Correction: Prevalence of multiple chronic conditions by U.S. state and territory, 2017.
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ABSTRACT:
SUBMITTER: Newman D
PROVIDER: S-EPMC7514035 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Correction: Prevalence of multiple chronic conditions by U.S. state and territory, 2017.
Newman Daniel D Tong Michelle M Levine Erica E Kishore Sandeep S
PloS one 20200924 9
[This corrects the article DOI: 10.1371/journal.pone.0232346.]. ...[more]
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Project description:INTRODUCTION:To design effective policy and interventions, public health officials must have an accurate and granular picture of the state of multiple chronic conditions (MCC) in their region. The objective of this research is to describe the prevalence and distribution of MCC in New York State. METHODS:We performed a secondary data analysis of the Behavioral Risk Factor Surveillance System (BRFSS) from 2011 through 2016 for New York adults (n = 76,186). We analyzed the self-reported prevalence of individuals having 0, 1, 2, or ? 3 chronic conditions by sex, race/ethnicity, age, health insurance type, annual household income, and whether respondents lived in New York City. We also examined the most common condition dyads and triads. Finally, we assessed the prevalence of MCC (2 or more chronic conditions) by county across New York State, and neighborhood within New York City. RESULTS:During 2011-2016, 25.2% of adults in New York State had zero chronic conditions, 24.1% had 1 condition, 18.4% had 2 conditions, and 32.4% had 3 or more. The most prevalent dyad was hypertension and high cholesterol in 17.0% of individuals. The most prevalent triad was hypertension, high cholesterol, and arthritis in 4.5% of individuals. County prevalence of MCC ranged from 42.6% in Westchester County to 66.1% in Oneida County. The prevalence of MCC in New York City neighborhoods ranged from 33.5% in Gramercy Park-Murray Hill to 60.6% in High Bridge-Morrisania. CONCLUSION:This research contributes to the field's understanding of multiple chronic conditions and allows policy and public health leaders in New York to better understand the prevalence and distribution of MCC.
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To analyse and compare patterns among different AYUSH systems
To identify the prescription patterns visiting the AYUSH care.
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Project description:BACKGROUND:Although 1-in-5 adults have multiple (? 2) chronic conditions, limited attention has been given to the association between multiple chronic conditions and employment. METHODS:Cross-sectional data (2011 National Health Interview Survey) and multivariate regression analyses were used to examine the association among multiple chronic conditions, employment, and labor force outcomes for U.S. adults aged 18-64 years, controlling for covariates. RESULTS:Among U.S. adults aged 18-64 years (unweighted, n = 25,458), having multiple chronic conditions reduced employment probability by 11-29%. Some individual chronic conditions decreased employment probability. Among employed adults (unweighted, n = 16,096), having multiple chronic conditions increased the average number of work days missed due to injury/illness in the past year by 3-9 days. CONCLUSIONS:Multiple chronic conditions are a barrier to employment and increase the number of work days missed, placing affected individuals at a financial disadvantage. Researchers interested in examining consequences of multiple chronic conditions should give consideration to labor force outcomes.
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Project description:In 2006, the Centers for Medicare & Medicaid Services, which administers the Medicare program in the United States, launched the Chronic Condition Data Warehouse (CCW). The CCW contains all Medicare fee-for-service (FFS) institutional and non-institutional claims, nursing home and home health assessment data, and enrollment/eligibility information from January 1, 1999 forward for a random 5% sample of Medicare beneficiaries (and 100% of the Medicare population from 2000 forward). Twenty-one predefined chronic condition indicator variables are coded within the CCW, to facilitate research on chronic conditions. The current article describes this new data source, and the authors demonstrate the utility of the CCW in describing the extent of chronic disease among Medicare beneficiaries. Medicare claims were analyzed to determine the prevalence, utilization, and Medicare program costs for some common and high cost chronic conditions in the Medicare FFS population in 2005. Chronic conditions explored include diabetes, chronic obstructive pulmonary disease (COPD), heart failure, cancer, chronic kidney disease (CKD), and depression. Fifty percent of Medicare FFS beneficiaries were receiving care for one or more of these chronic conditions. The highest prevalence is observed for diabetes, with nearly one-fourth of the Medicare FFS study cohort receiving treatment for this condition (24.3 percent). The annual number of inpatient days during 2005 is highest for CKD (9.51 days) and COPD (8.18 days). As the number of chronic conditions increases, the average per beneficiary Medicare payment amount increases dramatically. The annual Medicare payment amounts for a beneficiary with only one of the chronic conditions is $7,172. For those with two conditions, payment jumps to $14,931, and for those with three or more conditions, the annual Medicare payments per beneficiary is $32,498. The CCW data files have tremendous value for health services research. The longitudinal data and beneficiary linkage within the CCW are features of this data source which make it ideal for further studies regarding disease prevalence and progression over time. As additional years of administrative data are accumulated in the CCW, the expanded history of beneficiary services increases the value of this already rich data source.
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Project description:BackgroundIt has been proposed that the presence of a multiple territory stroke pattern (MTSP) on brain imaging may aid identification of patients with covert atrial fibrillation (AF). However, it is uncertain whether this association holds true among patients treated with intravenous recombinant tissue plasminogen activator (rtPA) because clot fragmentation may affect MTSP prevalence.Methods/designRetrospective analysis of 149 acute ischemic stroke patients treated with intravenous rtPA who underwent brain MRI. Presence of multiple acute infarctions on brain MRI that involved more than one vascular territory was considered to denote MTSP. Stroke etiology was categorized as nonembolic, cardioembolic (CES), and embolic stroke of undetermined source (ESUS).ResultsIn the entire cohort, subjects with CES and ESUS had significantly more often an MTSP than subjects with other determined stroke mechanism (P= .007). Although numerically relatively more patients had an MTSP as compared to a non-MTSP among subjects with CES (52% versus 33.9%) and ESUS (44% versus 34.7%), this difference did not reach significance after Bonferroni-adjustment for multiple comparisons (P> .05, each). There was no difference in the prevalence of an MTSP among subjects with known (n = 11/51; 21.6%) versus subsequently diagnosed (n = 1/3; 33.3%) AF (P= .54).ConclusionsOur findings indicate that the known association of multiterritory infarct with AF and ESUS is maintained after thrombolysis. In light of its high specificity, MTSP represents a good marker for AF-related stroke etiology; nevertheless, overall sensitivity for AF was low highlighting that an absent MTSP does not rule out AF.
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