Puriri Medical Centre - a case study
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Transcript of Puriri Medical Centre - a case study
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Puriri Medical Centre – a case study
Dr. Juliet Rumball SmithPublic Health Physician, [email protected]
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Puriri Medical Centre– a case study10,000 patients, 63% Māori, high deprivation. Located in a small town in the Far North. Who are their population and what are their
needs?
Are there differences in these needs and in health service use within their practice population?
How do they compare against practices that are similar?
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How is this helpful? 3 examples
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What are the health needs of your patients?
Example 1Indicator: CHRONIC CONDITIONS (prevalence)
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The unknown patient
• 36 patients with non-documented diabetes• 71 patients with non-documented cardio-
vascular disease
2 + LTC((prevalence)
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What is the service use for your patients? How do you compare?
Example 2Indicator: ED ATTENDANCE
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Visits to Emergency Department
163 per 1,000 patients (adjusted for age and ethnicity). Lower rates for Puriri patients compared to peer group and whole of Northland
More triage 1 – 3, more likely to be admitted, more likely to be GP referred. Fewer avoidable (ASH-like) attendances Patients of higher acuity compared to other practices.
=High quality assessment of acute problems and access to urgent care for Puriri patients
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Are there differences in health service use in our practice compared to other similar practices? For different groups of patients?Example 3 Indicator: SEEING THE GP
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For Puriri patients compared to other practices
MāoriNon-Māori
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SEEING THE GP For different patients within the practice
CONGESTIVE HEART FAILURE Māori Non-MāoriCHRONIC OBSTRUCTIVE PULMONARY DISEASE Māori Non-Māori
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Questions….
What is appropriate care?Is there overuse or underuse? Is this inequity in access relative to need? Does it matter?
Age-standardised rate per 1000 people – first specialist assessmentMāoriNon-MāoriRate ratio
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In summary• Joint project – Health Partners, NDHB, Northland
Primary Healthcare Organisations as part of NDHB Neighbourhood Healthcare Homes.
• Showed how data can be used to improve understanding of a population’s health needs, health service use, and identify variability.
• Designed to raise questions, and to stimulate further exploration and intervention.
• Many thanks to all the contributors.