Population health profile of the. Western Melbourne. Division of General Practice: supplement

Transcription

1 Population health profile of the Melbourne Division of General Practice: supplement Population Profile Series: No. 43a PHIDU December 006

2 Copyright Commonwealth of Australia 006 This work may be reproduced and used subject to acknowledgement of the source of any material so reproduced. National Library of Australia Cataloguing in Publication entry Population health profile of the Melbourne Division of General Practice: supplement. Bibliography. ISBN (web).. Public health - Victoria - West Melbourne - Statistics.. Health status indicators - Victoria - West Melbourne - Statistics. 3. Health service areas - Victoria - West Melbourne. 4. West Melbourne - Statistics, Medical. I. Public Health Information Development Unit (Australia). (Series : Population profile series ; no. 43a) ISSN Population Profile Series Public Health Information Development Unit, The University of Adelaide A Collaborating Unit of the Australian Institute of Health and Welfare This profile was produced by PHIDU, the Public Health Information Development Unit at The University of Adelaide, South Australia. The work was funded under a grant from the Australian Government Department of Health and Ageing. The views expressed in this profile are solely those of the authors and should not be attributed to the Department of Health and Ageing or the Minister for Health and Ageing. Interpretation of differences between data in this profile and similar data from other sources needs to be undertaken with care, as such differences may be due to the use of different methodology to produce the data. Suggested citation: PHIDU. (006) Population health profile of the Melbourne Division of General Practice: supplement. Population Profile Series: No. 43a. Public Health Information Development Unit (PHIDU), Adelaide. Enquiries about or comments on this publication should be addressed to: PHIDU, The University of Adelaide, South Australia 5005 Phone: or PHIDU@publichealth.gov.au This publication, the maps and supporting data, together with other publications on population health, are available from the PHIDU website ( Published by Public Health Information Development Unit, The University of Adelaide Contributors: Anthea Page, Sarah Ambrose, Kristin Leahy and John Glover ii

3 Population health profile of the Melbourne Division of General Practice: supplement This profile is a supplement to the Population health profile of the Melbourne Division of General Practice, dated November 005, available from This supplement includes an update of the population of the Melbourne Division of General Practice, as well as additional indicators and aspects of the Division s socioeconomic status, use of GP services and health. The contents are: Population [updated to June 005] Additional socio-demographic indicators Unreferred attendances patient flow/ GP catchment Additional prevalence estimates: chronic diseases and risk factors combined Avoidable hospitalisations: hospital admissions resulting from ambulatory care sensitive conditions Avoidable mortality For further information on the way Division totals in this report have been estimated, please refer to the Notes on the data section of the Population health profile, November 005 ( Population The Melbourne Division had an Estimated Resident Population of 7,06 at 30 June 005. Figure : Annual population change,, Melbourne, Victoria and Australia, 99 to 996, 996 to 00 and 00 to 005 Annual % change Over the five years from 99 to 996, the Division s population increased by.% on average each year, above that in Melbourne (0.8%), and Victoria (0.6%) as a whole. From 996 to 00, the annual percentage increase was.9%, again higher than in Melbourne (.3%), Victoria (.%) and Australia (.3%). From 00 to 005, the population increase of.% was around twice the annual increases for Melbourne and Victoria. Table : Population by age, and Australia, 005 Age group (years) Australia No. % No. % , ,978, , 4.4,89, , ,878, ,50.6 4,984, , 5.6,398, , , , ,07.5 Total 7, ,38, As shown in the accompanying table and the age-sex pyramid (Figure ), the had marginally more children aged 0 to 4 years (0.%), 5 to 4 year old young people (4.4%) and people in the 5 to 44 year age group (3.7%) than Australia as a whole (with 9.6%, 3.9% and 8.9%, respectively) (Table ). Conversely, the 45 years and over age groups had lower proportions compared to Australia as a whole.

4 Age (years) Figure : Population in and Australia, by age and sex, 005 Australia Males Females Males Females Population 005 Population 00 Males Females Males Females Proportion of population: per cent The most notable differences in the age distribution of the Division s population (when compared to Australia overall) are: from 0 to 4 years a higher proportion of males and females; from 0 to 9 years fewer males and females; from 0 to 39 years higher proportions of both males and females; and at 45 years and over lower proportions of both males and females. Figure 3: Population projections for, by age and sex, 005 and 00 Age (years) Proportion of population: per cent Additional socio-demographic indicators The population projections for the Division show a number of changes in age distribution, with the 00 population projected to have: at younger ages lower proportions of children, teenagers and young adults, aged 0 to 4 years; from 5 to 44 years lower proportions of both males and females; and at 45 years and over higher proportions of both males and females (most notably at ages 60 to 74 years). Please refer to the earlier Population health profile of the Melbourne Division of General Practice, dated November 005, available from for other socio-demographic indicators. Figure 4: Index of Relative Socio-Economic Disadvantage,, 00 Index, Least disadvantaged Most disadvantaged Q Q Q3 Q4 Q5 Quintile of socioeconomic disadvantage of area One of four socioeconomic indexes for areas produced at the 00 ABS Census is the Index of Relative Socio-Economic Disadvantage. The has an index score of 9, below the score for Australia of 000: this score varies widely across the Division, from 788 in the most disadvantaged areas to 053 in the least disadvantaged areas. Note: each quintile comprises approximately 0% of the population of the Division. A new indicator, produced for the first time at the 00 ABS Census, shows the number of jobless families with children under 5 years of age. There were substantially more jobless families in the (3.6%), compared to Melbourne as a whole (4.7%) (Figure 5, Table ). With the introduction of the 30% rebate for private health insurance premiums, there was a once-off registration process, providing information of the postcode and residence of those who had such insurance (these data are not available at this area level for later dates). In 00, the Division had a markedly lower proportion of people with private health insurance (9.8%), compared to Melbourne (49.%) (Figure 5, Table ).

5 Figure 5: Socio-demographic indicators,, Melbourne, Victoria and Australia, 00 Jobless families with children under 5 years old Private health insurance, 30 June Per cent Melbourne DGP Per cent Melbourne DGP Table : Socio-demographic indicators,, Melbourne, Victoria and Australia, 00 Indicator No. % No. % No. % No. % Jobless families with children 6, , , , under 5 years old Private health insurance (30 June) 7,99 9.8,653, ,96, ,67, Details of the distribution of jobless families and of the population covered by private health insurance are shown by Statistical Local Area (SLA) in Maps and, respectively. Map : Jobless families with children under 5 years of age by SLA,, 00 Per cent Melton Balance Melton- East Brimbank Keilor Brimbank- Sunshine Moonee Valley - Essendon Maribyrnong 30.0% or more 4.0% to 9.9% 8.0% to 3.9%.0% to 7.9% fewer than.0% not mapped # Melbourne- Remainder # data were not mapped: see Mapping note under Methods Map : People covered by private health insurance by SLA,, 30 June 00 Per cent Melton Balance Melton- East Brimbank Keilor Brimbank- Sunshine Moonee Valley - Essendon Maribyrnong Fewer than 8.0% 8.0% to 33.9% 34.0% to 39.9% 40.0% to 45.9% 46.0% or more not mapped # Melbourne- Remainder # data were not mapped: see Mapping note under Methods 3

6 GP services to residents of the The following tables include information, purchased from Medicare Australia, of the movement of patients and GPs between Divisions. Note that the data only include unreferred attendances recorded under Medicare: unreferred attendances not included are those for which the cost is met by the Department of Veterans Affairs or a compensation scheme; or are provided by salaried medical officers in hospitals, community health services or Aboriginal Medical Services, and which are not billed to Medicare. At any attendance, one or more services may have been provided. Four fifths (80.9%) of all unreferred attendances to residents of the were provided in the Division (ie. by a GP with a provider number in the Division): this represented,6,805 GP unreferred attendances (Table 3). A further 5.9% of unreferred attendances to residents were provided by GPs with a provider number in North West, with 5.6% provided by GPs in. Table 3: Patient flow People living in by Division where attendance occurred, 003/04 Division Unreferred attendances Number Name No. % 3 306,6, North West 87, , Westgate DGP 7, Southcity DGP 8, Northern DGP- Melbourne, Central Highlands DGP 0, Other.. 45,8 3.0 Total..,503, Based on address in Medicare records Division of GP based on provider number 3 Proportion of all unreferred attendances of patients with an address in Division 306 by Division in which attendance occurred Four fifths (80.9%) of unreferred attendances provided by GPs with a provider number in were also to people living in the Division (ie. their Medicare address was in the Division) (Table 4). A further 5.8% of unreferred attendances provided by GPs in the Division were to residents of Westgate DGP, with 5.3% to people living in North West. Table 4: GP catchment Unreferred attendances provided by GPs in by Division of patient address, 003/04 Division Unreferred attendances Number Name No. % 3 306,6, Westgate DGP 87, North West 79, , Central Highlands DGP 7, Northern DGP-Melbourne 9, Other.. 5, Total..,503, Division of GP based on provider number Based on address in Medicare records 3 Proportion of all unreferred attendances to GPs with a provider number in Division 306 by Division of patient address 4

7 Additional prevalence estimates: chronic diseases and risk factors combined Please refer to the earlier Population health profile of the Melbourne Division of General Practice, dated November 005, available from for the separate prevalence estimates of chronic disease; measures of self-reported health and risk factors. The process by which the estimates have been made, and details of their limitations, are also described in the Notes on the data section of this earlier profile. In this section two estimates, which combine the prevalence of selected chronic diseases with a risk factor, are shown for the Division. The measures are of people who had asthma and were smokers, and people who had type diabetes and were overweight or obese: note that the estimates have been predicted from self-reported data, and are not based on clinical records or physical measures. It is estimated that there were relatively more people in who had asthma and were smokers, compared to Melbourne as a whole (Figure 6, Table 5): that is, the prevalence rates per,000 population were higher, although the rate consistent with that for Australia. The rate of people in who had type diabetes and were overweight/ obese was above the rates in Melbourne and Australia. Figure 6: Estimates of selected chronic diseases and risk factors,, Melbourne and Australia, 00 Melbourne Australia Variable Rate per,000 Had asthma and were smokers (8+ years) Had type diabetes and were overweight/ obese (5+ years) Table 5: Estimates of selected chronic diseases and risk factors,, Melbourne, Victoria and Australia, 00 Variable No. Rate No. Rate No. Rate No. Rate Had asthma 5, , , , smoked 3 Had type diabetes were overweight/ obese 4 3, , , ,76 5. No. is a weighted estimate of the number of people in reporting these chronic conditions/ with these risk factors and is derived from synthetic predictions from the 00 NHS Rate is the indirectly age-standardised rate per,000 population 3 Population aged 8 years and over 4 Population aged 5 years and over 5

8 Avoidable hospitalisations: hospital admissions resulting from ambulatory care sensitive conditions The rationale underlying the concept of avoidable hospitalisations is that timely and effective care of certain conditions, delivered in a primary care setting, can reduce the risk of hospitalisation. Admissions to hospital for these ambulatory care sensitive (ACS) conditions can be avoided in three ways. Firstly, for conditions that are usually preventable through immunisation or nutritional intervention, disease can be prevented almost entirely. Secondly, diseases or conditions that can lead to rapid onset problems, such as dehydration and gastroenteritis, can be treated. Thirdly, chronic conditions, such as congestive heart failure, can be managed to prevent or reduce the severity of acute flare-ups to avoid hospitalisation. This measure does not include other aspects of avoidable morbidity, namely potentially preventable hospitalisations (hospitalisations resulting from diseases preventable through population based health promotion strategies, e.g. alcohol-related conditions; and most cases of lung cancer) and hospitalisations avoidable through injury prevention (e.g. road traffic accidents). For information on the ambulatory care sensitive conditions and ICD codes included in the analysis in this section, please refer to the Atlas of Avoidable Hospitalisations in Australia: ambulatory care-sensitive conditions, available from In 00 to 00, the 7,53 admissions from ambulatory care sensitive (ACS) conditions accounted for 8.5% of all admissions in the (Table 6, Figure 7), marginally below the levels in Victoria (8.8%) and Australia (8.7%). Table 6: Avoidable and unavoidable hospitalisations,, Victoria, and Australia, 00/0 Category Victoria Australia No. Rate % No. Rate % No. Rate % Avoidable 7,53 3, ,35, ,786, Unavoidable 77,8 33, ,50,437 3, ,88,99 9, Total 84,435 36, ,655,57 34, ,370,985 3, Admissions resulting from ACS conditions Rate is the indirectly age-standardised rate per 00,000 population Figure 7: Avoidable hospitalisations,, Victoria and Australia, 00/0 Rate per 00,000 3,500 3,000,500,000,500, Victoria Australia Admissions resulting from ACS conditions The rate of avoidable hospitalisations in, 3,99.9 admissions per 00,000 population, is higher than the rates for Victoria (a rate of,983.) and for Australia (,847.5). Diabetes complications, congestive heart failure, chronic obstructive pulmonary disease, asthma and angina were the five conditions with the highest rates of avoidable hospitalisations in the (Figure 8, Table 7). Table 7 shows the number, rate and proportion of avoidable hospitalisations, for the individual ACS conditions, as well as the vaccine-preventable; acute; and chronic sub-categories. The majority of avoidable hospitalisations are attributable to chronic health conditions. The predominance of hospitalisations for chronic conditions in this period can be primarily attributed to the large number of admissions for diabetes complications. Dehydration and gastroenteritis, and dental conditions have the highest rates of avoidable hospitalisations for the acute conditions. 6

9 Figure 8: Avoidable hospitalisations by condition, and Victoria, 00/0 Victoria Diabetes complications Congestive heart failure Chronic obstructive pulmonary disease Asthma Angina Dehyration and gastroenteritis Dental conditions Convulsions and epilepsy Cellulitis Ear, nose and throat infections Iron deficiency anaemia Perforated/bleeding ulcer Pyelonephritis Pelvic inflammatory disease Influenza and pneumonia Gangrene Other vaccine-preventable conditions Hypertension Ruptured appendix ,000,00 Rate per 00,000 Admissions resulting from ACS conditions: excludes nutritional deficiencies as less than ten admissions Table 7: Avoidable hospitalisations by condition,, Victoria and Australia, 00/0 Sub-category/ condition Melbourne DGP Victoria Australia No. Rate No. Rate No. Rate Vaccine-preventable , , Influenza and pneumonia , ,0 67. Other vaccine preventable , Chronic 3 5,089, ,33, ,545,86 Diabetes complications,460, , , Iron deficiency anaemia , , Hypertension , , Congestive heart failure , , Angina , , Chronic obstructive pulmonary disease , , Asthma , ,009.3 Acute, ,53, ,93,035 Dehydration and gastroenteritis , , Convulsions and epilepsy , , Ear, nose and throat infections , , Dental conditions , , Perforated/bleeding ulcer , , Ruptured appendix , Pyelonephritis , , Pelvic inflammatory disease , , Cellulitis , , Gangrene , , Total avoidable hospitalisations 4 7,53 3, ,35, ,786,847.5 Admissions resulting from ACS conditions Rate is the indirectly age-standardised rate per 00,000 population 3 Excludes nutritional deficiencies as less than ten admissions 4 Sub-category and condition numbers and rates do not add to the reported total avoidable admissions: five conditions (influenza pneumonia, other vaccine preventable, diabetes complications, ruptured appendix and gangrene) are counted in any diagnosis, so may be included in more than one condition group 7

10 Avoidable mortality Avoidable and amenable mortality comprises those causes of death that are potentially avoidable at the present time, given available knowledge about social and economic policy impacts, health behaviours, and health care (the latter relating to the subset of amenable causes). For information on the avoidable and amenable mortality conditions and ICD codes included in the analysis in this section, please refer to the Australian and New Zealand Atlas of Avoidable Mortality, available from Almost three quarters (7.6%) of all deaths in at ages 0 to 74 years over the period 997 to 00 are considered to be avoidable, consistent with the proportion for Melbourne (7.0%) (Table 8). However, the rate in the Division is notably (%) higher than that in Melbourne. Deaths amenable to health care (amenable mortality, a subset of avoidable mortality) accounted for 8.4% of all deaths at ages 0 to 74 years in, also consistent with 8.7% in Melbourne. Table 8: Avoidable and unavoidable mortality (0 to 74 years) by area,, Melbourne, Victoria and Australia, 997 to 00 Mortality category No. Rate No. Rate No. Rate No. Rate Avoidable, , , ,845.8 % of total (Amenable) (909) (88.3) (,406) (78.4) (8,406) (8.4) (76,49) (85.) (% of total) (8.9) (..) (8.7) (..) (8.7) (..) (8.7) (..) Unavoidable , , , % of total Total mortality 3, , , , % Rate is the indirectly age-standardised rate per 00,000 population Rates of avoidable mortality were higher for males than for females in each of the comparator areas. s rate of avoidable mortality for males was 76.6 deaths per 00,000 males, higher than the rate of 53. for females. The rate of amenable mortality for males in the Division was also higher, 95.3, compared to 8. for females, a rate ratio of.8 (Figure 9, Table 9). Figure 9: Avoidable and amenable mortality by sex (0 to 74 years),, Melbourne, Victoria and Australia, 997 to 00 Note: the different scales Avoidable Amenable Rate per 00,000 Males Females Rate per 00, Males Females 0 0 8

11 Table 9: Avoidable and amenable mortality (0 to 74 years) by sex,, Melbourne, Victoria and Australia, 997 to 00 Mortality category and sex No. Rate No. Rate No. Rate No. Rate Avoidable Males, , , , Females , , , Total, , , ,845.8 Rate ratio M:F...8 **...74 **...77 **...8 ** Amenable Males , , , Females , , , Total , , , Rate ratio M:F...8 *...8 **... **...5 ** Rate is the indirectly age-standardised rate per 00,000 population Rate ratio (M:F) is the ratio of male to female rates; rate ratios differing significantly from.0 are shown with * p <0.05; ** p <0.0 Another way of measuring premature mortality is to calculate the number of years of life lost (YLL), which takes into account the years a person could have expected to live at each age of death based on the average life expectancy at that age. The numbers of YLL for, Melbourne, Victoria and Australia over the period of analysis are shown in Table 0 by mortality category. However, given the substantial variation in the populations of these areas, a comparison of the proportion of YLL for each area is also shown. YLL from avoidable mortality accounted for 7.8% of total YLL (0 to 74 years) for Melbourne DGP, consistent with the proportion for Melbourne. The proportion of YLL from amenable mortality for (8.3%) was also consistent with that for Melbourne (8.%). Table 0: Years of life lost from avoidable mortality (0 to 74 years),, Melbourne, Victoria and Australia, 997 to 00 Mortality category No. % of total No. % of total No. % of total No. % of total Avoidable 39, , , ,37, (Amenable) (5,756) (8.3) (0,67) (8.) (30,758) (8.) (,98,430) (8.0) Unavoidable 5,688 8., , ,303,89 8. Total 55, , ,05, ,630, Years of life lost were calculated using the remaining life expectancy method (this provides an estimate of the average time a person would have lived had he or she not died prematurely). The reference life table was the Coale and Demeny Model Life Table West level 6 female (for both males and females), with the YLL discounted to net present value at a rate of 3 per cent per year. 9

12 In each of the areas in Table, the majority of avoidable mortality at ages 0 to 74 years occurred in the 65 to 74 year age group (Table ), with,478.8 deaths per 00,000 population in the Melbourne Division. The 45 to 64 year age group accounted for the next highest rate of avoidable death in all of the comparators, with a rate 307. in the Melbourne Division. Table : Avoidable and amenable mortality by age,, Melbourne, Victoria and Australia, 997 to 00 Mortality category and age (years) No. Rate No. Rate No. Rate No. Rate Avoidable , , ,0 45., , , , , , , , , , , ,493,358. Total, , , ,845.8 Amenable , , , , , , , , , , Total , , , Rate is the indirectly age-standardised rate per 00,000 population Table shows the number and age-standardised death rate by selected major condition group and selected causes included in the avoidable mortality classification. The highest rates of avoidable mortality for the selected major condition groups in the were for cancer, with a rate of 75.6 deaths per 00,000 population, and cardiovascular diseases, 67.9 deaths per 00,000 population (Table, Figure 0). For the selected causes within the condition groups, the two major causes of avoidable mortality were ischaemic heart disease and lung cancer, with rates of 50.3 per 00,000 population and 6.5 per 00,000, respectively. Table : Avoidable mortality (0 to 74 years) by major condition group and selected cause,, Melbourne, Victoria and Australia, 997 to 00 Condition group/ selected cause No. Rate No. Rate No. Rate No. Rate Cancer , , , Colorectal cancer 85 3.,8 4. 3, , Lung cancer , ,44 3., Cardiovascular diseases , , , Ischaemic heart disease , , , Cerebrovascular diseases ,03.7,947.9, Respiratory system 7., ,6.5,6 3.0 diseases Chronic obstructive ,45 9., ,395.6 pulmonary disease Unintentional injuries 5.4, , ,4 5.9 Road traffic injuries ,9 7.3, ,38 9. Intentional injuries 0 3.9, , , Suicide and self inflicted 00.7,877.4,75.3, injuries Rate is the indirectly age-standardised rate per 00,000 population 0

13 Rates in the Division were generally above, or consistent with, those for Melbourne and Australia: the exceptions were in the injury categories (Figure 0). Figure 0: Avoidable mortality (0 to 74 years) by major condition group and selected cause,, Melbourne and Australia, 997 to 00 Melbourne Australia Condition group/ selected cause Cancer Colorectal cancer Lung cancer Rate per 00,000 Cardiovascular diseases Ischaemic heart disease Cerebrovascular diseases Respiratory system diseases Chronic obstructive pulmonary disease Unintentional injuries Road traffic injuries Intentional injuries Suicide and self inflicted injuries

14 Notes on the data Data sources and limitations General References to Melbourne relate to the Melbourne Statistical Division. Data sources Table 3 details the data sources for the material presented in this profile. Table 3: Data sources Section Population Figures and ; Table Figure 3 Source Estimated Resident Population, ABS, 30 June for the periods shown Estimated Resident Population, ABS, 30 June 005; Population Projections, ABS, 30 June 00 (unpublished) Additional socio-demographic indicators Figure 4 ABS SEIFA package, Census 00 Table ; Figure 5; Map Jobless families, ABS, 00 (unpublished) Table ; Figure 5; Map Private health insurance, from Hansard GP services patient flow/ GP catchment Tables 3 and 4 Medicare Australia, 003/04 Additional prevalence estimates: chronic diseases and risk factors combined Figure 6; Table 5 Estimated from 00 National Health Survey (NHS), ABS (unpublished) Avoidable hospitalisations: hospital admissions resulting from ambulatory care sensitive conditions Tables 6 and 7; Figures 7 and 8 National Hospital Morbidity Database at Australian Institute of Health Welfare, 00/0; data produced in HealthWIZ by Prometheus Information (not available in public release dataset) Avoidable mortality Tables 8, 9, 0, and ; Figures 9 and 0 ABS Deaths ; data produced in HealthWIZ by Prometheus Information (not available in public release dataset) The projected population at June 00 is based on the 00 ERP. As such, it is somewhat dated, and does not take into account more recent demographic trends: it is however the only projection series available at the SLA level for the whole of Australia. Methods For background information on the additional prevalence estimates presented in this profile, please refer to the Notes on the data section of the Population health profile, November 005 ( Please also refer to the November 005 profile for information on the data converters. Mapping In some Divisions the maps may include a very small part of an SLA which has not been allocated any population; or has a population of less than 00 or has less than % of the SLAs total population; or there were less than five cases (i.e. jobless families, people with health insurance): these areas are mapped with a pattern.

15 Statistical geography of the For information on the postcodes in the Division, please refer the Department of Health and Ageing website also included in table format in the Notes on the data section of the Population health profile, November 005 ( Statistical Local Areas (SLAs) are defined by the Australian Bureau of Statistics to produce areas for the presentation and analysis of data. In this Division, some Local Government Areas (LGAs) have been split into SLAs. For example, the LGA of Brimbank has two SLAs, Sunshine (all in the Division) and Keilor (part in the Division). These SLAs and all or part of the other SLAs listed in Table 4 comprise the Division. Table 4: SLAs and population in, 005 on 00 boundaries SLA code SLA name Per cent of the SLA s population in the Division * Estimate of the SLA s 005 population in the Division 8 Brimbank (Keilor) ,666 8 Brimbank (Sunshine) , Maribyrnong , Melbourne (Remainder) Melton (East) , Melton (Balance) 33. 3, Moonee Valley (Essendon) 9.4 6,34 * Proportions are approximate and are known to be incorrect in some cases, due to errors in the concordance used to allocate CDs to form postal areas Acknowledgements Funding for these profiles was provided by the Population Health Division of the Department of Health and Ageing (DoHA). Further developments and updates When the re-aligned boundaries are released and DoHA have made known their geographic composition, PHIDU will examine the need to revise and re-publish these profiles (Population health profile, dated November 005, and the Population health profile: supplement, dated December 006). PHIDU contact details For general comments, data issues or enquiries re information on the web site, please contact PHIDU: Phone: or PHIDU@publichealth.gov.au 3