data 101 stuart harris principal public health intelligence analyst

Data 101

Stuart HarrisPrincipal Public Health Intelligence Analyst

2

In this session…

- Types of data

- Data quality

- Choosing outcome indicators

Introduction to primary data sources

3

Data through our lives

Census; local authority data; deprivation indices; surveys

PH mortality file; vital statistics; compendium

PH births file; vital statistics; compendium Inpatient data (SUS; HES); GP

data; community information systems; screening uptake (IC)Healthcare + immunisations

uptake; maternity data; HV needs assessment


4

Data types

• Person/event based • Aggregated• Collections and tools

For each type – examples and resources


5

Person/event based data• Only available under confidentiality agreements to

appropriate organisations

• Individual records. e.g.- Births- Mortality- HES- A&E attendances

• May be anonymised

• Record linkage increasingly difficult

• May or may not have NHS number

• Confidentiality issues


6

Common characteristics

Each line is one event (birth, death, episode of care)

Usually includes:

• relevant dates eg birth, death, admission

• geographical data eg postcode, LA

• appropriate details of event e.g. cause of death, place of death, diagnosis, procedure

Some socioeconomic data may be inferred


7

ONS mortality file – some fieldsDate of Birth Date of registration

Date of Death Sex

Age Causes of death (15 occurrences)

Age Unit (1=years, 2=months, 3=weeks, 4=days)

Underlying cause of death (non-neonatal)

Postcode of residence Secondary cause of death

Communal Establishment Code (H=Home, E=Elsewhere

Neonatal indicator

Establishment where death occurred Country of place of birth

Place of residence (LA, Ward, Region)

Standard Occupation Classification

LA place of death Place of death


8

HES has many more fieldsRefer to data dictionary for full list: http://www.hscic.gov.uk/hesdatadictionary


9

Advantages of individual level dataFar more flexibility

• Aggregate by numerous characteristics

• Possible to construct trend data

• Possible to link to other data sets

• Data may be processed as required (e.g. standardised)

However, can require considerable effort and time to produce required outputs.

May not be comparable with routinely produced statistics


10

Elementary record linkage

• If you have a common field in two sets of records you can link records

• eg NHS number (link HES and mortality records) – with permission!

• Postcode (link mortality to Gridlink to IMD for Super Output Area (LSOA) deprivation scores)


11

Principles of record linkage

Admissions numbers

Quintile 1 000000

Quintile 2 000000

Quintile 3 000000

Quintile 4 000000

Quintile 5 000000

population

00000

00000

00000

00000

00000

Rate

000

000

000

000

000

HES record

ID procedure postcode

XX1 2XX

Gridlink

Postcode SOA

XX1 2XX YYYYYYY

IMD

SOA IMD score quintile

YYYYYY ZZZZZ 5

/ =


12

Confidentiality

• ONS releases data under one of two acts:

• National Health Service Act 1977 (Section 124A as amended by the Health Act 1999)

• Census Act 1920 (Section 5)

• Data supplied under confidentiality declarations

• No statistics may be published which will reveal personal information

• In practice this means no numbers under 5 (including 0’s)

• Avoid indirect disclosure (disclosure by differencing) e.g. subtracting males from a total will reveal that the count for females is under 5


13

Confidentiality

Methods that can be used to protect tables:

• Table re-design

• Grouping categories within a table

• Aggregating across a number of time periods

• Using a higher level of geography

Suppression

• Suppression of rows and/or columns

• Suppression of cells

• In both row and cell suppression, some secondary suppression is usually necessary


14

Aggregate data

Census

HSCIC Indicator Portal

Neighbourhood Statistics (NeSS)

ONS births/deaths statistics

• These do not include individual data

• Rates may already be calculated

• Quick for standard queries


15

Census

• Conducted every 10 years by ONS (latest 2011)

• Statutory survey undertaken at household level

• Covers wide range of topics(demography, household structure, amenities, employment, health/disability, migration)

• Extensive range of outputs across a wide variety of types of area

• Can be difficult to find/extract required statistics


16

HSCIC Indicator PortalContains a variety of indicator sets, including;

• Clinical Commissioning Group Indicators

• Compendium of Population Health Indicators

• Local Basket of Inequalities Indicators

• GP Practice Data

• Social Care Indicators

• NHS Outcome Framework Indicators

Collections of Excel spreadsheets


17

HSCIC Indicator Portalhttps://indicators.ic.nhs.uk/webview/

• Contains hundreds of Excel spreadsheets

• Compendium is best collection of data on health and disease (including mortality rates)

• LBOI indicators cover wider determinants

• Data available for Local Authorities, CCGs


18

HSCIC Indicator Portal


19

Neighbourhood Statistics (NeSS)

• NeSS established in 2001 (http://www.neighbourhood.statistics.gov.uk)

• Contains over 300 datasets, covering Health, Housing, Education, Deprivation, Age, Ethnicity and Census data

• Around 1 billion counts of information, to neighbourhood level

• On-line guidance available to help users through the site

• Can search by postcode or area of interest, down to small area geographies


20

Neighbourhood Statistics site


21 Introduction to primary data sources

22

NOMIS

• NOMIS website presents official labour market statistics (www.nomisweb.co.uk)

• Can obtain profiles by local authority and ward

• Alternatively, can construct more detailed queries

• Good source for benefits (job seekers, Incapacity Benefit, Employment and Support Allowance)

• Also good source from which to extract Census data


24

Collections and tools

PHE produces and maintains a large number of indicator collections and tools.

All of these collections and tools can be accessed on line via the PHE Data Gateway (https://www.gov.uk/guidance/phedata-and-analysis-tools)

Most of the collections and tools are interactive, and users can determine the types of outputs they wish to produce


25

Collections and tools

Examples include;

• Health profiles

• Public Health Outcomes Framework

• GP Practice Profiles

• Single topic profiles

• Spend and Outcomes Tool

• Return on Investment Tools (Smoking, Alcohol, Physical Activity)


26

Health Profiles

• A member of the ‘official statistics’ collection

• Health profiles provide a general overview of the health situation in an area

• Available in pdf format or interactive online

• Web link - http://www.apho.org.uk/default.aspx?QN=P_HEALTH_PROFILES


28

Public Health Outcomes Framework• A member of the ‘official statistics’ collection

• Contains a wider range of indicators relating to key public health issues

• Indicators across five domains• Overarching indicators, wider determinants of health, health

improvement, health protection, healthcare and premature mortality

• Available in pdf format or interactive online

• Web link - http://www.phoutcomes.info/


30

National General Practice Profiles• Contains data at individual GP practice level

• Practice figures may be benchmarked against host CCG or national deprivation decile

• Mainly web based, but can download summary pdfs

• Many indicators QOF based

• link - http://fingertips.phe.org.uk/profile/general-practice


32

Single topic profilesMany are available, including;

• Breastfeeding

• Cardiovascular disease

• Health protection profile

• Injury profiles

• Liver disease profiles

• Local tobacco control profiles

• Sexual and reproductive health profiles


33

Spend and Outcome Tool

• Operates at LA and CCG level

• Provides an overview of spend and outcomes across key areas of business (not just public health)

• Excel based tool, download from web site (LA pdf factsheets can also be downloaded)

• Training video and case studies available on website

• link - http://www.yhpho.org.uk/default.aspx?RID=49488


35

NICE Return on Investment Tools

• Tools available for tobacco, physical activity and alcohol

• Provides estimates of costs and savings (healthcare and wider) from different mixes and levels of interventions

• Operates at LA and CCG level

• Excel based tool, download from web site

• Training videos and guides available on website

• link - https://www.nice.org.uk/About/What-we-do/Into-practice/Return-on-investment-tools


37

Types of data not covered

Survey data – apart from census

Other examples include • Integrated household survey• Labour force survey

Modelled data – e.g. synthetic estimates


38

Support Available

PHE’s local South West Knowledge and Intelligence Service is able to provide advice and assistance in using many data sets, profiles and tools.

Our Principal Knowledge Transfer Facilitator is Nicola Bowtell ([email protected]).

For specific support in using the Return on Investment tools contact [email protected]


39

Data quality

What is ‘quality’ data?

• Accurate

• Timely

• Appropriate measure

• Consistent – between areas, over time


40

Example – population counts

Different sources

• Census

• Population estimates

• Electoral registers

• GP practice registers

Each has particular strengths and weaknesses


41

Example – hospital admissions

Different sources

• Patient Administration System (PAS)

• Secondary Uses Service (SUS)

• Hospital Episodes Statistics (HES)

Often a trade-off between timeliness and data quality (accuracy)


42

Example – mortality statistics

Some elements of the data are more likely to be accurate than others

• Age, gender, counts

• Cause of death – diagnosis, changes in coding

• Occupation

• Consistency – compiled from registration office returns across the country


43

Considerations regarding data quality Some things to consider when evaluating data quality

• How is it collected? (statutory return, voluntary return, survey)

• Why is it collected? (HES, QOF data)

• Is data coverage complete? (missing values)

• Are definitions clear? – are they consistently applied across areas, over time

• Is there a published quality assurance process?

• Is it a new or an established collection?


44

Example – QOF based prevalence estimates

Widely used e.g. in GP Practice Profiles

• Why is it collected? – set GP payment levels

• How is it collected? – GPs compile registers of patients with certain conditions, submit annual returns

• Is it accurate? – Limited quality control/checking.

• Is it complete? – Only includes diagnosed patients, excludes exceptions

• Is it appropriate? – does it actually measure prevalence?


45

Pointers for assessing data quality

Some suggestions

• Examine meta-data and/or technical guides – should provide information on how data is collected, how indicator is calculated, and any caveats regarding the data

• Ask an expert – people who have thorough knowledge of data sets and extensive experience of using them are best placed to advise on strengths and weaknesses

Often it is not the data sets or indicators themselves that are the problem, but the manner in which they are used!


46

Choosing outcome indicators wisely

Not specifically covered here, but many of the themes covered in the assessing data quality section are relevant

Key publication – ‘The Good Indicators Guide’ – download from APHO website - http://www.apho.org.uk/resource/item.aspx?RID=44584


data 101 stuart harris principal public health intelligence analyst

Documents

health data

data data quality

primary data sourcesperson

specialist data sources

secondary data sources

data types personevent

main data coding

additional data fields