Patient-Facts: Single Site, Exploratory, Cross-Sectional Analysis

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dc.contributorPatient-Centered Outcomes Research Institute
dc.contributor.authorPEDSnet
dc.contributor.otherChildren's Hospital of Philadelphia
dc.date.accessioned2024-07-30T19:37:10Z
dc.date.created2024-06-05
dc.description.abstractThis check assesses how much clinical data is available for patients. It provides a screen shot of clinical data for a single site.
dc.description.abstract#### How to Access This Check 1. You may access the module's R package in [GitHub](https://github.com/ssdqa/https://github.com/ssdqa/patientfacts).<br> Or, run in R ```{r} install_github('ssdqa/https://github.com/ssdqa/patientfacts') ``` 2. Using the provided vignettes on GitHub or help in R, follow parameter input instructions for "Single Site", "Exploratory Analysis", "Cross-Sectional Analysis" requirements.
dc.identifier.urihttps://pedsnet.org/metadata/handle/20.500.14642/741
dc.publisherPEDSnet
dc.relation.urihttps://github.com/ssdqa/patientfacts
dc.rightsa CC-BY Attribution 4.0 License.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectData Quality Check Categorizations::Data Quality Category::Completeness
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Data Source Comparison::Single Site Analysis
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Exploratory Analysis
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Temporal Evaluation::Cross-Sectional Analysis
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Analysis Level::Person-Level Analysis
dc.subjectData Quality Check Categorizations::Error Detection Approach::Data Quality Probe::Information Density
dc.subjectData Quality Check Categorizations::Error Detection Approach::Data Quality Probe::Missing Expected Data
dc.subjectData Quality Check Categorizations::Error Detection Approach::Clinical Probe::Clinical Follow-Up
dc.subjectData Quality Check Categorizations::Error Detection Approach::Clinical Probe::Utilization Patterns
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Data Visualization::Bar Graph
dc.subjectData Quality Check Categorizations::Dataset Evaluation Strategy::Exploratory Analysis::Frequency Distribution
dc.titlePatient-Facts: Single Site, Exploratory, Cross-Sectional Analysis
dspace.entity.typeDQCheck
local.description.rawThe raw data output of this check produces ten columns of data: <br> | Column | Data Type | Definition | |-----------------------|-----------|----------------------------------------------------------------------------------------------------------------------------------| |`study` | character | a user provided string label for the study | |`site` | character | the name of the site being targeted OR "combined" if multiple sites were provided | |`visit_type` | character | string indicating the visit type | |`domain` | character | string indicating the domain | |`median_all_with0s` | numeric | overall median facts per year of follow up across the cohort, including patients that do not have evidence of the domain | |`median_all_without0s` | numeric | overall median facts per year of follow up across the cohort, excluding patients that do not have evidence of the domain | |`n_tot` | numeric | total number of patients in the cohort | |`n_w_fact` | numeric | number of patients in the cohort with a fact in the domain of interest | |`median_site_with0s` | numeric |`site`-specific median facts per year of follow up across the cohort, including patients that do not have evidence of the domain | |`median_site_without0s` | numeric |`site`-specific median facts per year of follow up across the cohort, excluding patients that do not have evidence of the domain | {.dqcheck-table}
local.description.vizThis check outputs a faceted bar graph that summarizes the median number of facts per patient. The domain is shown along the y-axis with the median fact count along the x-axis. The user can customize the facets used such as visit_type, site, age category, etc.
local.dqcheck.requirementcohort
local.dqcheck.requirementstudy_name
local.dqcheck.requirementpatient_level_tbl
local.dqcheck.requirementvisit_types
local.dqcheck.requirementomop_or_pcornet
local.dqcheck.requirementmulti_or_single_site
local.dqcheck.requirementtime
local.dqcheck.requirementtime_span
local.dqcheck.requirementtime_period
local.dqcheck.requirementp_value
local.dqcheck.requirementage_groups
local.dqcheck.requirementanomaly_or_exploratory
local.dqcheck.requirementdomain_tbl
local.dqcheck.requirementvisit_type_table
local.subject.flatSingle Site Analysis
local.subject.flatExploratory Analysis
local.subject.flatCross-Sectional Analysis
local.subject.flatPerson-Level Analysis
local.subject.flatCompleteness
local.subject.flatInformation Density
local.subject.flatMissing Expected Data
local.subject.flatClinical Follow-Up
local.subject.flatUtilization Patterns
local.subject.flatBar Graph
local.subject.flatFrequency Distribution

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Patient Facts