Number of potentially preventable hospitalisations - diabetes complications per 100,000 people of all ages, 2014-15 to 2017-18

Identifying and definitional attributes

Metadata item type:Indicator
Indicator type:Indicator
Short name:Diabetes complications hospitalisations, 2014-15 to 2017-18
METeOR identifier:724543
Registration status:Australian Commission on Safety and Quality in Health Care, Standard 27/04/2021
Description:

Number of potentially preventable hospitalisations for diabetes complications, per 100,000 people, all ages, age and sex standardised. 

Indicator set:Australian Atlas of Healthcare Variation 2021 Australian Commission on Safety and Quality in Health Care, Standard 27/04/2021
Quality statement:National Healthcare Agreement: PI 18-Selected potentially preventable hospitalisations, 2018 QS Health, Standard 30/01/2018

Collection and usage attributes

Population group age from:

All ages

Computation description:

Inclusion codes, description and additional requirements

ICD-10-AM  (8th to 10th  editions) diagnosis code Description Additional requirements
E10 Type 1 diabetes mellitus

Principal diagnosis only

Include all codes from the three-character levels

E11 Type 2 diabetes mellitus

Principal diagnosis only

Include all codes from the three-character levels

E13 Other specified diabetes mellitus

Principal diagnosis only

Include all codes from the three-character levels

E14 Unspecified diabetes mellitus
 

Principal diagnosis only

Include all codes from the three-character levels

Exclusion codes and description

Care type Description
7.3 Newborn—unqualified days only
9.0 Organ procurement—posthumous
10.0 Hospital boarder

 

Presented as a number of hospitalisations per 100,000 people.

Rates are directly age- and sex- standardised, to the 30 June 2001 Australian population, using 5-year age groups: 0-4, 5-9, … , 80-84, 85 and over.

Indigenous and other Australian rates are directly age and sex standardised, to the 2001 Australian population, using 5-year age groups: 0-4, 5-9, … , 60–64, 65 and over.

Population estimates at 31 December are calculated as an average of the 30 June population estimates before and after the relevant December to derive a midpoint (31 December) population estimate.

For more information about age-standardisation in general see glossary item Age-standardised rate. 

Analysis by Statistical Area Level 3 (SA3) 2016 is based on:

  • Statistical Area Level 2 (SA2) 2011 of usual residence of the patient for 2014-15 to 2016-17, converted to SA3 (ASGS 2016) equivalents through an ABS concordance file
  • SA2 2016 of usual residence of the patient for 2017-18.

Suppress data (number and rate) if at least one of the following conditions are met:

  • the total denominator is less than 1,000
  • the total numerator is less than 20

Age and sex standardised rates are also suppressed where the denominator for at least one of the age and sex groups used to calculate the rate is below 30 and results of sensitivity analysis indicate that the rates are volatile. However, for SA3 data, if the volatility of the rate is not found to have a material impact on its decile, the rate is published with caution. For more information about the sensitivity analysis, see the Technical supplement of the Fourth Atlas.

Consequential suppression may be applied to preserve confidentialised data.

Computation:

100,000 × (Numerator ÷ Denominator)

Numerator:

The number of diabetes complications hospitalisations, 2014-15 to 2017-18

Numerator data elements:
Data Element / Data SetEpisode of care—principal diagnosis, code (ICD-10-AM 8th edn) ANN{.N[N]}
Data Source
National Hospital Morbidity Database (NHMD)
NMDS / DSS
Admitted patient care NMDS 2014-15
Guide for use

Data source type: Administrative by-product data


Data Element / Data SetEpisode of care—principal diagnosis, code (ICD-10-AM 9th edn) ANN{.N[N]}
Data Source
National Hospital Morbidity Database (NHMD)
NMDS / DSS
Admitted patient care NMDS 2015-16
Guide for use

Data source type: Administrative by-product data


Data Element / Data SetEpisode of care—principal diagnosis, code (ICD-10-AM 9th edn) ANN{.N[N]}
Data Source
National Hospital Morbidity Database (NHMD)
NMDS / DSS
Admitted patient care NMDS 2016-17
Guide for use

Data source type: Administrative by-product data


Data Element / Data SetEpisode of care—principal diagnosis, code (ICD-10-AM 10th edn) ANN{.N[N]}
Data Source
National Hospital Morbidity Database (NHMD)
NMDS / DSS
Admitted patient care NMDS 2017-18
Guide for use

Data source type: Administrative by-product data


Data Element / Data SetPerson—date of birth, DDMMYYYY
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Admitted patient care NMDS 2014-15 to 2017-18

Data source type: Administrative by-product data


Data Element / Data SetEpisode of admitted patient care—admission date, DDMMYYYY
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Admitted patient care NMDS 2014-15 to 2017-18

Data source type: Administrative by-product data


Data Element / Data SetPerson—sex, code A
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Admitted patient care NMDS 2014-15 to 2017-18

Data source type: Administrative by-product data


Data Element / Data SetHospital service—care type, code N[N]
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Admitted patient care NMDS 2014-15 to 2017-18

Data source type: Administrative by-product data


Denominator:

Total population as at 31 December 2014, 31 December 2015, 31 December 2016 and 31 December 2017.

Denominator data elements:
Data Element / Data SetPerson—estimated resident population of Australia, total people N[N(7)]
Data Source
ABS Australian Demographic Statistics
Guide for use

Data source type: Census based plus administrative by-product data.


Data Element / Data SetPerson—estimated resident population of Australia, total people N[N(7)]
Data Source
ABS Regional Population by Age and Sex, Australia
Guide for use

Data source type: Census based plus administrative by-product data


Data Element / Data SetPerson—estimated resident population of Australia, total people N[N(7)]
Data Source
ABS Indigenous estimates and projections (2016 Census-based)
Guide for use

Data source type: Census based plus administrative by-product data


Disaggregation:

SA3 2016

Remoteness (ASGS) Remoteness structure 2016) 
Socio-Economic Indexes for Areas (SEIFA 2016) Index of Relative Socioeconomic Disadvantage (IRSD 2016)

Primary Health Network (PHN) 2017

State and territory by Aboriginal and Torres Islander status

 

Disaggregation data elements:
Data Element / Data SetPerson—area of usual residence, statistical area level 2 (SA2) code (ASGS 2016) N(9)
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Data source type: Administrative by-product data


Data Element / Data SetPerson—Indigenous status, code N
Data Source
National Hospital Morbidity Database (NHMD)
Guide for use

Data source type: Administrative by-product data


Representational attributes

Representation class:Rate
Data type:Integer
Unit of measure:Episode
Format:

N[NNNN]

Data source attributes

Data sources:
Data SourceNational Hospital Morbidity Database (NHMD)
Frequency
Annual
Data custodian

Australian Institute of Health and Welfare



Data SourceABS Australian Demographic Statistics
Frequency
Quarterly
Data custodian

Australian Bureau of Statistics



Data SourceABS Regional Population by Age and Sex, Australia
Frequency
Annually
Data custodian

Australian Bureau of Statistics



Data SourceABS Indigenous estimates and projections (2016 Census-based)
Frequency
Periodic
Data custodian

Australian Bureau of Statistics


Accountability attributes

Methodology:

Statistical Area Level 3 (SA3s) are geographic areas defined in the ABS Australian Statistical Geography Standard (ASGS). The aim of SA3s is to create a standard framework for the analysis of ABS data at the regional level through clustering groups of SA2s that have similar regional characteristics. There are 340 spatial SA3s covering the whole of Australia without gaps or overlaps. They are designed to provide a regional breakdown of Australia. SA3s generally have a population of between 30,000 and 130,000 people. There are approximately 78 with fewer than 30,000 people and 46 with more than 130,000 as at 30 June 2016. The Other Territories of Jervis Bay, Cocos (Keeling) Islands, Christmas Island and Norfolk Island are each represetned by a SA3 in the 2016 ASGS.  For further information see the ABS publication, Population by Age and Sex, Regions of Australia, 2016.

The scope of the NHMD is episodes of care for admitted patients in all public and private acute and psychiatric hospitals, free-standing day hospital facilities and alcohol and drug treatment centres in Australia. Hospitals operated by the Australian Defence Force, corrections authorities and in Australia’s off-shore territories are not in scope, but some are included. 

 

Reporting requirements:

Australian Commission on Safety and Quality in Health Care

Australian Atlas of Healthcare Variation 2021

Organisation responsible for providing data:

Australian Institute of Health and Welfare

Accountability:

Australian Commission on Safety and Quality in Health Care

Release date:28/04/2021

Source and reference attributes

Submitting organisation:

Australian Commission on Safety and Quality in Health Care

Reference documents:

For more information about potentially preventable hospitalisations see:

National Healthcare Agreement: PI 18–Selected potentially preventable hospitalisations, 2019

Australian Atlas of Healthcare Variation, 2017: Technical Supplement

Relational attributes

Related metadata references:

See also ABS Estimated resident population (total population), QS Health, Standard 08/06/2011

See also ABS Indigenous experimental estimates and projections, QS Health, Standard 08/06/2011, Indigenous, Endorsed 11/09/2012

See also Australian Atlas of Healthcare Variation: Number of potentially preventable hospitalisations - diabetes complications, per 100,000 people, 2014–15 Australian Commission on Safety and Quality in Health Care, Standard 07/06/2017

See also Data quality statement: Admitted Patient Care 2015-16 AIHW Data Quality Statements, Endorsed 27/11/2019

See also Data quality statement: Admitted Patient Care 2016-17 AIHW Data Quality Statements, Endorsed 27/11/2019

See also Data quality statement: Admitted Patient Care 2017-18 AIHW Data Quality Statements, Endorsed 27/11/2019

See also Data quality statement: National Hospital Morbidity Database 2014–15 AIHW Data Quality Statements, Endorsed 31/08/2016