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At least 55 records · Page 3Linked to original sources
PubMed2006

Data sources for measuring comorbidity: a comparison of hospital records and medicare claims for cancer patients.

BACKGROUND: Identifying appropriate comorbidity data sources is a key consideration in health services and outcomes research. OBJECTIVE: Using cancer patients as an example, we compared comorbid conditions identified: 1) on the discharge facesheet versus full hospital medical record and 2) in the hospital record versus Medicare claims, both precancer diagnosis and associated with a cancer treatment-related index hospitalization. METHODS: We used data from 1995 Surveillance, Epidemiology and End Results patterns of care studies for 1,382 patients. Comorbid conditions were ascertained from the hospital record associated with the most definitive cancer treatment and Medicare claims. We calculated the prevalence for and assessed concordances among 12 conditions derived from the hospital record facesheet; full hospital record; Medicare claims precancer diagnosis, with and without a rule-out algorithm applied; and Medicare claims associated with an index hospitalization. RESULTS: The proportion of patients with one or more comorbid conditions varied by data source, from 21% for the facesheet to 85% for prediagnosis Medicare claims without the rule-out algorithm. Condition prevalences were substantially lower for the facesheet compared with the full hospital record. For prediagnosis Medicare claims, condition prevalences were more than 1.7 times greater in the absence of an algorithm to screen for rule-out diagnoses. Measures assessing concordance between the full hospital record and prediagnosis Medicare claims (rule-out algorithm applied) showed modest agreement. CONCLUSIONS: The hospital record and Medicare claims are complementary data sources for identifying comorbid conditions. Comorbidity is greatly underascertained when derived only from the facesheet of the hospital record. Investigators using Part B Medicare claims to measure comorbidity should remove conditions that are listed for purposes of generating bills but are not true comorbidities.

Aged↗
PubMed1984

Epidemiological investigations on rheumatoid arthritis in Stockholm. The use of different data sources.

The general aim of the thesis was to see how different data sources available in Stockholm County could be used for epidemiological investigations on rheumatoid arthritis (RA). The specific aims were: to study the mortality among persons with RA and the causes of the postulated high mortality in RA, to study the possible preventive effect of oral contraceptive use on the incidence of RA and to study the quality of the in-patient register with regard to RA. Four sources were used: An epidemiological survey of RA in Stockholm, the in-patient register of Stockholm County, the Stockholm County sample of the national health interview survey and the national cause-of-death register. These data sources were compared and validated against each other and other data collected. The possibilities and limitations in the use of these different sources were assessed in a series of epidemiological investigations of which the main findings were the following: Persons with RA had an increased mortality compared to the general population. This applied to persons with RA identified in a random sample from the general population as well as to persons hospitalized with RA. The excess mortality was particularly high in the hospitalized group. RA was rarely recorded as the cause of death. The mortality was strongly correlated to the severity of the disease, and drug use was not found to be the main cause of the high mortality. There was a slight reduction in incidence of RA among oral contraceptive users compared with non users, particularly for women with age at onset of RA over 40. At least 80% of the cases recorded as RA in the in-patient register were judged to be "true" cases of RA. The documentation of the cases as well as the accuracy of the diagnosis varied strongly between different types of departments.

Arthritis, Rheumatoid↗
PubMed2002

Automating data acquisition into ontologies from pharmacogenetics relational data sources using declarative object definitions and XML.

Ontologies are useful for organizing large numbers of concepts having complex relationships, such as the breadth of genetic and clinical knowledge in pharmacogenomics. But because ontologies change and knowledge evolves, it is time consuming to maintain stable mappings to external data sources that are in relational format. We propose a method for interfacing ontology models with data acquisition from external relational data sources. This method uses a declarative interface between the ontology and the data source, and this interface is modeled in the ontology and implemented using XML schema. Data is imported from the relational source into the ontology using XML, and data integrity is checked by validating the XML submission with an XML schema. We have implemented this approach in PharmGKB (http://www.pharmgkb.org/), a pharmacogenetics knowledge base. Our goals were to (1) import genetic sequence data, collected in relational format, into the pharmacogenetics ontology, and (2) automate the process of updating the links between the ontology and data acquisition when the ontology changes. We tested our approach by linking PharmGKB with data acquisition from a relational model of genetic sequence information. The ontology subsequently evolved, and we were able to rapidly update our interface with the external data and continue acquiring the data. Similar approaches may be helpful for integrating other heterogeneous information sources in order make the diversity of pharmacogenetics data amenable to computational analysis.

Databases, Factual↗
PubMed2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources.

MOTIVATION: Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. RESULTS: We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is "task agnostic", in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer's disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. AVAILABILITY AND IMPLEMENTATION: miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Humans↗
PubMed1983

Data sources for health care quality evaluation.

The central purpose of this article is to review the major approaches to evaluation of health care quality in terms of its use of different data sources. The areas of application, advantages, and disadvantages of seven data sources are presented, including direct observation, clinical records, record abstracts, clinical and administrative staff survey, patient survey, significant others survey, and population survey. Then the selection of data sources is discussed as this process is influenced by the answers to seven critical questions concerning the context of the quality assurance effort.

Data Collection↗
PubMed2007

Home injuries mortality: sensitivity and specificity analysis of different data sources and operative definitions.

UNLABELLED: The aim of this longitudinal study was to test different operational definitions of home accident mortality. METHODS: The sources of data were the Emergency Information System, hospital discharge reports and the mortality registry of the Lazio Region, 2000-2001. We selected all emergency room visits for unintentional traumas that occurred at home. A 9-month follow-up was performed to calculate mortality rates. A sensitivity analysis of in-hospital mortality, deaths within 30 days and deaths from home accident E-codes was performed. A gold standard definition of home accident-related deaths was proposed. RESULTS: We observed 598 home accident-related fatalities (29.1% of all the deaths found in the follow-up study). In-hospital mortality, deaths within 30 days and deaths for home accident E-codes had sensitivity values of 63.4%, 63.4% and 59.4%, respectively; positive predictive values were 78.1%, 67.1% and 100%, respectively. CONCLUSIONS: The best operational definition of home injury was based on in-hospital mortality, while mortality based on E-codes reported on death certificates was lacking. In order to measure the real burden of home injuries, hospital and mortality data must be integrated.

Accidents, Home↗
PubMed2004

Transplant data: sources, collection, and caveats.

By examining the sources, quality and organization of transplant data available, as well as making observations about data reporting patterns and accuracy, we hope to improve understanding of existing results, help researchers with study design and stimulate new exploratory initiatives. The primary data source, collected by the OPTN, has benefited from extensive recent technological advances. Transplant professionals now report patient and donor data more easily, quickly, and accurately, improving data timeliness and precision. Secondary sources may be incorporated, improving the accuracy and expanding the scope of analyses. For example, auxiliary mortality data allows more accurate survival analysis and conclusions regarding the completeness of center-reported post-transplant follow-up. Furthermore, such sources enable examination of outcomes not reported by centers, such as mortality after waiting list removal, providing more appropriate comparisons of waiting list and post-transplant mortality. Complex collection and reporting processes require specific analytical methods and may lead to potential pitfalls. Patterns in the timing of reporting adverse events differ from those for 'positive' events, yielding the need for care in choosing cohorts and censor dates to avoid bias. These choices are further complicated by the use of multiple sources of data, with different time lags and reporting patterns.

Humans↗
PubMed1997

Data sources for pharmacoeconomic and health services research.

Different types of databases available for health-related research, the data contained in these databases, and potential applications for pharmacists or researchers are discussed. Case studies that demonstrate uses for health databases are presented. Databases can be organized by facility, by health care provider, by disease or organ, or by sector. The types of data they contain include financial data, utilization data, demographic data, and outcomes data. Data can be obtained from the public sector, the private sector, or the researcher's own health system. The costs and time associated with using existing databases are often less than those required to collect data, but the quality and accessibility of the data must also be considered. The researcher's choice of database will depend on the research question. Health care databases can be used for health management and decision-making, quality review and evaluation, outcomes research, episode-of-illness studies, and evaluation of treatment protocols. Researchers must comply with patient-confidentiality and other agreements when accessing data. The format of the data needs to be matched with the hardware and software to be used in the analysis, and the data need to be loaded, verified, and cleaned before use. In deciding which of the many available data sources to use, researchers must determine the appropriate balance between external data and data available within their own health systems. The decision on whether to use existing data sources or to collect data prospectively will depend on the research question, the available resources, and the scope of the study.

Computer Communication Networks↗
PubMed1997

Differences in procedure use, in-hospital mortality, and illness severity by gender for acute myocardial infarction patients: are answers affected by data source and severity measure?

OBJECTIVES: According to some studies, women with heart disease receive fewer procedures and have higher in-hospital death rates than men. These studies vary by data source (hospital discharge abstract versus detailed clinical information) and severity measurement methods. The authors examined whether evaluations of gender differences for acute myocardial infarction patients vary by data source and severity measure. METHODS: The authors considered 10 severity measures: four using clinical medical record data and six using discharge abstracts (diagnosis and procedure codes). The authors studied all 14,083 patients admitted in 1991 for acute myocardial infarction to 100 hospitals nationwide, examining in-hospital death and use of coronary angiography, coronary artery bypass graft surgery (CABG), and percutaneous transluminal coronary angioplasty (PTCA). Logistic regression was used to calculate odds ratios for death and procedure use for women compared with men, controlling for age and each of the severity scores. RESULTS: After adjusting only for age, women were significantly more likely than men to die and less likely to receive CABG and coronary angiography. Severity measures provided different assessments of whether women were sicker than men; for all cases, clinical data-based MedisGroups rated women's severity compared with men's, whereas four code-based severity measures viewed women as sicker. After adjusting for severity and age, women were significantly more likely than men to die in-hospital and less likely to receive coronary angiography and CABG; women and men had relatively equal adjusted odds ratios of receiving PTCA. Odds ratios reflecting gender differences in procedure use and death rates were similar across severity measures. CONCLUSIONS: Comparisons of severity-adjusted in-hospital death rates and invasive procedure use between men and women yielded similar findings regardless of data source and severity measure.

Angioplasty, Balloon, Coronary↗
PubMed2003

Missing, mediocre, or merely obsolete? An evaluation of UK data sources for coronary heart disease.

STUDY OBJECTIVE: Coronary heart disease (CHD) is the commonest cause of death in the UK. However, there is no single comprehensive source of information to support CHD prevention and treatment strategies. Therefore this study evaluated the availability and quality of UK CHD data sources since 1981. DESIGN: Data sources for England and Wales were identified and appraised on: (1) CHD patient numbers (myocardial infarction, angina, hypertension, and heart failure); (2) uptake of medical and surgical CHD treatments, and (3) population trends in major cardiovascular risk factors. SETTING: England and Wales (population 53 million). MAIN RESULTS: Population and mortality data were easily accessible from Office for National Statistics and British Heart Foundation Annual CHD Statistics; population based risk factor data came principally from the British Regional Heart Study, the General Household Survey, and the Health Survey for England. They were limited for 1981, but more extensive by 2000. Hospital admissions information since 1998 was available online from HES; but trend data and details of interventions were scant. Limited primary care data on consultation rates, prescribing, and treatment uptake were available from published audits and studies. CONCLUSIONS: Information on CHD in the UK is fragmented, patchy, and mixed in quality. Data for women, the elderly populatiom, and ethnic minorities were particularly scarce, exacerbating inequalities. Future CHD disease monitoring and evaluation will require comprehensive and accurate population based information on trends in patient numbers, treatment uptake, and risk factors.

Blood Pressure↗
PubMed2006

Variability in physical constant parameter values from standard data sources and the implication of this variability for risk analysis.

Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. However, considerable variability has recently been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis-molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0E + 06 for VP, and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.

Chemical Phenomena↗
PubMed2006

Variability in physical constant parameter values from standard data sources and the implication of this variability for risk analysis.

Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. Recently, however, considerable variability has been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis--molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0 x 10(6) for VP and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.

Journal Article↗
PubMed2005

Development of the Diabetes Indicators and Data Sources Internet Tool (DIDIT).

Developing a Web-based tool that involves the input, buy-in, and collaboration of multiple stakeholders and contractors is a complex process. Several elements facilitated the development of the Web-based Diabetes Indicators and Data Sources Internet Tool (DIDIT). The DIDIT is designed to enhance the ability of staff within the state-based Diabetes Prevention and Control Programs (DPCPs) and the Centers for Disease Control and Prevention (CDC) to perform diabetes surveillance. It contains information on 38 diabetes indicators (measures of health or factors associated with health) and 12 national- and state-level data sources. Developing the DIDIT required one contractor to conduct research on content for diabetes indicators and data sources and another contractor to develop the Web-based application to house and manage the information. During 3 years, a work group composed of representatives from the DPCPs and the Division of Diabetes Translation (DDT) at the CDC guided the development process by 1) gathering information on and communicating the needs of users and their vision for the DIDIT, 2) reviewing and approving content, and 3) providing input into the design and system functions. Strong leadership and vision of the project lead, clear communication and collaboration among all team members, and a commitment from the management of the DDT were essential elements in developing and implementing the DIDIT. Expertise in diabetes surveillance and software development, enthusiasm, and dedication were also instrumental in developing the DIDIT.

Diabetes Mellitus, Type 2↗
PubMed2005

Electronic data sources for kinetic models of cell signaling.

Functional understanding of signaling pathways requires detailed information about the constituent molecules and their interactions. Simulations of signaling pathways therefore build upon a great deal of data from various sources. We first survey electronic data resources for cell signaling modeling and then based on the type of data representation the data sources are broadly classified into five groups. None of the data sources surveyed provide all required data in a ready-to-be-modeled fashion. We then put forward a "wish list" for the desired attributes for an ideal modeling centric database. Finally, we close with perspectives on how electronic data sources for cell signaling modeling have developed. We suggest that future directions in such data sources are largely model-driven and are hinged on interoperability of data sources.

Computer Simulation↗
PubMed1998

The selection of data sources for use in modelling studies.

Economic analysis has become increasingly important in healthcare in general, and particularly with respect to pharmaceuticals. Therefore, it is vital that the methods used in such evaluations are carefully scrutinised and refined. However, guidelines contain only a limited number of recommendations for the use of secondary data in modelling studies. In this manuscript, the selection of data sources in modelling studies will be addressed. The objectives of this manuscript are as follows: (i) to present a general strategy on how to determine the appropriateness of a data source for a model; and (ii) to present recommendations on a transparent reporting format for the selection of data sources.

Drug Costs↗
PubMed2000

A Canadian comparison of data sources for coronary artery bypass surgery outcome "report cards".

BACKGROUND: Prior comparisons of administrative versus clinical data for creating coronary artery bypass graft (CABG) surgery outcome "report cards" are all from the United States and yield inconsistent conclusions regarding the validity of administrative data report cards. In this study, we compared 2 CABG surgery outcome report cards for Ontario, Canada: one derived from clinical data from the Cardiac Care Network of Ontario and one derived from administrative data from the Canadian Institute for Health Information. METHODS: Data from 4 fiscal years, 1992-93 through 1995-96, were used. The Canadian Institute for Health Information report card was derived from administrative data only. The Cardiac Care Network report card drew on prospectively collected clinical information that included variables such as left ventricular ejection fraction but also required linkages to the Canadian Institute for Health Information data for ascertainment of selected comorbidities and in-hospital mortality rates. Logistic regression models were used to calculate risk-adjusted death rates for each of the 9 hospitals performing CABG surgery in Ontario. RESULTS: The risk-adjusted death rates were quite similar between data sources for 7 of the 9 hospitals. For 2 hospitals, rather large absolute differences in adjusted death rates of 0.58% and 0.64% were seen between report cards. There was a strong correlation between data sources for risk-adjusted hospital death rates (intraclass correlation coefficient = 0.927, P <.001) and for rankings of adjusted hospital death rates (Spearman correlation coefficient = 0.828, P =.02). CONCLUSION: These results from Ontario, Canada, reveal general similarities between administrative and clinical data report cards for CABG surgery. However, clinical data are likely needed if individual hospitals are to be publicly scrutinized in outcome report cards.

Adult↗
PubMedDate not supplied

Homicide in the workplace in Ontario: occupations at risk and limitations of existing data sources.

This study has identified workplace homicides in Ontario from 1975 to 1985, described those at risk, and examined what existing data sources are most suitable for locating the occurrence of these events. Homicides were identified from two sources: the Office of the Chief Coroner and the Ontario Mortality Database (OMDB). Of the 84 homicides identified, 87% occurred among males; the average annual work-related homicide rate was 0.17 per 100,000 workers, with a male-to-female ratio of 5.2:1. The rates in males were about one-eighth of those reported in California and Texas. The highest rates occurred among policemen, gas station attendants, security guards, and taxi drivers, and in restaurants and in certain retail operations such as jewelry stores. These homicides represented about 4% of all traumatic workplace fatalities. Firearms were responsible for 56% of these homicides and the motive was robbery in 50%. The OMDB proved to be an awkward source from which to identify such deaths because there is no "injury-at-work" field on death certificates. Other existing sources of data were not able to locate work-related homicides. Guidelines to protect those at high risk of assault and homicide should be developed.

Adolescent↗
PubMed2002

Vital statistics as a data source.

A focus group convened at a National Institutes of Health (NIH) Stillbirth Conference discussed issues related to vital statistics as a data source on fetal mortality. Fetal death is a tragic occurence and part of the continuum of pregnancy outcomes. A primary source of data is the National Vital Statistics System fetal death component, which is routinely used to track mortality trends and to provide the context for nonrepresentative investigations. The data are also used to examine differentials in mortality by characteristics and to evaluate data quality. Issues concerning how to improve the vital statistics data include culture and context; data instrument; persons providing information; what information is available to the information provider; processing issues; and use of data. Perhaps most important is to enhance recognition of fetal death both for the individual confronting a loss and to promote research. Other studies are needed to augment the information obtainable through vital records.

Culture↗