A Comparison of Death Records Between the United States Renal Data System and a Large Integrated Health Care System.
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ABSTRACT:
SUBMITTER: Shaw SF
PROVIDER: S-EPMC7270980 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo compare health care utilization between Canadian and U.S. residents.Data sourcesNationally representative 2007 surveys from the Medical Expenditure Panel Survey for the United States and the Canadian Community Health Survey for Canada.Study designWe use descriptive and multivariate methods to examine differences in health care utilization rates for visits to medical providers, nurses, chiropractors, specialists, dentists, and overnight hospital stays, usual source of care, Pap smear tests, and mammograms.Principal findingsThe poor and less educated were more likely to utilize health care in Canada than in the United States. The differences were especially pronounced for having a usual source of care and for visits to providers, specialists, and dentists. Health care use for residents with high incomes and higher levels of education were not markedly different between the two countries and often higher for U.S residents. Foreign-born residents were more likely to use health care in Canada than in the United States. The descriptive results were confirmed in multivariate regressions.ConclusionsGiven the magnitude of our results, the health insurance structure in Canada might have played an important role in improving access to care for subpopulations examined in this study.
| S-EPMC3626357 | biostudies-literature
Project description:BackgroundCollection of accurate Hispanic ethnicity data is critical to evaluate disparities in health and health care. However, this information is often inconsistently recorded in electronic health record (EHR) data.ObjectiveTo enhance capture of Hispanic ethnicity in the Veterans Affairs EHR and compare relative disparities in health and health care.MethodsWe first developed an algorithm based on surname and country of birth. We then determined sensitivity and specificity using self-reported ethnicity from the 2012 Veterans Aging Cohort Study survey as the reference standard and compared this to the research triangle institute race variable from the Medicare administrative data. Finally, we compared demographic characteristics and age-adjusted and sex-adjusted prevalence of conditions in Hispanic patients among different identification methods in the Veterans Affairs EHR 2018-2019.ResultsOur algorithm yielded higher sensitivity than either EHR-recorded ethnicity or the research triangle institute race variable. In 2018-2019, Hispanic patients identified by the algorithm were more likely to be older, had a race other than White, and foreign born. The prevalence of conditions was similar between EHR and algorithm ethnicity. Hispanic patients had higher prevalence of diabetes, gastric cancer, chronic liver disease, hepatocellular carcinoma, and human immunodeficiency virus than non-Hispanic White patients. Our approach evidenced significant differences in burden of disease among Hispanic subgroups by nativity status and country of birth.ConclusionsWe developed and validated an algorithm to supplement Hispanic ethnicity information using clinical data in the largest integrated US health care system. Our approach enabled clearer understanding of demographic characteristics and burden of disease in the Hispanic Veteran population.
| S-EPMC10114212 | biostudies-literature
Project description:The United States Renal Data System (USRDS) began in 1989 through US Congressional authorization under National Institutes of Health competitive contracting. Its history includes five contract periods, two of 5 years, two of 7.5 years, and the fifth, awarded in February 2014, of 5 years. Over these 25 years, USRDS reporting transitioned from basic incidence and prevalence of end-stage renal disease (ESRD), modalities, and overall survival, as well as focused special studies on dialysis, in the first two contract periods to a comprehensive assessment of aspects of care that affect morbidity and mortality in the second two periods. Beginning in 1999, the Minneapolis Medical Research Foundation investigative team transformed the USRDS into a total care reporting system including disease severity, hospitalizations, pediatric populations, prescription drug use, and chronic kidney disease and the transition to ESRD. Areas of focus included issues related to death rates in the first 4 months of treatment, sudden cardiac death, ischemic and valvular heart disease, congestive heart failure, atrial fibrillation, and infectious complications (particularly related to dialysis catheters) in hemodialysis and peritoneal dialysis patients; the burden of congestive heart failure and infectious complications in pediatric dialysis and transplant populations; and morbidity and access to care. The team documented a plateau and decline in incidence rates, a 28% decline in death rates since 2001, and changes under the 2011 Prospective Payment System with expanded bundled payments for each dialysis treatment. The team reported on Bayesian methods to calculate mortality ratios, which reduce the challenges of traditional methods, and introduced objectives under the Health People 2010 and 2020 national health care goals for kidney disease.
| S-EPMC4455192 | biostudies-other
Project description:Nonalcoholic fatty liver disease (NAFLD) is a global public health problem. However, the natural history of NAFLD is incomplete. This is a retrospective cohort study of patients identified with NAFLD by diagnosis codes in a large, community-based health care delivery system. The objectives were (1) to follow patients from initial NAFLD presentation through progression to cirrhosis and/or decompensated cirrhosis to liver cancer, liver transplant, and death for up to 10 years; and (2) to conduct disease progression analysis restricted to patients with NAFLD identified as having diabetes at baseline. A total of 98,164 patients with full NAFLD and 26,488 with diabetes were divided into three baseline prevalent states: (1) no cirrhosis, (2) compensated cirrhosis, and (3) decompensated cirrhosis. In baseline patients without cirrhosis, annual rates of compensated cirrhosis, decompensated cirrhosis, and death were 0.28%, 0.31%, and 0.63% per year, respectively. With baseline compensated cirrhosis, the annual rates of decompensation and death were 2.4% and 6.7% per year. Finally, in those with decompensated cirrhosis at baseline, the death rate was 8.0% per year. In those without cirrhosis and with cirrhosis at baseline, the rates of liver cancer and death were increased approximately 2-fold in the diabetic subpopulation compared with the full NAFLD cohort. Age and comorbidities increased with increasing disease severity. Cox proportional hazards regression analysis showed that cirrhosis was strongly associated with death and liver cancer, and that diabetes was associated with a significant increase in the hazard of both liver cancer and death (2.56 [2.04-3.20] and 1.43 [1.35-1.52]), respectively. Conclusion: The findings of this community-based study further our understanding of the natural history of NAFLD and demonstrate that diabetes is a major factor in the progression of this disease.
| S-EPMC7789841 | biostudies-literature
Project description:Insight into health conditions associated with death can inform healthcare policy. We aimed to cluster 27,525,663 deceased people based on the health conditions associated with death to study the associations between the health condition clusters, demographics, the recorded underlying cause and place of death. Data from all deaths in the United States registered between 2006 and 2016 from the National Vital Statistics System of the National Center for Health Statistics were analyzed. A self-organizing map (SOM) was used to create an ordered representation of the mortality data. 16 clusters based on the health conditions associated with death were found showing significant differences in socio-demographics, place, and cause of death. Most people died at old age (73.1 (18.0) years) and had multiple health conditions. Chronic ischemic heart disease was the main cause of death. Most people died in the hospital or at home. The prevalence of multiple health conditions at death requires a shift from disease-oriented towards person-centred palliative care at the end of life, including timely advance care planning. Understanding differences in population-based patterns and clusters of end-of-life experiences is an important step toward developing a strategy for implementing population-based palliative care.
| S-EPMC6678953 | biostudies-literature
Project description:ImportanceThere are few population-based studies addressing trends in neonatal intensive care unit (NICU) admission and NICU patient-days, especially in the subpopulation that, by gestational age (GA) and birth weight (BW), might otherwise be able to stay in the room with their mothers.ObjectiveTo describe population-based trends in NICU admissions, NICU patient-days, readmissions, and mortality in the birth population of a large integrated health care system.Design, setting, and participantsThis cohort study was conducted using data extracted from electronic medical records at Kaiser Permanente Southern California (KPSC) health care system. Participants included all women who gave birth at KPSC hospitals and their newborns from January 1, 2010, through December 31, 2018. Data extraction was limited to data entry fields whose contents were either numbers or fixed categorical choices. Rates of NICU admission, NICU patient-days, readmission rates, and mortality rates were measured in the total population, in newborns with GA 35 weeks or greater and BW 2000 g or more (high GA and BW group), and in the remaining newborns (low GA and BW group). Admissions to the NICU and NICU patient-days were risk adjusted with a machine learning model based on demographic and clinical characteristics before NICU admission. Changes in the trends were assessed with 2-sided correlated seasonal Mann-Kendall test. Data analysis was performed in August 2019.ExposuresAdmission to the NICU and NICU patient-days among the birth cohort.Main outcomes and measuresThe primary outcomes were NICU admission and NICU patient-days in the total neonatal population and GA and BW subgroups. The secondary outcomes were readmission and mortality rates.ResultsOver the study period there were 320 340 births (mean [SD] age of mothers, 30.1 [5.7] years; mean [SD] gestational age, 38.6 [1.97] weeks; mean [SD] birth weight, 3302 [573] g). The risk-adjusted NICU admission rate decreased from a mean of 14.5% (95% CI, 14.2%-14.7%) to 10.9% (95% CI, 10.7%-11.7%) (P for trend = .002); 92% of the change was associated with changes in the care of newborns in the high GA and BW group. The number of risk-adjusted NICU patient-days per birth decreased from a mean of 1.50 patient-days (95% CI, 1.43-1.54 patient-days) to 1.40 patient-days (95% CI, 1.36-1.48 patient-days) (P for trend = .03); 70% of the change was associated with newborns in the high GA and BW group. The unadjusted 30-day readmission rates and mortality rates did not change.Conclusions and relevanceAdmission rates to the NICU and numbers of NICU patient-days decreased over the study period without an increase in readmissions or mortality. The observed decrease was associated with the high GA and BW newborn population. How much of this decrease is attributable to intercurrent health care systemwide quality improvement initiatives would require further investigation. The remaining unexplained variation suggests that further changes are also possible.
| S-EPMC7303809 | biostudies-literature
Project description: Not available
| S-EPMC153099 | biostudies-literature
Project description:BACKGROUND:Influenza causes an estimated 3000 to 50,000 deaths per year in the United States of America (US). Timely and representative data can help local, state, and national public health officials monitor and respond to outbreaks of seasonal influenza. Data from cloud-based electronic health records (EHR) and crowd-sourced influenza surveillance systems have the potential to provide complementary, near real-time estimates of influenza activity. The objectives of this paper are to compare two novel influenza-tracking systems with three traditional healthcare-based influenza surveillance systems at four spatial resolutions: national, regional, state, and city, and to determine the minimum number of participants in these systems required to produce influenza activity estimates that resemble the historical trends recorded by traditional surveillance systems. METHODS:We compared influenza activity estimates from five influenza surveillance systems: 1) patient visits for influenza-like illness (ILI) from the US Outpatient ILI Surveillance Network (ILINet), 2) virologic data from World Health Organization (WHO) Collaborating and National Respiratory and Enteric Virus Surveillance System (NREVSS) Laboratories, 3) Emergency Department (ED) syndromic surveillance from Boston, Massachusetts, 4) patient visits for ILI from EHR, and 5) reports of ILI from the crowd-sourced system, Flu Near You (FNY), by calculating correlations between these systems across four influenza seasons, 2012-16, at four different spatial resolutions in the US. For the crowd-sourced system, we also used a bootstrapping statistical approach to estimate the minimum number of reports necessary to produce a meaningful signal at a given spatial resolution. RESULTS:In general, as the spatial resolution increased, correlation values between all influenza surveillance systems decreased. Influenza-like Illness rates in geographic areas with more than 250 crowd-sourced participants or with more than 20,000 visit counts for EHR tracked government-lead estimates of influenza activity. CONCLUSIONS:With a sufficient number of reports, data from novel influenza surveillance systems can complement traditional healthcare-based systems at multiple spatial resolutions.
| S-EPMC6094455 | biostudies-literature
Project description:Background Despite its high prevalence and clinical significance, clinical measurement of lipoprotein(a) is rare but has not been systematically quantified. We assessed the prevalence of lipoprotein(a) testing overall, in those with various cardiovascular disease (CVD) conditions and in those undergoing cardiac testing across 6 academic medical centers associated with the University of California, in total and by year from 2012 to 2021. Methods and Results In this observational study, data from the University of California Health Data Warehouse on the number of individuals with unique lipoprotein(a) testing, unique CVD diagnoses (using International Classification of Diseases, Tenth Revision [ICD-10], codes), and other unique cardiac testing were collected. The proportion of total individuals, the proportion of individuals with a given CVD diagnosis, and the proportion of individuals with a given cardiac test and lipoprotein(a) testing any time during the study period were calculated. From 2012 to 2021, there were 5 553 654 unique adults evaluated in the University of California health system, of whom 18 972 (0.3%) had lipoprotein(a) testing. In general, those with lipoprotein(a) testing were more likely to be older, men, and White race, with a greater burden of CVD. Lipoprotein(a) testing was performed in 6469 individuals with ischemic heart disease (2.9%), 836 with aortic stenosis (3.1%), 4623 with family history of CVD (3.3%), 1202 with stroke (1.7%), and 612 with coronary artery calcification (6.1%). For most conditions, the prevalence of testing in the same year as the diagnosis of CVD was relatively stable, with a small upward trend over time. Lipoprotein(a) testing was performed in 10 753 individuals (1.8%) who had lipid panels, with higher rates with more specialized testing, including coronary computed tomography angiography (6.8%) and apolipoprotein B (63.0%). Conclusions Lipoprotein(a) testing persists at low rates, even among those with diagnosed CVD, and remained relatively stable over the study period.
| S-EPMC10547299 | biostudies-literature
Project description: Not available
| S-EPMC152636 | biostudies-literature