Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 8 de 8
Filtrar
1.
Public Health Rep ; 135(2): 211-219, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32053469

RESUMO

OBJECTIVES: The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations. MATERIALS AND METHODS: We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region. RESULTS: We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region. PRACTICE IMPLICATIONS: The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.


Assuntos
Índice de Massa Corporal , Registros Eletrônicos de Saúde , Sistemas de Informação Geográfica , Obesidade/epidemiologia , Adolescente , Adulto , Criança , Pré-Escolar , Colorado/epidemiologia , Feminino , Humanos , Masculino , Vigilância da População/métodos , População Urbana/estatística & dados numéricos
2.
J Public Health Manag Pract ; 26(4): E1-E10, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-30789593

RESUMO

CONTEXT: Although local childhood obesity prevalence estimates would be valuable for planning and evaluating obesity prevention efforts in communities, these data are often unavailable. OBJECTIVE: The primary objective was to create a multi-institutional system for sharing electronic health record (EHR) data to produce childhood obesity prevalence estimates at the census tract level. A secondary objective was to adjust obesity prevalence estimates to population demographic characteristics. DESIGN/SETTING/PARTICIPANTS: The study was set in Denver County, Colorado. Six regional health care organizations shared EHR-derived data from 2014 to 2016 with the state health department for children and adolescents 2 to 17 years of age. The most recent height and weight measured during routine care were used to calculate body mass index (BMI); obesity was defined as BMI of 95th percentile or more for age and sex. Census tract location was determined using residence address. Race/ethnicity was imputed when missing, and obesity prevalence estimates were adjusted by sex, age group, and race/ethnicity. MAIN OUTCOME MEASURE(S): Adjusted obesity prevalence estimates, overall, by demographic characteristics and by census tract. RESULTS: BMI measurements were available for 89 264 children and adolescents in Denver County, representing 73.9% of the population estimate from census data. Race/ethnicity was missing for 4.6%. The county-level adjusted childhood obesity prevalence estimate was 13.9% (95% confidence interval, 13.6-14.1). Adjusted obesity prevalence was higher among males, those 12 to 17 years of age, and those of Hispanic race/ethnicity. Adjusted obesity prevalence varied by census tract (range, 0.4%-24.7%). Twelve census tracts had an adjusted obesity prevalence of 20% or more, with several contiguous census tracts with higher childhood obesity occurring in western areas of the city. CONCLUSIONS: It was feasible to use a system of multi-institutional sharing of EHR data to produce local childhood obesity prevalence estimates. Such a system may provide useful information for communities when implementing obesity prevention programs.

3.
J Natl Compr Canc Netw ; 17(10): 1166-1172, 2019 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-31590146

RESUMO

BACKGROUND: Oral tyrosine kinase inhibitors (TKIs) have been the standard of care for chronic myeloid leukemia (CML) since 2001. However, few studies have evaluated changes in the treatment landscape of CML over time. This study assessed the long-term treatment patterns of oral anticancer therapies among patients with CML. METHODS: This retrospective cohort study included patients newly diagnosed with CML between January 1, 2000, and December 31, 2016, from 10 integrated healthcare systems. The proportion of patients treated with 5 FDA-approved oral TKI agents-bosutinib, dasatinib, imatinib, nilotinib, and ponatinib-in the 12 months after diagnosis were measured, overall and by year, between 2000 and 2017. We assessed the use of each oral agent through the fourth-line setting. Multivariable logistic regression estimated the odds of receiving any oral agent, adjusting for sociodemographic and clinical characteristics. RESULTS: Among 853 patients with CML, 81% received an oral agent between 2000 and 2017. Use of non-oral therapies decreased from 100% in 2000 to 5% in 2005, coinciding with imatinib uptake from 65% in 2001 to 98% in 2005. Approximately 28% of patients switched to a second-line agent, 9% switched to a third-line agent, and 2% switched to a fourth-line agent. Adjusted analysis showed that age at diagnosis, year of diagnosis, and comorbidity burden were statistically significantly associated with odds of receiving an oral agent. CONCLUSIONS: A dramatic shift was seen in CML treatments away from traditional, nonoral chemotherapy toward use of novel oral TKIs between 2000 and 2017. As the costs of oral anticancer agents reach new highs, studies assessing the long-term health and financial outcomes among patients with CML are warranted.


Assuntos
Antineoplásicos/uso terapêutico , Leucemia Mielogênica Crônica BCR-ABL Positiva/tratamento farmacológico , Administração Oral , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Antineoplásicos/farmacologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Adulto Jovem
4.
JCO Clin Cancer Inform ; 3: 1-10, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31487201

RESUMO

PURPOSE: To evaluate health care systems for the availability of population-level data on the frequency of use and results of clinical molecular marker tests to inform precision cancer care. METHODS: We assessed cancer-related molecular marker test data availability across 12 US health care systems in the Cancer Research Network. Overall, these systems provide care to a diverse population of more than 12 million people in the United States. We performed qualitative analyses of test data availability for five blood-based protein, nine germline, and 14 tissue-based tumor marker tests in each health care system's electronic health record and tumor registry using key informants, test code lists, and manual review of data types and output. We then performed quantitative analyses to estimate the proportion of patients with cancer with test utilization data and results for specific molecular marker tests. RESULTS: Health systems were able to systematically capture population-level data on all five blood protein markers, six of 14 tissue-based tumor markers, and none of the nine germline markers. Successful, systematic data capture was achievable for tests with electronic data feeds for test results (blood protein markers) or through prior manual abstraction by tumor registrars (select tumor-based markers). For test results stored in scanned image files (particularly germline and tumor marker tests), information on which test was performed and test results was not readily accessible in an electronic format. CONCLUSION: Even in health care systems with sophisticated electronic health records, there were few codified data elements available for evaluating precision cancer medicine test use and results at the population level. Health care organizations should establish standards for electronic reporting of precision medicine tests to expedite cancer research and facilitate the implementation of precision medicine approaches.


Assuntos
Registros Eletrônicos de Saúde , Neoplasias/epidemiologia , Biomarcadores Tumorais , Coleta de Dados , Assistência à Saúde , Gerenciamento Clínico , Humanos , Biópsia Líquida , Técnicas de Diagnóstico Molecular , Neoplasias/diagnóstico , Neoplasias/etiologia , Neoplasias/terapia , Medicina de Precisão , Vigilância em Saúde Pública , Pesquisa , Estados Unidos/epidemiologia
5.
J Occup Environ Med ; 60(11): e569-e574, 2018 11.
Artigo em Inglês | MEDLINE | ID: mdl-30188491

RESUMO

OBJECTIVE: We assessed the relationship between diabetes mellitus (DM) and measures of worker productivity, direct health care costs, and costs associated with lost productivity (LP) among health care industry workers across two integrated health care systems. METHODS: We used data from the Value Based Benefit Design Health and Wellness Study Phase II (VBD), a prospective study of employees surveyed across health systems. Survey and health care utilization data were linked to estimate LP and health care utilization costs. RESULTS: Mean marginal lost productive time per week was 0.56 hours higher for respondents with DM. Mean adjusted monthly total health care utilization costs were $467 higher for respondents with DM. CONCLUSION: The impact of DM is reflected in higher rates of LP and higher indirect costs for employers related to LP and higher health care resource use.


Assuntos
Efeitos Psicossociais da Doença , Diabetes Mellitus/economia , Eficiência , Custos de Cuidados de Saúde/estatística & dados numéricos , Setor de Assistência à Saúde/estatística & dados numéricos , Absenteísmo , Adolescente , Adulto , Idoso , Registros Eletrônicos de Saúde , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Presenteísmo , Estudos Prospectivos , Autorrelato , Adulto Jovem
6.
J Public Health Manag Pract ; 23(6): 674-683, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28628584

RESUMO

INTRODUCTION: Data networks, consisting of pooled electronic health data assets from health care providers serving different patient populations, promote data sharing, population and disease monitoring, and methods to assess interventions. Better understanding of data networks, and their capacity to support public health objectives, will help foster partnerships, expand resources, and grow learning health systems. METHODS: We conducted semistructured interviews with 16 key informants across the United States, identified as network stakeholders based on their respective experience in advancing health information technology and network functionality. Key informants were asked about their experience with and infrastructure used to develop data networks, including each network's utility to identify and characterize populations, usage, and sustainability. RESULTS: Among 11 identified data networks representing hundreds of thousands of patients, key informants described aggregated health care clinical data contributing to population health measures. Key informant interview responses were thematically grouped to illustrate how networks support public health, including (1) infrastructure and information sharing; (2) population health measures; and (3) network sustainability. CONCLUSION: Collaboration between clinical data networks and public health entities presents an opportunity to leverage infrastructure investments to support public health. Data networks can provide resources to enhance population health information and infrastructure.


Assuntos
Redes de Comunicação de Computadores/tendências , Disseminação de Informação/métodos , Informática em Saúde Pública/métodos , Redes de Comunicação de Computadores/economia , Registros Eletrônicos de Saúde/tendências , Política de Saúde/economia , Política de Saúde/tendências , Humanos , Informática em Saúde Pública/tendências
7.
EGEMS (Wash DC) ; 5(1): 24, 2017 Dec 06.
Artigo em Inglês | MEDLINE | ID: mdl-29881741

RESUMO

Objectives: Measuring obesity prevalence across geographic areas should account for environmental and socioeconomic factors that contribute to spatial autocorrelation, the dependency of values in estimates across neighboring areas, to mitigate the bias in measures and risk of type I errors in hypothesis testing. Dependency among observations across geographic areas violates statistical independence assumptions and may result in biased estimates. Empirical Bayes (EB) estimators reduce the variability of estimates with spatial autocorrelation, which limits the overall mean square-error and controls for sample bias. Methods: Using the Colorado Body Mass Index (BMI) Monitoring System, we modeled the spatial autocorrelation of adult (≥ 18 years old) obesity (BMI ≥ 30 kg m2) measurements using patient-level electronic health record data from encounters between January 1, 2009, and December 31, 2011. Obesity prevalence was estimated among census tracts with >=10 observations in Denver County census tracts during the study period. We calculated the Moran's I statistic to test for spatial autocorrelation across census tracts, and mapped crude and EB obesity prevalence across geographic areas. Results: In Denver County, there were 143 census tracts with 10 or more observations, representing a total of 97,710 adults with a valid BMI. The crude obesity prevalence for adults in Denver County was 29.8 percent (95% CI 28.4-31.1%) and ranged from 12.8 to 45.2 percent across individual census tracts. EB obesity prevalence was 30.2 percent (95% CI 28.9-31.5%) and ranged from 15.3 to 44.3 percent across census tracts. Statistical tests using the Moran's I statistic suggest adult obesity prevalence in Denver County was distributed in a non-random pattern. Clusters of EB obesity estimates were highly significant (alpha=0.05) in neighboring census tracts. Concentrations of obesity estimates were primarily in the west and north in Denver County. Conclusions: Statistical tests reveal adult obesity prevalence exhibit spatial autocorrelation in Denver County at the census tract level. EB estimates for obesity prevalence can be used to control for spatial autocorrelation between neighboring census tracts and may produce less biased estimates of obesity prevalence.

8.
Clin J Am Soc Nephrol ; 12(1): 87-94, 2017 01 06.
Artigo em Inglês | MEDLINE | ID: mdl-28028051

RESUMO

BACKGROUND AND OBJECTIVES: Only a minority of patients with CKD progress to renal failure. Despite the potential benefits of risk stratification in the CKD population, risk prediction models are not routinely used. Our objective was to develop and externally validate a clinically useful and pragmatic prediction model for the 5-year risk of progression to RRT in stage 3 or 4 CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used a retrospective cohort design. The development cohort consisted of 22,460 Kaiser Permanente Northwest members with stage 3 or 4 CKD (baseline 2002-2008). The validation cohort consisted of 16,553 Kaiser Permanente Colorado members with stage 3-4 CKD (baseline 2006-2008). The final model included eight predictors: age, sex, eGFR, hemoglobin, proteinuria/albuminuria, systolic BP, antihypertensive medication use, and diabetes and its complications. RESULTS: In the Northwest and Colorado cohorts, there were 737 and 360 events, and observed 5-year Kaplan-Meier risks of 4.72% (95% confidence interval [95% CI], 4.38 to 5.06) and 2.57% (95% CI, 2.30 to 2.83), respectively. Our prediction model performed extremely well in the development cohort, with a c-statistic of 0.96, an R2 of 79.7%, and good calibration. We had similarly good performance in the external validation cohort, with a c-statistic of 0.95, R2 of 81.2%, and good calibration. In the external validation cohort, the observed risk was slightly lower than the predicted risk in the highest-risk quintile. Using the top quintile of predicted risk as a cutpoint gave a sensitivity of 92.2%. CONCLUSIONS: We developed a pragmatic prediction model and risk score for predicting the 5-year RRT risk in stage 3 and 4 CKD. This model uses variables that are typically available in routine primary care settings, and can be used to help guide important decisions such as timing of referral to nephrology and fistula placement.


Assuntos
Modelos Biológicos , Insuficiência Renal Crônica/terapia , Terapia de Substituição Renal , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Albuminúria/urina , Anti-Hipertensivos/uso terapêutico , Pressão Sanguínea , Complicações do Diabetes/epidemiologia , Feminino , Taxa de Filtração Glomerular , Hemoglobinas/metabolismo , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Medição de Risco/métodos , Fatores Sexuais , Sístole , Fatores de Tempo
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...