Validation of Self-Reported Race in a Canadian Provincial Renal Administrative Database

Background:Administrative data are commonly used to study clinical outcomes in renal disease. Race is an important determinant of renal health delivery and outcomes in Canada but is not validated in most administrative data, and the correlation with census-based definitions of race is unknown.Objectives:Validation of self-reported race (SRR) in a Canadian provincial renal administrative database (Patient Records and Outcome Management Information System [PROMIS]) and comparison with the Canadian census categories of race.Design:Prospective patient survey study to validate SRR in PROMIS.Setting:British Columbia, Canada.Patients:Adult patients registered in PROMIS.Measurements:Survey SRR was used as gold standard to validate SRR in PROMIS. Self-reported race in PROMIS was compared with census race categories.Methods:This is a cross-sectional telephone survey of a random sample of all adults in PROMIS conducted between February 2016 and November 2016. Responders selected a race category from PROMIS and from the Canadian census. Sensitivity (Sn) and specificity (Sp) were calculated with 95% confidence intervals (CIs).Results:A total of 21 039 patients met inclusion criteria, 1677 were selected for the survey and 637 participated (38% response rate). There were no differences between the PROMIS, sampled, and responder populations. PROMIS SRR had an accuracy of 95.3% (95% CI: 94.2%-97.0%) when validated against the survey SRR with Sn and Sp ≥90% in all race groups except in Aboriginals (Sn 87.5%). The positive and negative predictive values were ≥95%, except in very low and high–prevalence groups, respectively. The Canadian census had an accuracy of 95.7% (95% CI: 94.4%-97.6%) when validated against PROMIS SRR with Sn and Sp ≥90%. The results did not differ in subgroups based on age, sex, birth outside Canada, or renal group (glomerulonephritis, chronic kidney disease, hemodialysis, peritoneal dialysis, transplant recipients, or live donors).Limitations:Analysis of minority groups and lower prevalence groups is limited by sample size. Results may not be generalizable to other administrative databases.Conclusions:We have shown high accuracy of PROMIS SRR that validates its use in the secondary analysis of administrative data for research. There is high correlation between PROMIS and census race categories which allows linkage with other data sources that use census-based definitions of race.

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Estimation of National Colorectal-Cancer Incidence Using Claims Databases

Journal of Cancer Epidemiology ◽

10.1155/2012/298369 ◽

2012 ◽

Vol 2012 ◽

pp. 1-7 ◽

Cited By ~ 35

Author(s):

C. Quantin ◽

E. Benzenine ◽

M. Hägi ◽

B. Auverlot ◽

M. Abrahamowicz ◽

...

Keyword(s):

Colorectal Cancer ◽

Administrative Data ◽

Cancer Incidence ◽

Past History ◽

Cancer Registries ◽

Administrative Databases ◽

Administrative Database ◽

Predictive Values ◽

Colorectal Cancer Incidence ◽

Incident Cases

Background.The aim of the study was to assess the accuracy of the colorectal-cancer incidence estimated from administrative data.Methods.We selected potential incident colorectal-cancer cases in 2004-2005 French administrative data, using two alternative algorithms. The first was based only on diagnostic and procedure codes, whereas the second considered the past history of the patient. Results of both methods were assessed against two corresponding local cancer registries, acting as “gold standards.” We then constructed a multivariable regression model to estimate the corrected total number of incident colorectal-cancer cases from the whole national administrative database.Results.The first algorithm provided an estimated local incidence very close to that given by the regional registries (646 versus 645 incident cases) and had good sensitivity and positive predictive values (about 75% for both). The second algorithm overestimated the incidence by about 50% and had a poor positive predictive value of about 60%. The estimation of national incidence obtained by the first algorithm differed from that observed in 14 registries by only 2.34%.Conclusion.This study shows the usefulness of administrative databases for countries with no national cancer registry and suggests a method for correcting the estimates provided by these data.

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Accuracy of ICD-9 coding for Clostridium difficile infections: a retrospective cohort

Epidemiology and Infection ◽

10.1017/s0950268806007655 ◽

2006 ◽

Vol 135 (6) ◽

pp. 1010-1013 ◽

Cited By ~ 82

Author(s):

D. B. SCHEURER ◽

L. S. HICKS ◽

E. F. COOK ◽

J. L. SCHNIPPER

Keyword(s):

Clostridium Difficile ◽

Administrative Data ◽

Epidemiological Surveillance ◽

Administrative Database ◽

Test Results ◽

Micro Data ◽

Cytotoxic Assay ◽

Predictive Values ◽

Sensitivity Specificity ◽

Microbiological Data

SUMMARYClostridium difficile (C. diff) is a major nosocomial problem. Epidemiological surveillance of the disease can be accomplished by microbiological or administrative data. Microbiological tracking is problematic since it does not always translate into clinical disease, and it is not always available. Tracking by administrative data is attractive, but ICD-9 code accuracy for C. diff is unknown. By using a large administrative database of hospitalized patients with C. diff (by ICD-9 code or cytotoxic assay), this study found that the sensitivity, specificity, positive, and negative predictive values of ICD-9 coding were 71%, 99%, 87%, and 96% respectively (using micro data as the gold standard). When only using symptomatic patients the sensitivity increased to 82% and when only using symptomatic patients whose test results were available at discharge, the sensitivity increased to 88%. C. diff ICD-9 codes closely approximate true C. diff infection, especially in symptomatic patients whose test results are available at the time of discharge, and can therefore be used as a reasonable alternative to microbiological data for tracking purposes.

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Administrative Data Fail to Accurately Identify Cases of Healthcare-Associated Infection

Infection Control and Hospital Epidemiology ◽

10.1086/502684 ◽

2006 ◽

Vol 27 (4) ◽

pp. 332-337 ◽

Cited By ~ 77

Author(s):

Eileen R. Sherman ◽

Kateri H. Heydon ◽

Keith H. St. John ◽

Eva Teszner ◽

Susan L. Rettig ◽

...

Keyword(s):

Positive Predictive Value ◽

Administrative Data ◽

Active Surveillance ◽

Predictive Value ◽

Healthcare Associated Infection ◽

Cross Sectional ◽

Policy Makers ◽

Predictive Values ◽

Healthcare Associated ◽

Very High

Objective.Some policy makers have embraced public reporting of healthcare-associated infections (HAIs) as a strategy for improving patient safety and reducing healthcare costs. We compared the accuracy of 2 methods of identifying cases of HAI: review of administrative data and targeted active surveillance.Design, Setting, and Participants.A cross-sectional prospective study was performed during a 9-month period in 2004 at the Children's Hospital of Philadelphia, a 418-bed academic pediatric hospital. “True HAI” cases were defined as those that met the definitions of the National Nosocomial Infections Surveillance System and that were detected by a trained infection control professional on review of the medical record. We examined the sensitivity and the positive and negative predictive values of identifying HAI cases by review of administrative data and by targeted active surveillance.Results.We found similar sensitivities for identification of HAI cases by review of administrative data (61%) and by targeted active surveillance (76%). However, the positive predictive value of identifying HAI cases by review of administrative data was poor (20%), whereas that of targeted active surveillance was 100%.Conclusions.The positive predictive value of identifying HAI cases by targeted active surveillance is very high. Additional investigation is needed to define the optimal detection method for institutions that provide HAI data for comparative analysis.

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How to use administrative data for surgical outcomes in acute diverticulitis

General Surgery ◽

10.18282/gs.v1i1.32 ◽

2016 ◽

Vol 1 (1) ◽

pp. 15 ◽

Cited By ~ 2

Author(s):

Michael K-Y Hong ◽

Anita R Skandarajah ◽

Omar D Faiz ◽

Ian P Hayes

Keyword(s):

New Zealand ◽

Administrative Data ◽

Surgical Outcomes ◽

Acute Diverticulitis ◽

Complicated Diverticulitis ◽

Administrative Database ◽

Coding System ◽

Diverticular Bleeding ◽

Predictive Values ◽

Uncomplicated Diverticulitis

<p>The measurement of quality outcomes is crucial in surgical care. Administrative data are increasingly used but their ability to provide clinically useful information is reliant on how closely the coding can define a particular cohort. In acute admissions for diverticular disease, it is important to differentiate between complicated and uncomplicated diverticulitis, and between diverticulitis and diverticular bleeding. We aim to develop a method to define clinically relevant cohorts of patients from an administrative database in acute diverticulitis. Codes for acute diverticulitis were found from the ICD-10-AM (Australia and New Zealand) coding system, and the accuracy was established with retrospective chart review and cross-referenced with a clinical database at a single institution. Coding of non-diverticular and missed diverticular cases was examined to determine non-diverticular codes that could differentiate these cases. These were combined into logic algorithms designed to differentiate between uncomplicated and complicated diverticulitis admissions derived from an administrative database. Specific K57 diverticular codes possessed sensitivity and positive predictive values of 0.92 and 0.69 for uncomplicated diverticulitis, respectively, with 0.61 and 0.92 for complicated diverticulitis, respectively, based on 153 cases. Most of the missing cases were usually complicated diverticulitis whilst some cases coded incorrectly as uncomplicated diverticulitis were often found as undifferentiated abdominal pain. Diagnostic codes combined into algorithms that accounted for predictable variations improved cohort definition. In conclusion, algorithms with combined codes improved definitions of clinically relevant cohorts for acute diverticulitis from an Australian or New Zealand administrative database. This method may be used to develop logic algorithms for other surgical conditions and enable widespread measurement of relevant surgical outcomes.</p>

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Validation of Coding Algorithms for the Identification of Patients with Primary Biliary Cirrhosis Using Administrative Data

Canadian Journal of Gastroenterology ◽

10.1155/2010/237860 ◽

2010 ◽

Vol 24 (3) ◽

pp. 175-182 ◽

Cited By ~ 12

Author(s):

Robert P Myers ◽

Abdel Aziz M Shaheen ◽

Andrew Fong ◽

Alex F Wan ◽

Mark G Swain ◽

...

Keyword(s):

Primary Biliary Cirrhosis ◽

Administrative Data ◽

Large Scale ◽

Optimal Algorithm ◽

Epidemiological Studies ◽

Population Based ◽

Sensitivity Analyses ◽

Administrative Databases ◽

Biliary Cirrhosis ◽

Predictive Values

BACKGROUND: Large-scale epidemiological studies of primary biliary cirrhosis (PBC) have been hindered by difficulties in case ascertainment.OBJECTIVE: To develop coding algorithms for identifying PBC patients using administrative data – a widely available data source.METHODS: Population-based administrative databases were used to identify patients with a diagnosis code for PBC from 1994 to 2002. Coding algorithms for confirmed PBC (two or more of antimitochondrial antibody positivity, cholestatic liver biochemistry and/or compatible liver histology) were derived using chart abstraction data as the reference. Patients with a recorded PBC diagnosis but insufficient confirmatory data were classified as ‘suspected PBC’.RESULTS: Of 189 potential PBC cases, 119 (60%) had confirmed PBC and 28 (14%) had suspected PBC. The optimal algorithm including two or more uses of a PBC code had a sensitivity of 94% (95% CI 71% to 100%) and positive predictive values of 73% (95% CI 61% to 75%) for confirmed PBC, and 89% (95% CI 82% to 94%) for confirmed or suspected PBC. Sensitivity analyses revealed greater accuracy among women, and with the use of multiple data sources and one or more years of data. Inclusion of diagnosis codes for conditions frequently misclassified as PBC did not improve algorithm performance.CONCLUSIONS: Administrative databases can reliably identify patients with PBC and may facilitate epidemiological investigations of this condition.

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Factors associated with use of restraints on older adults with home care: A secondary analysis of a cross-sectional survey study

International Journal of Nursing Studies ◽

10.1016/j.ijnurstu.2018.07.019 ◽

2019 ◽

Vol 89 ◽

pp. 39-45 ◽

Cited By ~ 2

Author(s):

Kristien Scheepmans ◽

Koen Milisen ◽

Koen Vanbrabant ◽

Louis Paquay ◽

Hendrik Van Gansbeke ◽

...

Keyword(s):

Older Adults ◽

Home Care ◽

Secondary Analysis ◽

Survey Study ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Factors Associated

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Response to: ‘COVID-19 in paediatric rheumatology patients treated with b/tsDMARDs: a cross-sectional patient survey study’ by Cuceoglu et al

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-218364 ◽

2020 ◽

pp. annrheumdis-2020-218364

Author(s):

Carlo Salvarani ◽

Gianluigi Bajocchi ◽

Pamela Mancuso ◽

Elena Galli ◽

Francesco Muratore ◽

...

Keyword(s):

Patient Survey ◽

Paediatric Rheumatology ◽

Survey Study ◽

Cross Sectional

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Accuracy of reporting of Aboriginality on administrative health data collections using linked data in NSW, Australia

BMC Medical Research Methodology ◽

10.1186/s12874-020-01152-2 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Michael A. Nelson ◽

Kim Lim ◽

Jason Boyd ◽

Damien Cordery ◽

Allan Went ◽

...

Keyword(s):

Record Linkage ◽

Linked Data ◽

Aboriginal People ◽

Patient Survey ◽

Health Data ◽

Weight Of Evidence ◽

Cross Sectional ◽

Predictive Values ◽

Administrative Health Data ◽

Data Collections

Abstract Background Aboriginal people are under-reported on administrative health data in Australia. Various approaches have been used or proposed to improve reporting of Aboriginal people using linked records. This cross-sectional study used self-reported Aboriginality from the NSW Patient Survey Program (PSP) as a reference standard to assess the accuracy of reporting of Aboriginal people on NSW Admitted Patient (APDC) and Emergency Department Data Collections (EDDC), and compare the accuracy of selected approaches to enhance reporting Aboriginality using linked data. Methods Ten PSP surveys were linked to five administrative health data collections, including APDC, EDDC, perinatal, and birth and death registration records. Accuracy of reporting of Aboriginality was assessed using sensitivity, specificity, and positive and negative predictive values (PPVs and NPVs) and F score for the EDDC and APDC as baseline and four enhancement approaches using linked records: “Most recent linked record”, “Ever reported as Aboriginal”, and two approaches using a weight of evidence, “Enhanced Reporting of Aboriginality (ERA) algorithm” and “Multi-stage median (MSM)”. Results There was substantial under-reporting of Aboriginality on APDC and EDDC records (sensitivities 84 and 77% respectively) with PPVs of 95% on both data collections. Overall, specificities and NPVs were above 98%. Of people who were reported as Aboriginal on the PSP, 16% were not reported as Aboriginal on any of their linked records. Record linkage approaches generally increased sensitivity, accompanied by decrease in PPV with little change in overall F score for the APDC and an increase in F score for the EDDC. The “ERA algorithm” and “MSM” approaches provided the best overall accuracy. Conclusions Weight of evidence approaches are preferred when record linkage is used to improve reporting of Aboriginality on administrative health data collections. However, as a substantial number of Aboriginal people are not reported as Aboriginal on any of their linked records, improvements in reporting are incomplete and should be taken into account when interpreting results of any analyses. Enhancement of reporting of Aboriginality using record linkage should not replace efforts to improve recording of Aboriginal people at the point of data collection and addressing barriers to self-identification for Aboriginal people.

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Validity of administrative database code algorithms to identify vascular access placement, surgical revisions, and secondary patency

The Journal of Vascular Access ◽

10.1177/1129729818762008 ◽

2018 ◽

Vol 19 (6) ◽

pp. 561-568 ◽

Cited By ~ 2

Author(s):

Ahmed A Al-Jaishi ◽

Louise M Moist ◽

Matthew J Oliver ◽

Danielle M Nash ◽

Jamie L Fleet ◽

...

Keyword(s):

Positive Predictive Value ◽

Administrative Data ◽

Vascular Access ◽

Predictive Value ◽

Catheter Insertion ◽

Administrative Databases ◽

Secondary Patency ◽

Operating Characteristics ◽

Predictive Values ◽

Arteriovenous Access

Background: We assessed the validity of physician billing codes and hospital admission using International Classification of Diseases 10th revision codes to identify vascular access placement, secondary patency, and surgical revisions in administrative data. Methods: We included adults (≥18 years) with a vascular access placed between 1 April 2004 and 31 March 2013 at the University Health Network, Toronto. Our reference standard was a prospective vascular access database (VASPRO) that contains information on vascular access type and dates of placement, dates for failure, and any revisions. We used VASPRO to assess the validity of different administrative coding algorithms by calculating the sensitivity, specificity, and positive predictive values of vascular access events. Results: The sensitivity (95% confidence interval) of the best performing algorithm to identify arteriovenous access placement was 86% (83%, 89%) and specificity was 92% (89%, 93%). The corresponding numbers to identify catheter insertion were 84% (82%, 86%) and 84% (80%, 87%), respectively. The sensitivity of the best performing coding algorithm to identify arteriovenous access surgical revisions was 81% (67%, 90%) and specificity was 89% (87%, 90%). The algorithm capturing arteriovenous access placement and catheter insertion had a positive predictive value greater than 90% and arteriovenous access surgical revisions had a positive predictive value of 20%. The duration of arteriovenous access secondary patency was on average 578 (553, 603) days in VASPRO and 555 (530, 580) days in administrative databases. Conclusion: Administrative data algorithms have fair to good operating characteristics to identify vascular access placement and arteriovenous access secondary patency. Low positive predictive values for surgical revisions algorithm suggest that administrative data should only be used to rule out the occurrence of an event.

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Diagnostic Accuracy of Health Care Administrative Diagnosis Codes to Identify Nontuberculous Mycobacteria Disease: A Systematic Review

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab035 ◽

2021 ◽

Vol 8 (5) ◽

Author(s):

Carlos Mejia-Chew ◽

Lauren Yaeger ◽

Kevin Montes ◽

Thomas C Bailey ◽

Margaret A Olsen

Keyword(s):

Health Care ◽

Diagnostic Accuracy ◽

Administrative Data ◽

International Classification Of Diseases ◽

Administrative Database ◽

Cochrane Central Register ◽

Predictive Values ◽

Diagnosis Codes ◽

Database Research ◽

Classification Of Diseases

Abstract Background Health care administrative database research frequently uses standard medical codes to identify diagnoses or procedures. The aim of this review was to establish the diagnostic accuracy of codes used in administrative data research to identify nontuberculous mycobacterial (NTM) disease, including lung disease (NTMLD). Methods We searched Ovid Medline, Embase, Scopus, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov from inception to April 2019. We included studies assessing the diagnostic accuracy of International Classification of Diseases, 9th edition, Clinical Modification (ICD-9-CM) diagnosis codes to identify NTM disease and NTMLD. Studies were independently assessed by 2 researchers, and the Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess bias and quality. Results We identified 5549 unique citations. Of the 96 full-text articles reviewed, 7 eligible studies of moderate quality (3730 participants) were included in our review. The diagnostic accuracy of ICD-9-CM diagnosis codes to identify NTM disease varied widely across studies, with positive predictive values ranging from 38.2% to 100% and sensitivity ranging from 21% to 93%. For NTMLD, 4 studies reported diagnostic accuracy, with positive predictive values ranging from 57% to 64.6% and sensitivity ranging from 21% to 26.9%. Conclusions Diagnostic accuracy measures of codes used in health care administrative data to identify patients with NTM varied across studies. Overall the positive predictive value of ICD-9-CM diagnosis codes alone is good, but the sensitivity is low; this method is likely to underestimate case numbers, reflecting the current limitations of coding systems to capture NTM diagnoses.

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