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raw.tpp schema

Available on backends: TPP

This schema defines the data (both primary care and externally linked) available in the
OpenSAFELY-TPP backend. For more information about this backend, see
"SystmOne Primary Care".

The data provided by this schema are minimally transformed. They are very close to the
data provided by the underlying database tables. They are provided for data development
and data curation purposes.

from ehrql.tables.raw.tpp import (
    apcs_cost_historical,
    apcs_historical,
    covid_therapeutics_raw,
    isaric,
    medications,
    ons_deaths,
    wl_clockstops,
    wl_openpathways,
)

many rows per patient

apcs_cost_historical

This table contains some historical APCS cost data.

It has been exposed to users for data exploration, and may be removed in future.

Columns

apcs_ident 🔗 integer: Never NULL
grand_total_payment_mff 🔗 float
tariff_initial_amount 🔗 float
tariff_total_payment 🔗 float
admission_date 🔗 date
discharge_date 🔗 date

many rows per patient

apcs_historical

This table contains some historical APCS data.

It has been exposed to users for data exploration, and may be removed in future.

Columns

apcs_ident 🔗 integer: Never NULL
admission_date 🔗 date
discharge_date 🔗 date
spell_core_hrg_sus 🔗 string

many rows per patient

covid_therapeutics_raw

The COVID Therapeutics dataset contains information on COVID treatments used in inpatient
and outpatient settings.

Metadata

Data provider NHS England
Participation / Coverage Inpatients and outpatients treated with antivirals/nMABs for COVID-19 in England
Provenance Data sourced largely from BlueTeq system (forms completed by clinicians)
Update frequency in OpenSAFELY Approximately weekly
Delay between event occurring and event appearing in OpenSAFELY Approximately 2-9 days
Collected information Treatment start date; therapeutic intervention; COVID indication, current status, risk group, region

Overview

Antivirals and neutralising monoclonal antibodies (nMABs) for COVID-19 can be
administered in inpatient setting or, for outpatients, in COVID Medicine Delivery
Units (CMDUs) specifically set up for this purpose. For patients considered for
these treatments, clinicians submit completed forms to NHS England. Each row
represents one completed form for one course of treatment. Data received by
OpenSAFELY currently covers patients who were approved for treatment. The patient
may or may not have actually received the treatment or completed the course (but we
assume that they usually do). They may have another form completed for another
treatment, either because it was decided to give them a different treatment, or for
some other reason. They may in theory also have another form completed some months
later for another instance of infection.

Treatment dates may be in the past or future at the point when the form is
submitted.

Note that this dataset contains some duplicate rows – some full duplicates and
some partial duplicates.

More Information

Treatment guidelines
Draft Data Report (currently only available to internal staff)

Columns

current_status 🔗 string

Status of form/application.

Possible values: Approved, Treatment Complete, Treatment Not Started, Treatment Stopped

covid_indication 🔗 string

Treatment setting/indication.

Possible values: non_hospitalised, hospitalised_with, hospital_onset

diagnosis 🔗 string

Always has the value 'Covid-19'.

intervention 🔗 string

Intervention or therapeutic name. Expected to be one of:

Baricitinib
Casirivimab and imdevimab
Molnupiravir
Paxlovid
Remdesivir
sarilumab (sic)
Sotrovimab
Tocilizumab

treatment_start_date 🔗 date

Entered by the clinician and can represent either a future planned start
date or a past date at the time of form submission.

CASIM05_risk_cohort 🔗 string

High-risk group to which the patient was considered to belong. Derived from
tick-boxes. Multiple groups can be selected and will be joined with the word
and e.g. liver disease and rare neurological conditions.

The available groups as at the time of writing are listed below. However
note that the precise wording used has changed over time and so filtering by
a specific disease name may not be reliable.

Downs syndrome
HIV or AIDS
IMID
haematologic malignancy
Patients with a haematological diseases (sic)
immune deficiencies
liver disease
primary immune deficiencies
rare neurological conditions
rare neurological diseases
renal disease
sickle cell disease
solid cancer
solid organ recipients
stem cell transplant recipients

MOL1_high_risk_cohort 🔗 string

The available groups as at the time of writing are listed below. However
note that the precise wording used has changed over time and so filtering by
a specific disease name may not be reliable.

Downs syndrome
HIV or AIDS
IMID
haematologic malignancy
Patients with a haematological diseases (sic)
immune deficiencies
liver disease
primary immune deficiencies
rare neurological conditions
rare neurological diseases
renal disease
sickle cell disease
solid cancer
solid organ recipients
stem cell transplant recipients

SOT02_risk_cohorts 🔗 string

The available groups as at the time of writing are listed below. However
note that the precise wording used has changed over time and so filtering by
a specific disease name may not be reliable.

Downs syndrome
HIV or AIDS
IMID
haematologic malignancy
Patients with a haematological diseases (sic)
immune deficiencies
liver disease
primary immune deficiencies
rare neurological conditions
rare neurological diseases
renal disease
sickle cell disease
solid cancer
solid organ recipients
stem cell transplant recipients

form_name 🔗 string

Name and version of the patient registration form used to register the
treatment.

received 🔗 date

Date form submitted.

count 🔗 integer

Number of forms.

age_at_received_date 🔗 integer

Can occasionally be zero, presumably indicating an unknown or missing value
as minimum eligibility age is 12.

region 🔗 string

NHS England region in which the CMDU submitting the form is located.

load_date 🔗 date

Date on which the current dataset was imported.

many rows per patient

isaric

ISARIC is a dataset of COVID-19-related hospital admissions,
with coverage across the majority of hospitals across the UK,
including much richer clinical information
than collected in national Hospital Episode Statistics datasets.

The data in this table covers a subset of the ISARIC data columns available in TPP,
sourced from the ISARIC COVID-19 Clinical Database.

All columns included have deliberately been taken as strings while in a preliminary phase.

Descriptions taken from CCP_REDCap_ISARIC_data_dictionary_codebook.pdf
which also has information on the data expected for each column.

!!! warning
ISARIC data can only be used in collaboration with ISARIC researchers
who must be involved in working on the study and writing it up.

Refer to the OpenSAFELY database build report
to see when this data was last updated.

Columns

age 🔗 string: Age
age_factor 🔗 string: TODO
calc_age 🔗 string: Calculated age (comparing date of birth with date of enrolment). May be inaccurate if a date of February 29 is used.
sex 🔗 string: Sex at birth.
ethnic___1 🔗 string: Ethnic group: Arab.
ethnic___2 🔗 string: Ethnic group: Black.
ethnic___3 🔗 string: Ethnic group: East Asian.
ethnic___4 🔗 string: Ethnic group: South Asian.
ethnic___5 🔗 string: Ethnic group: West Asian.
ethnic___6 🔗 string: Ethnic group: Latin American.
ethnic___7 🔗 string: Ethnic group: White.
ethnic___8 🔗 string: Ethnic group: Aboriginal/First Nations.
ethnic___9 🔗 string: Ethnic group: Other.
ethnic___10 🔗 string: Ethnic group: N/A.
covid19_vaccine 🔗 string: Has the patient received a Covid-19 vaccine (open label licenced product)?
covid19_vaccined 🔗 date: Date first vaccine given (Covid-19) if known.
covid19_vaccine2d 🔗 date: Date second vaccine given (Covid-19) if known.
covid19_vaccined_nk 🔗 string: First vaccine given (Covid-19) but date not known.
corona_ieorres 🔗 string: Suspected or proven infection with pathogen of public health interest.
coriona_ieorres2 🔗 string: Proven or high likelihood of infection with pathogen of public health interest.
coriona_ieorres3 🔗 string: Proven infection with pathogen of public health interest.
inflammatory_mss 🔗 string: Adult or child who meets case definition for inflammatory multi-system syndrome (MIS-C/MIS-A).
cestdat 🔗 date: Onset date of first/earliest symptom.
chrincard 🔗 string: Chronic cardiac disease, including congenital heart disease (not hypertension).

Possible values: YES, NO, Unknown
hypertension_mhyn 🔗 string: Hypertension (physician diagnosed).

Possible values: YES, NO, Unknown
chronicpul_mhyn 🔗 string: Chronic pulmonary disease (not asthma).

Possible values: YES, NO, Unknown
asthma_mhyn 🔗 string: Asthma (physician diagnosed).

Possible values: YES, NO, Unknown
renal_mhyn 🔗 string: Chronic kidney disease.

Possible values: YES, NO, Unknown
mildliver 🔗 string: Mild liver disease.

Possible values: YES, NO, Unknown
modliv 🔗 string: Moderate or severe liver disease

Possible values: YES, NO, Unknown
chronicneu_mhyn 🔗 string: Chronic neurological disorder.

Possible values: YES, NO, Unknown
malignantneo_mhyn 🔗 string: Malignant neoplasm.

Possible values: YES, NO, Unknown
chronichaemo_mhyn 🔗 string: Chronic haematologic disease.

Possible values: YES, NO, Unknown
aidshiv_mhyn 🔗 string: AIDS/HIV.

Possible values: YES, NO, Unknown
obesity_mhyn 🔗 string: Obesity (as defined by clinical staff).

Possible values: YES, NO, Unknown
diabetes_type_mhyn 🔗 string: Diabetes and type.

Possible values: NO, 1, 2, N/K
diabetescom_mhyn 🔗 string: Diabetes with complications.

Possible values: YES, NO, Unknown
diabetes_mhyn 🔗 string: Diabetes without complications.

Possible values: YES, NO, Unknown
rheumatologic_mhyn 🔗 string: Rheumatologic disorder.

Possible values: YES, NO, Unknown
dementia_mhyn 🔗 string: Dementia.

Possible values: YES, NO, Unknown
malnutrition_mhyn 🔗 string: Malnutrition.

Possible values: YES, NO, Unknown
smoking_mhyn 🔗 string: Smoking.

Possible values: Yes, Never Smoked, Former Smoker, N/K
hostdat 🔗 date: Admission date at this facility.
hooccur 🔗 string: Transfer from other facility?
hostdat_transfer 🔗 date: Admission date at previous facility.
hostdat_transfernk 🔗 string: Admission date at previous facility not known.
readm_cov19 🔗 string: Is the patient being readmitted with Covid-19?
dsstdat 🔗 date: Date of enrolment.
dsstdtc 🔗 date: Outcome date.

many rows per patient

medications

This table is an extension of the tpp.medications table.

It contains additional fields whose contents are not yet well understood, with the
aim of facilitating exploratory analysis for data development and data curation
purposes.

Columns

date 🔗 date
dmd_code 🔗 dm+d code
consultation_id 🔗 integer: ID of the consultation associated with this event
medication_status 🔗 integer: Medication status. The values might map to the descriptions below from the
data dictionary. Note that this still needs to be confirmed.

0 - Normal

4 - Historical

5 - Blue script

6 - Private

7 - Not in possession

8 - Repeat dispensed

9 - In possession

10 - Dental

11 - Hospital

12 - Problem substance

13 - From patient group direction

14 - To take out

15 - On admission

16 - Regular medication

17 - As required medication

18 - Variable dose medication

19 - Rate-controlled single regular

20 - Only once

21 - Outpatient

22 - Rate-controlled multiple regular

23 - Rate-controlled multiple only once

24 - Rate-controlled single only once

25 - Placeholder

26 - Unconfirmed

27 - Infusion

28 - Reducing dose blue script

Always >= 0 and <= 28

many rows per patient

ons_deaths

Registered deaths

Date and cause of death based on information recorded when deaths are
certified and registered in England and Wales from February 2019 onwards.
The data provider is the Office for National Statistics (ONS).
This table is updated approximately weekly in OpenSAFELY.

This table includes the underlying cause of death, place of death, and up to
15 medical conditions mentioned on the death certificate.
These codes (cause_of_death_01 to cause_of_death_15) are not ordered meaningfully.

More information about this table can be found in following documents provided by the ONS:

In the associated database table ONS_Deaths,
a small number of patients have multiple registered deaths.
This table contains all registered deaths.
The ehrql.tables.ons_deaths table contains the earliest registered death.

!!! tip
To return one row per patient from ehrql.tables.raw.tpp.ons_deaths,
for example the latest registered death, you can use:

```py
ons_deaths.sort_by(ons_deaths.date).last_for_patient()
```

Columns

date 🔗 date: Patient's date of death.
place 🔗 string: Patient's place of death.

Possible values: Care Home, Elsewhere, Home, Hospice, Hospital, Other communal establishment
underlying_cause_of_death 🔗 ICD-10 code
cause_of_death_01 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_02 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_03 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_04 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_05 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_06 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_07 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_08 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_09 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_10 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_11 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_12 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_13 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_14 🔗 ICD-10 code: Medical condition mentioned on the death certificate.
cause_of_death_15 🔗 ICD-10 code: Medical condition mentioned on the death certificate.

many rows per patient

wl_clockstops

National Waiting List Clock Stops

The columns in this table have the same data types as the columns in the associated
database table. The three "pseudo" columns are small
exceptions, as they are converted from binary columns to string columns.

Columns

activity_treatment_function_code 🔗 string
priority_type_code 🔗 string
pseudo_organisation_code_patient_pathway_identifier_issuer 🔗 string
pseudo_patient_pathway_identifier 🔗 string
pseudo_referral_identifier 🔗 string
referral_request_received_date 🔗 string
referral_to_treatment_period_end_date 🔗 string
referral_to_treatment_period_start_date 🔗 string
source_of_referral_for_outpatients 🔗 string
waiting_list_type 🔗 string
week_ending_date 🔗 string

many rows per patient

wl_openpathways

National Waiting List Open Pathways

Columns

activity_treatment_function_code 🔗 string
current_pathway_period_start_date 🔗 string
priority_type_code 🔗 string
pseudo_organisation_code_patient_pathway_identifier_issuer 🔗 string
pseudo_patient_pathway_identifier 🔗 string
pseudo_referral_identifier 🔗 string
referral_request_received_date 🔗 string
referral_to_treatment_period_end_date 🔗 string
referral_to_treatment_period_start_date 🔗 string
source_of_referral 🔗 string
waiting_list_type 🔗 string
week_ending_date 🔗 string