Search

Background With the advent of modern endoscopes and a better anatomic understanding of the skull base, the indications of endonasal approaches are increasing. These procedures may be complicated by high rates of postoperative cerebrospinal fluid (CSF) leak, and reconstruction of the defect remains challenging. In the anterior skull base, vascularized grafts have been reported as superior in preventing CSF leakage and infection. The Hadad-Bassagasteguy flap, being a pedicled flap, is our first line flap to reconstruct the skull base. When we were not successful with this flap, we resorted to different flaps. Objective We modified the originally described temporoparietal fascial flap by Fortes et al and applied clinically. The objective of this paper is to briefly describe the modification of the flap and to review the clinical outcome. Methods From 2014 to 2018, in 6 cases of CSF leak with the appropriate indication, we used the temporoparietal myofascial flap repair that is a modification of the temporoparietal fascial flap by Fortes et al. We took all the 6 patients in our study and followed them up. Results All of the 6 repairs were successful, and no CSF leak was found just after the operation in 6- to 48-month follow-up. Conclusion We recommend our modified novel temporoparietal myofascial flap as a very good option in case of failed cases of postoperative CSF leak.

Background and aim Medically managed opioid withdrawal (detox) can increase the risk of subsequent opioid overdose. We assessed the association between mortality following detox and receipt of medications for opioid use disorder (MOUD) and residential treatment after detox. Design Cohort study generated from individually linked public health data sets. Setting Massachusetts, USA. Participants A total of 30 681 opioid detox patients with 61 819 detox episodes between 2012 and 2014. Measurements Treatment categories included no post-detox treatment, MOUD, residential treatment or both MOUD and residential treatment identified at monthly intervals. We classified treatment exposures in two ways: (a) 'on-treatment' included any month where a treatment was received and (b) 'with-discontinuation' individuals were considered exposed through the month following treatment discontinuation. We conducted multivariable Cox proportional hazards analyses and extended Kaplan-Meier estimator cumulative incidence for all-cause and opioid-related mortality for the treatment categories as monthly time-varying exposure variables. Findings Twelve months after detox, 41% received MOUD for a median of 3 months, 35% received residential treatment for a median of 2 months and 13% received both for a median of 5 months. In on-treatment analyses for all-cause mortality compared with no treatment, adjusted hazard ratios (AHR) were 0.34 [95% confidence interval (CI) = 0.27-0.43] for MOUD, 0.63 (95% CI = 0.47-0.84) for residential treatment and 0.11 (95% CI = 0.03-0.43) for both. In with-discontinuation analyses for all-cause mortality, compared with no treatment, AHRs were 0.52 (95% CI = 0.42-0.63) for MOUD, 0.76 (95% CI = 0.59-0.96) for residential treatment and 0.21 (95% CI = 0.08-0.55) for both. Results were similar for opioid-related overdose mortality. Conclusions Among people who have undergone medically managed opioid withdrawal, receipt of medications for opioid use disorder, residential treatment or the combination of medications for opioid use disorder and residential treatment were associated with substantially reduced mortality compared with no treatment.

Objectives. To estimate the annual prevalence of opioid use disorder (OUD) in Massachusetts from 2011 to 2015. Methods. We performed a multisample stratified capture–recapture analysis to estimate OUD prevalence in Massachusetts. Individuals identified from 6 administrative databases for 2011 to 2012 and 7 databases for 2013 to 2015 were linked at the individual level and included in the analysis. Individuals were stratified by age group, sex, and county of residence. Results. The OUD prevalence in Massachusetts among people aged 11 years or older was 2.72% in 2011 and 2.87% in 2012. Between 2013 and 2015, the prevalence increased from 3.87% to 4.60%. The greatest increase in prevalence was observed among those in the youngest age group (11–25 years), a 76% increase from 2011 to 2012 and a 42% increase from 2013 to 2015. Conclusions. In Massachusetts, the OUD prevalence was 4.6% among people 11 years or older in 2015. The number of individuals with OUD is likely increasing, particularly among young people.

Background Recent studies have demonstrated the effectiveness of family-centered, pediatric weight management programs in reducing childhood obesity. Yet, programs to optimize the care of low-income children with obesity are needed. We sought to examine the comparative effectiveness of two, potentially scalable pediatric weight management programs delivered to low-income children in a clinical or community setting. Materials and methods The Clinic and Community Approaches to Healthy Weight Trial is a randomized trial in two communities in Massachusetts that serve a large population of low-income children and families. The two-arm trial compares the effects of a pediatric weight management program delivered in the Healthy Weight Clinics of two federally qualified health centers (FQHC) to the Healthy Weight and Your Child programs delivered in two YMCAs. Eligible children are 6 to 12 years old with a body mass index (BMI) ≥ 85th percentile seen in primary care at the two FQHCs. Both programs are one-year in duration and have at least 30 contact hours throughout the year. Measures are collected at baseline, 6 months, and 1 year. The main outcome is 1-year change in BMI (kg/m2) and percent change of the 95th percentile (%BMIp95). Conclusion The Clinic and Community Approaches to Healthy Weight Trial seeks to 1) examine the comparative effects of a clinical and community based intervention in improving childhood obesity, and 2) inform the care of >7 million children with obesity covered by the Children's Health Insurance Program or Medicaid.

Introduction Massachusetts developed and used bidirectional electronic referrals to connect clinical patients across the state to interventions run by community organizations. The objective of our study was to determine whether the use of Massachusetts's electronic referral system (MA e-Referral) reached racial/ethnic groups experiencing health disparities and whether it was associated with improved health outcomes. Methods We assembled encounter-level medical records from September 2013 through June 2017 for patients at Massachusetts clinics funded by the Clinical Community Partnerships for Prevention into 2 cohorts. First, all patients meeting program eligibility guidelines for an e-Referral (N = 21,701) were examined to assess the distribution of e-Referrals among populations facing health disparities; second, a subset of 3,817 people with hypertension were analyzed to detect changes in blood pressure after e-Referral to an evidence-based community intervention. Results Non-Hispanic black (OR, 1.4; 95% confidence interval [CI], 1.2-1.6) and Hispanic patients (OR, 1.3; 95% CI, 1.1-1.4) had higher odds than non-Hispanic white patients of being referred electronically. Patients completing their hypertension intervention had 74% (95% CI, 1.2-2.5) higher odds of having an in-control blood pressure reading than patients who were not electronically referred. Conclusion Clinical to community linkage to interventions through MA e-Referral reached non-Hispanic black, Hispanic, and Spanish-speaking populations and was associated with improved blood pressure control.

Background Medical care, public health, and criminal justice systems encounters could serve as touchpoints to identify and intervene with individuals at high-risk of opioid overdose death. The relative risk of opioid overdose death and proportion of deaths that could be averted at such touchpoints are unknown. Methods We used 8 individually linked data sets from Massachusetts government agencies to perform a retrospective cohort study of Massachusetts residents ages 11 and older. For each month in 2014, we identified past 12-month exposure to 4 opioid prescription touchpoints (high dosage, benzodiazepine co-prescribing, multiple prescribers, or multiple pharmacies) and 4 critical encounter touchpoints (opioid detoxification, nonfatal opioid overdose, injection-related infection, and release from incarceration). The outcome was opioid overdose death. We calculated Standardized Mortality Ratios (SMRs) and Population Attributable Fractions (PAFs) associated with touchpoint exposure. Results The cohort consisted of 6,717,390 person-years of follow-up with 1315 opioid overdose deaths. We identified past 12-month exposure to any touchpoint in 2.7% of person-months and for 51.8% of opioid overdose deaths. Opioid overdose SMRs were 12.6 (95% CI: 11.1, 14.1) for opioid prescription and 68.4 (95% CI: 62.4, 74.5) for critical encounter touchpoints. Fatal opioid overdose PAFs were 0.19 (95% CI: 0.17, 0.21) for opioid prescription and 0.37 (95% CI: 0.34, 0.39) for critical encounter touchpoints. Conclusions Using public health data, we found eight candidate touchpoints were associated with increased risk of fatal opioid overdose, and collectively identified more than half of opioid overdose decedents. These touchpoints are potential targets for development of overdose prevention interventions.

The aim of this study was to evaluate whether veterans in Massachusetts receiving opioids and/or benzodiazepines from both Veterans Health Administration (VHA) and non-VHA pharmacies are at higher risk of adverse events compared with those receiving opioids at VHA pharmacies only.A cohort study of veterans who filled a prescription for any Schedule II through V substance at a Massachusetts VHA pharmacy. Prescriptions were recorded in the Massachusetts Department of Public Health Chapter 55 data set.The study sample included 16,866 veterans residing in Massachusetts, of whom 9238 (54.8%) received controlled substances from VHA pharmacies only and 7628 (45.2%) had filled prescriptions at both VHA and non-VHA pharmacies ("dual care users") between October 1, 2013, and December 31, 2015. Our primary outcomes were nonfatal opioid overdose, fatal opioid overdose, and all-cause mortality.Compared with VHA-only users, more dual care users resided in rural areas (12.6% vs 10.6%), received high-dose opioid therapy (26.3% vs 7.3%), had concurrent prescriptions of opioids and benzodiazepines (34.8% vs 8.2%), and had opioid use disorder (6.8% vs 1.6%) (P.0001 for all). In adjusted models, dual care users had higher odds of nonfatal opioid overdose (odds ratio [OR], 1.29; 95% CI, 0.98-1.71) and all-cause mortality (OR, 1.66; 95% CI, 1.43-1.93) compared with VHA-only users. Dual care use was not associated with fatal opioid overdoses.Among veterans in Massachusetts, receipt of opioids from multiple sources was associated with worse outcomes, specifically nonfatal opioid overdose and mortality. Better information sharing between VHA and non-VHA pharmacies and prescribers has the potential to improve patient safety.

Homelessness is poorly captured in most administrative data sets making it difficult to understand how, when, and where this population can be better served. This study sought to develop and validate a classification model of homelessness. Our sample included 5,050,639 individuals aged 11 years and older who were included in a linked dataset of administrative records from multiple state-maintained databases in Massachusetts for the period from 2011–2015. We used logistic regression to develop a classification model with 94 predictors and subsequently tested its performance. The model had high specificity (95.4%), moderate sensitivity (77.8%) for predicting known cases of homelessness, and excellent classification properties (area under the receiver operating curve 0.94; balanced accuracy 86.4%). To demonstrate the potential opportunity that exists for using such a modeling approach to target interventions to mitigate the risk of an adverse health outcome, we also estimated the association between model predicted homeless status and fatal opioid overdoses, finding that model predicted homeless status was associated with a nearly 23-fold increase in the risk of fatal opioid overdose. This study provides a novel approach for identifying homelessness using integrated administrative data. The strong performance of our model underscores the potential value of linking data from multiple service systems to improve the identification of housing instability and to assist government in developing programs that seek to improve health and other outcomes for homeless individuals.

BACKGROUND/OBJECTIVES: Potentially inappropriate opioid prescribing (PIP) may contribute to risk for fatal opioid overdose among older adults (age 50+). Our objective was to examine the effect of age on the likelihood of PIP exposure, as well as the effect of PIP exposure on adverse outcomes. DESIGN: Retrospective cohort study SETTING: Data from multiple state agencies in Massachusetts, 2011–2015 PARTICIPANTS: Over 3 million adult Massachusetts residents (3,078,163) who received at least one prescription opioid during the study period; approximately half (1,589,365) were older adults (age 50+). MEASUREMENTS: We measured exposure to five types of PIP: high-dose opioids, co-prescription with benzodiazepines, multiple opioid prescribers, multiple opioid pharmacies, and continuous opioid therapy without a pain diagnosis. We examined three adverse outcomes: non-fatal opioid overdose, fatal opioid overdose, and all-cause mortality. RESULTS: The rate of any PIP exposure increased with age, ranging from 2% among individuals age 18–29 to 14% among those age 50 and older. Older adults also had elevated rates of exposure to two or more different types of PIP, including 5% of adults age 50–69 and 4% of adults age 70 or older, in comparison to 2.5% of age 40–49 and lower percentages in younger age groups. Among covariates assessed, increasing age was the greatest positive predictor of PIP exposure. In analyses stratified by age, exposure to both any PIP and specific types of PIP were associated with non-fatal overdose, fatal overdose, and all-cause mortality among both younger and older adults. CONCLUSION: Older adults are more likely to be exposed to PIP, which elevates their risk for adverse events. Strategies to reduce exposure to PIP, and to improve outcomes among those already exposed, will be instrumental to addressing the opioid crisis as it manifests among older adults.

BACKGROUND: Opioid-related overdoses and deaths among adolescents in the United States continue to increase, but little is known about adolescents who experience opioid-related non-fatal overdose (NFOD). Our objective was to describe (1) the characteristics of adolescents aged 11-17 who experienced NFOD and (2) their receipt of medications for opioid use disorder (MOUD) in the 12 months following NFOD, compared with adults. METHODS: We created a retrospective cohort using six Massachusetts state agency datasets linked at the individual level, with information on 98% of state residents. Individuals entered the cohort if they experienced NFOD between January 1, 2012 and December 31, 2014. We compared adolescents to adults experiencing NFOD, examining individual characteristics and receipt of medications for opioid use disorder (MOUD)—methadone, buprenorphine, or naltrexone. RESULTS: Among 22,506 individuals who experienced NFOD during the study period, 195 (0.9%) were aged 11-17. Fifty-two percent (102/195) of adolescents were female, whereas only 38% of adults were female (P

INTRODUCTION: Opioid overdose deaths quintupled in Massachusetts between 2000 and 2016. Potentially inappropriate opioid prescribing practices (PIP) are associated with increases in overdoses. The purpose of this study was to conduct spatial epidemiological analyses of novel comprehensively linked data to identify overdose and PIP hotspots. METHODS: Sixteen administrative datasets, including prescription monitoring, medical claims, vital statistics, and medical examiner data, covering >98% of Massachusetts residents between 2011–2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: ≥100 morphine milligram equivalents (MMEs), co-prescription of benzodiazepines and opioids, cash purchases of opioid prescriptions, opioid prescriptions without a recorded pain diagnosis, and opioid prescriptions through multiple prescribers or pharmacies. Using spatial autocorrelation and cluster analyses, overdose and PIP hotspots were identified among 538 ZIP codes. RESULTS: More than half of the adult population (n=3,143,817, ages 18 and older) were prescribed opioids. Nearly all ZIP codes showed increasing rates of overdose over time. Overdose clusters were identified in Worcester, Northampton, Lee/Tyringham, Wareham/Bourne, Lynn, and Revere/Chelsea (Getis-Ord Gi*; p< 0.05). Large PIP clusters for ≥100 MMEs and prescription without pain diagnosis were identified in Western Massachusetts; and smaller clusters for multiple prescribers in Nantucket, Berkshire, and Hampden Counties (p

BACKGROUND: Potentially inappropriate prescribing (PIP) may contribute to opioid overdose. OBJECTIVE: To examine the association between PIP and adverse events. DESIGN: Cohort study. PARTICIPANTS: Three million seventy-eight thousand thirty-four individuals age ≥ 18, without disseminated cancer, who received prescription opioids between 2011 and 2015. MAIN MEASURES: We defined PIP as (a) morphine equivalent dose ≥ 100 mg/day in ≥ 3 months; (b) overlapping opioid and benzodiazepine prescriptions in ≥ 3 months; (c) ≥ 4 opioid prescribers in any quarter; (d) ≥ 4 opioid-dispensing pharmacies in any quarter; (e) cash purchase of prescription opioids on ≥ 3 occasions; and (f) receipt of opioids in 3 consecutive months without a documented pain diagnosis. We used Cox proportional hazards models to identify PIP practices associated with non-fatal opioid overdose, fatal opioid overdose, and all-cause mortality, controlling for covariates. KEY RESULTS: All six types of PIP were associated with higher adjusted hazard for all-cause mortality, four of six with non-fatal overdose, and five of six with fatal overdose. Lacking a documented pain diagnosis was associated with non-fatal overdose (adjusted hazard ratio [AHR] 2.21, 95% confidence interval [CI] 2.02–2.41), as was high-dose opioids (AHR 1.68, 95% CI 1.59–1.76). Co-prescription of benzodiazepines was associated with fatal overdose (AHR 4.23, 95% CI 3.85–4.65). High-dose opioids were associated with all-cause mortality (AHR 2.18, 95% CI 2.14–2.23), as was lacking a documented pain diagnosis (AHR 2.05, 95% CI 2.01–2.09). Compared to those who received opioids without PIP, the hazard for fatal opioid overdose with one, two, three, and ≥ four PIP subtypes were 4.24, 7.05, 10.28, and 12.99 (test of linear trend, p

Objectives. We evaluated the overall and sociodemographic disparities in trends in prevalence of childhood overweight and obesity in Massachusetts public school districts between 2009 and 2014. Methods. In 2009, Massachusetts mandated annual screening of body mass index for students in grades 1, 4, 7, and 10. This was part of the statewide Mass in Motion prevention programs. We assessed trends in the prevalence of overweight and obesity between 2009 and 2014 by district, gender, grade, and district income. Results. From 2009 to 2014, prevalence decreased 3.0 percentage points (from 34.3% to 31.3%) statewide. The 2014 district-level rates ranged from 13.9% to 54.5% (median = 31.2%). When stratified by grade, the decreasing trends were significant only for grades 1 and 4. Although rates of districts with a median household income greater than $37 000 improved notably, rates of the poorest remain unchanged and were approximately 40%. Conclusions. Although overall prevalence began to decrease, the geographic and socioeconomic disparities in childhood obesity are widening and remain a public health challenge in Massachusetts. Special efforts should be made to address the needs of socioeconomically disadvantaged districts and to narrow the disparities in childhood obesity.

Although American children snack more than ever before, the parental role in promoting snacking is not well understood. In 2012–2013 at baseline in an intervention study to prevent childhood obesity in low-income Massachusetts communities, n = 271 parents of children aged 2–12 years completed surveys regarding nutritive and non-nutritive reasons they offered children snacks, demographics, and dietary factors. An analysis of variance demonstrated that parents reported offering snacks (mean/week, standard deviation (SD)) for nutritive reasons like promoting growth (x̄ = 2.5, SD 2.2) or satisfying hunger (x̄ = 2.4, SD 2.1) almost twice as often as non-nutritive reasons like keeping a child quiet (x̄ = 0.7, SD 1.5) or celebrating events/holidays (x̄ = 0.8, SD 1.1). Parents reported giving young children (2–5 years) more snacks to reward behavior (1.9 vs. 1.1, p &lt, 0.001), keep quiet (1.0 vs. 0.5, p &lt, 0.001), and celebrate achievements (1.7 vs. 1.0, p &lt, 0.001) than parents of older children (6–12 years). Multivariable logistic regression models were used to obtain adjusted odds ratios, which indicated reduced child adherence to dietary recommendations when parents offered snacks to reward behavior (Odds Ratio (OR) = 0.83, 95% Confidence Interval (CI) 0.70–0.99), celebrate events/holidays (OR = 0.72, 95% CI 0.52–0.99), or achievements (OR = 0.82, 95% CI 0.68–0.98). Parental intentions around child snacking are likely important targets for obesity prevention efforts.

ObjectiveThis study examines the extent to which insufficient sleep is associated with diet quality in students taking part in the Massachusetts Childhood Obesity Research Demonstration Project.MethodsData were collected in Fall 2012 for all 4th and 7th grade children enrolled in public schools in two Massachusetts communities. During annual body mass index (BMI) screening, students completed a survey that assessed diet, physical activity, screen time, and sleep. Of the 2456 enrolled students, 1870 (76%) had complete survey data. Generalized estimating equations were used to examine associations between sleep duration and dietary outcomes (vegetables, fruits, 100% juice, juice drinks, soda, sugar-sweetened beverages and water), accounting for clustering by school. Models were adjusted for community, grade, race/ethnicity, gender, television in the bedroom, screen time, and physical activity.ResultsIn adjusted models, students who reported sleeping < 10 hours/day consumed soda more frequently (β = 0.11, 95% CI: 0.03, 0.20) and vegetables less frequently (β = -0.09, 95% CI: -0.18, -0.01) compared with students who reported ≥ 10 hours/day. No significant associations were observed between sleep duration and fruits, 100% juice, juice drinks or water.ConclusionsIn this population, insufficient sleep duration was associated with more frequent soda and less frequent vegetable consumption. Longitudinal research is needed to further examine these relationships.

BACKGROUND AND OBJECTIVE: Associations of inadequate sleep with numerous health outcomes among youth necessitate identifying its modifiable determinants. Television (TV) has been associated with sleep curtailment, but little is known about small screens (eg, smartphones), which can be used in bed and emit notifications. Therefore, we examined associations of different screens in sleep environments with sleep duration and perceived insufficient rest or sleep. METHODS: Participants included 2048 fourth- and seventh-graders participating in the Massachusetts Childhood Obesity Research Demonstration Study in 2012 to 2013. Using linear and log binomial regression, we examined cross-sectional associations of small screens and TVs in sleep environments and screen time with weekday sleep duration and perceived insufficient rest or sleep in the past week. RESULTS: Children who slept near a small screen (compared with never) reported 20.6 fewer minutes of sleep (95% confidence interval [CI], −29.7 to −11.4) and had a higher prevalence of perceived insufficient rest or sleep (prevalence ratio, 1.39; 95% CI, 1.21 to 1.60). Children who slept in a room with a TV (compared with no TV) reported 18.0 fewer minutes of sleep (95% CI, −27.9 to −8.1). TV or DVD viewing and video or computer game playing were associated with both sleep outcomes (P < .01). Some associations were stronger among Hispanic, non-Hispanic black, and older children (P < .05 for heterogeneity). CONCLUSIONS: Sleeping near a small screen, sleeping with a TV in the room, and more screen time were associated with shorter sleep durations. Presence of a small screen, but not a TV, in the sleep environment and screen time were associated with perceived insufficient rest or sleep. These findings caution against unrestricted screen access in children’s bedrooms.

Author(s): Blaine, Rachel E; Franckle, Rebecca L; Ganter, Claudia; Falbe, Jennifer; Giles, Catherine; Criss, Shaniece; Kwass, Jo-Ann; Land, Thomas; Gortmaker, Steven L; Chuang, Emmeline; Davison, Kirsten K; MA-CORD Project Group | Abstract: IntroductionAlthough evidence-based interventions to prevent childhood obesity in school settings exist, few studies have identified factors that enhance school districts' capacity to undertake such efforts. We describe the implementation of a school-based intervention using classroom lessons based on existing "Eat Well and Keep Moving" and "Planet Health" behavior change interventions and schoolwide activities to target 5,144 children in 4th through 7th grade in 2 low-income school districts.MethodsThe intervention was part of the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project, a multisector community-based intervention implemented from 2012 through 2014. Using mixed methods, we operationalized key implementation outcomes, including acceptability, adoption, appropriateness, feasibility, implementation fidelity, perceived implementation cost, reach, and sustainability.ResultsMA-CORD was adopted in 2 school districts that were facing resource limitations and competing priorities. Although strong leadership support existed in both communities at baseline, one district's staff reported less schoolwide readiness and commitment. Consequently, fewer teachers reported engaging in training, teaching lessons, or planning to sustain the lessons after MA-CORD. Interviews showed that principal and superintendent turnover, statewide testing, and teacher burnout limited implementation; passionate wellness champions in schools appeared to offset implementation barriers.ConclusionFuture interventions should assess adoption readiness at both leadership and staff levels, offer curriculum training sessions during school hours, use school nurses or health teachers as wellness champions to support teachers, and offer incentives such as staff stipends or play equipment to encourage school participation and sustained intervention activities.

Objective To examine the extent to which a clinical intervention resulted in reduced body mass index (BMI) z-scores among 2–12 year old children compared to routine practice (treatment as usual, TAU). Methods The Massachusetts Childhood Obesity Research Demonstration project (MA-CORD) is a multifaceted initiative to prevent childhood obesity among low-income children. In the federally qualified community health centers (FQHC) of two communities (Intervention Site #1 and #2), we implemented (1) pediatric weight management training; (2) electronic decision supports for clinicians; (3) on-site Healthy Weight Clinics; (4) community health worker integration; and (5) healthful clinical environment changes. One FQHC in a demographically-matched community served as the TAU site. Using electronic health records, we assessed BMI z-scores and used linear mixed models to examine BMI z-score change over 2 years in each intervention site compared to a TAU site. Results Compared to children in the TAU site (n=2286), children in Intervention site #2 (n=1368) had a significant decline in BMI z-scores following the start of the intervention (−0.16 units/year; 95% CI: −0.21, −0.12). We found no evidence of an effect in Intervention site #1 (n=111). Conclusions The MA-CORD clinical interventions were associated with modest improvement in BMI z-scores in one of two intervention communities compared to a TAU community.

Objectives. We used electronic health record (EHR) data to determine rates and patient characteristics in offering cessation interventions (counseling, medications, or referral) and initiating quit attempts. Methods. Ten community health centers in New York City contributed 30 months of de-identified patient data from their EHRs. Results. Of 302 940 patients, 40% had smoking status recorded and only 34% of documented current smokers received an intervention. Women and younger patients were less likely to have their smoking status documented or to receive an intervention. Patients with comorbidities that are exacerbated by smoking were more likely to have status documented (82.2%) and to receive an intervention (52.1%), especially medication (10.8%). Medication, either alone (odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.5, 2.3) or combined with counseling (OR = 1.8; 95% CI = 1.5, 2.3), was associated with higher quit attempts compared with no intervention. Conclusions. Data from EHRs demonstrated underdocumentation of smoking status and missed opportunities for cessation interventions. Use of data from EHRs can facilitate quality improvement efforts to increase screening and intervention delivery, with the potential to improve smoking cessation rates.

Introduction The etiology of childhood obesity is multidimensional and includes individual, familial, organizational, and societal factors. Policymakers and researchers are promoting social–ecological approaches to obesity prevention that encompass multiple community sectors. Programs that successfully engage low-income families in making healthy choices are greatly needed, yet little is known about the extent to which stakeholders understand the complexity of barriers encountered by families. The objective of this study was to contextually frame barriers faced by low-income families reported by community stakeholders by using the Family Ecological Model (FEM). Methods From 2012 through 2013, we conducted semistructured interviews with 39 stakeholders from 2 communities in Massachusetts that were participating in a multisector intervention for childhood obesity prevention. Stakeholders represented schools; afterschool programs; health care; the Special Supplemental Nutrition Program for Women, Infants, and Children; and early care and education. Interviews were audio-recorded, transcribed, coded, and summarized. Results Stakeholder reports of the barriers experienced by low-income families had a strong degree of overlap with FEM and reflected awareness of the broader contextual factors (eg, availability of community resources, family culture, education) and social and emotional dynamics within families (eg, parent knowledge, social norms, distrust of health care providers, chronic life stressors) that could affect family adoption of healthy lifestyle behaviors. Furthermore, results illustrated a level of consistency in stakeholder awareness across multiple community sectors. Conclusion The congruity of stakeholder perspectives with those of low-income parents as summarized in FEM and across community sectors illustrates potential for synergizing the efforts necessary for multisector, multilevel community interventions for the prevention of childhood obesity.

Objectives. We examined electronic health records (EHRs) to assess the impact of systems change on tobacco use screening, treatment, and quit rates among low-income primary care patients in Louisiana. Methods. We examined EHR data on 79 777 patients with more than 1.2 million adult primary care encounters from January 1, 2009, through January 31, 2012, for evidence of systems change. We adapted a definition of “systems change” to evaluate a tobacco screening and treatment protocol used by medical staff during primary care visits at 7 sites in a public hospital system. Results. Six of 7 sites met the definition of systems change, with routine screening rates for tobacco use higher than 50%. Within the first year, a 99.7% screening rate was reached. Sites had a 9.5% relative decrease in prevalence over the study period. Patients were 1.03 times more likely to sustain quit with each additional intervention (95% confidence interval = 1.02, 1.04). Conclusions. EHRs can be used to demonstrate that routine clinical interventions with low-income primary care patients result in reductions in tobacco use and sustained quits.

Childhood obesity is highly prevalent, is associated with both short- and long-term adverse outcomes, disproportionately affects racial/ethnic minority and economically deprived children, and represents a major threat to public health. Among the most promising approaches for its prevention and management are multilevel, multisector strategies.The Massachusetts Childhood Obesity Research Demonstration (MA-CORD) Study was a comprehensive, systematic intervention to prevent and reduce childhood obesity among low-income children ages 2-12 years in two selected cities in Massachusetts. Building on the Obesity Chronic Care Model, MA-CORD expanded a state public health department community-level obesity prevention initiative that incorporated evidence-based interventions in primary healthcare, the Women, Infants, and Children program, early care and education, schools/afterschool programs, as well as community-wide programs to improve food, beverage, physical activity (PA), and messaging environments. The study used a combination of pre- and post-time series and quasi-experimental designs to examine the extent to which the intervention resulted in changes in BMI, individual-level lifestyle behaviors, satisfaction with healthcare services, and quality of life among children, as well as changes in health policies, programs, and environments in the two intervention cities, compared to a comparison city. The intervention period was 2 years.MA-CORD will determine the extent to which a multisetting, multilevel intervention that integrates activities in primary care with broader public health interventions in schools, early care and education, and the community at large can improve children's dietary and PA behaviors and ultimately reduce obesity in low-income children.

Background Recent evidence suggests that opening a grocery store in a food desert does not translate to better diet quality among community residents. Purpose This study evaluated the influence of proximity to a healthy food store on the effect of a dietary behavioral intervention on diet among obese adults randomized to either a high fiber or American Heart Association diet intervention. Methods Participants were recruited from Worcester County, Massachusetts, between June 2009 and January 2012. Dietary data were collected via 24-hour recalls at baseline and 3, 6, and 12 months post-intervention. Based on in-store inspection data, a store was considered as having adequate availability of healthy foods if it had at least one item available in each of 20 healthy food categories. Linear models evaluated maximum change in dietary outcomes in relation to road distance from residence to the nearest June healthy food store. The analysis was conducted in January to June 2014. Results On average, participants (N=204) were aged 52 years, BMI=34.9, and included 72% women and 89% non-Hispanic whites. Shorter distance to a healthy food store was associated with greater improvements in consumption of fiber (b=–1.07 g/day per mile, p p =0.03) with and without covariate adjustment. Conclusions The effectiveness of dietary interventions is significantly influenced by the presence of a supportive community nutrition environment. Considering the nationwide efforts on promotion of healthy eating, the value of improving community access to healthy foods should not be underestimated. Clinical Trial Registration Number: NCT00911885

Background The United States Public Health Service (USPHS) Guideline for Treating Tobacco Use and Dependence includes ten key recommendations regarding the identification and the treatment of tobacco users seen in all health care settings. To our knowledge, the impact of system-wide brief interventions with cigarette smokers on smoking prevalence and health care utilization has not been examined using patient population-based data. Methods and Findings Data on clinical interventions with cigarette smokers were examined for primary care office visits of 104,639 patients at 17 Harvard Vanguard Medical Associates (HVMA) sites. An operational definition of “systems change” was developed. It included thresholds for intervention frequency and sustainability. Twelve sites met the criteria. Five did not. Decreases in self-reported smoking prevalence were 40% greater at sites that achieved systems change (13.6% vs. 9.7%, p

Dural sinus malformation (DSM), a form of dural arteriovenous shunt (DAVS), is an extremely rare vascular anomaly seen less frequently than vein of Galen malformation. We report a case of DSM, detailing initial presentation and delayed complication of cerebellar haemorrhage due to venous stasis within the DSM leading to progressive thrombosis and venous outflow obstruction.

Background Research has shown that self-reports of smoking during pregnancy may underestimate true prevalence. However, little is known about which populations have higher rates of underreporting. Availability of more accurate measures of smoking during pregnancy could greatly enhance the usefulness of existing studies on the effects of maternal smoking offspring, especially in those populations where underreporting may lead to underestimation of the impact of smoking during pregnancy. Methods and Findings In this paper, we develop a statistical Monte Carlo model to estimate patterns of underreporting of smoking during pregnancy, and apply it to analyze the smoking self-report data from birth certificates in the state of Massachusetts. Our results illustrate non-uniform patterns of underreporting of smoking during pregnancy among different populations. Estimates of likely underreporting of smoking during pregnancy were highest among mothers who were college-educated, married, aged 30 years or older, employed full-time, and planning to breastfeed. The model's findings are validated and compared to an existing underreporting adjustment approach in the Maternal and Infant Smoking Study of East Boston (MISSEB). Conclusions The validation results show that when biological assays are not available, the Monte Carlo method proposed can provide a more accurate estimate of the smoking status during pregnancy than self-reports alone. Such methods hold promise for providing a better assessment of the impact of smoking during pregnancy.

Thomas Land and colleagues show that among Massachusetts Medicaid subscribers, use of a comprehensive tobacco cessation pharmacotherapy benefit was followed by a substantial decrease in claims for hospitalizations for acute myocardial infarction and acute coronary heart disease., Background Insurance coverage of tobacco cessation medications increases their use and reduces smoking prevalence in a population. However, uncertainty about the impact of this coverage on health care utilization and costs is a barrier to the broader adoption of this policy, especially by publicly funded state Medicaid insurance programs. Whether a publicly funded tobacco cessation benefit leads to decreased medical claims for tobacco-related diseases has not been studied. We examined the experience of Massachusetts, whose Medicaid program adopted comprehensive coverage of tobacco cessation medications in July 2006. Over 75,000 Medicaid subscribers used the benefit in the first 2.5 years. On the basis of earlier secondary survey work, it was estimated that smoking prevalence declined among subscribers by 10% during this period. Methods and Findings Using claims data, we compared the probability of hospitalization prior to use of the tobacco cessation pharmacotherapy benefit with the probability of hospitalization after benefit use among Massachusetts Medicaid beneficiaries, adjusting for demographics, comorbidities, seasonality, influenza cases, and the implementation of the statewide smoke-free air law using generalized estimating equations. Statistically significant annualized declines of 46% (95% confidence interval 2%–70%) and 49% (95% confidence interval 6%–72%) were observed in hospital admissions for acute myocardial infarction and other acute coronary heart disease diagnoses, respectively. There were no significant decreases in hospitalizations rates for respiratory diagnoses or seven other diagnostic groups evaluated. Conclusions Among Massachusetts Medicaid subscribers, use of a comprehensive tobacco cessation pharmacotherapy benefit was associated with a significant decrease in claims for hospitalizations for acute myocardial infarction and acute coronary heart disease, but no significant change in hospital claims for other diagnoses. For low-income smokers, removing the barriers to the use of smoking cessation pharmacotherapy has the potential to decrease short-term utilization of hospital services. Please see later in the article for the Editors' Summary, Editors' Summary Background Smoking is the leading preventable cause of death in the world. Globally, it is responsible for one in ten deaths among adults. In developed countries, the death toll is even higher—in the USA and the UK, for example, one in five deaths are caused by cigarette smoking. In the USA alone, where a fifth of adults smoke, smoking accounts for more than 400,000 deaths every year; globally, smoking causes 5 million deaths per year. On average, smokers die 14 years earlier than nonsmokers, and half of all long-term smokers will die prematurely because of a smoking-related disease. These diseases include lung cancer, other types of cancer, heart disease, stroke, and lung diseases such as chronic airway obstruction, bronchitis, and emphysema. And, for every smoker who dies from one of these smoking-related diseases, another 20 will develop at least one serious disease because of their addiction to tobacco. Why Was This Study Done? About half of US smokers try to quit each year but most of these attempts fail. Many experts believe that counseling and/or treatment with tobacco cessation medications such as nicotine replacement products help smokers to quit. In the USA, where health care is paid for through private or state health insurance, there is some evidence that insurance coverage of tobacco cessation medications increases their use and reduces smoking prevalence. However, smoking cessation treatment is poorly covered by US health insurance programs, largely because of uncertainty about the impact of such coverage on health care costs. It is unknown, for example, whether the introduction of publicly funded tobacco cessation benefits decreases claims for treatment for tobacco-related diseases. In this longitudinal study (a study that follows a group of individuals over a period of time), the researchers ask whether the adoption of comprehensive coverage of tobacco cessation medications by the Massachusetts Medicaid program (MassHealth) in July 2006 has affected claims for treatment for tobacco-related diseases. During its first two and half years, more than 75,000 MassHealth subscribers used the tobacco cessation medication benefit and smoking prevalence among subscribers declined by approximately 10% (38.3% to 28.8%). What Did the Researchers Do and Find? The researchers used MassHealth claims data and a statistical method called generalized estimating equations to compare the probability of hospitalization prior to the use of tobacco cessation medication benefit with the probability of hospitalization after benefit use among MassHealth subscribers. After adjusting for other factors that might have affected hospitalization such as influenza outbreaks and the implementation of the Massachusetts Smoke-Free Workplace Law in July 2004, there was a statistically significant annualized decline in hospital admissions for heart attack of 46% after use of the tobacco cessation medication benefit. That is, the calculated annual rate of admissions for heart attacks was 46% lower after use of the benefit than before among MassHealth beneficiaries. There was also a 49% annualized decline in admissions for coronary atherosclerosis, another smoking-related heart disease. There were no significant changes in hospitalization rates for lung diseases (including asthma, pneumonia, and chronic airway obstruction) or for seven other diagnostic groups. What Do These Findings Mean? These findings show that, among MassHealth subscribers, the use of a tobacco cessation medication benefit was followed by a significant decrease in claims for hospitalization for heart attack and for coronary atherosclerosis but not for other diseases. It does not, however, show that the reduced claims for hospitalization were associated with a reduction in smoking because smoking cessation was not recorded by MassHealth. Furthermore, it is possible that the people who used the tobacco cessation medication benefit shared other characteristics that reduced their chances of hospitalization for heart disease. For example, people using tobacco cessation medication might have been more likely to adhere to prescription schedules for medications such as statins that would also reduce their risk of heart disease. Finally, these findings might be unique to Massachusetts, so similar studies need to be undertaken in other states. Nevertheless, the results of this study suggest that, for low-income smokers, removing financial barriers to the use of smoking cessation medications has the potential to produce short-term decreases in the use of hospital services that will, hopefully, outweigh the costs of comprehensive tobacco cessation medication benefits. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000375. The US Centers for Disease Control and Prevention Office on Smoking and Health has information on all aspects of smoking and health, including advice on how to quit The UK National Health Service Choices Web site provides advice about quitting smoking; more advice on quitting is provided by Smokefree The American Heart Association provides information on heart disease, including advice on how to quit smoking (in several languages) Information about MassHealth is available, including information on smoking and tobacco use prevention

Background Approximately 50% of smokers die prematurely from tobacco-related diseases. In July 2006, the Massachusetts health care reform law mandated tobacco cessation coverage for the Massachusetts Medicaid population. The new benefit included behavioral counseling and all medications approved for tobacco cessation treatment by the U.S. Food and Drug Administration (FDA). Between July 1, 2006 and December 31, 2008, a total of 70,140 unique Massachusetts Medicaid subscribers used the newly available benefit, which is approximately 37% of all Massachusetts Medicaid smokers. Given the high utilization rate, the objective of this study is to determine if smoking prevalence decreased significantly after the initiation of tobacco cessation coverage. Methods and Findings Smoking prevalence was evaluated pre- to post-benefit using 1999 through 2008 data from the Massachusetts Behavioral Risk Factor Survey (BRFSS). The crude smoking rate decreased from 38.3% (95% C.I. 33.6%–42.9%) in the pre-benefit period compared to 28.3% (95% C.I.: 24.0%–32.7%) in the post-benefit period, representing a decline of 26 percent. A demographically adjusted smoking rate showed a similar decrease in the post-benefit period. Trend analyses reflected prevalence decreases that accrued over time. Specifically, a joinpoint analysis of smoking prevalence among Massachusetts Medicaid benefit-eligible members (age 18–64) from 1999 through 2008 found a decreasing trend that was coincident with the implementation of the benefit. Finally, a logistic regression that controlled for demographic factors also showed that the trend in smoking decreased significantly from July 1, 2006 to December 31, 2008. Conclusion These findings suggest that a tobacco cessation benefit that includes coverage for medications and behavioral treatments, has few barriers to access, and involves broad promotion can significantly reduce smoking prevalence.