diff --git a/CHANGELOG.txt b/CHANGELOG.txt new file mode 100644 index 0000000..37f07c1 --- /dev/null +++ b/CHANGELOG.txt @@ -0,0 +1,40 @@ +LDHC Regional excel report discovery update. + +Changelog v1.2 +------------------------------------------------------------------ +On title page, the date on row 9 is bold +Changed notes on title page to introduction and changed introduction +Lead analyst row 30 on title page is now bold +On the Sub ICB, ICB and Region tabs, the MMM YYYY Publication text from row 3 is removed +On the sub ICB and ICB pages, the table lines now stop after the data stops. + + +Changelog V1.1 +------------------------------------------------------------------ +Automated CSV and Zip processes. Code now zips and allocates both CSV and Zip files to right location. +Automated Year folder creation. Detects year and creates folder if necessary. +Changed trend monitor path to root/Output/Opt Out Tracking. +Automated Archiving of trend monitor. +Cleaned up NCDes ethinicity report. Changed font, fixed formatting errors. +Fixed date error in NCdes ethnicty report. +Updated code so it gets practice details from SQL database. +Updated code to find practices not in our SQL database, and tag them as "Unknown" in report. +Fixed Data mismatch in ethinicity report. + + +Changelog V1.0 +------------------------------------------------------------------ +Updated two file: +create_publication.py - added lines of code to run excel job and print statement saying its running +output/outputs.py - added function to run excel job + +Added four files: +Changelog.txt - to report changes made +output/fonts.py - contains various fonts for excel +output/outputcsvtoinputexcel.py - converts the NCDes output dataframe to a dataframe for the excel job +output/outputexcel.py - prints excel file out + +Added three files in root_directory: +templates/template_AHC_practice_YYYY_MMM.xlsx : A template file to write over +templates/CONTROL_FILE_NCDes : Contains information for title page +templates/practice_mapping : A csv which contains Sub_ICB, ICB and region mapping for each practice. diff --git a/README.md b/README.md index 40734b6..ea55754 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -> Warning: This is the README for the publically accessible version of the NCDes package. If you are an analyst please don't use the below instructions to run the publication process. +> #Warning: This branch contains retired code which was used for the NCDES data source emailed to the PCD team each month. This pipeline is no longer in use as the data source has now been replaced with directly sourcing data from the CQRS self-serve tool. The 'main' branch now uses the CQRS self-serve data source. This branch should only be used if data is emailed to us and should be treated with caution as it may not be up to date if subsequent updates have been pushed to main.

 

@@ -46,7 +46,7 @@ root | |---Current | | |---ncdes_synthetic_data.csv | |---Archive -| |---Data dictionary yy_yy +| |---Data_dictionary_current | |---indicator dictionary.csv | |---measure dictionary.csv | @@ -56,7 +56,7 @@ root | | |---Missing Measures History.csv | | |---Unexpected Indicators History.csv | | |---Unexpected Measures History.csv -| |---NCD_yy_yy +| | | |---Opt Out Tracking | | |---Archive | | | |---NCD_Opt_Out_Tracking_month.xlsx @@ -74,21 +74,19 @@ root ## Instructions for publication production After the above set up steps have been completed you can follow the below instructions to create the publication. Please note that you will not be able to run the code as this requires access to a private server. The data on the private server contains reference data that is used for mapping purposes. The reference tables used contain data from the [epraccur file](https://digital.nhs.uk/services/organisation-data-service/file-downloads/gp-and-gp-practice-related-data) and the [ONS code history database](https://www.ons.gov.uk/methodology/geography/geographicalproducts/namescodesandlookups/codehistorydatabasechd) -1) Move the 'config.json' from the 'public_meta_data' folder into the package at the same level as this 'README'. +1) In the config file edit the root directory value so that it matches the root of the directory that you set up. Make use of escape characters and end path with a double "\\\\" e.g. "\\\\\\\example\\\root\\\directory\\\\". -2) In the config file edit the root directory value so that it matches the root of the directory that you set up. Make use of escape characters and end path with a double "\\\\" e.g. "\\\\\\\example\\\root\\\directory\\\\". - -3) Download the epcn excel file from this [webpage](https://digital.nhs.uk/services/organisation-data-service/file-downloads/gp-and-gp-practice-related-data). Move it to the location specified in the above diagram. Copy the absolute path of this file and use it as the "epcn_path" in the config.json. +2) Download the epcn excel file from this [webpage](https://digital.nhs.uk/services/organisation-data-service/file-downloads/gp-and-gp-practice-related-data). Move it to the location specified in the above diagram. Copy the absolute path of this file and use it as the "epcn_path" in the config.json. 3) Move the 'ncdes_synthetic_data.csv' from the 'public_meta_data' folder into your '{root_directory}\Input\Current' folder. -4) Next you will need to move the indicator dictionary.csv and measure dictionary.csv into the Data dictionary yy_yy folder. To ensure you have the most up to date files download the latest data dictionary, this can be found on the relevant publication page. As an example the 22/23 service's data dictionary can be found [Here](https://files.digital.nhs.uk/1A/E5649B/NCDes_Data_Dictionary_22_23_v2.0.xlsx). You will then need to split the indicator and measure sheets into two individual csv files and name them 'indicator dictionary.csv' and 'measure dictionary.csv' respectively. An example of these files is given in the public_meta_data folder. Remember to move these files to the 'Data dictionary yy_yy' folder in your file tree. +4) Next you will need to move the indicator dictionary.csv and measure dictionary.csv into the Data_dictionary_current folder. To ensure you have the most up to date files download the latest data dictionary, this can be found on the relevant publication page. As an example the 22/23 service's data dictionary can be found [Here](https://files.digital.nhs.uk/1A/E5649B/NCDes_Data_Dictionary_22_23_v2.0.xlsx). You will then need to split the indicator and measure sheets into two individual csv files and name them 'indicator dictionary.csv' and 'measure dictionary.csv' respectively. An example of these files is given in the public_meta_data folder. 5) Run the 'create_publication.py' file by typing the below command into your terminal ``` python -m ncdes.create_publication ``` -The output of the job can then be found in the '{root_directory}\Output\NCD_yy_yy' folder. +The output of the job can then be found in the '{root_directory}\Output\YY_YY' folder. > WARNING: Please note that python uses the '\\' character as an escape character. To ensure your inserted paths work insert an additional '\\' each time it appears in your defined path. E.g. 'C:\Python25\Test scripts' becomes 'C:\\\Python25\\\Test scripts' diff --git a/ncdes/create_publication.py b/ncdes/create_publication.py index cf2a803..4566224 100644 --- a/ncdes/create_publication.py +++ b/ncdes/create_publication.py @@ -11,7 +11,10 @@ from .output import outputs from .utils.adhoc_fix import remove_problem_indicators, remove_problem_measures, remove_problem_indicator_measure_pairs +import warnings +warnings.simplefilter(action="ignore", category=UserWarning) +pd.options.mode.chained_assignment = None CORRECT_COLUMN_ORDER_NCDes_with_geogs = [ "PRACTICE_CODE", @@ -28,12 +31,12 @@ def main() -> None: print("\n"*3,"Loading config file") config = data_load.load_json_config_file(".\\config.json") - print("Establish SQL connection") + print("Establishing SQL connection") connection = sql_connection.connect(server=config["server"], database=config["database"]) root_directory = config["root_directory"] - print("Loading in NCDes data") + print("Loading NCDes data") ncdes_raw = data_load.load_csvs_in_directory_as_concat_dataframe(f"{root_directory}\\Input\\Current") print("Cleaning NCDes data") @@ -42,7 +45,7 @@ def main() -> None: geo_ccg_sql_str, geo_reg_sql_str, stp_sql_str, prac_sql_str = data_load.get_sql_query_strings(reporting_period) - print("Loading in SQL mapping data") + print("Loading SQL mapping data") geo_ccg_df = pd.read_sql(sql=geo_ccg_sql_str, con=connection) geo_reg_df = pd.read_sql(sql=geo_reg_sql_str, con=connection) stp_df = pd.read_sql(sql=stp_sql_str, con=connection) @@ -51,14 +54,14 @@ def main() -> None: print("Formatting SQL mapping data") geo_ccg_df, geo_reg_df, stp_df = processing_steps.sql_df_cols_to_upper_case(geo_ccg_df, geo_reg_df, stp_df) - print("Loading in epcn data") + print("Loading ePCN data") raw_epcn = data_load.load_epcn_excel_table(epcn_path=config["epcn_path"]) epcn_df = processing_steps.epcn_transform(raw_epcn) - print("Creating super mapping table") + print("Creating mapping table") mapping_table = processing_steps.create_mapping_table(geo_ccg_df, geo_reg_df, stp_df, prac_df, epcn_df) - print("Merging NCDes data with supermapping data") + print("Merging NCDes data with mapping data") NCDes_with_geogs = processing_steps.merge_tables_fill_Na_reorder_cols(mapping_df=mapping_table, ncdes_df_cleaned=ncdes_clean, CORRECT_COLUMN_ORDER_NCDes_with_geogs=CORRECT_COLUMN_ORDER_NCDes_with_geogs) print("Starting validation checks") @@ -86,7 +89,8 @@ def main() -> None: NCDes_problem_meas_rem = remove_problem_measures.remove(NCDes_problem_ind_rem, ["Num Patients in Set"]) print("Removing problem indicator measure combos") NCDes_problem_meas_rem = remove_problem_indicator_measure_pairs.remove(NCDes_problem_ind_rem, [("NCDMI198", "Numerator")]) - + NCDes_problem_meas_rem = remove_problem_indicator_measure_pairs.remove(NCDes_problem_ind_rem, [("NCD012", "Denominator")]) + print("Joining ruleset ID to copy of output data for ruleset-specific outputs") NCDes_with_rulesets = processing_steps.merge_data_with_ruleset_id(NCDes_problem_meas_rem, root_directory) @@ -118,4 +122,4 @@ def main() -> None: if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/ncdes/data/data_load.py b/ncdes/data/data_load.py index 55a4f44..4386399 100644 --- a/ncdes/data/data_load.py +++ b/ncdes/data/data_load.py @@ -17,7 +17,7 @@ def load_csvs_in_directory_as_concat_dataframe(directory): """ phase_file_names = os.listdir(directory) - print(f"loading in files {phase_file_names}") + print(f"Loading in files {phase_file_names}") holder = [] for phase in phase_file_names: @@ -26,7 +26,7 @@ def load_csvs_in_directory_as_concat_dataframe(directory): output_df = pd.concat(holder, ignore_index=True) - print("data loaded") + print("Data loaded") return output_df @@ -99,8 +99,7 @@ def load_indicator_and_measure_data_dictionaries(root): Measure and Indicator dictionary in pandas dataframe """ - indicator_dictionary = pd.read_csv(f"{root}Input\\Data dictionary 23_24\\indicator dictionary.csv") - measure_dictionary = pd.read_csv(f"{root}Input\\Data dictionary 23_24\\measure dictionary.csv") - + indicator_dictionary = pd.read_csv(f"{root}Input\\Data_dictionary_current\\indicator dictionary.csv") + measure_dictionary = pd.read_csv(f"{root}Input\\Data_dictionary_current\\measure dictionary.csv") return indicator_dictionary, measure_dictionary diff --git a/ncdes/output/outputcsvtoinputexcel.py b/ncdes/output/outputcsvtoinputexcel.py index 80729c2..639bb89 100644 --- a/ncdes/output/outputcsvtoinputexcel.py +++ b/ncdes/output/outputcsvtoinputexcel.py @@ -148,8 +148,8 @@ def add_summary(df:pd.DataFrame, num_prac_cols : int) -> pd.DataFrame: result_series.append(num) #append the summary, add England as first value, and move to top row - result_series = pd.Series(result_series, index = df.columns) - df2 = df.append(result_series, ignore_index=True) + df2 = df.copy() + df2.loc[len(df2)] = result_series df2 = pd.concat([df2.iloc[-1:], df2.iloc[:-1]], ignore_index=True) return df2 diff --git a/ncdes/output/outputexcel.py b/ncdes/output/outputexcel.py index c35c26c..781a1be 100644 --- a/ncdes/output/outputexcel.py +++ b/ncdes/output/outputexcel.py @@ -17,7 +17,7 @@ def set_border(ws, df, end_col): cell.border = Border(top=thin, left=thin, right=thin, bottom=thin) -def main_to_excel(NCDes_main_df: pd.DataFrame, root_directory :str, server, database, service_year="NCD_23_24") -> None: +def main_to_excel(NCDes_main_df: pd.DataFrame, root_directory :str, server, database, service_year) -> None: """ Converts LDHC_output_df into an excel file. root_directory = directory of root diff --git a/ncdes/output/outputs.py b/ncdes/output/outputs.py index 6c4a689..7b097a2 100644 --- a/ncdes/output/outputs.py +++ b/ncdes/output/outputs.py @@ -25,7 +25,6 @@ def check_and_create_folder(folder_path): os.makedirs(folder_path) - def save_NCDes_main_to_csv(NCDes_problem_ind_rem, root_directory): dates_table = get_date_for_name(NCDes_problem_ind_rem) file_name = get_file_name(dates_table) @@ -36,11 +35,11 @@ def save_NCDes_main_to_csv(NCDes_problem_ind_rem, root_directory): #check if month folder exists, if not create one data_month = get_data_month(NCDes_problem_ind_rem) - print(f"data month is {data_month}") + print(f"Data month is {data_month}") check_and_create_folder(f"{root_directory}Output\\{file_folder}\\CSV_archive\\{data_month}") #to csv - print("converting main df to csv") + print("Converting main df to csv (takes a while)") NCDes_problem_ind_rem.to_csv(f"{root_directory}Output\\{file_folder}\\CSV_archive\\{data_month}" + r"\\" + file_name + ".csv", index=False) @@ -53,13 +52,15 @@ def save_NCDes_main_to_zip(NCDes_problem_ind_rem, root_directory): #to zip with zipfile.ZipFile(f'{root_directory}Output\\{file_folder}\\Zip_archive\\{data_month}\\{file_name}.zip','w') as zipMe: filenamecsv = f"{file_name}.csv" - print(f"filename is {filenamecsv}") + print(f"File name is {filenamecsv}") file = f"{root_directory}Output\\{file_folder}\\CSV_archive\\{data_month}\\" + filenamecsv zipMe.write(file, arcname=filenamecsv, compress_type=zipfile.ZIP_DEFLATED) def save_NCDes_main_to_excel(NCDes_problem_ind_rem, root_directory, server, database): - main_to_excel(NCDes_problem_ind_rem, root_directory, server, database) + dates_table = get_date_for_name(NCDes_problem_ind_rem) + file_folder = get_file_folder(dates_table) + main_to_excel(NCDes_problem_ind_rem, root_directory, server, database, file_folder) def save_trendmonitor(NCDes_problem_ind_rem, root_directory): data_month = get_data_month(NCDes_problem_ind_rem) @@ -69,7 +70,6 @@ def save_NCDes_by_ruleset_to_csvs(NCDes_with_rulesets, root_directory): dates_table = get_date_for_name(NCDes_with_rulesets) file_name = get_file_name(dates_table) file_folder = get_file_folder(dates_table) - data_month = get_data_month(NCDes_with_rulesets) #to csv for RULESET_ID in NCDes_with_rulesets['Ruleset ID'].unique(): @@ -102,8 +102,7 @@ def get_date_for_name(NCDes_with_geogs): An object that has all the correct date data we need to create the filename """ - - date = pd.to_datetime(NCDes_with_geogs["ACH_DATE"].iloc[0], infer_datetime_format=True) + date = pd.to_datetime(NCDes_with_geogs["ACH_DATE"].iloc[0]) dates_table = NCDes_with_geogs[["ACH_DATE"]].drop_duplicates() @@ -137,15 +136,14 @@ def get_file_folder(dates_table): year = dates_table["Year"].iloc[0] if int(month_num) >= 4: - file_folder = r"NCD_" + year + "_" + str(int(year) + 1) + file_folder = year + "_" + str(int(year) + 1) elif int(month_num) < 4: - file_folder = r"NCD_" + str(int(year) - 1) + "_" + year + file_folder = str(int(year) - 1) + "_" + year return file_folder def archive_input_as_csv(ncdes_raw, root_directory): - today = (datetime2.today()).strftime("%Y_%m_%d") ncdes_raw.to_csv(f"{root_directory}Input\\Archive\\NCDes_" + today + ".csv", index=False) diff --git a/ncdes/output/trendmonitor.py b/ncdes/output/trendmonitor.py index 8a80a92..60b5a59 100644 --- a/ncdes/output/trendmonitor.py +++ b/ncdes/output/trendmonitor.py @@ -107,7 +107,7 @@ def write_trend_monitor(NCDes_main_df: pd.DataFrame, root_directory :str, data_m override = check_if_copy(excel_df, month) if override == 0: - print("Done no changes to trend monitor.") + print("Done - No changes to trend monitor.") #Else override, THIS WILL ONLY OVERRIDE LAST ROW, ASSUMING DATA IS NEWEST elif override == 1: row_num, col_num = excel_df.shape diff --git a/ncdes/processing/validation_check.py b/ncdes/processing/validation_check.py index 81d95d4..bafbcab 100644 --- a/ncdes/processing/validation_check.py +++ b/ncdes/processing/validation_check.py @@ -156,7 +156,7 @@ def save_check_results(path, type_of_check, df_check_results, ncd_table_col_name else: new_file = df_check_results # Overwrite existing file - print(f"overwriting previous {type_of_check} {ncd_table_col_name_str} archive file") + print(f"Overwriting previous {type_of_check} {ncd_table_col_name_str} archive file") new_file.to_csv(path, index=False) return diff --git a/public_meta_data/indicator dictionary.csv b/public_meta_data/indicator dictionary.csv index 2350430..f929c72 100644 --- a/public_meta_data/indicator dictionary.csv +++ b/public_meta_data/indicator dictionary.csv @@ -1,5 +1,4 @@ Indicator ID,Indicator Description,Ruleset ID,Payment or Management Information (MI) - NCD001,Percentage of registered patients referred to a social prescribing service.,Personalised Care,MI NCD003,Percentage of at-risk patients aged 18 to 64 years inclusive who received a seasonal influenza vaccination between 1 September and 31 March.,Vaccination & Immunisation,Payment NCD004,Percentage of patients aged two or three years on 31 August of the relevant financial year who received a seasonal influenza vaccination between 1 September and 31 March.,Vaccination & Immunisation,Payment @@ -118,6 +117,4 @@ NCDMI189,"Percentage of permanent care home residents aged 18 years or over, who NCDMI198,Mean number of patient contacts as part of weekly care home round per care home resident aged 18 years and over.,Enhanced Health in Care Homes,MI NCDMI199,"Percentage of patients aged 65 years or over, who received a seasonal influenza vaccination between 1 September and 31 March.",Vaccination & Immunisation,MI NCDMI200,Percentage of registered patients with a recording of ethnicity.,Tackling Health Inequalities,MI - -NCDMI205,"Percentage of patients on the QOF Coronary Heart Disease, Peripheral Arterial Disease, or Stroke/TIA Register, who have a recording of non-HDL cholesterol in the preceding 12 months that is lower than 2.5 mmol/L, or where non-HDL cholesterol is not recorded then� a recording of LDL cholesterol in the preceding 12 months that is lower than 1.8 mmol/L.",Cardiovascular Disease Prevention,MI - +NCDMI205,"Percentage of patients on the QOF Coronary Heart Disease, Peripheral Arterial Disease, or Stroke/TIA Register, who have a recording of non-HDL cholesterol in the preceding 12 months that is lower than 2.5 mmol/L, or where non-HDL cholesterol is not recorded then  a recording of LDL cholesterol in the preceding 12 months that is lower than 1.8 mmol/L.",Cardiovascular Disease Prevention,MI diff --git a/public_meta_data/measure dictionary.csv b/public_meta_data/measure dictionary.csv index cbde514..e19b98e 100644 --- a/public_meta_data/measure dictionary.csv +++ b/public_meta_data/measure dictionary.csv @@ -1,13 +1,9 @@ - MEASURE ID,MEASURE_DESCRIPTION,MEASURE_TYPE - Management Information,Management information count for indicator, Denominator,Denominator count for indicator, Numerator,Numerator count for indicator, ABPDEC12M,Patients who chose not to undertake ambulatory blood pressure monitoring or home blood pressure monitoring in the 12 months up to and including the payment period end date.,PCA - -ABPDEC24M,"Patients whose first �high� blood pressure reading from 1 April 2020 to the day before the quality of service start date, was in the 6 months up to the quality of service start date and chose not to undertake ambulatory blood pressure monitoring or home blood pressure monitoring in the 24 months up to and including the payment period end date.",PCA - +ABPDEC24M,"Patients whose first “high” blood pressure reading from 1 April 2020 to the day before the quality of service start date, was in the 6 months up to the quality of service start date and chose not to undertake ambulatory blood pressure monitoring or home blood pressure monitoring in the 24 months up to and including the payment period end date.",PCA ACNOPQSNSD,Patients with no non-steroidal anti-inflammatory drug prescription in the 3 months prior to the quality service start date and an oral anticoagulant prescription in the 3 months prior to the quality service start date,Exclusion AGEUM50F55,Male patients under 50 years old and female patients under 55 years old.,Exclusion ANTICOAG3M,Patients who have not had an oral anticoagulant prescription code recorded in the 3 months up to and including the achievement date.,Exclusion @@ -17,9 +13,7 @@ ASTB3M_DAT,Patients who have not had an asthma diagnosis code recorded at least ASTRES_DAT,Patients who do not have an 'active' (unresolved and have received asthma-related drug treatment in the 12 months up to and including the achievement date) diagnosis of asthma .,Exclusion ASTRESLAT,Patients who have an asthma resolve code recorded up to and including the achievement date and the asthma resolve code is after their latest asthma code recorded at least 3 months before the achievement date.,Exclusion BPDEC1,Patient chose not to have their blood pressure recorded in the 5 years leading up to and including the payment period end date,PCA - -BPLAT_2,Patients who did not have a latest blood pressure reading from the 1 April 2020 to the quality service start date which was �high� (i.e. with systolic value >= 140 or diastolic value >= 90) nor have a �high� blood pressure reading from 6 months before the quality service start date up to and including the achievement date.,Exclusion - +BPLAT_2,Patients who did not have a latest blood pressure reading from the 1 April 2020 to the quality service start date which was “high” (i.e. with systolic value >= 140 or diastolic value >= 90) nor have a “high” blood pressure reading from 6 months before the quality service start date up to and including the achievement date.,Exclusion BPLAT6M,Patients who had a high blood pressure reading in the 6 months up to and including the payment period end date and either (i) their latest blood pressure reading from 1 April 2020 and prior to the quality service start date was not high or (ii) they did not have a blood pressure reading from 1 April 2020 and prior to the quality service start date.,PCA BTHPALDIZC,"Patient with no breathlessness, palpitation, syncope/dizziness or chest discomfort between quality service start date up to and including achievement date",Exclusion C19CON_DAT,Patients who have a persisting COVID-19 vaccination contraindication,PCA @@ -49,10 +43,8 @@ HFB3M_DAT,Patients who have not had a heart failure diagnosis code recorded at l HFRESLAT,Patients who have a heart failure resolve code recorded up to and including the achievement date and the heart failure resolve code is on or after their latest heart failure code recorded at least 3 months before the achievement date.,Exclusion HLTHAPDEC,Patient chose not to receive a learning disability health action plan in the 12 months leading up to and including the payment period end date.,PCA HLTHCHKDEC,Patient chose not to receive a learning disability health check in the 12 months leading up to and including the PPED,PCA - -HOMECONF18,"Patient is less than 18 years of age at the quality service end date, and doesn�t currently live in a nursing home or residential home and doesn�t have an acute confusion diagnosis. ",Exclusion -HOMETMP_18,"Patient is less than 18 years of age at the quality service end date, and doesn�t currently live in a nursing home, residential home and isn't a temporary resident. ",Exclusion - +HOMECONF18,"Patient is less than 18 years of age at the quality service end date, and doesn’t currently live in a nursing home or residential home and doesn’t have an acute confusion diagnosis. ",Exclusion +HOMETMP_18,"Patient is less than 18 years of age at the quality service end date, and doesn’t currently live in a nursing home, residential home and isn't a temporary resident. ",Exclusion HYPLATUNR,Patients who have an unresolved diagnosis of hypertension,Exclusion L12MNODOAC,Patients with no direct-acting oral anti-coagulant (DOAC) prescription in the 12 months from the quality service start date up to and including the achievement date,Exclusion LATNURSPER,"Patients whose latest housing status was not recorded as a permanent resident in a residential or nursing home, up to and including the achievement date.",Exclusion @@ -60,9 +52,7 @@ LD_DAT,Patient does not have a diagnosis of learning disabilities up to and incl LIPIDTHER,"Patient's who received a lipid lowering therapy prescription in the 6 months leading up to and including the quality service start date where lipid lowering therapy includes: Stains, ezetimibe, bempedoic acid, inclisiran, PCSK9 inhibitors, and icosapent ethyl",Exclusion MEDRVWDEC,Patient chose not to receive a structured medication review in the 12 months leading up to and including the payment period end date.,PCA MH_MHREM,"Patient does not have an unresolved diagnosis of psychosis, schizophrenia or bipolar affective disorder.",Exclusion - -MILDINTAST,Patients who have a diagnosis of mild asthma which has not been superseded by a more severe asthma diagnosis and have an �inhaled corticosteroid not indicated� code recorded in the 12 months leading up to and including the payment period end date and also have have been prescribed less than 3 SABA prescriptions in the 12 months up to and including the achievement date if 18 years and over or have been prescribed less than 4 SABA prescriptions in the 12 months up to and including the achievement date if under 18 years.,PCA - +MILDINTAST,Patients who have a diagnosis of mild asthma which has not been superseded by a more severe asthma diagnosis and have an ‘inhaled corticosteroid not indicated’ code recorded in the 12 months leading up to and including the payment period end date and also have have been prescribed less than 3 SABA prescriptions in the 12 months up to and including the achievement date if 18 years and over or have been prescribed less than 4 SABA prescriptions in the 12 months up to and including the achievement date if under 18 years.,PCA N_AT_RISK,"Patient does not have at least one of the following conditions in their record: CRD, Unresolved Asthma, CHD, CKD, Diabetes, unresolved perstisting immunosuppression diagnosis, expiring immunosuppression diagnosis, immunosuppressive procedure, immunosuppressive drug treatment, CLD, CND, High BMI aged 16 years or over, BMI value of 40 or more, LD, splenic dysfunction or care home residency.",Exclusion NATRISKU18,"Patient is less than 65 years at the quality service end date OR patient is less than 18 years or greater than 65 years at the quality service end date AND does not have at least one of the following conditions: CRD, Unresolved Asthma, CHD, CKD, Diabetes, unresolved perstisting immunosuppression diagnosis, expiring immunosuppression diagnosis, immunosuppressive procedure, immunosuppressive drug treatment, CLD, CND, High BMI aged 16 years or over, BMI value of 40 or more, LD, splenic dysfunction or care home residency. ",Exclusion NOACELOOP,Patient not on long-term prescription for either angiotensin converting enzyme (ACE) inhibitor or loop diuretic medication,Exclusion @@ -96,9 +86,7 @@ PAT_AGEU75,Patient age is less than 75 years at the quality service end date.,Ex PAT_ETHWNS,Patient from white ethnic grouping or has no ethnicity stated,Exclusion PCSPDEC,"Patient chose not to receive a personalised care and support plan, in the 12 months leading up to and including the payment period end date.",PCA PEPULCB3M,Patients who have not had a upper gastrointestinal (GI) bleed code or a peptic ulceration code recorded at least 3 months before the achievement date.,Exclusion - -PRELAT6M,"Patients whose first �high� blood pressure reading from 1 April 2020 to the day before the quality of service start date, was in the 6 months up to the quality of service start date and received clinically appropriate follow-up prior to the quality service start date.",Exclusion - +PRELAT6M,"Patients whose first “high” blood pressure reading from 1 April 2020 to the day before the quality of service start date, was in the 6 months up to the quality of service start date and received clinically appropriate follow-up prior to the quality service start date.",Exclusion QRISKVAL10,"Patients whose latest QRISK2 or QRISK3 score was under 10%, recorded at any point leading up to the achievement date.",Exclusion QRISKVAL20,"Patients whose latest QRISK2 or QRISK3 score was 20% or under, recorded at any point leading up to the achievement date.",Exclusion REGL3M_DAT,Patients registered within 3 months of end of payment period,PCA @@ -113,6 +101,4 @@ TXSTAT_DAT,Patients who have an expiring statin contraindication recorded in the UNRESAFIB,Patients with unresolved atrial fibrillation,Exclusion XFLU_DAT,Persisting Flu vaccine contraindications recorded up to and including the achievement date.,PCA XSTAT_DAT,Patients who have a persisting statin contraindication.,PCA - Num Patients in Set,Copy of denominator which is sometimes provided by CQRS and needs removing,Exclusion -