Māori Pathways to and Through Health Care for STEMIs in New Zealand

Summer Studentship Research by Ellie Tuzzolino-Smith

Terminology & Current Practice • STEMI: S-T elevation Myocardial Infarction.

Determined with ECG. More sever form of heart attack. Usually caused by blood clot, occluding coronary arteries, often these arteries are smaller than they should be due to arthrosclerosis.

• CODE STEMI: Protocol at Whangarei Hospital at time of study where patients presenting with STEMI flown by helicopter to Auckland for rescue PCI.

Terminology & Current Practice • Rescue PCI: Percutaneous Coronary intervention,

cardio angiography performed, clot (if found) is aspirated, vessel is dilated with a balloon and metal stent is placed in any arteries with significantly decreased lumen size. To reduce risk of permanent damage to myocardium needs to occur within 90-120mins from onset of pain (White, 2012).

• Thrombolysis/ TNK: Tenecteplase, current drug used for alternative intervention in case of STEMI. Dissolves clot that is causing the STEMI. To reduce risk of permanent damage to myocardium needs to occur within 30mins from onset of pain (White, 2012).

Background

According to NDHB data, mortality rates from acute myocardial infarction (MI) in Māori in

Northland are 3-6 times Non-Māori.

In contrast, an initial study of management of STEMI patients in Northland referred for acute angiography and stenting at Auckland hospital

showed 79% were Pākehā men (White, 2012).

Aims To determine any inequities in care pathways

pre-, during and post-admission between Māori and Non-Māori presenting with

STEMI in Northland in 2011-12.

Methods Data retrieved from: • The PREDICT primary care database • Patient files • Concerto (Northland DHB’s electronic clinical

record system) • STEMI audit data and cardiac rehabilitation data. It was collated into a standard format. Analysis of demographic, pre-admission, intra hospital and post-discharge variables was carried out.

Baseline demographics for Northland STEMI patients 2011-2012 Total STEMI patents in 2011-2012: 106 Minus-Out of Northland residence: 99 Minus-Files not pulled before 21/01/2013: 96

Māori (%/n) Non-Māori (%/n) Total 18 78 Males 83.3% (15) 73.1% (57) Females 16.7% (3) 26.9% (21) Median age 58 68 Median Age: Males: 57 Females: 67 Males: 67 Females:68 NZdep Quintile:1&2 11.1% (2) 14.1% (11) 3&4 11.1% (2) 33.3% (26) 5&6 55.6% (10) 24.4% (19) 7&8 0% (0) 15.4% (12) 9&10 22.2% (4) 12.8% (10)

Māori (%/n) Non-Māori (%/n)

Entered in Predict: 77.8% (14) 44.9% (35)

Predict risk >15%: 78.6% (11) 71.4% (11)

Predict multiple risk factors 100% (14) 71.4% (11)

Predict patients with: Diabetes

64.3% (9)

22.9% (25)

Previous MI 21.4% (3) 34.3% (12)

Current Smoker

57.1% (8) 14.3% (5)

BMI>25 83.3% (10) 75.9% (29)

BP > 140/90 28.6% (4) 8.6% (3)

Prescribed interventions

72.7% (8) 52% (13)

Pre-Hospital Admission Factors

Māori (rate/100,000/year) Non-Māori (rate/100,000/year)

35-49 Years 24.3 7.3 50-74 Years 246.8 53.1 75+ Years 1021.0 737.4

Female Male Female Male 35-49 Years 6.3 46.0 0.0 15.1 50-74 Years 135.4 376.2 22.5 83.3 75+ Years 796.0 1363.6 700.7 781.9

Annualised Myocardial infarction deaths for 2006-2008

Māori (rate/100,000/year) Non-Māori (rate/100,000/year)

35-49 Years 22.3 18.7

50-74 Years 65.1 64.9

75+ Years 73 105.1

Annualised STEMI rates. Average of 2011-2012

Distances by car

Admitted to: Māori (%/n) Non-Māori (%/n) Bay of Islands ED 22.2% (4) 6.4% (5)

Dargaville ED 5.6% (1) 9% (7) Kaitaia ED 11.1% (2) 9% (7) Rawene ED 0% (0) 1.3% (1) Whangarei ED 61.1% (11) 74.4% (58)

Sent by GP/White cross 11.1% (2) 5.1% (4)

Live: Māori (%/n) Non-Māori (%/n) <30min of Hospital 83.3% (15) 64.1% (50)

>30min of Hospital 16.7% (3) 35.9% (28)

Driving distance from home to hospital

Initial admission factors

Clinical presentation

• Pre-ED thrombolysis was more likely to occur if patients lived further than 30 minutes from a hospital, and overall, the CODE STEMI pathway was more likely to be offered to patients living within 30 minutes of Whangārei hosp (both stat sig).

• The travel time from onset of pain to time of call to GP/ambulance is of no difference between Maori and non-Maori.

Treatment Decisions

Māori (%/n) Non-Māori (%/n) Pre-ED Thrombolysis 5.6% (1) 11.5% (9) ED Thrombolysis 50% (9) 30.8% (24) CODE STEMI 38.9% (7) 47.4% (37) Non-Urgent 5.6% (1) 6.4% (5) Diagnostic angio 88.9% (16) 88.5% (69) PCI: 55.6% (10) 73.1%(57) Successful Stenting 80% (8) 84.2% (48) Unsuccessful Stent 20% (2) 15.8% (9) Diagnostic ECHO 83.3%(15) 83.3% (60)

Total STEMI patients mortality

Mortality Thrombolysis patients vs PCI •Of the 2 Māori who died, both had been sent for CODE STEMI and had succesful PCI. •Of the 9 Non-Māori who died,

•3 went for CODE STEMI but had unsuccessful PCI •3 had thrombolysis only •2 had thrombolysis followed by unsuccesful PCI •1 refused treatment

Māori (%/n) Non-Māori (%/n) Deceased before discharge 0% (0) 7.7% (6)

Deceased before outpatient appt.

5.6% (1) 11.5% (9)

Deceased within 6months STEMI

11.1% (2) 11.5% (9)

Māori (%/n) Non-Māori (%/n)

Have Outpatient records 76.5% (13) 87% (60)

Reported follow up ECHO: 27.8% (5) 32.9% (24)

Reported follow up ETT: 5.9% (1) 11.6% (7)

Cardiac Monitoring Test: 0% (0) 5.8% (4)

Offered cardiac rehab: 82.4% (14) 84.1% (58)

Attended (of Offered): 35.7% (5) 55.2% (32)

Post STEMI follow up

ECHO: Echocardiogram (Cardiac Ultrasound) ETT: Exercise tolerance test (done on treadmill hooked up to ECG)

Discussion 1) Only 18/96 were Māori of these most were entered

in predict and most lived within 30minutes of the hospital, indicating that this group was not reflective of true Māori population. This group may face less barriers to health care and further investigation must be done into what barriers the unrepresented Māori are facing to health care.

2)There are inequities that need to be addressed, in terms of geographical access to CVD and STEMI management in Northland. Wider availability of treadmill testing and angiography, and systematic use of pre-ED thrombolysis may have a greater impact on patient outcomes than putting more effort into the CODE STEMI pathway. Further research is also needed to assess and address barriers for Māori to primary care, CVD risk assessment and management.

3)However there were no statistically significant inequities identified in the pathway of care between Māori and Non-Māori in this study, once STEMI was diagnosed, the mortality outcomes were similar. Geographical proximity to Whangārei hospital (<30mins by road) was the primary determinant of whether patients followed the CODE STEMI protocol rather than whether they were Māori or Non-Māori.

Strengths of this study • Looking directly at patient files enabled a

greater depth of knowledge to be gained. • Opportunity for further analysis as medication

data was also obtained. Weaknesses • Information on modes of transport to the

hospital would have been helpful in analysing timing and distance and should have been recorded during file data collection.

Opportunity for further research • Gain ethics approval to look at if each STEMI

patient was filling their medication scripts post STEMI.

• More qualitative research is needed to determine further, the barriers Māori are facing to CVD prevention and management and how they can be addressed, so that CVD inequities can be diminished.

• For example issues around health literacy, GP services and emergency transport in a more rural setting could be investigated further. Along with whether Māori want to go to hospital.

Acknowledgements Drs Clair Mills, Kyle Eggleton and Stephen Jennison: Supervisors Anil Shetty: Mapping, Technical support Ryan Howard & Sue Vallancey: STEMI Audit Data Stephen Jennison, Wendy Coleman & Lorraine Parker: Cardiac Rehabilitation Data Medical Records Staff: File Retrieval Pukawakawa Staff and Program: Facility Usage Northland DHB: Facility usage and creating the opportunity to carry out this study. University of Auckland: Funders of the Studentship programme.

Summer Studentship, personal experience

•How recruited. •Māori students doing Māori research, will get funding. •Jobs I did. •What I enjoyed: Meeting people, seeing how DHBs work, Analysis, living at home. •What I found challenging: Data collection, understanding statistics.