for patients from socioeconomically disadvantaged backgrounds is a recognized public health priority. OBJECTIVE Our aim was to determine if implementation of a system-wide screening intervention could reduce disparities in the setting of improved overall screening rates. DESIGN This was an interrupted time series (ITS) analysis before and after a population management intervention. PARTICIPANTS Patients eligible for CRC screening (age 52-75 years without prior total colectomy) in an 18-practice research network from 15 June 2009 to 15 June 2012 participated in the study. INTERVENTION The Technology for Optimizing Population Care (TopCare) intervention electronically identified patients overdue for screening and facilitated contact by letter or telephone scheduler, with or without physician involvement. Patients identified by algorithm as high risk for non-completion entered into intensive patient navigation. MAIN MEASURES Patients were dichotomized as ≤ high school diploma (≤ HS), an indicator of socioeconomic disadvantage, vs. >HS diploma (> HS). The monthly disparity between ≤ HS and > HS with regard to CRC screening completion was examined. KEY RESULTS At baseline, 72 % of 47,447 eligible patients had completed screening, compared with 75 % of 51,442 eligible patients at the end of follow-up (p HS patients in June 2009 (65.7 % vs. 74.5 %, p p p CONCLUSIONS A multifaceted population management intervention sensitive to the needs of vulnerable patients modestly narrowed disparities in CRC screening, while also increasing overall screening rates. Embedding interventions for vulnerable patients within larger population management systems represents an effective approach to increasing overall quality of care while also decreasing disparities.
    Journal of General Internal Medicine 02/2015; 30(7). DOI:10.1007/s11606-015-3227-4 · 3.45 Impact Factor
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    ABSTRACT: Background Lack of timely medication intensification and inadequate medication safety monitoring are two prevalent and potentially modifiable barriers to effective and safe chronic care. Innovative applications of health information technology tools may help support chronic disease management. Objective To examine the clinical impact of a novel health IT tool designed to facilitate between-visit ordering and tracking of future laboratory testing. Design and Participants Clinical trial randomized at the provider level (n = 44 primary care physicians); patient-level outcomes among 3,655 primary care patients prescribed 5,454 oral medicines for hyperlipidemia, diabetes, and/or hypertension management over a 12-month period. Main Measures Time from prescription to corresponding follow-up laboratory testing; proportion of follow-up time that patients achieved corresponding risk factor control (A1c, LDL); adverse event laboratory monitoring 4 weeks after medicine prescription. Key Results Patients whose physicians were allocated to the intervention (n = 1,143) had earlier LDL laboratory assessment compared to similar patients (n = 703) of control physicians [adjusted hazard ratio (aHR): 1.15 (1.01-1.32), p = 0.04]. Among patients with elevated LDL (486 intervention, 324 control), there was decreased time to LDL goal in the intervention group [aHR 1.26 (0.99-1.62)]. However, overall there were no significant differences between study arms in time spent at LDL or HbA1c goal. Follow-up safety monitoring (e.g., creatinine, potassium, or transaminases) was relatively infrequent (ranging from 7 % to 29 % at 4 weeks) and not statistically different between arms. Intervention physicians indicated that lack of reimbursement for non-visit-based care was a barrier to use of the tool. Conclusions A health IT tool to support between-visit laboratory monitoring improved the LDL testing interval but not LDL or HbA1c control, and it did not alter safety monitoring. Adoption of innovative tools to support physicians in non-visit-based chronic disease management may be limited by current visit-based financial and productivity incentives.
    Journal of General Internal Medicine 01/2015; 30(5). DOI:10.1007/s11606-014-3152-y · 3.45 Impact Factor
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    ABSTRACT: Increasing access to care may be insufficient to improve the health of patients with diabetes mellitus and unmet basic needs (hereinafter referred to as material need insecurities). How specific material need insecurities relate to clinical outcomes and the use of health care resources in a setting of near-universal access to health care is unclear. To determine the association of food insecurity, cost-related medication underuse, housing instability, and energy insecurity with control of diabetes mellitus and the use of health care resources. Cross-sectional data were collected from June 1, 2012, through October 31, 2013, at 1 academic primary care clinic, 2 community health centers, and 1 specialty center for the treatment of diabetes mellitus in Massachusetts. A random sample of 411 patients, stratified by clinic, consisted of adults (aged ≥21 years) with diabetes mellitus (response rate, 62.3%). The prespecified primary outcome was a composite indicator of poor diabetes control (hemoglobin A1c level, >9.0%; low-density lipoprotein cholesterol level, >100 mg/dL; or blood pressure, >140/90 mm Hg). Prespecified secondary outcomes included outpatient visits and a composite of emergency department (ED) visits and acute care hospitalizations (ED/inpatient visits). Overall, 19.1% of respondents reported food insecurity; 27.6%, cost-related medication underuse; 10.7%, housing instability; 14.1%, energy insecurity; and 39.1%, at least 1 material need insecurity. Poor diabetes control was observed in 46.0% of respondents. In multivariable models, food insecurity was associated with a greater odds of poor diabetes control (adjusted odds ratio [OR], 1.97 [95% CI, 1.58-2.47]) and increased outpatient visits (adjusted incident rate ratio [IRR], 1.19 [95% CI, 1.05-1.36]) but not increased ED/inpatient visits (IRR, 1.00 [95% CI, 0.51-1.97]). Cost-related medication underuse was associated with poor diabetes control (OR, 1.91 [95% CI, 1.35-2.70]) and increased ED/inpatient visits (IRR, 1.68 [95% CI, 1.21-2.34]) but not outpatient visits (IRR, 1.07 [95% CI, 0.95-1.21]). Housing instability (IRR, 1.31 [95% CI, 1.14-1.51]) and energy insecurity (IRR, 1.12 [95% CI, 1.00-1.25]) were associated with increased outpatient visits but not with diabetes control (OR, 1.10 [95% CI, 0.60-2.02] and OR, 1.27 [95% CI, 0.96-1.69], respectively) or with ED/inpatient visits (IRR, 1.49 [95% CI, 0.81-2.73] and IRR, 1.31 [95% CI, 0.80-2.13], respectively). An increasing number of insecurities was associated with poor diabetes control (OR for each additional need, 1.39 [95% CI, 1.18-1.63]) and increased use of health care resources (IRR for outpatient visits, 1.09 [95% CI, 1.03-1.15]; IRR for ED/inpatient visits, 1.22 [95% CI, 0.99-1.51]). Material need insecurities were common among patients with diabetes mellitus and had varying but generally adverse associations with diabetes control and the use of health care resources. Material need insecurities may be important targets for improving care of diabetes mellitus.
    JAMA Internal Medicine 12/2014; 175(2). DOI:10.1001/jamainternmed.2014.6888 · 13.12 Impact Factor
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    ABSTRACT: Background: Patient navigation (PN) can improve breast cancer care among disadvantaged women. We evaluated the impact of a PN program on follow-up after an abnormal mammogram. Methods: Between 2007 and 2010, disadvantaged women with an abnormal mammogram (Breast Imaging-Reporting and Data System [BI-RADS] codes 0, 3, 4, 5) cared for in a community health center (CHC) with PN were compared to those receiving care in 11 network practices without PN. Multivariable logistic regression and Cox proportional hazards modeling were used to compare the percentages receiving appropriate follow-up and time to follow-up between the groups. Results: Abnormal mammography findings were reported for 132 women in the CHC with PN and 168 from practices without PN. The percentage of women with appropriate follow-up care was higher in the practice with PN than in non-PN practices (90.4% vs. 75.3%, adjusted p=0.006). RESULTS varied by BI-RADS score for women in PN and non-PN practices (BI-RADS 0, 93.7% vs. 90.2%, p=0.24; BI-RADS 3, 85.7% vs. 49.2%, p=0.003; BI-RADS 4/5, 95.1% vs. 82.8%, p=0.26). Time to follow-up was similar for BI-RADS 0 and occurred sooner for women in the PN practice than in non-PN practices for BI-RADS 3 and 4/5 (BI-RADS 3, adjusted hazard ratio [aHR], 95% confidence interval [CI]: 2.41 [1.36-4.27], BI-RADS 4/5, aHR [95% CI]: 1.41 [0.88-2.24]). Conclusions: Disadvantaged women from a CHC with PN were more likely to receive appropriate follow-up after an abnormal mammogram than were those from practices without PN. Expanding PN to include all disadvantaged women within primary care networks could improve equity in cancer care.
    Journal of Women's Health 12/2014; 24(2). DOI:10.1089/jwh.2014.4954 · 2.05 Impact Factor
  • Steven J Atlas ·
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    ABSTRACT: Commentary on: Friedly JL, Comstock BA, Turner JA, et al. A randomized trial of epidural glucocorticoid injections for spinal stenosis. N Engl J Med 2014;371:11-21. Context Degenerative lumbar spinal stenosis is a common cause of low back and leg pain in older individuals. The evidence supporting non-surgical treatments, including oral medications, physical treatments and spinal injections, is limited.1 Despite the lack of strong evidence supporting the use of epidural steroid injections (ESIs) for lumbar spinal stenosis, their use has increased dramatically since 2000.2 This multicentre, randomised trial compared the effectiveness of ESIs with lidocaine to epidural injections of lidocaine alone.
    Evidence-Based Medicine 10/2014; 20(1). DOI:10.1136/ebmed-2014-110083
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    ABSTRACT: Engaging physicians and practice leaders through regular performance reporting is a key goal of patient-centered medical home improvement efforts. We developed and implemented an interactive, Web-based performance dashboard for primary care practices with input from provider focus groups. Adapting a business software application, individual physician and practice-level reports included information on visit-based and panel productivity, patient panel demographics, and outcome measures (quality of care, patient experience of care, and resource utilization). User training occurred prior to dissemination. Over 2 rounds of reporting, 69% to 77% of users viewed their report within 30 days and 79% of users found the report informative.
    The Journal of ambulatory care management 10/2014; 37(4):339-348. DOI:10.1097/JAC.0000000000000044
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    ABSTRACT: Objective To determine which area-based socioeconomic status (SES) indicator is best suited to monitor health care disparities from a delivery system perspective.Data Sources/Study Setting142,659 adults seen in a primary care network from January 1, 2009 to December 31, 2011.Study DesignCross-sectional, comparing associations between area-based SES indicators and patient outcomes.Data CollectionAddress data were geocoded to construct area-based SES indicators at block group (BG), census tract (CT), and ZIP code (ZIP) levels. Data on health outcomes were abstracted from electronic records. Relative indices of inequality (RIIs) were calculated to quantify disparities detected by area-based SES indicators and compared to RIIs from self-reported educational attainment.Principal FindingsZIP indicators had less missing data than BG or CT indicators (p < .0001). Area-based SES indicators were strongly associated with self-report educational attainment (p < .0001). ZIP, BG, and CT indicators all detected expected SES gradients in health outcomes similarly. Single-item, cut point defined indicators performed as well as multidimensional indices and quantile indicators.Conclusions Area-based SES indicators detected health outcome differences well and may be useful for monitoring disparities within health care systems. Our preferred indicator was ZIP-level median household income or percent poverty, using cut points.
    Health Services Research 09/2014; 50(2). DOI:10.1111/1475-6773.12229 · 2.78 Impact Factor
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    ABSTRACT: The long-term effects of interventions to improve colorectal (CRC) screening in vulnerable populations are uncertain. The authors evaluated the impact of patient navigation (PN) on the equity of CRC prevention over a 5-year period. A culturally tailored CRC screening PN program was implemented in 1 community health center (CHC) in 2007. In a primary care network, CRC screening rates from 2006 to 2010 among eligible patients from the CHC with PN were compared with the rates from other practices without PN. Multivariable logistic regression models for repeated measures were used to assess differences over time. Differences in CRC screening rates diminished among patients at the CHC with PN and at other practices between 2006 (49.2% vs 62.5%, respectively; P < .001) and 2010 (69.2% vs 73.6%, respectively; P < .001). The adjusted rate of increase over time was higher at the CHC versus other practices (5% vs 3.4% per year; P < .001). Among Latino patients at the CHC compared with other practices, lower CRC screening rates in 2006 (47.5% vs 52.1%, respectively; P = .02) were higher by 2010 (73.5% vs 67.3%, respectively; P < .001). Similar CRC screening rates among non-English speakers at the CHC and at other practices in 2006 (44.3% vs 44.7%, respectively; P = .79) were higher at the CHC by 2010 (70.6% vs 58.6%, respectively; P < .001). Adjusted screening rates increased more over time for Latino and non-English speakers at the CHC compared with other practices (both P < .001). A PN program increased CRC screening rates in a CHC and improved equity in vulnerable patients. Long-term funding of PN programs has the potential to reduce cancer screening disparities. Cancer 2014. © 2014 American Cancer Society.
    Cancer 07/2014; 120(13). DOI:10.1002/cncr.28682 · 4.89 Impact Factor
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    ABSTRACT: Background: Advances in information technology (IT) now permit population-based preventive screening, but the best methods remain uncertain. We evaluated whether involving primary care providers (PCPs) in a visit-independent population management IT application led to more effective cancer screening. Methods: We conducted a cluster-randomized trial involving 18 primary care practice sites and 169 PCPs from June 15, 2011, to June 14, 2012. Participants included adults eligible for breast, cervical, and/or colorectal cancer screening. In practices randomized to the intervention group, PCPs reviewed real-time rosters of their patients overdue for screening and provided individualized contact (via a letter, practice delegate, or patient navigator) or deferred screening (temporarily or permanently). In practices randomized to the comparison group, overdue patients were automatically sent reminder letters and transferred to practice delegate lists for follow-up. Intervention patients without PCP action within 8 weeks defaulted to the automated control version. The primary outcome was adjusted average cancer screening completion rates over 1-year follow-up, accounting for clustering by physician or practice. Results: Baseline cancer screening rates (80.8% vs 80.3%) were similar among patients in the intervention (n = 51,071) and comparison group (n = 52,799). Most intervention providers used the IT application (88 of 101, 87%) and users reviewed 7984 patients overdue for at least 1 cancer screening (73% sent reminder letter, 6% referred directly to a practice delegate or patient navigator, and 21% deferred screening). In addition, 6128 letters were automatically sent to patients in the intervention group (total of 12,002 letters vs 16,378 letters in comparison practices; P < .001). Adjusted average cancer screening rates did not differ among intervention and comparison practices for all cancers combined (81.6% vs 81.4%; P = .84) nor breast (82.7% vs 82.7%; P = .96), cervical (84.1% vs 84.7%; P = .60), or colorectal cancer (77.8% vs 76.2%; P = .33). Conclusions: Involving PCPs in a visit-independent population management IT application resulted in similar cancer screening rates compared with an automated reminder system, but fewer patients were sent reminder letters. This suggests that PCPs were able to identify and exclude from contact patients who would have received automated reminder letters but not undergone screening.
    The Journal of the American Board of Family Medicine 07/2014; 27(4):474-85. DOI:10.3122/jabfm.2014.04.130319 · 1.98 Impact Factor
  • S. A. Berkowitz · S. J. Atlas · R. W. Grant · D. J. Wexler ·
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    ABSTRACT: AimsTo develop glycaemic goal individualization algorithms and assess potential impact on a healthcare system and different segments of the population with diabetes. MethodsA cross-sectional observational study of patients with diabetes in a primary care network age > 18 years with an HbA1c measured between 1 January and 31 December 2011. We applied diabetes guidelines to create targeted algorithms 1 and 2, which assigned HbA1c goals based on age, duration of diabetes (< 15 years or < 10 years), diabetes complications and Charlson co-morbidity score (< 6 or < 4) [targeted algorithm 2 was designed to assign more patients a goal < 64 mmol/mol (8.0%) than targeted algorithm 1]. Each patient's HbA1c was compared with these targeted goals and to the ‘standard’ goal < 53 mmol/mol (7.0%). Agreement was tested using McNemar's test. ResultsOverall, 55.7% of 12 199 patients would be considered controlled under the ‘standard’ approach, 61.2% under targeted algorithm 1 and 67.5% under targeted algorithm 2. Targeted algorithm 1 reclassified 1213 (23.6%) patients considered uncontrolled under the standard approach to controlled, P < 0.001. Targeted algorithm 2 reclassified 1844 (35.2%) patients, P < 0.001. Compared with those controlled under the standard goal, there was no significant difference in the proportion of those controlled using targeted goals who had Medicaid, had less than a high school diploma or received primary care in a federally qualified health centre. Conclusions Two automated targeted algorithms would reclassify one quarter to one third of patients from uncontrolled to controlled within a primary care network without differentially affecting vulnerable patient subgroups.This article is protected by copyright. All rights reserved.
    Diabetic Medicine 03/2014; 31(7). DOI:10.1111/dme.12427 · 3.12 Impact Factor
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    ABSTRACT: Objective To optimize a new visit-independent, population-based cancer screening system (TopCare) by using Operations Research techniques to simulate: (1) changes in patient outreach staffing levels (delegates, navigators), (2) modifications to user workflow within the IT system, and (3) changes in cancer screening recommendations. Materials and Methods TopCare was modeled as a multi-server, multi-phase queueing system. Simulation experiments implemented the queueing network model following a next-event time-advance mechanism, where systematic adjustments were made to staffing levels, IT workflow settings, and cancer screening frequency in order to assess their impact on overdue screenings per patient. Results TopCare reduced the average number of overdue screenings per patient from 1.17 at inception to 0.86 during simulation to 0.23 at steady state. Increases in workforce improved the effectiveness of TopCare. Specifically, increasing delegate or navigator staff level by one person improved screening completion rates by 1.3% or 12.2%, respectively. In contrast, changes in the amount of time a patient entry stays on delegate and navigator lists had little impact on overdue screenings. Finally, lengthening the screening interval increased efficiency within TopCare by decreasing overdue screenings at the patient level, resulting in a smaller number of overdue patients needing delegates for screening and a higher fraction of screenings completed by delegates. Conclusions Simulating the impact of changes in staffing, system parameters, and clinical inputs on the effectiveness and efficiency of care can inform the allocation of limited resources in population management.
    Journal of the American Medical Informatics Association 02/2014; 21:e129-e135. DOI:10.1136/amiajnl-2013- · 3.50 Impact Factor
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    ABSTRACT: To determine whether frequent emergency department (ED) users are more likely to make at least one and a majority of visits for mental health, alcohol, or drug-related complaints compared to non-frequent users. We performed a retrospective cohort study exploring frequent ED use and ED diagnosis at a single, academic hospital and included all ED patients between January 1 and December 31, 2010. We compared differences in ED visits with a primary International Classification of Diseases, 9th Revision visit diagnosis of mental health, alcohol or drug-related diagnoses between non-frequent users (<4 visits during previous 12-months) and frequent (repeat [4-7 visits], highly frequent [8-18 visits] and super frequent [≥19 visits]) users in univariate and multivariable analyses. Frequent users (2496/65201 [3.8%] patients) were more likely to make at least one visit associated with mental health, alcohol, or drug-related diagnoses. The proportion of patients with a majority of visits related to any of the three diagnoses increased from 5.8% among non-frequent users (3616/62705) to 9.4% among repeat users (181/1926), 13.1% among highly frequent users (62/473), and 25.8% (25/97 patients) in super frequent users. An increasing proportion of visits with alcohol-related diagnoses was observed among repeat, highly frequent, and super frequent users but was not found for mental health or drug-related complaints. Frequent ED users were more likely to make a mental health, alcohol or drug-related visit, but a majority of visits were only noted for those with alcohol-related diagnoses. To address frequent ED use, interventions focusing on managing patients with frequent alcohol-related visits may be necessary.
    The American journal of emergency medicine 09/2013; 31(10). DOI:10.1016/j.ajem.2013.08.006 · 1.27 Impact Factor
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    ABSTRACT: BACKGROUND: Patient navigator (PN) programs can improve breast cancer screening in low income, ethnic/racial minorities. Refugee women have low breast cancer screening rates, but it has not been shown that PN is similarly effective. OBJECTIVE: Evaluate whether a PN program for refugee women decreases disparities in breast cancer screening. DESIGN: Retrospective program evaluation of an implemented intervention. PARTICIPANTS: Women who self-identified as speaking Somali, Arabic, or Serbo-Croatian (Bosnian) and were eligible for breast cancer screening at an urban community health center (HC). Comparison groups were English-speaking and Spanish-speaking women eligible for breast cancer screening in the same HC. INTERVENTION: Patient navigators educated women about breast cancer screening, explored barriers to screening, and tailored interventions individually to help complete screening. MAIN MEASURES: Adjusted 2-year mammography rates from logistic regression models for each calendar year accounting for clustering by primary care physician. Rates in refugee women were compared to English-speaking and Spanish-speaking women in the year before implementation of the PN program and over its first 3 years. RESULTS: There were 188 refugee (36 Somali, 48 Arabic, 104 Serbo-Croatian speaking), 2,072 English-speaking, and 2,014 Spanish-speaking women eligible for breast cancer screening over the 4-year study period. In the year prior to implementation of the program, adjusted mammography rates were lower among refugee women (64.1 %, 95 % CI: 49-77 %) compared to English-speaking (76.5 %, 95 % CI: 69 %-83 %) and Spanish-speaking (85.2 %, 95 % CI: 79 %-90 %) women. By the end of 2011, screening rates increased in refugee women (81.2 %, 95 % CI: 72 %-88 %), and were similar to the rates in English-speaking (80.0 %, 95 % CI: 73 %-86 %) and Spanish-speaking (87.6 %, 95 % CI: 82 %-91 %) women. PN increased screening rates in both younger and older refugee women. CONCLUSION: Linguistically and culturally tailored PN decreased disparities over time in breast cancer screening among female refugees from Somalia, the Middle East and Bosnia.
    Journal of General Internal Medicine 05/2013; 28(11). DOI:10.1007/s11606-013-2491-4 · 3.42 Impact Factor
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    ABSTRACT: Objectives: To assess the ability of a health information technology system to facilitate population- based breast cancer screening. Study Design: Cohort study with 2-year follow-up after a 1-year cluster randomized trial. Methods: Study population was women 42 to 69 years old receiving care within a 12-practice primary care network. The management informatics system (1) identified women overdue for mammograms, (2) connected them to primary care providers using a web-based tool, (3) created automatically generated outreach letters for patients specified by providers, (4) monitored for subsequent mammography scheduling and completion, and (5) provided practice delegates with a list of women remaining unscreened for reminder phone calls. Eligible women overdue for a mammogram during a 1-year study period included those overdue at study start (prevalent cohort) and those who became overdue during follow-up (incident cohort). The main outcome measure was mammography completion rates over 3 years. Results: Among 32,688 eligible women, 9795 (30%) were overdue for screening (4487 intervention, 5308 control). Intervention patients were somewhat younger, more likely to be non-Hispanic white, and more likely to have health insurance compared with control patients. Adjusted completion rates in the prevalent cohort (n = 6697) were significantly higher among intervention patients after 3 years (51.7% vs 45.8%; P = .002). For patients in the incident cohort (n = 3098), adjusted completion rates after 2 years were 53.8% versus 48.7%, respectively (P = .052). Conclusions: Population-based informatics systems can enable sustained increases in mammography screening rates beyond rates seen with office-based visit reminders.
    The American journal of managed care 12/2012; 18(12):821-9. · 2.26 Impact Factor

  • Annals of Emergency Medicine 10/2012; 60(4):S155. DOI:10.1016/j.annemergmed.2012.06.472 · 4.68 Impact Factor

  • Archives of internal medicine 05/2012; 172(10):821-3. DOI:10.1001/archinternmed.2012.1229 · 17.33 Impact Factor
  • Richard W. Grant · Clemens S. Hong · Steven J. Atlas ·

    Annals of internal medicine 04/2012; 156(8):607-607. DOI:10.1059/0003-4819-156-8-201204170-00015 · 17.81 Impact Factor

Publication Stats

4k Citations
418.96 Total Impact Points


  • 1994-2015
    • Massachusetts General Hospital
      • • Department of Medicine
      • • Massachusetts General Hospital Imaging
      Boston, Massachusetts, United States
  • 1996-2014
    • Harvard University
      Cambridge, Massachusetts, United States
  • 1996-2011
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2005
    • National Institutes of Health
      베서스다, Maryland, United States
  • 2004
    • Brigham and Women's Hospital
      Boston, Massachusetts, United States