Managing a diabetes database: using a data dictionary and processing health records

EUropean Best Information through Regional Outcomes in Diabetes

Managing a diabetes database: using a data dictionary and processing health records

Scott CunninghamUniversity of Dundee, Scotland

The BIRO Academy2nd Residential Course

Brussels, 23rd-25th January 2011

The BIRO Academy 2nd Residential Course Brussels, 23rd-25th January 2011

Introduction

• Background• Defining a European common diabetes

dataset• Defining a European diabetes data

dictionary• Processing health records• Conclusions


Background

• BIRO WP2: Core diabetes indicators– clinical review of current evidence

• Candidate indicators• Core indicators• Basis for dataset


Background

• Accurate comparisons of diabetes indicators • Standardised data currency– Consistent data storage– Consistent aggregation

• Data standards– Quality– Relevance– Consistency– Avoid duplication

• Reduction in costs of data development

• EUBIROD Common Diabetes Dataset


Common Diabetes Dataset

• “The WP will ensure the definition of a minimum dataset that can be used as a common data reference for the extraction of compatible entities at the international level.”

• “A coding/decoding mechanism will be identified to translate regional data in entities that can contribute to the definition of a shared information system.”

• Existing data standards…






• Methodology– Clinical review (BIRO WP2)– Analysis of BIRO partner datasets (7 partners)

• Scottish Diabetes Dataset• DiabCare• Umbria AMD data file• EUCID project used for validation

– Review carried out for EUBIROD• 20 partners

• Common dataset for diabetes– Clinical definitions– International System of units (SI)




• DiabCare data items do not have clear definitions

• Forum for Quality System in Diabetes (FQSD) and Scottish definitions available

• EUBIROD definitions based on understanding of common methods of recording



• Each BIRO Dataset item recorded as a “Parameter”

• Parameters have a unique reference– Are clearly defined– Have an associated data type– May have a unit of measurement (e.g.kg/m2)– May have an upper or lower boundary– May have a locally defined guideline value– Based on evidence and best practice



• Data items assigned “validity” rating after comparison across datasets– “High” Validity: High Validity items consistent

across ≥90% of analysed datasets– “Medium” Validity: consistent across ≥60% and

<90% of analysed datasets– “Low” Validity: those which are consistent across

<60% of analysed datasets



• 25 High Validity Data Items Identified• Basic Patient Information

– e.g. Type of Diabetes, Date of Birth, Year of Diagnosis

• Risk Factors– e.g. Smoking Status

• Clinical Measurements– e.g. Weight, Height, SBP, DBP, HbA1c, Creatinine

• Examinations– e.g. Eye Examinations

• Outcomes– e.g. End Stage Renal Failure



• Clinical profile data– Country– Data Source Type

• e.g. GP, Hospital Clinic (Diabetes), Regional Register

– Name of Clinic– Clinic Denominator (Population)– Geographical Area– Website– Contact details





• Already used for data repository design– Cyprus

• Available and browseable online• EUBIROD Dataset:

http://www.eubirod.eu/webPortal/?q=en/node/8







• Standardised European data currency• Mandatory items– Unique patient identifier– Diabetes diagnosis– Date of diagnosis– Gender– Outcome dates (approximated or default if

necessary)

• Basis of data dictionary…


Diabetes Data Dictionary

• “The WP will create an electronic directory inclusive of concept and data dictionaries for diabetes care and prevention, thereby allowing to dynamically link the clinical knowledge-base to the systematic evaluation of health systems outcomes.”



• Explain ‘data about the data’• Formally document dataset compliance• Issues with local data– Local knowledge essential to explain anomalies

• Local recording methods• Data quality criteria• XML documentation



• Web application to allow entry of local info• Data can be reviewed and updated as local

datasets change• Explain local deviations from definitions• Gain local knowledge• Consistent output produced across all

partners• Validated XML created for each data source








• Type of diabetes





• Data standards evolve:– HbA1c: IFCC measurement (mmol/mol)– Waist circumference– Estimated glomerular filtration rate (eGFR)– Laterality for foot/eye data?– Previous foot ulcer– Additional defined diabetes types

• LADA, MODY, Pancreatic Pathology, Secondary Diabetes, Drug Induced, etc

– New drug therapies

• Boundary values included to omit anomalies



Parameter Lower Boundary Upper Boundary

Date of Birth ≥01/01/1900 Current Date

Date of Diagnosis ≥DOB Current Date

Episode Date ≥DOB Current Date

Cigarettes per day 0 100

Alcohol Intake 0 60

Weight 5 300

Height 0.3 3

Body Mass Index 0.01 100

Systolic Blood Pressure 10 400

Diastolic Blood Pressure 10 300

HbA1c 2.15 25.02

Creatinine 3 1999

Total Cholesterol 0.01 50

HDL 0.01 5

Triglycerides 0.01 100

Average Injections 0 20

LDL 0.01 15

Commencement of patient activity ≥DOB Current Date

Completion of patient activity ≥DOB Current Date


Processing Health Records

• Mappings defined from local datasets to EUBIROD standard– Local controlled vocabularies– Non-standard units of measurement

• Dataset and data dictionary at core of EUBIROD developments– More later!

• Case study – Scotland!



• Scottish Care Information – Diabetes Collaboration (SCI-DC)

• National system for NHS Scotland• Began as a research project (DARTS)– Started small and developed

• First minimum dataset – June 1998• National system status 2002• Full coverage by 2006– All GP sites and hospital clinics– Specialist services and web data entry

• Shared electronic record for diabetes



• Extract in standard format• Consolidate into common structures• Record linkage using unique reference






Clinical Guidelines





• System designed for clinical care• Supporting single data entry across systems• Secondary data use– Clinical audit– Research and enhancing evidence base– Direct patient access


Tayside – Annual Report 2010

Duration in years as a percentage of diabetes type in Tayside


Scottish Diabetes Survey 2009

Diabetes prevalence in each NHS board


Monitoring for Quality Improvement

• Scotland’s diabetes prevalence– 2002: 103,835 (2%)– 2009: 228,004 (4.4%)

• Type 1 diabetes: 13%• Type 2 diabetes: 87%



• 2005 – 2007 estimates: diabetes-related admissions account for ~12% of Scotland’s inpatient costs of £2.4bn– £26 million for type 1 diabetes– £275 million for type 2 diabetes

• One in ten people in hospital have diabetes• 60% of people with diabetes admitted as inpatients

have been admitted as emergencies• 2008: Diabetes UK estimated that diabetes

accounted for 10% off all NHS expenditure in UK– £9 billion per year, or £1 million every hour– Double a 2002 Department of Health estimate



• 2009 Scottish Diabetes Survey– 9735 (4.3%) reported as having ever had a foot

ulcer– 1132 (0.5%) had a lower limb amputation– Lower limb amputation rates are 15 times higher

in people with diabetes than those without

– 21471 (9.5%) have a record of a previous MII– 11575 (5.1%) recorded as having had a CVA– 80% of people with diabetes will die from

cardiovascular complications



• 2009 Scottish Diabetes Survey– 20.6% had retinopathy present in one or both eyes– 1,824 (0.8%) people with diabetes recorded as blind– Diabetic retinopathy is the leading cause off blindness in

people of working age in the UK

– 254 (0.9%) off those with type 1 and 872 (0.4%) of those with type 2 diabetes have been recorded as having end stage renal failure

– 32.7% overweight (BMI 25-29.9kg/m2)– 51.0% obese (BMI 30kg/m2 or over)– 19.5% are current smokers



EUCID


EUBIROD



Conclusions

• Data standards improve:– Quality– Relevance– Consistency– Avoid duplication

• If you measure it, you can improve it!• All levels of infrastructure can be reported– Local– National– International


Conclusions

• We have covered:– Defining a European common diabetes dataset– Defining a European diabetes data dictionary– Processing health records

• Case study – Scotland

• Principles can be applied internationally


References

• EUBIROD Data Dictionary:http://www.eubirod.eu/webPortal/?q=en/node/8

• The International System of Units:http://www.bipm.org/en/si/

• NHS Scotland Data Dictionary:http://www.datadictionary.scot.nhs.uk/

• EUBIROD Data Source Questionnaire:http://questionnaire.eubirod.eu/


Questions?

Thank you for your attention!

Documents

Managing a diabetes database: using a data dictionary and processing health records