dr john f. lambert - na.eventscloud.com
TRANSCRIPT
Dr John F. Lambert Orange Health Service, NSW, Australia
“The Gorilla”
#NZhealthcareCongress @DrJaffleOz
Use twitter during the discussion for questions if you are shy (and can tweet)
#NZhealthcareCongress @DrJaffleOz 1
14 attendees
over 220
attendees
Plus one (clearly multi-lingual) attendee from Auckland, Australia!
“Better Outcomes, Lower Cost”
But, there are diverse forces at play ◦ Medicare rebates
◦ ABF Funding – Surgical
◦ ABF Funding – Medical
◦ Private funding
◦ Many Outcome Measures
◦ IHPA
◦ Specialist Colleges
◦ QALY???
◦ The patient perhaps?
#NZhealthcareCongress @DrJaffleOz 2
Often we get stuck - which outcomes, and whose cost?
Paid to Clinician Fixed payment per service, flat rate regardless of co-morbities
Do more in rooms/lab, do more per hour, make more!
Rates are supposed to reflect time and effort
Rates can be adjusted in theory (e.g. Ophthalmology, Echo)
New items must be cost neutral in theory
Incentive for technology that
minimises challenges of variations in clinical mix
maximises number of cases per hour
allows “scope creep” (e.g. in room INR testing)
reduces costs (of course), but no incentive for PREVENTION
#NZhealthcareCongress @DrJaffleOz 3
Public Hospital Surgery (& Procedures) ◦ Fixed rate per service, adjusted for complexity ◦ Penalised for doing more cases than quota ◦ Incentive for technology that
minimises challenges of variations in clinical mix
(diagnostic and therapeutic)
reduces length of stay and rates of complications
reduces costs per service (of course)
PREVENTS admissions
#NZhealthcareCongress @DrJaffleOz 4
Public Hospital Acute Medicine ◦ Fixed rate per service, adjusted for complexity ◦ Incentive for technology that
improves/ speeds diagnostic accuracy
improves/ speeds therapeutic efficiency
minimises challenges/ expense of variations in clinical mix
has less side effects affecting LOS or outcomes
reduces length of stay and rates of complications
reduces costs per service (of course)
PREVENTS admissions
#NZhealthcareCongress @DrJaffleOz 5
Health Insurance
Heavily regulated, largely mirrors public payers
Niche Markets ◦ Sports Medicine
◦ Plastic Surgery
◦ Genome based technologies
◦ Off Label or novel drugs
◦ Research
#NZhealthcareCongress @DrJaffleOz 6
Cost shifting – somebody else’s problem Inadequate assessment of TCO Failure to connect cost with proven benefit Failure to measure impact of change (benefit) Person creating cost not aware of cost Inertia / Habit / History / Preference Failure to utilise technology to maximal benefit Unexpected negative outcomes Ethical behaviour
#NZhealthcareCongress @DrJaffleOz 7
Where the money is! ◦ ALL funders like prevention most of all (if it works) ◦ Primary - Prevention
Weight & activity monitoring
Dietary monitoring
◦ Secondary – Community Based Care
Monitoring compliance of above, plus therapeutics
◦ (In Home Delivery of Services) ◦ Health Apps / IT systems
#NZhealthcareCongress @DrJaffleOz 8
#NZhealthcareCongress @DrJaffleOz 9
Clinical
Financial
IT
Biomedical
Risk Management
#NZhealthcareCongress @DrJaffleOz 10
Clinical ◦ What does the technology do
◦ To whom? (Can vs. Should – defining scope)
Essential interface with cost here… often unrecognised
◦ Clinical Governance (incl. credentialling)
◦ Health Information Management
◦ Infection Control
◦ Pharmacy
◦ Ego, bias, history, preference vs science and evidence
#NZhealthcareCongress @DrJaffleOz 11
Financial ◦ TCO, not just purchase cost
Consumables, including utilities & waste/ spares
Replacement cost, expected lifetime
Maintenance costs, including PM and licences ◦ What is on each side of the see-saw? Quantifiable benefits?
e.g. cost per QALY, cost per time reduction in LOS, cost per prevented admission
◦ Recycling potential ◦ “Soft” benefits, indirect cost reductions (private incentives) ◦ Cost caused by scope creep
#NZhealthcareCongress @DrJaffleOz 12
IT ◦ Often forgotten or not well integrated ◦ Increasingly every device has an IP address ◦ Value great if done well ◦ What to do with the data? ◦ Security/ privacy concerns impede usability ◦ Huge potential with using private sector data
Fitbit, Garmin & others
Apple health app concept
#NZhealthcareCongress @DrJaffleOz 13
How can you assess a piece of software? Who is responsible if a doctor uses an app on
their personal iDevice and implements the advice and causes harm due to an error in the app?
What if the app is an “approved” app? Interdependencies are a pain – OS upgrades! Perhaps we need a concept of “trust level”
#NZhealthcareCongress @DrJaffleOz 14
Tremendous opportunity
Connectivity at an all time high
#NZhealthcareCongress @DrJaffleOz 15