Acute Demand

……an overview

January 2011

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Davis,P. (2010) Quality or Quantity? Markets or Management? University of Auckland

NZ Public Hospital Performance 2

Hospital beds & discharges(1988 – 2001)

Day-stay

Inpatient

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

AHB CHE HHS DHB

Reform phase and year

Nu

mb

er

of

be

ds

uti

lis

ed

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

Nu

mb

er

of

dis

ch

arg

es

Number of discharges Number of inpatient discharges Number of beds utilised

Day stay

Inpatient

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Total Hospital Discharges per 1,000 Population (2007)

8 4

1 0 9

1 2 61 2 61 3 51 3 9

1 6 21 6 31 6 51 6 61 7 2

2 2 7

2 7 4

0

5 0

1 0 0

1 5 0

2 0 0

2 5 0

3 0 0

F R G E R N O R S W IT Z S W E O E C DM e d ia n

AU S * IT A* N Z U S * U K N E T H C AN ** 2006

Source: OECD Health Data 2009 (June 2009).

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Increase in Life Expectancy at Birth (1986–2006)

4.1

2.22.3

2.8

3.53.7

4.34.3

4.74.74.84.5

4.9

5.45.55.4

5.85.85.8

6.8

0

1

2

3

4

5

6

7

New

Zealand

France Germany Australia OECD

Median

Switzerland United

K ingdom*

Canada* Netherlands United

States*

Female Male

* 1985–2005

Source: OECD Health Data 2008, “June 2008.”

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Philosophy of Kaiser Permanente:

“Unplanned hospital admissions

are a sign of system failure”

Ham, C. (2006), Developing Integrated Care

in the NHS: adapting lessons from Kaiser,

Health Services Management Centre, Birmingham University

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Acute demand – what does it look like?

ED

Some increase: but national ED data prior to 2009/10 not as robust as inpatient data

Acute inpatient (excludes short stay admissions <24 hours, electives, and mental health admissions)

2000-2009: increase from 323,000 to 371,000 pa - 2/3 in Auckland.

A 15% increase, but only 2.4% greater than the increase in population.

ED and Acute Inpatient Demand per 10/000 Last 5 Years

0

500

1,000

1,500

2,000

2,500

2005 2005/06 2006 2006/07 2007 2007/08 2008 2008/09 2009 2009/10

Rat

e p

er 1

0,00

0

ED

Acute

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What is driving it…... conditions?Time Series of Acute Discharges 2000 - 2009

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Calendar year

Maternity

Medical

Surgery

Pop'n/10

21% increase in acute medical discharges (2000 – 2009)

The top 8 conditions accounted for 24% of acute inpatient discharges in 2009

Diagnosis Related Groupings Discharges% of Total

Chest Pain 13,236 3.6%

Oesophagitis Gastroent & Misc Digestive System 12,980 3.5%

Respiratory Infections/Inflammations 12,838 3.5%

Cellulitis 10,995 3.0%

Neonate Admission 10,338 2.8%

Circulatory Disorders 9,385 2.5%

Chronic Obstructive Airways Disease 9,362 2.5%

Abdominal Pain or Mesenteric Adenitis 9,155 2.5%

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OECD Health Care Quality Indicators Database 2009

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The people perspective

Emergency Department (ED) use in previous 12 months (age standardised)

0

2

4

6

8

10

12

14

1996/97 2002/03 2006/07

perc

ent

Men

Women

Inpatient overnight admissions in the previous 12 months (age standardised)

0

2

4

6

8

10

12

1996/97 2002/03 2006/07

perc

ent Men

Women

NZ Health Survey

1996/97, 2002/03, 2006/07

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Frequent attenders

All ED Visits 2009/10

2%, 10%

6%, 20%

11%, 30%

19%, 40%

26%, 50%31%, 55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

% of Unique Patients

% o

f Vol

ume/

Visi

ts

600k unique individuals with an average of 1.5 visits to ED per year

About 75% of patients visited only once

1.5 % visited >6 times

One person visited 145 times

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The main demographic drivers

Acute I npatient Discharge and Population Composition by Age Band 2009: Maori

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Under 5 05 to 24 15 to 24 25 to 44 45 to 64 65 +

% of Population % of Acute Discharges

Acute I npatient Discharge and Population Composition by Age Band 2009: Pacific

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Under 5 05 to 24 15 to 24 25 to 44 45 to 64 65 +

% of Population % of Acute Discharges

Acute Inpatient Discharge and Population Composition by Age Band 2009

0%

5%

10%

15%

20%

25%

30%

35%

40%

Under 5 05 to 24 15 to 24 25 to 44 45 to 64 65 +0%

5%

10%

15%

20%

25%

30%

35%

40%

% of Population % of Acute Discharges

Age (total population) Ethnicity.. Acute I npatient Discharge and Population Composition by Age Band 2009: Maori

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Under 5 05 to 24 15 to 24 25 to 44 45 to 64 65 +

% of Population % of Acute Discharges

25% growth for Maori 2000-2009

56% growth for Pacific 2000-2009

30% growth for people 65+

2000 - 2009

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Conditions also vary by ethnicity

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and by DHB……….

Composition of Number of Discharges (2009) by MDC Comparing Metropolitan and Provincial

MDC Metropolitan Provincial

Respiratory System 18.2% 14.9%Circulatory System 17.4% 16.7%Nervous System 10.9% 8.6%Digestive System 9.3% 13.1%Preg/Childbirth/Puerperium 8.8% 2.7%Musculoskeletal 7.9% 10.7%Ear/Nose/Mouth/Throat 5.5% 4.0%Skin, Subcutaneous Tissue & Breast 4.1% 5.2%Kidney Urinary Tract 3.1% 4.4%Injury/Poison/Toxic of Drugs 2.9% 4.4%

2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

2% 4% 6% 8% 10% 12% 14% 16% 18%

Metropolitan

Provincial

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tActual and Expected Acute Inpatient Discharges 2009 Calendar

Year

05,000

10,00015,00020,00025,00030,00035,00040,00045,00050,000

DHB of Domicile

Dis

char

ges

Actual Discharges

Expected Discharges

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Change in inpatient discharge rates (2000 – 2009)

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ED admissions & discharges

ED Attendance per 100 People

0

10

20

30

40

50

60

70

00 01-04 05-14 15-24 25-44 45-64 65-74 75-84 85+

age band

Att

end

ance

per

100

po

pn

.

EDD Ratio

EDA Ratio

Total Ratio

ED attenders & admission:

• strong association with age – the elderly

• weaker association with ethnicity and deprivation

ED attenders not admitted:

• people from deprivation quintile 4&5 = 40% of the population yet 55% of non-admitted patients

DHB factors are significant

• smaller DHBs have a higher proportion of ED attenders not admitted

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Relationships

Statistically significant inverse relationships between: • size of the DHB population and ED not admitted numbers• GP/nurse consults and ED not admitted numbers – if West Coast and Wairarapa excludedNo apparent relationship with VLCA

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Relationship between GPs & Acute Hospital Discharge Rates

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Relationship between GPs & Acute Hospital Discharge Rates

High acute

discharge rates

Low GP FTE per 100,000 High GP FTE per 100,000

DHB Acute ASR GP FTE DHB Acute ASR GP FTE

Wairarapa 1184 74 Tairawhiti 1201 84

Counties Manukau 1102 59 Lakes 1153 83

Waitemata 1049 58 Hawkes Bay 1061 80

Bay of Plenty 1012 79 Auckland 1052 103

Hutt Valley 1009 67 Whanganui 958 88

South Canterbury 971 85

Low acute discharge rates

Waikato 882 67 Southland 939 83

Taranaki 823 56 Northland 866 81

MidCentral 803 71 Canterbury 860 84

West Coast 724 75 Capital & Coast 778 84

Nelson Marlborough 722 75 Otago 752 94Acute inpatient discharge rate, age standardised. (2009)

Medical Council Workforce Survey (2009)

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The system

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Community

services

ED Inpatient Community

• Primary Care (distribution & availability – inc after hours)• Changing GP practice• Poor access to diagnostics and specialist opinions• Changing referral patterns (variability++)• variable attachment with general practice• Financial barriers• Changing use of ambulances• Fragmentation of services

• Improved ED services & facilities• Changing (& variable) admission thresholds• Inpatient bed availability• Repeat attenders• Local behaviours

• Bed availability• Advances in medical technology• Discharge planning

• Family & community support• Relationship with primary care• Primary care capability & capacity• Aged residential care capability & capacity

Patients – changing:

demographics – two broad segments – young adult & elderly

morbidity – more chronic illness

expectations – more “consumerism” + a “medicalised” population

more self-referral, but people confused about where to go

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Through a consumer’s eyes……..

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And it depends on the problem definition

Growth• reducing our overall growth rate requires a focus on metropolitan Auckland

Variation between DHBs presents a significant improvement opportunity. Addressing this will require• good comparative data• clinical engagement• an understanding of local initiatives/patterns of behaviour/admission thresholds• a whole of system approach - ? the DHB funder role

Its complex - there’s no “silver bullet”

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What works

Kings Fund Seminar

• Proactive management of people with long term conditions, especially people with multiple conditions• Integrated working between health and social care• Multiple coordinated strategies, underpinned by an integrated information system• Use of advance directives and a range of alternatives to hospital eg hospice• Preventing re-admissions – active management of transitions• The use of “virtual” wards in the community• The use of practice based commissioning enabling integration between general practices and other services• A single assessment and coordinated care approach for older people at risk of hospital admission

Ham C, Imison C, Jennings M (2010) Avoiding hospital admissions, lessons from evidence and experience.

Kings Fund

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Next steps

• Expert Roundtable – second meeting• Sector engagement

o BSMC business cases – DHBs & primary careo DHBs – through their regular meetingso ED Advisory Group – Feb 2011o Professional groups eg Colleges

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Useful resources

Basu A, Brinson D (2008) The Effectiveness of Interventions for Reducing Ambulatory Sensitive Hospitalisations: A Systematic Review. HSAC Report

Blunt I, Bardsley M, Dixon J (2010) Trends in Emergency Admissions in England 2004 – 2009. Nuffield Trust

Blunt I, Bardsley M, Dixon J (2010) Trends in Emergency Admissions in England 2004 – 2009: is greater efficiency breeding inefficiency?. Nuffield Trust

Booz, Allen, Hamilton (2007) Key Drivers of Demand in the Emergency Department. NSW Department of Health

Curry N, Ham C (2010) Clinical and Service Integration, the route to improved outcomes. Kings Fund

Ham C, Imison C, Jennings M (2010) Avoiding hospital admissions, lessons from evidence and experience. Kings Fund

NZHTA Report 8 (1998) Emergency Department Attendance a critical appraisal of the key literature. New Zealand Health Technology Assessment, University of Otago

Purdy S (2010) Avoiding Hospital Admissions, what does the research evidence say? Kings Fund

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Appendix

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Age Standardised Rates*

DHB of DomicileAcute In Patient

Discharges 2009ED 2009/10

Rate:ED presentation: Acute In Patient Discharges

Northland 866 2,454 2.8

Waitemata 1,049 2,241 2.1

Auckland 1,052 2,027 1.9

Counties Manukau 1,102 2,056 1.9

Waikato 882 2,527 2.9

Lakes 1,153 4,493 3.9

Bay of Plenty 1,012 3,441 3.4

Tairawhiti 1,201 3,971 3.3

Taranaki 823 4,365 5.3

Hawkes Bay 1,061 2,494 2.4

Whanganui 958 3,264 3.4

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tAge Standardised Rates*

DHB of DomicileAcute In Patient

Discharges 2009ED 2009/10

Rate:ED presentation: Acute In Patient Discharges

MidCentral 803 2,302 2.9

Hutt Valley 1,009 3,221 3.2

Capital and Coast 778 1,738 2.2

Wairarapa 1,184 5,483 4.6

Nelson Marlborough 722 2,611 3.6

West Coast 724 4,675 6.5

Canterbury 803 2,080 2.6

South Canterbury 971 2,930 3.0

Otago 752 2,187 2.9

Southland 939 4,316 4.6

National 945 3,089 3.3