= i2b2 - GEM data load for GENVASC

== Patient Request

UHLDWH.DWBRICCS.dbo.UVW_GENVASC_PATIENTS_GEM => UHLDBSQLCORP02.LLR_CSS.dbo.BRICCS_GENVASC_PATIENTS

== Data Response


UHLDBSQLCORP02.LLR_CSS.dbo.Genvasc_Clinical_ReadCode => UHLDWH.DWBRICCS.dbo.Genvasc_Clinical_ReadCode

UHLDBSQLCORP02.LLR_CSS.dbo.Genvasc_Ethnic_ReadCode => UHLDWH.DWBRICCS.dbo.Genvasc_Ethnic_ReadCode

== Health Check Read Codes

||= Field Name =||= Read Code v3 =||= Concept Code =||
|| Cardiovascular disease risk assessment declined || XaN8t ||  ||
|| Cardiovascular disease risk assessment offered || XaPl0 ||  ||
|| Informed consent given || XaLQR ||  ||
|| Patient informed about research study || 9Q... ||  ||
|| Cigarette consumption || Ub1tI ||  ||
|| Smoking cessation advice || Ua1Nz ||  ||
|| Health education - smoking || 6791. ||  ||
|| Referral to smoking cessation advisor || XaItC ||  ||
|| Not interested in stopping smoking || XaIkY ||  ||
|| Cigar consumption || Ub1tJ ||  ||
|| Loose tobacco consumption || Y01e6 ||  ||
|| Smoker || 137R. || HCK:0000496 ||
|| Ex-smoker || Ub1na || HCK:0000516 ||
|| Never smoked tobacco || XE0oh || HCK:0000541 ||
|| Current non-smoker || 137L. || HCK:0000495 ||
|| Ethnic groups (census) || 9S... ||  ||
|| - White - ethnic group || 9S1.. ||  ||
|| - Other ethnic non-mixed (NMO) || 9SA.. ||  ||
|| - Ethnic groups (census) NOS || 9SZ.. ||  ||
|| - Mixed ethnic census group || XaFwG ||  ||
|| - Black - ethnic group || XaFwH ||  ||
|| - Asian - ethnic group || XaFwz ||  ||
|| - Other ethnic group || XaFx1 ||  ||
|| Ethnic category - 2001 census || XaJQu ||  ||
|| - British or mixed British - ethnic category 2001 census || XaJQv ||  ||
|| - Irish - ethnic category 2001 census || XaJQw ||  ||
|| - Other White background - ethnic category 2001 census || XaJQx ||  ||
|| - White and Black Caribbean - ethnic category 2001 census || XaJQy ||  ||
|| - White and Black African - ethnic category 2001 census || XaJQz ||  ||
|| - White and Asian - ethnic category 2001 census || XaJR0 ||  ||
|| - Other Mixed background - ethnic category 2001 census || XaJR1 ||  ||
|| - Indian or British Indian - ethnic category 2001 census || XaJR2 ||  ||
|| - Pakistani or British Pakistani - ethnic category 2001 census || XaJR3 ||  ||
|| - Bangladeshi or British Bangladeshi - ethn categ 2001 census || XaJR4 ||  ||
|| - Other Asian background - ethnic category 2001 census || XaJR5 ||  ||
|| - Caribbean - ethnic category 2001 census || XaJR6 ||  ||
|| - African - ethnic category 2001 census || XaJR7 ||  ||
|| - Other Black background - ethnic category 2001 census || XaJR8 ||  ||
|| - Chinese - ethnic category 2001 census || XaJR9 ||  ||
|| - Other - ethnic category 2001 census || XaJRA ||  ||
|| - Ethnic category not stated - 2001 census || XaJRB ||  ||
|| FH: Cardiovascular disease 1st degree female reltve < 65 yrs || XaP9M || HCK:0000537 ||
|| FH: Cardiovascular disease 1st degree male relative < 55 yrs || XaP9K || HCK:0000536 ||
|| Alcohol intake || 136.. ||  ||
|| Advice on alcohol consumption || Xa1dA ||  ||
|| Enjoys light exercise || 1383. ||  ||
|| Enjoys moderate exercise || 1384. ||  ||
|| Enjoys heavy exercise || 1385. ||  ||
|| Body mass index - observation || 22K.. || HCK:0000502 ||
|| O/E - height || 229.. || HCK:0000500 ||
|| O/E - weight || 22A.. || HCK:0000501 ||
|| Waist circumference || Xa041 ||  ||
|| Ideal body weight || 66CB. ||  ||
|| Advice about weight || XaADJ ||  ||
|| Dietary advice || 8CA4. ||  ||
|| Refer to weight management programme || XaJSu ||  ||
|| Referral to dietitian || XaBSz ||  ||
|| Pulse rate || X773s ||  ||
|| Pulse regular || XM02J ||  ||
|| Pulse irregular || X76JE ||  ||
|| O/E - Systolic BP reading || 2469. || HCK:0000503 ||
|| O/E - Diastolic BP reading || 246A. ||  ||
|| Fasting || X78x9 ||  ||
|| Serum cholesterol level || XE2eD || ||
|| Serum HDL cholesterol level || 44P5. ||  ||
|| Serum triglyceride levels || XE2q9 ||  ||
|| Serum LDL cholesterol level || 44P6. ||  ||
|| Serum glucose level || 44f.. ||  ||
|| Total cholesterol:HDL ratio || 44PF. || HCK:0000508 ||
|| HbA1c level (DCCT aligned) || XaERp ||  ||
|| Cardiovascular event risk || XaIpv ||  ||
|| Cardiovascular disease risk assessment done || XaPkZ || HCK:0000538 ||
|| Follow-up arranged || 8H8.. ||  ||
|| High risk of diabetes mellitus || XaZLG ||  ||


Atrial fibrillation Codes: G5730, XaOft, XaOft, XaOfa, XaOfa, Xa2E8, Xa2E8, X202R, X202R, X202S, X202S, Xa7nI, Xa7nI, XaEga, XaEga

Type 2 Diabetes:  XaOPt, X40J5, C1090, C1091, C1092, C1093, C1094, C1095, C1097, XaELQ, XaFWI, XaFn7, XaFn8, XaFn9, XaEnp, XaEnq, XaKyX, C1096, XaFmA, XaJQp, XaF05, XaIzQ, XaIzR, X40J6, X40JJ, C1011, C1031, XaIrf, XM1Xk

Chronic Kidney Disease: XaLHI, XaNbo, XaNbn, XaO3t, XaO3u, XaO3v, XaO3w, XaO3x, XaO3y, XaLHJ, XaO3z, XaO40, XaLHK, XaO41, XaO42, XaLHH, XaO3r, XaO3s, XaLHG, XaO3p, XaO3q

Rheumatoid Arthritis: N040., N0421, N042z, X701k, X705v, X705u, X705t, N042., N040J, N040H, N0403, N0401, N0405, N0409, N0400, N040F, N0402, N0404, N0407, N040A, N040G, N040L, N040M, N040C, N040D, N040B, N0408, X701m, X701j, X701i, X701h, X701l, Nyu10, Nyu1G, Nyu11, XaBMO, Xa3gL, Nyu12, Xa3gM, Xa3gN, Xa3gO, Xa3gP, G5yA., N040T, N040K, N040E, N0406, N041., XE1DU, X705I, G5y8.

Excluded - Presumed Type 1

X40J4	Type I diabetes mellitus
Xa4g7	Unstable type I diabetes mellitus
X40JY	Insulin-dependent diabetes mellitus secretory diarrhoea synd
C1080	Type I diabetes mellitus with renal complications
C1081	Type I diabetes mellitus with ophthalmic complications
C1082	Type I diabetes mellitus with neurological complications
C1083	Type I diabetes mellitus with multiple complications
C1085	Type I diabetes mellitus with ulcer
C1086	Type I diabetes mellitus with gangrene
C1088	Type I diabetes mellitus - poor control
C1089	Type I diabetes mellitus maturity onset
XaELP	Type I diabetes mellitus without complication
XaFWG	Type I diabetes mellitus with hypoglycaemic coma
XaFmK	Type I diabetes mellitus with peripheral angiopathy
XaFmL	Type I diabetes mellitus with arthropathy
XaFmM	Type I diabetes mellitus with neuropathic arthropathy
XaEnn	Type I diabetes mellitus with mononeuropathy
XaEno	Type I diabetes mellitus with polyneuropathy
XaKyW	Type 1 diabetes mellitus with gastroparesis
C1087	Type I diabetes mellitus with retinopathy
XaF04	Type I diabetes mellitus with nephropathy
XaFm8	Type I diabetes mellitus with diabetic cataract
XaIzM	Type 1 diabetes mellitus with persistent proteinuria
XaIzN	Type 1 diabetes mellitus with persistent microalbuminuria
XaJSr	Type 1 diabetes mellitus with exudative maculopathy
C1010	Type 1 diabetes mellitus with ketoacidosis
C1030	Type 1 diabetes mellitus with ketoacidotic coma
XM1Xk	Xa4g7	Xa4g7	Unstable type I diabetes mellitus
XM1Xk	C1088	C1088	Type I diabetes mellitus - poor control

Excluded - not sure if Type 1 or Type 2:

C10..	Diabetes mellitus
XaOPu	Latent autoimmune diabetes mellitus in adult
X40JA	Secondary diabetes mellitus
XaMzI	Cystic fibrosis related diabetes mellitus
X40JB	Secondary pancreatic diabetes mellitus
X40JC	Secondary endocrine diabetes mellitus
XSETK	Drug-induced diabetes mellitus
XaJlR	Secondary diabetes mellitus without complication
XaJUI	Diabetes mellitus induced by non-steroid drugs
XaJlM	DM induced by non-steroid drugs without complication
XaJlL	Secondary pancreatic diabetes mellitus without complication
X40JG	Genetic syndromes of diabetes mellitus
X40JI	Diabetes mellitus autosomal dominant
X40JO	Congenital lipoatrophic diabetes
X40JS	Hyperproinsulinemia
XSETH	Maturity onset diabetes mellitus in young
X40JZ	Diabetes-deafness syndrome maternally transmitted
XSETp	Diabetes mellitus due to insulin receptor antibodies
XM1Xk	Unstable diabetes
X008t	Diab insipidus,diab mell,optic atrophy and deafness

== Recreating the Health Check Discussion

Below are some questions with responses by Sarah-Jane Gray (in italics) about the Read Codes used to generate a QRisk Score:

- What (Read code or otherwise) do the CCG use to identify that a health check has occurred for payment purposes?
    ''XaPkZ - Cardiovascular disease risk assessment done''

- For questions where the answer is a tick box (yes/no) is there a way to differentiate for all cases between an answer of ‘no’ / unticked and the question not being answered?
    ''No – one of the drawbacks of the system in terms of data gathering is that the read codes are for a positive response and rarely a negative. Tickbox indicates a ‘yes’ response to that question but absence of a tick could be either ‘no’ or ‘not applicable / not asked’''

- Similarly, for questions where the answer is a number, is there a way to differentiate for all cases between an answer of zero and the question not being answered?
    ''Generally with numeric, because a negative (0) can be recorded, question not being answered is not the same as a negative response.''

- What audit data is available for the data completeness for health checks?
    ''Might need more explanation on what you mean for this one J''

- For calculations such as QRisk or BMI, is it possible for the health check form to be filled in such a way that they are not calculated?
    ''Yes. These should be recorded as part of a health check but there is the possibility (particularly with QRISK being a tool external to the template which ‘pops up’) but it is possible to complete the template without calculating these.''

- For calculations such as QRisk or BMI, is it possible for the calculation to be based on historic data?  Is there a limit to how old that data can be?
    ''Yes. This is generally the most recent reading in the last 5yrs except ‘treated for hypertension’ in QRISK which needs to be hypertension diagnosis (any time) but hyp meds prescribed within last 6 months of the calculation. For BMI/BP, if nothing is recorded then a default value considering the patient’s age, sex and ethnicity is calculated.''

- Is there a way to correctly identify all the values associated with a health check or QRisk calculation? 
    ''Not easily. We can produce a template specification for the NHS Health Check template which lists all the codes used (this is what you attached to the original email) but not for the QRISK calculation.''
 

- In addition, we want to make sure that we have all the information that was used to calculate the QRisk score.  From what I can gather, the following fields are required for this calculation:
 - Ethnicity
 - Age > ''directly taken from patient demographic information''
 - Sex > ''directly taken from patient demographic information''
 - Smoking Status 
 - Systolic blood pressure 
 - Total cholesterol:HDL ratio 
 - BMI 
 - Family History of CHD in 1st degree relative under 60 > ''both codes used in the template will mark this as positive. On S1 is just ‘Family history of CVD’ ?''
 - Townsend deprivation score > ''directly taken from patient demographic information (if postcode recognised)''
 - Treated hypertension > ''Any codes in the HYP cluster (I can provide these) with hypertension medication in <6m''
 - Rhematoid arthritis > ''Any codes in the RARTH cluster''
 - Chronic renal disease > ''Any codes in the CKD cluster''
 - Type 2 diabetes > ''Codes and children of X40J5 (“Type II diabetes mellitus’)''
 - Atrial fibrillation > ''Any codes in the AFIB cluster''
 - ''+ also ‘personal history of CVD’''

- Do you know what algorithm for calculating QRisk is used in SystemOne, as this may resolve the ambiguities?
    ''Afraid not, and I can’t see any way of obtaining this from S1 – will see if it’s available elsewhere.''


== Health Check Information

Information about the Health Check can be found on the [[http://www.hscic.gov.uk/nhshealthcheck|HSCIC Health Check]] page.  This includes a [[http://www.hscic.gov.uk/media/9445/NHS-Health-Check---Read-Code-Mapping-Guidance-XLS-396kb/xls/NHS_Health_Check_-_Read_Code_Mapping_Guidance.xls|list of mappings]] for the codes between Read v2 and v3.

== Primary Care Medication Coding

After speaking to Stephanie Webb, I have gleaned the following information about primary care medication data:

- It is extracted from System One and EMIS into the GEM data warehouse
- System One data is ''probably'' in Read Code format.
- EMIS is ''probably'' not, but don't know what format it is in.

== Patient Post Codes

After speaking to Stephanie Webb, I have gleaned the following information about patient post codes data.

- Post code data is not historic, only current post code data is recorded.
- GEM do not get post code data from the primary care IT systems, but get the information from the Exeter database.
- It may be possible to get the data from System One and EMIS, but this would involve an additional charge.