Patient Records Consistency: Single Site, Anomaly Detection, Cross-Sectional Analysis


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dc.contributorPatient-Centered Outcomes Research Institute
dc.contributor.authorPEDSnet Data Coordinating Center
dc.contributor.authorWieand, Kaleigh
dc.contributor.authorBailey, Charles
dc.contributor.authorRazzaghi, Hanieh
dc.contributor.authorDickinson, Kimberley
dc.contributor.otherPEDSnet Data Coordinating Center
dc.date.accessioned2025-01-08T16:06:33Z
dc.date.created2024-12-17
dc.description.abstractThis check provides analyses to identify anomalous data at the level of a single site. The Patient Record Consistency module, part of the larger SSDQA ecosystem, tests the consistency of clinical data representation within a patient's record. The goal is to ensure that the patient's information is confirmatory and complete, such that two events that are expected to co-exist do both occur within the same patient (i.e. a leukemia diagnosis and chemotherapy).
dc.identifier.urihttps://hdl.handle.net/20.500.14642/929
dc.identifier.urihttps://doi.org/10.24373/pdsp-429
dc.publisherPEDSnet
dc.relation.urihttps://github.com/ssdqa/patientrecordconsistency
dc.rightsa CC-BY Attribution 4.0 License.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectSingle Site Analysis
dc.subjectData Anomaly Method
dc.subjectCross-Sectional Analysis
dc.subjectPerson-Level Analysis
dc.titlePatient Records Consistency: Single Site, Anomaly Detection, Cross-Sectional Analysis
dspace.entity.typeDQCheck
local.code.package# install.packages("devtools") devtools::install_github('ssdqa/patientrecordconsistency')
local.description.rawThis check produces a raw data output containing 11 columns of data: <br> |Column |Data Type|Definition | |---------------------|---------|------------------------------------------------------------------------------------| |`site` |character|the name of the site being targeted | |`fu_bin` |character|the categorical bin of follow up time defined by the user in the fu_breaks parameter| |`concept1` |character|the name of the first event being compared in the similarity index | |`concept2` |character|the name of the second event being compared in the similarity index | |`cocount` |numeric |the number of patients with evidence of both events | |`concept1_ct` |numeric |the number of patients with evidence of event 1 | |`concept2_ct` |numeric |the number of patients with evidence of event 2 | |`concept_count_union`|numeric |the number of patients with evidence of either event | |`jaccard_index` |numeric |the jaccard similarity index (cocount / concept_count_union) | |`concept1_prop` |numeric |the proportion of patients with evidence of event 1 (cocount / concept1_ct) | |`concept2_prop` |numeric |the proportion of patients with evidence of event 2 (cocount / concept2_ct) | {.dqcheck-table}
local.description.vizThis check outputs a bar graph displaying the Jaccard similarity index for categories of F/U time. The length of F/U "bins" are provided by the user via a vector of integers for breaks. Each bin includes the starting integer and up to but NOT including the ending integer. For example, [0,1) includes patients with F/U between 0 and 0.99 years.
local.dqcheck.categoryConcordance
local.dqcheck.clinicalprobeConfirmatory Clinical Data
local.dqcheck.clinicalprobeClinical Consistency
local.dqcheck.clinicalprobeExpected Clinical Event Representation
local.dqcheck.measurementJaccard Similarity Index
local.dqcheck.probeMissing Expected Data
local.dqcheck.probeMisclassification Detection
local.dqcheck.requirementcohort
local.dqcheck.requirementprc_event_file
local.dqcheck.requirementomop_or_pcornet
local.dqcheck.requirementmulti_or_single_site
local.dqcheck.requirementanomaly_or_exploratory
local.dqcheck.requirementage_groups
local.dqcheck.requirementpatient_level_tbl
local.dqcheck.requirementfu_breaks
local.dqcheck.requirementp_value
local.dqcheck.requirementtime
local.dqcheck.requirementtime_span
local.dqcheck.requirementtime_period
local.dqcheck.typeCohort Fitness
local.dqcheck.vizBar Graph
relation.isCodeOfDQCheck929c8dfc-2c8b-4e62-8e1d-0fa06c542832
relation.isCodeOfDQCheck.latestForDiscovery929c8dfc-2c8b-4e62-8e1d-0fa06c542832

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Patient Records Consistency