robyn mcdermott mbbs, fafphm, mph, phd. director ccdp, jcu cairns
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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
Glycemiaetc
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 learned• Implementation plan
Phase 3 (May 2014 – June 2015)• Economic 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
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