Abstract
Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.
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The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement
Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.
Misclassification in Administrative Claims Data: Quantifying the Impact on Treatment Effect Estimates
Abstract: Misclassification is present in nearly every epidemiologic study, yet is rarely quantified in analysis in favor of a focus on random error. In this review, we discuss past and present wisdom on misclassification and what measures should be taken to quantify this influential bias, with a focus on bias in pharmacoepidemiologic studies. To date, pharmacoepidemiology primarily uses data obtained from administrative claims, a rich source of prescription data, but susceptible to bias from unobservable factors including medication sample use, medications filled but not taken, health conditions that are not reported in the administrative billing data, and inadequate capture of confounders. Because of the increasing focus on comparative effectiveness research, we provide a discussion of misclassification in the context of an active comparator, including a demonstration of treatment effects biased away from the null in the presence of nondifferential misclassification. Finally, we highlight recently developed methods to quantify bias and offer these methods as potential options for strengthening the validity and quantifying uncertainty of results obtained from pharmacoepidemiologic research.
Administrative Healthcare Data: A Guide to Its Origin, Content, and Application Using SAS
This book provides a concise yet complete foundational knowledge of the business of healthcare.
Administrative Healthcare Data: A Guide to Its Origin, Content, and Application Using SAS explains the source and content of administrative healthcare data, which is the product of …
Excerpt of book can be downloaded or to view it online click here.
Dickstein, Craig, and Renu Gehring. Administrative Healthcare Data: A Guide to Its Origin, Content, and Application Using SAS. SAS Institute, 2014.
Assessing the Safety of New Arthritis Drugs: Are We There Yet?
Performance of a Rheumatoid Arthritis Records-Based Index of Severity
ABSTRACT
Objective. To assess the performance of a rheumatoid arthritis (RA) records-based index of severity (RARBIS) developed by a Delphi panel process in a cohort of patients with RA.
Methods. We reviewed the medical records of 120 RA patients from the New England Veteran’s Administration (VA) Healthcare System and collected data on markers of RA disease severity. Markers were refined through a Delphi panel process before developing the RARBIS based on chart review. The RARBIS includes 5 subscales on surgery, radiography, extraarticular manifestations, clinical status, and laboratory values. Factors that were regarded by the Delphi panel as highly relat- ed to severity of RA were assigned higher points on the index. We assessed the validity of the RAR- BIS by comparing it to the intensity of the actual RA treatment that these patients received: low, nei- ther biologic nor disease modifying antirheumatic drug (DMARD) use; moderate, therapy with DMARD such as hydroxychloroquine, gold, or sulfasalazine; high, treatment with stronger DMARD such as methotrexate, azathioprine, leflunomide, and cyclosporine; and very high, use of any bio- logics.
Results. The RARBIS had a range of 0 to 8. All subscales except extraarticular manifestations were statistically significantly related to intensity of RA treatment (chi-square test p ≤ 0.015); the over- all index was linearly correlated with intensity of RA treatment (r = 0.35, 95% CI 0.18–0.55). After adjusting for age and sex in a linear regression, the RARBIS was found to be an independent pre- dictor of intensity of treatment (ß for 1-point increase in score = 0.16, p = 0.002).
Conclusion. A medical records-based index of RA severity was developed with attention to face and criterion validity that correlated moderately with RA treatment intensity (construct validity) in a VA population. Further tests of the RARBIS are recommended before it can be used as a tool to adjust for RA disease severity in performing epidemiologic studies on the safety of drugs.
Evaluation of QUADAS, a tool for the quality assessment of diagnostic accuracy studies
ABSTRACT
Background: A quality assessment tool for diagnostic accuracy studies, named QUADAS, has recently been developed. Although QUADAS has been used in several systematic reviews, it has not been formally validated. The objective was to evaluate the validity and usefulness of QUADAS.
Methods: Three reviewers independently rated the quality of 30 studies using QUADAS. We assessed the proportion of agreements between each reviewer and the final consensus rating. This was done for all QUADAS items combined and for each individual item. Twenty reviewers who had used QUADAS in their reviews completed a short structured questionnaire on their experience of QUADAS.
Results: Over all items, the agreements between each reviewer and the final consensus rating were 91%, 90% and 85%. The results for individual QUADAS items varied between 50% and 100% with a median value of 90%. Items related to uninterpretable test results and withdrawals led to the most disagreements. The feedback on the content of the tool was generally positive with only small numbers of reviewers reporting problems with coverage, ease of use, clarity of instructions and validity.
Conclusion: Major modifications to the content of QUADAS itself are not necessary. The evaluation highlighted particular difficulties in scoring the items on uninterpretable results and withdrawals. Revised guidelines for scoring these items are proposed. It is essential that reviewers tailor guidelines for scoring items to their review, and ensure that all reviewers are clear on how to score studies. Reviewers should consider whether all QUADAS items are relevant to their review, and whether additional quality items should be assessed as part of their review.
A comparison of individual and area- based socio-economic data for monitoring social inequalities in health
Abstract
Background: Area-based indicators are commonly used to measure and track health outcomes by socio- economic group. This is largely because of the absence of socio-economic information about individuals in health administrative databases. The literature shows that the magnitude of differences in health outcomes varies depending on whether the socio-economic indicators are at the individual level or are area-based. This study compares the two types of indicators.
Data and methods: The data are from a file linking the results of the 1991 Census with deaths that occurred from
1991 to 2000―a 15% sample of the Canadian population aged 25 or older. The socio-economic indicator used for comparison is a material and social deprivation index, in individual and area- based versions. The health indicators are life expectancy and disability-free life expectancy, and risks of mortality and disability.
Results: The individual version of the deprivation index yields wider gaps in life expectancy and disability- free life expectancy than does the area-based version. These gaps vary by sex and geographic setting. However, both versions are associated with inequalities in mortality and disability, independent of each other.
Interpretation: Despite some limitations, area-based socio- economic indicators are useful in assessing inequalities in health. The inequalities that they identify are significant, consistent and reliable and can be tracked through time and for different geographic settings.
Keywords
area-based measure, deprivation, disability-free life expectancy, geography, life expectancy, social inequalities
The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration
The quality of reporting of studies of diagnostic accuracy is less than optimal. Complete and accurate reporting is necessary to enable readers to assess the potential for bias in the study and to evaluate the generalizability of the results.
A group of scientists and editors has developed the STARD (Standards for Reporting of Diagnostic Accuracy) statement to improve the reporting the quality of reporting of studies of diagnostic accuracy. The statement consists of a checklist of 25 items and flow diagram that authors can use to ensure that all relevant information is present.
This explanatory document aims to facilitate the use, under- standing, and dissemination of the checklist. The document contains a clarification of the meaning, rationale, and optimal use of each item on the checklist, as well as a short summary of the available evidence on bias and applicability.
The STARD statement, checklist, flowchart, and this explanation and elaboration document should be useful resources to improve reporting of diagnostic accuracy studies. Complete and informative reporting can only lead to better decisions in health care.
Veteran’s affairs hospital discharge databases coded serious bacterial infections accurately
Abstract
Objectives: We sought to test the ability of large health care utilization databases to accurately identify serious bacterial infections and opportunistic infections leading to hospital admission.
Study Design and Setting: We conducted a cross-sectional validation study using patients admitted to hospitals in the administrative database of the Department of Veterans Affairs, VISN 1, between 2001 and 2004. Detailed hospital chart abstraction protocols were developed to define a gold-standard diagnosis of serious bacterial infections and opportunistic infections. Hospital acquired infections were not considered.
Results: A total of 158 patients who were hospitalized for selected bacterial infections and 69 patients for opportunistic infections were identified using ICD-9 discharge diagnoses. The positive predictive values (PPV) of identifying specific bacterial infections that lead to hospital admissions varied between 100% and 66%. All conditions combined yielded a PPV of 80%. Once the gold-standard definition of bacterial conditions was broadened to hospital admissions due to any acute infectious condition, the PPV increased to 90%. Excluding systemic candidiasis, the average PPV for the selected opportunistic infections was 76%.
Conclusion: Our findings suggest that ICD-9 codes of selected serious infections from hospital discharge files can be used as substitutes for chart-based diagnoses.