A high positive predictive value algorithm using hospital administrative data identified incident cancer cases.
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Hospital factors and patient characteristics in the treatment of colorectal cancer: a population based study.Using hospital discharge data to identify incident pregnancy-associated cancers: a validation study.Using linked electronic data to validate algorithms for health outcomes in administrative databases.Validation of administrative hospital data for identifying incident pancreatic and periampullary cancer cases: a population-based study using linked cancer registry and administrative hospital data in New South Wales, AustraliaValidating a proxy for disease progression in metastatic cancer patients using prescribing and dispensing data.Identification of patients with nonmelanoma skin cancer using health maintenance organization claims data.Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries.Comparing methods for identifying pancreatic cancer patients using electronic data sources.Risk of hospitalization according to chemotherapy regimen in early-stage breast cancer.Congenital anomalies among live births in a polluted area. A ten-year retrospective study.Compliance with clinical practice guidelines for breast cancer treatment: a population-based study of quality-of-care indicators in ItalyCancer Incidence in HIV-Infected Versus Uninfected Veterans: Comparison of Cancer Registry and ICD-9 Code DiagnosesValidation of a coding algorithm to identify bladder cancer and distinguish stage in an electronic medical records database.Estimation of national colorectal-cancer incidence using claims databasesProtocol for validating cardiovascular and cerebrovascular ICD-9-CM codes in healthcare administrative databases: the Umbria Data Value ProjectIncidence and outcomes of pregnancy-associated cancer in Australia, 1994-2008: a population-based linkage study.Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocolThe impact of the lookback period and definition of confirmatory events on the identification of incident cancer cases in administrative data.Evaluation of algorithms to identify incident cancer cases by using French health administrative databases.Clinical and Economic Consequences of Early Cancer After Kidney Transplantation in Contemporary Practice.Assembling and validating data from multiple sources to study care for Veterans with bladder cancer.Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer.Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study.Measuring colorectal cancer incidence: the performance of an algorithm using administrative health data.Accuracy of administrative databases in detecting primary breast cancer diagnoses: a systematic reviewAccuracy of colorectal cancer ICD-9-CM codes in Italian administrative healthcare databases: a cross-sectional diagnostic studySensitivity and specificity of breast cancer ICD-9-CM codes in three Italian administrative healthcare databases: a diagnostic accuracy study
P2860
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P2860
A high positive predictive value algorithm using hospital administrative data identified incident cancer cases.
description
2007 nî lūn-bûn
@nan
2007 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2007 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
name
A high positive predictive val ...... ntified incident cancer cases.
@ast
A high positive predictive val ...... ntified incident cancer cases.
@en
type
label
A high positive predictive val ...... ntified incident cancer cases.
@ast
A high positive predictive val ...... ntified incident cancer cases.
@en
prefLabel
A high positive predictive val ...... ntified incident cancer cases.
@ast
A high positive predictive val ...... ntified incident cancer cases.
@en
P2093
P50
P1476
A high positive predictive val ...... ntified incident cancer cases.
@en
P2093
Daniela Di Cuonzo
Piera Vicari
Roberto Zanetti
P304
P356
10.1016/J.JCLINEPI.2007.05.017
P50
P577
2007-10-22T00:00:00Z