Title of dataset: Opioid Prescribing Data

Contact details: Dr Cathy Montgomery. C.a.montgomery@ljmu.ac.uk; 0151 904 6295

File formats: 
CSV

Column headings for tabular data: 
Cancer_dependence_Filter: Filter Variable to exclude those with read code or free text entry indicating cancer/dependence. 	
FinalLinkedProbs: Numerically recoded version of Linked Problems - reason given in EMIS system for opioid prescription. 	
Age: Age	
NewEthnicity: Ethnicity recoded according to UK census categories. 	
Locality: Recoded Locality for areas of Liverpool. 	
PartialPostcode: Partial postcode of GP surgery.	
Drug_name: Numerically recoded name of prescribed medication	
LowerLayerArea: LSOA according to the 2019 Indices of Multiple Deprivation	
NameDosageandQuantity: Name, dosage and quantity of prescribed medication	
DrugForm: Numerically recoded form of prescribed medication	
Dose: Dosing Instructions	
DDD: Daily Defined Dose	
MED: Morphine Equivalent Dose	
MED_sum: Sum of MED for all medications prescribed	
Average_MED: Average MED for all medications prescribed	
PrescriptionType: Acute vs. repeat/long-term. 	
PrescribedName: name of prescribed medication	
DrugName: Numerically recoded prescribed name	
EthnicOrigin	
LinkedProblemsCodeTerm	
CodedLinkedProb	
quintiles_MED_curr_Sum	

Data and file overview: This file contains opioid prescribing data for Chronic Non Cancer Pain (CNCP) diagnoses in primary care in NHS Liverpool CCG from 2016-2018. The file was shared by the business intelligence team at Liverpool CCG with Liverpool John Moores University. The team at NHS Liverpool CCG requested that anonymised identifiers were removed from the publicly available file, thus there are multiple rows for each patient included in our analyses in this CSV file. We were also asked to remove GP surgery codes and patient gender and occupation so that GP surgeries and patients could not be identified.