Housing-Sensitive Health Conditions Can Predict Poor-Quality Housing.

Improving housing quality may improve residents' health, but identifying buildings in poor repair is challenging. We developed a method to improve health-related building inspection targeting. Linking New York City Medicaid claims data to Landlord Watchlist data, we used machine learning to identify housing-sensitive health conditions correlated with a building's presence on the Watchlist. We identified twenty-three specific housing-sensitive health conditions in five broad categories consistent with the existing literature on housing and health. We used these results to generate a housing health index from building-level claims data that can be used to rank buildings by the likelihood that their poor quality is affecting residents' health. We found that buildings in the highest decile of the housing health index (controlling for building size, community district, and subsidization status) scored worse across a variety of housing quality indicators, validating our approach. We discuss how the housing health index could be used by local governments to target building inspections with a focus on improving health.

Variation in Preterm Birth Rates Across Prenatal Care Sites in New York.

OBJECTIVE: To investigate variation in preterm birth rates by the site at which prenatal care was received. DESIGN: Cross-sectional cohort study. SETTING: New York State. PARTICIPANTS: Claims and encounter data on singleton live births that were covered by New York Medicaid (N = 154,377). METHODS: We analyzed data from New York Medicaid and the American Community Survey. We established sites of prenatal care using geocoded billing addresses for prenatal visits. We calculated descriptive statistics and conducted logistic regression analyses to determine variation in crude and risk-adjusted preterm birth rates by prenatal care site. RESULTS: The crude preterm birth rates averaged 7.8% (range = 2.0%-18.7%) by prenatal care site. The adjusted preterm birth rate was 8.0% (range = 2.8%-18.5%) by prenatal care site. Risk-adjusted preterm birth site-level rates at the 90th percentile were 2.7 times higher than those in the 10th percentile. The variation in risk-adjusted preterm birth site-level rates was not fully explained by birth volume, rural site location, or racial and ethnic composition of the patients who received prenatal care at the site. CONCLUSION: Wide variation in risk-adjusted preterm birth rates across prenatal care sites exists, and factors beyond known individual demographics and medical factors contribute to the variation. Further research is warranted to identify why receiving care at some prenatal sites is associated with higher risk of preterm birth than receiving care at others.

Medicaid Value-Based Payments and Health Care Use for Patients With Mental Illness.

Importance: Medicaid patients with mental illness comprise one of the most high-need and complex patient populations. Value-based reforms aim to improve care, but their efficacy in the Medicaid program is unclear. Objective: To investigate if New York state's Medicaid value-based payment reform was associated with improved utilization patterns for patients with mental illness. Design, Setting, and Participants: This retrospective cohort study used a difference-in-differences analysis to compare changes in utilization between Medicaid beneficiaries whose outpatient practices participated in value-based payment reform and beneficiaries whose practices did not participate from before (July 1, 2013-June 30, 2015) to after reform (July 1, 2015-June 30, 2019). Participants were Medicaid beneficiaries in New York state aged 18 to 64 years with major depression disorder, bipolar disorder, and/or schizophrenia. Data analysis was performed from April 2021 to July 2023. Exposure: Beneficiaries were exposed to value-based payment reforms if their attributed outpatient practice participated in value-based payment reform at baseline (July 1, 2015). Main Outcomes and Measures: Primary outcomes were the number of outpatient primary care visits and the number of behavioral health visits per year. Secondary outcomes were the number of mental health emergency department visits and hospitalizations per year. Results: The analytic population comprised 306 290 individuals with depression (67.4% female; mean [SD] age, 38.6 [11.9] years), 85 105 patients with bipolar disorder (59.6% female; mean [SD] age, 38.0 [11.6] years), and 71 299 patients with schizophrenia (45.1% female; mean [SD] age, 40.3 [12.2] years). After adjustment, analyses estimated a statistically significant, positive association between value-based payments and behavioral health visits for patients with depression (0.91 visits; 95% CI, 0.51-1.30) and bipolar disorder (1.01 visits; 95% CI, 0.22-1.79). There was no statistically significant changes to primary care visits for patients with depression and bipolar disorder, but value-based payments were associated with reductions in primary care visits for patients with schizophrenia (-1.31 visits; 95% CI, -2.51 to -0.12). In every diagnostic population, value-based payment was associated with significant reductions in mental health emergency department visits (population with depression: -0.01 visits [95% CI, -0.02 to -0.002]; population with bipolar disorder: -0.02 visits [95% CI, -0.05 to -0.001]; population with schizophrenia: -0.04 visits [95% CI, -0.07 to -0.01]). Conclusions and Relevance: In this cohort study, Medicaid value-based payment reform was statistically significantly associated with an increase in behavioral health visits and a reduction in mental health emergency department visits for patients with mental illness. Medicaid value-based payment may be effective at altering health care utilization in patients with mental illness.

Not a New Story: Place- and Race-Based Disparities in COVID-19 and Influenza Hospitalizations among Medicaid-Insured Adults in New York City.

While SARS-CoV-2 is a novel virus, contagious respiratory illnesses are not a new problem. Limited research has examined the extent to which place- and race-based disparities in severe illness are similar across waves of the COVID-19 pandemic and historic influenza seasons. In this study, we focused on these disparities within a low-income population, those enrolled in Medicaid in New York City. We used 2015-2020 New York State Medicaid claims to compare the characteristics of patients hospitalized with COVID-19 during three separate waves of 2020 (first wave: January 1-April 30, 2020; second wave: May 1-August 31, 2020; third wave: September 1-December 31, 2020) and with influenza during the 2016 (July 1, 2016-June 30, 2017) and 2017 influenza seasons (July 1, 2017-June 30, 2018). We found that patterns of hospitalization by race/ethnicity and ZIP code across the two influenza seasons and the first wave of COVID-19 were similar (increased risk among non-Hispanic Black (aOR = 1.17, 95% CI: 1.10-1.25) compared with non-Hispanic white Medicaid recipients). Black/white disparities in hospitalization dissipated in the second COVID wave and reversed in the third wave. The commonality of disparities across influenza seasons and the first wave of COVID-19 suggests there are community factors that increase hospitalization risk across novel respiratory illness incidents that emerge in the period before aggressive public health intervention. By contrast, convergence in hospitalization patterns in later pandemic waves may reflect, in part, the distinctive public health response to COVID-19.

Severe maternal morbidity and mortality during delivery hospitalization of class I, II, III, and super obese women.

BACKGROUND: Previous studies show that obesity predisposes patients to higher risks of adverse pregnancy outcomes. Data on the relationship between increasing degrees of obesity and risks of severe maternal morbidity, including mortality, are limited. OBJECTIVE: We examined the association of increasing classes of obesity, especially super obesity, with the risk of severe maternal morbidity and mortality at the time of delivery hospitalization. STUDY DESIGN: Using New York City linked birth certificates and hospital discharge data, we conducted a retrospective cohort study. This study identified delivery hospitalizations for singleton, live births in 2008-2012. Women were classified as having obesity (class I, II, III, or super obesity), as opposed to normal weight or overweight, based on prepregnancy body mass index. Cases of severe maternal morbidity were identified based on International Classification of Diseases, Ninth Revision diagnosis and procedure codes according to Centers for Disease Control and Prevention criteria. Multivariable logistic regression was used to evaluate the association between obesity classes and severe maternal morbidity, adjusting for maternal sociodemographic characteristics. RESULTS: During 2008-2012, there were 570,997 live singleton births with available information on prepregnancy body mass index that met all inclusion criteria. After adjusting for maternal characteristics, women with class II (adjusted odds ratio, 1.14; 95% confidence interval, 1.05-1.23), class III (adjusted odds ratio, 1.34; 95% confidence interval, 1.21-1.49), and super obesity (adjusted odds ratio, 1.99; 95% confidence interval, 1.57-2.54) were all significantly more likely to have severe maternal morbidity than normal and overweight women. Super obesity was associated with specific severe maternal morbidity indicators, including renal failure, air and thrombotic embolism, blood transfusion, heart failure, and the need for mechanical ventilation. CONCLUSION: There is a significant dose-response relationship between increasing obesity class and the risk of severe maternal morbidity at delivery hospitalization. The risks of severe maternal morbidity are highest for women with super obesity. Given that this is a modifiable risk factor, women with prepregnancy obesity should be counseled on the specific risks associated with pregnancy before conception to optimize their pregnancy outcomes.

Social Determinants Matter For Hospital Readmission Policy: Insights From New York City.

This study assessed the impact of individual social risk factor variables and social determinants of health (SDOH) measures on hospital readmission rates and penalties used in the Centers for Medicare and Medicaid Services (CMS) Hospital Readmissions Reduction Program (HRRP). Using 2012-16 hospital discharge data from New York City, we projected HRRP penalties by augmenting CMS's readmission model for heart attack, heart failure, and pneumonia with SDOH scores constructed at each of four geographic levels and a measure of individual-level social risk. Including additional SDOH scores in the model, especially those constructed with the most granular geographic data, along with social risk factor variables substantially affects projected penalties for hospitals treating the highest proportion of patients with high SDOH scores. Improved performance occurred even after we included peer-group stratification in the HRRP model pursuant to the 21st Century Cures Act. Small improvements in model accuracy were associated with substantial shifts in projected performance. Our results suggest that CMS's continued omission of relevant patient and geographic data from the HRRP readmission model misallocates penalties attributable to SDOH and social risk factor effects to hospitals with the largest share of high-risk patients.

The Steroid Metabolome and Breast Cancer Risk in Women with a Family History of Breast Cancer: The Novel Role of Adrenal Androgens and Glucocorticoids.

BACKGROUND: No study has comprehensively examined how the steroid metabolome is associated with breast cancer risk in women with familial risk. METHODS: We examined 36 steroid metabolites across the spectrum of familial risk (5-year risk ranged from 0.14% to 23.8%) in pre- and postmenopausal women participating in the New York site of the Breast Cancer Family Registry (BCFR). We conducted a nested case-control study with 62 cases/124 controls individually matched on menopausal status, age, and race. We measured metabolites using GC-MS in urine samples collected at baseline before the onset of prospectively ascertained cases. We used conditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) per doubling in hormone levels. RESULTS: The average proportion of total steroid metabolites in the study sample were glucocorticoids (61%), androgens (26%), progestogens (11%), and estrogens (2%). A doubling in glucocorticoids (aOR = 2.7; 95% CI = 1.3-5.3) and androgens (aOR = 1.6; 95% CI = 1.0-2.7) was associated with increased breast cancer risk. Specific glucocorticoids (THE, THF αTHF, 6ß-OH-F, THA, and α-THB) were associated with 49% to 161% increased risk. Two androgen metabolites (AN and 11-OH-AN) were associated with 70% (aOR = 1.7; 95% CI = 1.1-2.7) and 90% (aOR = 1.9; 95% CI = 1.2-3.1) increased risk, respectively. One intermediate metabolite of a cortisol precursor (THS) was associated with 65% (OR = 1.65; 95% CI = 1.0-2.7) increased risk. E1 and E2 estrogens were associated with 20% and 27% decreased risk, respectively. CONCLUSIONS: Results suggest that glucocorticoids and 11-oxygenated androgens are positively associated with breast cancer risk across the familial risk spectrum. IMPACT: If replicated, our findings suggest great potential of including steroids into existing breast cancer risk assessment tools.

Public transportation and transmission of viral respiratory disease: Evidence from influenza deaths in 121 cities in the United States.

One important concern around the spread of respiratory infectious diseases has been the contribution of public transportation, a space where people are in close contact with one another and with high-use surfaces. While disease clearly spreads along transportation routes, there is limited evidence about whether public transportation use itself is associated with the overall prevalence of contagious respiratory illnesses at the local level. We examine the extent of the association between public transportation and influenza mortality, a proxy for disease prevalence, using city-level data on influenza and pneumonia mortality and public transit use from 121 large cities in the United States (US) between 2006 and 2015. We find no evidence of a positive relationship between city-level transit ridership and influenza/pneumonia mortality rates, suggesting that population level rates of transit use are not a singularly important factor in the transmission of influenza.

Impact of a Telephonic Intervention to Improve Diabetes Control on Health Care Utilization and Cost for Adults in South Bronx, New York.

OBJECTIVE: Self-management education and support are essential for improved diabetes control. A 1-year randomized telephonic diabetes self-management intervention (Bronx A1C) among a predominantly Latino and African American population in New York City was found effective in improving blood glucose control. To further those findings, this current study assessed the intervention's impact in reducing health care utilization and costs over 4 years. RESEARCH DESIGN AND METHODS: We measured inpatient (n = 816) health care utilization for Bronx A1C participants using an administrative data set containing all hospital discharges for New York State from 2006 to 2014. Multilevel mixed modeling was used to assess changes in health care utilization and costs between the telephonic diabetes intervention (Tele/Pr) arm and print-only (PrO) control arm. RESULTS: During follow-up, excess relative reductions in all-cause hospitalizations for the Tele/Pr arm compared with PrO arm were statistically significant for odds of hospital use (odds ratio [OR] 0.89; 95% CI 0.82, 0.97; P < 0.01), number of hospital stays (rate ratio [RR] 0.90; 95% CI 0.81, 0.99; P = 0.04), and hospital costs (RR 0.90; 95% CI 0.84, 0.98; P = 0.01). Reductions in hospital use and costs were even stronger for diabetes-related hospitalizations. These outcomes were not significantly related to changes observed in hemoglobin A1c during individuals' participation in the 1-year intervention. CONCLUSIONS: These results indicate that the impact of the Bronx A1C intervention was not just on short-term improvements in glycemic control but also on long-term health care utilization. This finding is important because it suggests the benefits of the intervention were long-lasting with the potential to not only reduce hospitalizations but also to lower hospital-associated costs.

Assessing Endogenous and Exogenous Hormone Exposures and Breast Development in a Migrant Study of Bangladeshi and British Girls.

Timing of breast development (or thelarche) and its endogenous and exogenous determinants may underlie global variation in breast cancer incidence. The study objectives were to characterize endogenous estrogen levels and bisphenol A (BPA) exposure using a migrant study of adolescent girls and test whether concentrations explained differences in thelarche by birthplace and growth environment. Estrogen metabolites (EM) and BPA-glucuronide (BPA-G) were quantified in urine spot samples using liquid chromatography tandem mass spectrometry (LC-MS/MS) from a cross-sectional study of Bangladeshi, first- and second-generation Bangladeshi migrants to the UK, and white British girls aged 5-16 years (n = 348). Thelarche status at the time of interview was self-reported and defined equivalent to Tanner Stage ≥2. We compared geometric means (and 95% confidence interval (CIs)) of EM and BPA-G using linear regression and assessed whether EM and BPA-G explained any of the association between exposure to the UK and the age at thelarche using hazard ratios and 95% confidence intervals. Average EM decreased with exposure to the UK, whereas BPA-G increased and was significantly higher among white British (0.007 ng/mL, 95% CI: 0.0024-0.0217) and second-generation British-Bangladeshi girls (0.009 ng/mL, 95% CI: 0.0040-0.0187) compared to Bangladeshi girls (0.002 ng/mL, 95% CI: 0.0018-0.0034). Two of four EM ratios (16-pathway/parent and parent/all pathways) were significantly associated with thelarche. The relationship between exposure to the UK and thelarche did not change appreciably after adding EM and BPA-G to the models. While BPA-G is often considered a ubiquitous exposure, our findings suggest it can vary based on birthplace and growth environment, with increasing levels for girls who were born in or moved to the UK. Our study did not provide statistically significant evidence that BPA-G or EM concentrations explained earlier thelarche among girls who were born or raised in the UK.

Evaluating Race and Ethnicity Reported in Hospital Discharge Data and Its Impact on the Assessment of Health Disparities.

BACKGROUND: Improving the collection and quality of race and ethnicity reported in hospital data is a key step in identifying disparities in health service utilization and outcomes and opportunities for quality improvement. OBJECTIVE: The objective of this study was to assess the quality of race/ethnicity reported in hospital discharge data and examine the impact on the identification of disparities in select health outcomes in New York City. RESEARCH DESIGN: Using the birth certificate as a gold standard, we examined the quality of hospital discharge race/ethnicity and estimated the impact of misclassification on racial/ethnic disparities in severe maternal morbidity and preventable hospitalizations. SUBJECTS: Delivery hospitalizations from the New York State hospital discharge data (Statewide Planning and Research Cooperative System) linked with 2015 New York City birth certificates. MEASURES: Sensitivity and positive predictive value (PPV). RESULTS: The non-Hispanic white and black race had relatively high sensitivity and PPV. Hispanic ethnicity and Asian race had moderate sensitivity and high PPV, but were often misclassified as "Other." As a result, health disparities may be underestimated for those of Hispanic ethnicity and Asian race, particularly for indicators that use population denominators drawn from another source. CONCLUSIONS: The quality of hospital discharge data varies by race/ethnicity and may underestimate disparities in some groups. Future research should validate findings with other data sources, identify driving factors, and evaluate progress over time.

Mobilizing Breast Cancer Prevention Research Through Smartphone Apps: A Systematic Review of the Literature.

Background: Breast cancer rates have been increasing worldwide, particularly among young women, suggesting important interactions between genes and health behaviors. At the same time, mobile technology, including smartphones applications (apps), has emerged as a new tool for delivering healthcare and health-related services. As of 2018, there were nearly 600 publicly available breast cancer apps designed to provide disease and treatment information, to manage disease, and to raise overall awareness. However, the extent to which apps are incorporated into breast cancer prevention research is unknown. Therefore, the objective of this review was to determine how mobile applications are being used for breast cancer prevention among women across the cancer control continuum. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched PubMed and Web of Science Core Collection databases using the keywords breast cancer, smartphone, mobile application, and phone app. Full-length journal articles available in English that addressed the research question were included. We categorized articles by prevention type (primary, secondary, and tertiary) and phase of research (protocol, development, feasibility, pilot, measurement, and effectiveness), and identified common themes and gaps. Results: Our search yielded 82 studies (69 unique) that used apps in breast cancer prevention research across 20 countries. Approximately half of the named apps were publicly available. The majority (73%) of studies targeted tertiary prevention; 15% targeted secondary and 13% targeted primary prevention. Apps were used across all phases of research with the predominant phase being feasibility in tertiary prevention (34%), effectiveness in secondary prevention (63%), and development (30%) and effectiveness (30%) in primary prevention. Common uses included assessing outcomes relevant to clinical care coordination, quality of life, increasing self-efficacy and screening behaviors, and tracking and managing health behaviors. Conclusions: We identified the following gaps: few effectiveness studies in tertiary prevention, minimal use of apps for breast cancer etiology or early detection, and few interventions in those at average risk of breast cancer. These findings suggest that while mobile apps can inform breast cancer prevention across the continuum, more work is needed to incorporate apps into primary prevention.

Determinants of Severe Maternal Morbidity and Its Racial/Ethnic Disparities in New York City, 2008-2012.

Objectives Severe maternal morbidity (SMM) is an important indicator for identifying and monitoring efforts to improve maternal health. Studies have identified independent risk factors, including race/ethnicity; however, there has been limited investigation of the modifying effect of socioeconomic factors. Study aims were to quantify SMM risk factors and to determine if socioeconomic status modifies the effect of race/ethnicity on SMM risk. Methods We used 2008-2012 NYC birth certificates matched with hospital discharge records for maternal deliveries. SMM was defined using an algorithm developed by the Centers for Disease Control and Prevention. Mixed-effects logistic regression models estimated SMM risk by demographic, socioeconomic, and health characteristics. The final model was stratified by Medicaid status (as a proxy for income), education, and neighborhood poverty. Results Of 588,232 matched hospital deliveries, 13,505 (229.6 per 10,000) had SMM. SMM rates varied by maternal age, birthplace, education, income, pre-existing chronic conditions, pre-pregnancy weight status, trimester of prenatal care entry, plurality, and parity. Race/ethnicity was consistently and significantly associated with SMM. While racial differences in SMM risk persisted across all socioeconomic groupings, the risk was exacerbated among Latinas and Asian-Pacific Islanders with lower income when compared to white non-Latinas. Similarly, living in the poorest neighborhoods exacerbated SMM risk among both black non-Latinas and Latinas. Conclusions for Practice SMM determinants in NYC mirror national trends, including racial/ethnic disparities. However, these disparities persisted even in the highest income and educational groups suggesting other pathways are needed to explain racial/ethnic differences.

Gestational Weight Gain and Severe Maternal Morbidity at Delivery Hospitalization.

OBJECTIVE: To examine whether women who varied from recommended gestational weight gain guidelines by the Institute of Medicine (IOM, now known as the National Academy of Medicine) were at increased risk of severe maternal morbidity during delivery hospitalization compared with those whose weight gain remained within guidelines. METHODS: We conducted a retrospective cohort study using linked 2008-2012 New York City discharge and birth certificate data sets. Cases of severe maternal morbidity were identified using International Classification of Diseases, 9th Revision, Clinical Modification codes based on the Centers for Disease Control and Prevention criteria, which consists of 21 indicators of possible life-threatening diagnoses, life-saving procedures, or death. Multivariable logistic regression was used to evaluate the association between gestational weight gain categories based on prepregnancy body mass index (BMI) and severe maternal morbidity adjusting for maternal demographics and socioeconomic status. The analysis was stratified by prepregnancy BMI categories. RESULTS: During 2008-2012, there were 515,148 term singleton live births in New York City with prepregnancy weight and gestational weight gain information. In 24.8%, 35.1%, 32.1%, and 8.0% of these births, women gained below, within, 1-19 lbs above, and 20 lbs or more above the IOM guidelines, respectively. After adjusting for maternal demographic and socioeconomic characteristics, women who had gestational weight gain 1-19 lbs above (adjusted odds ratio [AOR] 1.08, 95% CI 1.02-1.13) or 20 lbs or more above the IOM recommendations (AOR 1.21, 95% CI 1.12-1.31) had higher odds of overall severe maternal morbidity compared with women who gained within guidelines. Although the increased odds ratios (ORs) were statistically significant, this only resulted in an absolute rate increase of 2.1 and 6 cases of severe maternal morbidity per 1,000 deliveries for those who gained 1-19 and 20 lbs or more above recommendations, respectively. Women with gestational weight gain 20 lbs or more above recommendations had significantly higher ORs of eclampsia, heart failure during a procedure, pulmonary edema or acute heart failure, transfusion, and ventilation. CONCLUSION: Women whose gestational weight gain is in excess of IOM guidelines are at increased risk of severe maternal morbidity, although their absolute risks remain low.

Disparities in Preventable Hospitalizations Among Public Housing Developments.

INTRODUCTION: This study assesses preventable hospitalization rates among New York City residents living in public housing developments compared with all New York City residents and residents in low-income areas. Additionally, preventable hospitalization rates by development (one or multiple buildings in close proximity and served by the same management office) were determined. METHODS: The 2010-2014 New York City hospital discharge data were geocoded and linked with New York City Housing Authority records using building-level identifiers. Preventable hospitalizations resulting from ambulatory care-sensitive conditions were identified for public housing residents, citywide, and residents of low-income areas. Age-adjusted overall and ambulatory care-sensitive, condition-specific preventable hospitalization rates (11 outcomes) were determined and compared across groups to assess potential disparities. Additionally, rates were ranked and compared among public housing developments by quartiles. The analysis was conducted in 2016 and 2017. RESULTS: The age-adjusted rate of preventable hospitalization was significantly higher among public housing residents than citywide (rate ratio [RR]=2.67, 95% CI=2.65, 2.69), with the greatest disparities in hospitalizations related to diabetes (RR=3.12, 95% CI=3.07, 3.18) and asthma (RR=4.14, 95% CI=4.07, 4.21). The preventable hospitalization rate was also higher among residents of public housing than low-income areas (RR=1.33, 95% CI=1.31, 1.35). There were large differences between developments ranked in the top and bottom quartiles of preventable hospitalization (RR=1.81, 95% CI=1.76, 1.85) with the largest difference related to chronic obstructive pulmonary disease (RR=3.38, 95% CI=3.08, 3.70). CONCLUSIONS: Preventable hospitalization rates are high among public housing residents, and vary significantly by development and condition. By providing geographically granular information, geocoded hospital discharge data can serve as a valuable tool for health assessment and engagement of the healthcare sector and other stakeholders in interventions that address health inequities.

Estimating the Hospital Delivery Costs Associated With Severe Maternal Morbidity in New York City, 2008-2012.

OBJECTIVE: To quantify the average and total hospital delivery costs associated with severe maternal morbidity in excess of nonsevere maternal morbidity deliveries over a 5-year period in New York City adjusting for other sociodemographic and clinical factors. METHODS: We conducted a population-based cross-sectional study using linked birth certificates and hospital discharge data for New York City deliveries from 2008 to 2012. Severe maternal morbidity was defined using a published algorithm of International Classification of Diseases, 9 Revision, Clinical Modification disease and procedure codes. Hospital costs were estimated by converting hospital charges using factors specific to each year and hospital and to each diagnosis. These estimates approximate what it costs the hospital to provide services (excluding professional fees) and were used in all subsequent analyses. To estimate adjusted mean costs associated with severe maternal morbidity, we used multivariable regression models with a log link, gamma distribution, robust standard errors, and hospital fixed effects, controlling for age, race and ethnicity, neighborhood poverty, primary payer, number of deliveries, method of delivery, comorbidities, and year. We used the adjusted mean cost to determine the average and total hospital delivery costs associated with severe maternal morbidity in excess of nonsevere maternal morbidity deliveries from 2008 to 2012. RESULTS: Approximately 2.3% (n=13,502) of all New York City delivery hospitalizations were complicated by severe maternal morbidity. Compared with nonsevere maternal morbidity deliveries, these hospitalizations were clinically complicated, required more and intensive clinical services, and had a longer stay in the hospital. The average cost of delivery with severe maternal morbidity was $14,442 (95% CI $14,128-14,756), compared with $7,289 (95% CI $7,276-7,302) among deliveries without severe maternal morbidity. After adjusting for other factors, the difference between deliveries with and without severe maternal morbidity remained high ($6,126). Over 5 years, this difference resulted in approximately $83 million in total excess costs (13,502×$6,126). CONCLUSION: Severe maternal morbidity nearly doubled the cost of delivery above and beyond other drivers of cost, resulting in tens of millions of excess dollars spent in the health care system in New York City. These findings can be used to demonstrate the burden of severe maternal morbidity and evaluate the cost-effectiveness of interventions to improve maternal health.

Evaluating the Use of an Electronic Death Registration System for Mortality Surveillance During and After Hurricane Sandy: New York City, 2012.

OBJECTIVES: We evaluated the use of New York City's (NYC's) electronic death registration system (EDRS) to conduct mortality surveillance during and after Hurricane Sandy. METHODS: We used Centers for Disease Control and Prevention guidelines for surveillance system evaluation to gather evidence on usefulness, flexibility, stability, timeliness, and quality. We assessed system components, interviewed NYC Health Department staff, and analyzed 2010 to 2012 death records. RESULTS: Despite widespread disruptions, NYC's EDRS was stable and collected timely mortality data that were adapted to provide storm surveillance with minimal additional resources. Direct-injury fatalities and trends in excess all-cause mortality were rapidly identified, providing useful information for response; however, the time and burden of establishing reports, adapting the system, and identifying indirect deaths limited surveillance. CONCLUSIONS: The NYC Health Department successfully adapted its EDRS for near real-time disaster-related mortality surveillance. Retrospective assessment of deaths, advanced methods for case identification and analysis, standardized reports, and system enhancements will further improve surveillance. Local, state, and federal partners would benefit from partnering with vital records to develop EDRSs for surveillance and to promote ongoing evaluation.

Reliability of Reported Maternal Smoking: Comparing the Birth Certificate to Maternal Worksheets and Prenatal and Hospital Medical Records, New York City and Vermont, 2009.

Maternal smoking is captured on the 2003 US Standard Birth Certificate based on self-reported tobacco use before and during pregnancy collected on post-delivery maternal worksheets. Study objectives were to compare smoking reported on the birth certificate to maternal worksheets and prenatal and hospital medical records. The authors analyzed a sample of New York City (NYC) and Vermont women (n = 1,037) with a live birth from January to August 2009 whose responses to the Pregnancy Risk Assessment Monitoring System survey were linked with birth certificates and abstracted medical records and maternal worksheets. We calculated smoking prevalence and agreement (kappa) between sources overall and by maternal and hospital characteristics. Smoking before and during pregnancy was 13.7 and 10.4% using birth certificates, 15.2 and 10.7% using maternal worksheets, 18.1 and 14.1% using medical records, and 20.5 and 15.0% using either maternal worksheets or medical records. Birth certificates had "almost perfect" agreement with maternal worksheets for smoking before and during pregnancy (κ = 0.92 and 0.89) and "substantial" agreement with medical records (κ = 0.70 and 0.74), with variation by education, insurance, and parity. Smoking information on NYC and Vermont birth certificates closely agreed with maternal worksheets but was underestimated compared with medical records, with variation by select maternal characteristics. Opportunities exist to improve birth certificate smoking data, such as reducing the stigma of smoking, and improving the collection, transcription, and source of information.

How well do birth records serve maternal and child health programs? Birth registration system evaluation, New York City, 2008-2011.

National birth registration guidelines were revised in 2003 to improve data quality; however, few studies have evaluated the impact on local jurisdictions and their data users. In New York City (NYC), approximately 125,000 births are registered annually with the NYC Department of Health and Mental Hygiene, and data are used routinely by the department's maternal and child health (MCH) programs. In order to better meet MCH program needs, we used Centers for Disease Control and Prevention guidelines to assess birth data usefulness, simplicity, data quality, timeliness and representativeness. We interviewed birth registration and MCH program staff, reviewed a 2009 survey of birth registrars (n = 39), and analyzed 2008-2011 birth records for timeliness and completeness (n = 502,274). Thirteen MCH programs use birth registration data for eligibility determination, needs assessment, program evaluation, and surveillance. Demographic variables are used frequently, nearly 100 % complete, and considered the gold standard by programs; in contrast, medical variables' use and validity varies widely. Seventy-seven percent of surveyed birth registrars reported ≥1 problematic items in the system; 64.1 % requested further training. During 2008-2011, the median interval between birth and registration was 5 days (range 0-260 days); 11/13 programs were satisfied with timeliness. The NYC birth registration system provides local MCH programs useful, timely, and representative data. However, some medical items are difficult to collect, of low quality, and rarely used. We recommend enhancing training for birth registrars, continuing quality improvement efforts, increasing collaboration with program users, and removing consistently low-quality and low-use variables.