The rise and rise of chronic disease in Far North Queensland

A new Centre for Chronic Disease Prevention at JCU Cairns

Snapshot of past, current and future work

Robyn McDermott MBBS, FAFPHM, MPH, PhD.

Director CCDP, JCU Cairns

CBH Grand Rounds Friday 28 March 2014. Block “A” Lecture Theatre 12.15-1.30pm

Today

• Brief background and selected past and current descriptive work in far north Queensland

• Approach of the CCDP• Interventions• Where are we heading?

Some “political arithmetic of crowd disease” in Australia:CVD Death rates, 2007-8

Source: AIHW 2011, Age-standardised deaths per 100,000

CVD hospitalisation rates, 2007-8Source AIHW 2011: Age standardised hospitalisations per 100,000

Prevalence of diabetes, Indigenous NQ (WPHC) and Australia (AusDiab), 1999-2000

0

10

20

30

40

50

60

15-24 25-34 35-44 45-54 55-64 65+

Non-IndigenousAboriginalTorres Strait Islander

Age standardised rates for “ACS” avoidable admissions by Queensland Health District, 2003-6

Source: QHAPDC, 2007 (rates per 100,000)

Ambulatory Care Sensitive (ACS) avoidable hospitalisations for selected chronic diseases, Queensland, 1999-2006.

Source: QAPDC, 2007, rates per 100,000

Potentially Preventable Hospitalisations in SA (2007-9) - Top 15

Adjusted incidence rate ratios for CHD events in FNQ Aboriginal and TSI adults, 2000-7 (n=1706)

Source: McDermott et al, MJA, 2011

Measure IRR 95% CI

Obesity 1.7 1.01-2.8

High BP (>140/90) 1.5 1.01-2.3

Smoking 1.4 0.9-2.2

Low HDL (<1.0mmol/l) 1.3 0.9-1.9

High TG (>=2.0 mmol/l) 1.9 1.3-2.7

IFG (FBG 5.5-6.9 mmol/l) 1.3 0.8-2.2

Diabetes (FBG >=7.0) 2.4 1.6-3.6

Micro-albuminuria 1.4 0.9-2.3

Macro-albuminuria 4.6 2.9-7.1

Glycemia and albuminuria, especially when combined, predict much of the “gap” in CHD incidence

• Baseline prevalence of high glycemia is >25% • Baseline prevalence of albuminuria (>3.4 mmol/l) =

33.5%• Those with diabetes at baseline were 5.5 (4.2-7.3)

times more likely to have albuminuria than those without diabetes

• Adjusted CHD IRR for both diabetes and albuminuria = 5.9 (3.4-10.1)

Risk accumulation along the care continuum

Low birth weight

Maternal diabetes in pregnancyEpigeneticsAdolescent adiposity

Poor nutritionSmokingHigh BPLipids

Glycaemiaetc

Screening and

Secondary prevention in primary

care

Hospitalisation for

complications

Death

Rehab

“pushback” – CCDP preventive approach

Improve preventive systems for CD management

Study Design and Patient Recruitment

21 eligible clinics

Baseline data collection

Random allocation

8 intervention sites(250 patients: meanage 52.1, SD 13.1 yr)

13 control sites(305 patients: meanage 52.4, SD 13.9 yr)

Diabetes outreach team1. Diabetologist2. Nutritionist3. Diabetes healthcare

worker4. Podiatrist

51 patientsadded to regs

121 patientsadded to regs

Intervention Recall and

reminder system Health worker

training Regular

phonecalls Newsletter Workshop

19 patients lostto follow-up

30 patients lost tofollow-up

Follow-up data collection (282 patients) Follow-up data collection (396 patients)

Cluster Randomised Trial of HW-managed diabetes care system improvement in the Torres Strait, 1999-2001.

Hospitalisation of people with diabetes, Torres Strait, 1999-2002 (n=921), Cape York 2002-3 (n=240):

Proportion of diabetics hospitalised for avoidable conditions in previous 12 months

0

5

10

15

20

25

30

1999 2000 2002 2003

DR HospTorresOther hosp TorresDR Hosp CapeOther Hosp Cape

Measure 2004, n=34 2009, n=67 ANDIAB 2009

Age 54 52.4 56.8

Median HbA1c 9.35 9.53 8.0

Current smokers (%) 29% 30% 10%

% “good” glycemic control (A1c<7%)

16 20 26

% taking insulin 16% 32% 35%

% without albuminuria 25% 33% 67%

Mean weight, kg (BMI) 96.14 (34.7) 101.74 (35.9) N/A (30.2)

Can improved care processes be sustained with rising caseloads and current workforce

configuration?Snapshot from Island in the Central Group Torres, 2009.

Incident cases 3%, younger ages, increasing obesitySource: Forbes et al, 2012.

Getting Better at Chronic Care (GBACC) in North Queensland: a cluster RCT of

community health worker care co-ordination in remote FNQ settings

Robyn McDermott, Barbara Schmidt, Vickie Owens, Cilla Preece, Sean Taylor, Adrian Esterman

“Getting better at chronic care”Cluster RCT of health-worker led case management for

high risk clients

Aim: Test if HW-led care for high risk poorly managed adults with complicated T2DM would improve care processes (checks, referrals, self management) and outcomesPrimary outcome: improved HbA1cSecondary outcomes: Improved QoL, reduced CVD risk factors and complications (avoidable hospitalisations)

Mixed methods evaluation in 3 phasesNHMRC Partnership Project, 2011-2015

GBACC: mixed methods evaluation in 3 phases

Phase 1 (Intervention period: March 2012 – Sept 2013) Randomised controlled trial of intensive case management by IHWs

Phase 2 (Nov 2013 – Feb 2014)

Review of lessons learnedImplementation plan

Phase 3 (May 2014 – June 2015)• E

conomic analysis

• Rollout of model

12 Participating Communities*Intervention sites in phase 1 (randomly allocated)

Torres and NPA HHS• Badu*• Bamaga• Injinoo*• New Mapoon• Seisia• Umagico*

Cape York HHS• Kowanyama*• Mapoon*• Mareeba (Mulungu)

Cairns and Hinterland HHS• Mossman Gorge (ACYHC)*• Napranum• Yarrabah (GYHS)

PHASE 1:

COCONSORT DIAGRAM: GBACC, 2012-14, 2012-14RCT)

Enrolment: 12 sites recruited and 327 patients assessed as eligible

Excluded: 114 patients declined to participate

Group randomisation: 12 sites

AllocationIntervention: 6 sites (n=100 patients)Received intervention, n=100

Allocated to waitlist group: 6 sites(n=113 patients)

Follow upLost to follow-up (n=16)• Moved away (12)• Died (4)

Lost to follow up (n=6)• Moved away (3)• Died (2)• Withdrew from study (1)

Analysis

Analysed for primary outcome, n=108 (96%)

Analysed for primary outcome, n= 84 (84%)

Baseline data collected, n=213

Clinical care processes at baseline and follow up (%)

Baseline Endpoint (excluding 22 loss of follow up)

Control n=113 Intervention n=100 Control n=107 intervention n=84

No % (95% CI) No % (95% CI) No % (95% CI) No % (95% CI)

Foot check% 50 44.2 (35.0-53.5) 31 31.0 (21.8-40.2) 38 35.5 (26.3-44.7) 26 31.0 (20.9-41.0)

Seen by DM educator %

46 40.7 (31.6-49.9) 52 52.0 (42.1-61.9) 41 38.3 (29.0-47.6) 44 52.4 (41.6-63.2)

Seen by dietician % 22 19.5 (12.1-26.8) 30 30.0 (20.9-39.1) 21 19.6 (12.0-27.2) 37 44.0 (33.3-54.8)

Dentist check % 20 17.7 (10.6-24.8) 13 13.0 (6.3-19.7) 9 8.4 (3.1-13.7) 15 17.9 (9.6-26.5)

ECG check% 37 32.7 (24.0-41.5) 42 42.0 (32.2-51.8) 34 43.9 (34.4-53.4) 35 40.5 (29.8-51.1)

Eye check % 54 47.8 (38.5-57.1) 42 42.0 (32.2-51.8) 56 52.3 (42.8-61.9) 37 44.0 (33.3-54.8)

Smoker % 38 34.5 (25.6-43.5) 34 35.1 (25.5-44.7) 33 31.2 (22.4-40.4) 34 41.5 (30.7-52.2)

Blood sugar self-monitor %

45 40.9 (31.6-50.2) 46 46.0 (36.1-55.9) 63 59.4 (50.0-68.9) 44 52.4 (41.6-63.2)

Taking insulin% 55 48.7 (39.4-58.0) 40 40.0 (30.3-49.7) 47 43.9 (34.4-53.4) 40 47.6 (36.8-58.4)

Dyslipidemia % 83 73.5 (65.2-81.7) 84 84.0 (76.7-91.3) 91 85.0 (78.2-91.9) 76 90.5 (84.1-96.8)

Taking lipid lowering medicines%

5 4.4 (0.6-8.3) 3 3.0 (-0.4-6.4) 3 2.8 (-0.4-6.0) 5 6.0 (0.8-11.1)

Albuminuria and taking ACEi or ARB drugs

46 88.5 (79.6-97.3) 47 88.7 (80.0-97.4) 58 82.9 (73.9-91.8) 51 89.5 (81.4-97.6)

Adherent to all medicines

53 46.9 (37.6-56.2) 55 55.0 (45.1-64.9) 57 53.3 (43.7-62.8) 41 48.8 (38.0-59.6)

Had Fluvax 50 44.2 (35.0-53.5) 66 66.0 (56.6-75.4) 51 47.7 (38.1-57.2) 50 59.5 (48.9-70.2)

HbA1c measures at baseline and follow-up by group, absolute values: GBACC Phase 1 trial results

Baseline Endpoint9.2

9.4

9.6

9.8

10

10.2

10.4

10.6

10.8

11

ControlIntervention

FNQ Hospital Avoidance TrialCairns, Innisfail, Mareeba

2014-16

Health Innovation Fund Project OverviewFunded by QH (CARU)

Neil Beaton, Mary Streatfield, Robyn McDermott

Aim: to evaluate a new approach to community-based management of “frequent flyers” in FNQ hospitals –

Hospital Avoidance Trial, 2013-16

Background: Pilot HAP in Cairns showed a dramatic reduction in ED and inpatient episodes in 68 frequent flyers using a nurse-led case management approach.• Pragmatic RCT of intensive community-based case management of frequently

hospitalised adults with chronic conditions in 3 CHHHS sites• 530 patients in 3 sites randomly assigned to • 265 Intervention: usual care plus shared electronic record including CDM tool,

close case management (caseload for each care co-ord =<40) and self-management training and support

• 265 “controls”: usual care (referral to a medical home with offer of shared record)

• Eligibility criteria: 8 or more ED/inpatient episodes in the previous 12 months• Evaluation endpoints: Avoidable ED visits or hospital admissions over 18 months,

care processes (GPMP, referrals, self management training), intermediate clinical indicators (HbA1c, BP, Lipids, UACR/eGFR), disease progression, quality of life

• Economic (DRGs and AQoL) and process evaluation

2012-13 FY ED and Separations (patients)

Number of Visits >=5 >=8Cairns

ED 1,105 324 Inpatient 543 187 Total 2,979 1,006

MareebaED 751 235 Inpatient 122 40 Total 1,077 352

InnisfailED 369 104 Inpatient 95 32 Total 682 234

Total of three sites

ED 2,225 663

Inpatient 760 259 Total 4,738 1,592

FNQ HAT Trial design

Patient recruitment 3 sites, n=530Baseline interviews + data collection

Randomisation

Control group: n=265 Usual best practice care

GPMP, cdmNet audit & feedback

Intervention group: n=265GPMP, cdm tool audit & feedback

+ Case manager

Follow up data collection:Interviews, ED & inpatient episodesCdm tool audit, HIC/PBS, costings

Follow up data collection:Interviews, ED & inpatient episodesCdm tool audit, HIC/PBS, costings

Process evaluation including fidelity of

implementation

The patient journey, FNQ HAT

Patient identified as eligible by EDIS/HBCISand

invited to participate in the trial

Consent obtained

Consent not obtained Not in trial, usual care

Care co-ordinator conducts baseline assessment and interview,

arranges GP referral and GP consent to be in trial

RandomisationIntervention group:

GPMP, referrals, CDM tool, Care co-ordination, self management training

and support

Usual care group:Offer of shared record,

Referrals to AHPs

GPMP and referrals, care co-ordinator

Self management training

Allied health and medical specialists

Other services as required

Data capture and QI reports

to GPs from ED/IP and CDM

tool

Hospital admissions and ED visits

Why a Randomised Controlled Trial Design?

• RCT is the most robust study design which will give the highest level of evidence: all previous published studies looking at hospital avoidance (a complex intervention in a complex environment) were uncontrolled before-and-after designs – weak evidence for policy change and unable to be properly evaluated economically

• Controls provide the counterfactual for robust clinical and economic analysis

• Randomisation deals with selection/allocation bias

• Controls deal with secular trends in exposures and outcomes, regression to the mean and changes in the policy and fiscal environment.

• Good pilot data gives a clear effect size so a robust power calculation (sample size) will ensure the question can be clearly answered without (too much) statistical error

• Will be publishable and in the public domain, not sit on the shelf

• High scientific quality will be competitive for matching NHMRC Partnership Project Grant funding

Expanding the impact of our researchSource: Duryea, Hochman, Parfitt. Research Global: Feb 2007.

Expanding the impact of our researchSource: Duryea, Hochman, Parfitt. Research Global: Feb 2007.

Research outputs:egDiscoveriesPublicationsPatents

Research outputs:egDiscoveriesPublicationsPatents

ResearchTransfer: Engagementwith endusers

ResearchTransfer: Engagementwith endusers

ResearchOutcomes:New products or services

ResearchOutcomes:New products or services

Research Impact:Valueadded,Improvements achieved

Research Impact:Valueadded,Improvements achieved

National benefits

National benefits

Traditional quality domainTraditional

quality domainResearch impact scopeResearch impact scope

Association between PHC resourcing (staff) and costs of hospitalisation among diabetics in FNQ remote communities, 2001-5

(Gibson, Segal, McDermott 2011)

1

2

45

6 7

8

10

11

12

13

1415

17

21

18

20

010

0020

0030

0040

00

Mea

n in

-pa

tien

t cos

t per

pe

rson

.005 .01 .015 .02 .025

Mean phc staffing per person

Communities Fitted values

>Jan2001-Dec2005.^2003/04-Dec2005.Source:QldHealth. C-Coeff: -0.6862*(0.05sig)

(All FTE staffing levels)Diabetes-related hospital admissions> and PHC Staffing^

ACKNOWLEDGEMENTSThe CCDP is supported by QH Senior Clinical Research Fellowship and the Australian Primary Health Care Research Institute (APHCRI) as a PHC Centre for Research Excellence (CRE)GBACC is supported by NHMRC Partnership project grant 570149 FNQ HAT is funded by QH (CARU)

CCDP and CRE team includes: Admin: Jacqui Lavis and Sally McDonald Clinical Epidemiology: Sandy Campbell*, Robyn McDermott*, Klaus Gebel, Linton HarrissBiostatistics/informatics: Haider Mannan, Arindam DeyCommunity-based prevention studies group: Alan Clough*, Caryn West*PhD students: Ashleigh Sushames, Sean Taylor*, Barb Schmidt, Jan Robertson, Dympna Leonard, Russell Hayes, Richard Turner, Malcolm Forbes* (Masters)Health Economics: Kenny LawsonClinical Research Associates: Vickie Owens, Cilla PreeceCollaborating institutions: QH, UniSA, SAHMRI, UQ, Melbourne University, Baker-IDI, Menzies School of Health Research, Apunipima CYHC, Gurinny, Mulungu, AHCSA, QAIHC, UNSW

*Receiving NHMRC or NHF Fellowship support