021-medical_conditions

Medical conditions dataset

The Human Phenotype Project study medical conditions diagnosis data is based on self reported, participant provided information. Self-reported medical diagnosis are coded according to the WHO International Classification of Diseases 11th Revision (ICD-11) codes.

The medical conditions diagnosis information collection in the Human Phenotype Project is based on self reporting of conditions either through direct questions on specific conditions in self filled online questionnaires or through recall of conditions diagnosis in an interview with a research staff member.

During the registration phase of the study, participants are required to provide details about their medical conditions in the Initial Medical Survey. Further data is then gathered during an interview at the baseline visit and using the Follow-up Medical Survey when participants return for subsequent visits. The data source columns indicate where information was collected.

Data availability:

The information is stored in 1 parquet file: medical_conditions.parquet

from pheno_utils import PhenoLoader

pl = PhenoLoader('medical_conditions')
pl

PhenoLoader for medical_conditions with
12 fields
2 tables: ['medical_conditions', 'age_sex']

Data dictionary

pl.dict

	field_string	description_string	folder_id	feature_set	field_type	strata	data_coding	array	pandas_dtype	bulk_file_extension	relative_location	units	bulk_dictionary	sampling_rate	transformation	list_of_tags	stability	sexed	debut	completed
tabular_field_name
medical_condition	Medical condition name	Medical condition name	21	medical_conditions	Text	Primary	NaN	Multiple	string	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
icd11_code	ICD11 code	ICD-11 codes are the latest global system for ...	21	medical_conditions	Text	Primary	NaN	Multiple	string	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
data_source	Data source of medical condition	Data source the self reporting of medical cond...	21	medical_conditions	Text	Primary	NaN	Multiple	string	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
start_month	Start month	Start month	21	medical_conditions	Integer	Primary	NaN	Multiple	int	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
start_year	Start year	Start year	21	medical_conditions	Integer	Primary	NaN	Multiple	int	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
end_month	End month	Start month	21	medical_conditions	Integer	Primary	NaN	Multiple	int	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
end_year	Start year	Start year	21	medical_conditions	Integer	Primary	NaN	Multiple	int	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
collection_timestamp	Collection time	Collection time	21	medical_conditions	Datetime	Collection time	NaN	Single	datetime64[ns, Asia/Jerusalem]	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
collection_date	Collection date	Collection date	21	medical_conditions	Date	Collection time	NaN	Single	datetime64[ns]	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN
timezone	Timezone	Timezone	21	medical_conditions	Categorical (single)	Collection time	NaN	Single	category	NaN	medical_conditions/medical_conditions.parquet	NaN	NaN	NaN	NaN	NaN	Accruing	Both sexes	11/21/2018	NaN