Douglas Fahlbusch

Founder, Author, Doctor, Advisor. Cancer survivor. I get administrators and clinicians talking for greater empathy, efficiency and quality in healthcare.

[Douglas Fahlbusch @DougFahlbusch]

@VladoPerkovic Long-term function data is what actually moves practice - short-term signals rarely create any impact on a funding committee. The harder question after results like this is how fast the evidence reaches the clinics that would use it.

[Douglas Fahlbusch @DougFahlbusch]

@RachaelMorton12 @Sydney_Uni @ANZDATARegistry @ISNkidneycare @healthgovau @nswaci @CKRRenal @TrialsCentre @SydneySPH @KidneyHealth @SWIFTrial Embedding the economics into the program rather than bolting it on afterwards is the part that usually gets skipped. Evidence that arrives without a costing is evidence a health system can admire but not act on. Will follow this closely.

[Douglas Fahlbusch @DougFahlbusch]

@orygen_aus Effectiveness not equalling availability is the standing failure across digital health, not just mental health apps. We fund the trial and then leave the adoption pathway - reimbursement, workflow fit, who's accountable - to sort itself out. It doesn't.

[Douglas Fahlbusch @DougFahlbusch]

@cancerNSW That gap is a measurement design problem as much as a care one. Survival gets captured because the system already collects it; function and recovery aren't recorded anywhere, so they can't be improved. What we measure at each interaction sets the limit on what we can act on.

[Cancer Institute NSW @cancerNSW]

“We’ve become very good at measuring whether people survive, but we’re less good at how people live well after their diagnosis.”

Watch our recent NSW Cancer Summit – In Conversation event on survivorship in full: https://t.co/OKmtDCPp0z

[Douglas Fahlbusch @DougFahlbusch]

@ACTA_org Intellectual honesty is the right frame for registries. Most are built to report on care after the fact rather than inform the next decision. The gap isn't collection - it's whether anything flows back to the clinician in time to change what happens next.

[Douglas Fahlbusch @DougFahlbusch]

Australian health research has no shortage of evidence. What it lacks is a route from a completed trial to a funded, workflow-embedded change in practice. We keep investing in the generating and almost nothing in the arriving.

[Douglas Fahlbusch @DougFahlbusch]

Health systems are excellent at recording what happened and poor at noticing what's changing. Same data, two different jobs. Most of the value in longitudinal health data isn't the report at the end of the year — it's the signal you could have acted on in March.

[Douglas Fahlbusch @DougFahlbusch]

@NMHC The Report Card tells us how the system performed. The harder question is whether we can see it moving between report cards. Annual snapshots make trends visible in hindsight; what changes decisions is data that flags change while there's still time to act on it.

[Douglas Fahlbusch @DougFahlbusch]

@ageing_au @healthgovau Structured transition-to-practice is the right lever — the healthcare workforce problem is as much about the first 12 months as it is about recruitment. Worth tracking retention at 12 and 24 months, not just registrations.

[Douglas Fahlbusch @DougFahlbusch]

@SimonChapman6 An 80% cut with no modelling isn't a policy, it's a hypothesis someone else has to test in the field. The frustrating part is we do have the data to model it — excise, consumption and illicit-market series all exist. Choosing not to look is the decision being made.

[Douglas Fahlbusch @DougFahlbusch]

@PatMcGorry @BenCarrollMP @IngridStitt 2000 days is a useful number precisely because nobody set out to measure it. Reform commitments get funded and announced, but the interval between recommendation and implementation is rarely instrumented — so the lag only becomes visible when someone counts.

[Douglas Fahlbusch @DougFahlbusch]

@ROSA_Project The prevention case is well made. What's usually missing is the mechanism — most of the signal that would let us intervene early already passes through the system in routine encounters, then goes unlinked. ROSA is one of the few places in Australia where it doesn't.

[Douglas Fahlbusch @DougFahlbusch]

Surgery is one of the few moments a health system gets a whole person's physiology, function and social context in one place, on a known date, with consent to measure. We treat it as a logistics problem. It's the best prospective cohort we'll ever be handed.

[Douglas Fahlbusch @DougFahlbusch]

@PMalinauskasMP Adding clinicians is visible. What's invisible is what the system does with what those crews see. Every ramped patient and repeat call is a data point about unmet need upstream. Worth counting as evidence for change, not just workload.

[Douglas Fahlbusch @DougFahlbusch]

@AcademyHealth The quiet cost of weakening an evidence agency isn't the studies that don't get done. It's that the system keeps making the same decisions without ever learning whether they worked. Health services research is the feedback loop, not an add-on.

[Douglas Fahlbusch @DougFahlbusch]

@Health_Affairs Fragmentation isn't just a payment problem, it's a recurrence problem. Each episode of care generates the signal you'd need to intervene earlier, then discards it. New measures layered on that architecture mostly re-measure the gap.

[Douglas Fahlbusch @DougFahlbusch]

Most of what we know about a patient's trajectory is generated during health-system interactions — then discarded. Every episode is a prediction data point we never keep. Prevention doesn't need new tests so much as it needs us to stop throwing away the ones we already do.

[Douglas Fahlbusch @DougFahlbusch]

@jhoeksma @digitalhealth2 The trust framing is right. Australia learned the hard way with My Health Record that consent architecture decides adoption. Key question: would the Data Bank hold custody of the data, or just set the standards? Custody is where trust is actually won or lost.

[Douglas Fahlbusch @DougFahlbusch]

Every "no" from a health system is a data point about unmet need. We file them as decisions and never pool and review them as evidence. This refusal log is a rich untapped dataset for health policy - and nobody owns it.