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Most health systems don't have a strategy problem. They have an execution problem. Initiatives stall. Margins slip. Physicians disengage.

And the gap between what's expected and what gets delivered gets wider. I step in to close that gap.

09/29/2026

A physician group misses its RVU targets for a third straight quarter. Leadership schedules a meeting about engagement and accountability. No one revisits the compensation plan itself.

𝑃ℎ𝑦𝑠𝑖𝑐𝑖𝑎𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝑔𝑎𝑝𝑠 𝑎𝑟𝑒 𝑟𝑎𝑟𝑒𝑙𝑦 𝑎𝑛 𝑒𝑛𝑔𝑎𝑔𝑒𝑚𝑒𝑛𝑡 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.

They are an operating model problem, physicians are responding rationally to the incentive architecture they were given.

𝐅𝐢𝐯𝐞 𝐩𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐫𝐞𝐜𝐮𝐫 𝐚𝐜𝐫𝐨𝐬𝐬 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐰𝐢𝐭𝐡 𝐩𝐡𝐲𝐬𝐢𝐜𝐢𝐚𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐟𝐫𝐢𝐜𝐭𝐢𝐨𝐧:
→ Physicians are paid on individual RVU production while being asked to deliver team-based, protocol-driven care.

→ Call coverage stipends haven't been repriced as patient acuity and call frequency have climbed. → Quality and value-based incentives make up a small fraction of total compensation relative to production incentives.

→ New physicians are onboarded onto legacy comp plans built for a service line mix that no longer reflects current strategy. → Comp plan governance sits entirely with finance, with no standing physician input on design.

None of these are physician attitude problems.

All of them are comp architecture choices that were made, or never revisited, independent of how care is actually being asked to be delivered.

Systems that close this gap bring physicians into comp design from the start, price call and quality participation to reflect real demands, and revisit the plan every time service line strategy shifts.

📩 Start the conversation: link in bio.

09/24/2026

Discharge delays get blamed on bed capacity or case management staffing almost every time.

The real gap is upstream, in how the case management operating model is built to plan a discharge from day one of admission, not day of discharge.

Swipe through 👇

The free 15-Point Operational Readiness Assessment is pinned to the Malloy & Co. Featured section for systems ready to close the gap.

09/22/2026

A hospital's utilization management team logs 40 hours of peer-to-peer calls in a single week.

Throughput slows.
The instinct in the boardroom is to blame the payer.

Pior authorization friction is not primarily a payer relations problem. It is an operating model problem, and treating it as an adversarial negotiation misses where the actual leverage sits.

𝐅𝐨𝐮𝐫 𝐩𝐚𝐭𝐭𝐞𝐫𝐧𝐬 𝐬𝐡𝐨𝐰 𝐮𝐩 𝐚𝐜𝐫𝐨𝐬𝐬 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐬𝐭𝐫𝐮𝐠𝐠𝐥𝐞 𝐰𝐢𝐭𝐡 𝐔𝐌:
→ Authorization requests move between clinical documentation, case management, and physician advisors with no single accountable owner.

→ Denial reasons repeat month after month with no feedback loop back to the ordering physicians.

→ Peer-to-peer scheduling adds 24–72 hours before the conversation even happens, because there's no dedicated real-time channel.

→ UM staff are measured on call volume rather than resolution speed or downstream throughput impact.

None of these are payer behavior.

All of them are workflow design choices made or defaulted into, rarely revisited since.

𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐜𝐥𝐨𝐬𝐞 𝐭𝐡𝐢𝐬 𝐠𝐚𝐩 𝐫𝐞𝐝𝐞𝐬𝐢𝐠𝐧 𝐭𝐡𝐞 𝐡𝐚𝐧𝐝𝐨𝐟𝐟 𝐞𝐧𝐝 𝐭𝐨 𝐞𝐧𝐝:
• one accountable owner from order to authorization
• direct physician advisor access
• structured feedback loop that corrects clinical documentation before the next request goes out

📩 Start the conversation: link in bio.

09/17/2026

Pharmacy costs growing faster than patient volume is one of the most consequential and most misdiagnosed financial performance indicators in hospital operations.

𝐓𝐡𝐞 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐞:
• formulary tightening
• generic substitution campaigns
• drug spend audits by physician

Prescribing decisions are rarely where the structural gap lives.

Pharmacy cost performance is an operating model design problem — built into prescribing decision support architecture, formulary governance, waste controls, and the cost visibility clinicians have at the point of prescribing.
Here are the five structural failure points that drive chronic pharmacy cost growth.

Swipe through. 👇

If two or more appear in your environment, the cost trend has an operational design address, one that formulary audits and generic campaigns alone will not resolve.

The free 15-Point Operational Readiness Assessment is pinned to the Malloy & Co. Featured section for systems ready to look past drug spend by physician.

09/15/2026

Five years into federal price transparency requirements, most health systems have checked the compliance box.

And patients still routinely arrive without a realistic picture of what they'll owe, and go home to a bill they weren't expecting.

The gap between what price transparency is supposed to deliver and what patients actually experience isn't a communication or technology problem.

It's an operating model design problem.

→ Chargemaster rates, negotiated payer rates, and actual patient liability are three different numbers — and the architecture for surfacing the third one at the moment a scheduling conversation happens was never built.

𝑁𝑜𝑡 𝑎 𝑤𝑒𝑏𝑠𝑖𝑡𝑒 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.

𝐴 𝑑𝑎𝑡𝑎 𝑎𝑟𝑐ℎ𝑖𝑡𝑒𝑐𝑡𝑢𝑟𝑒 𝑔𝑎𝑝.

→ Pre-service cost estimation is built on expected procedure codes that haven't been confirmed clinically yet — making it structurally imprecise in ways no estimator tool fixes.

𝑁𝑜𝑡 𝑎 𝑡𝑒𝑐ℎ𝑛𝑜𝑙𝑜𝑔𝑦 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.

𝐴 𝑠𝑒𝑞𝑢𝑒𝑛𝑐𝑒 𝑝𝑟𝑜𝑏𝑙𝑒𝑚 𝑤ℎ𝑒𝑟𝑒 𝑡ℎ𝑒 𝑖𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛 𝑛𝑒𝑒𝑑𝑒𝑑 𝑡𝑜 𝑝𝑟𝑖𝑐𝑒 𝑎𝑐𝑐𝑢𝑟𝑎𝑡𝑒𝑙𝑦 𝑑𝑜𝑒𝑠𝑛'𝑡 𝑒𝑥𝑖𝑠𝑡 𝑦𝑒𝑡.

→ Financial counseling positioned after scheduling rather than at the decision point where cost information changes patient behavior.

𝑁𝑜𝑡 𝑎 𝑐𝑜𝑢𝑛𝑠𝑒𝑙𝑖𝑛𝑔 𝑠𝑡𝑎𝑓𝑓𝑖𝑛𝑔 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.

𝐴 𝑤𝑜𝑟𝑘𝑓𝑙𝑜𝑤 𝑡ℎ𝑎𝑡 𝑝𝑙𝑎𝑐𝑒𝑠 𝑐𝑜𝑠𝑡 𝑛𝑎𝑣𝑖𝑔𝑎𝑡𝑖𝑜𝑛 𝑤ℎ𝑒𝑟𝑒 𝑖𝑡'𝑠 𝑐𝑜𝑛𝑣𝑒𝑛𝑖𝑒𝑛𝑡 𝑓𝑜𝑟 𝑡ℎ𝑒 𝑠𝑦𝑠𝑡𝑒𝑚, 𝑛𝑜𝑡 𝑤ℎ𝑒𝑟𝑒 𝑖𝑡'𝑠 𝑢𝑠𝑒𝑓𝑢𝑙 𝑓𝑜𝑟 𝑡ℎ𝑒 𝑝𝑎𝑡𝑖𝑒𝑛𝑡.

→ Payer-specific liability variation not visible in the scheduling workflow, so every patient receives the same generic estimate regardless of their plan.

𝑁𝑜𝑡 𝑎 𝑏𝑖𝑙𝑙𝑖𝑛𝑔 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.
𝐴 𝑚𝑖𝑠𝑠𝑖𝑛𝑔 𝑖𝑛𝑡𝑒𝑔𝑟𝑎𝑡𝑖𝑜𝑛 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑠𝑐ℎ𝑒𝑑𝑢𝑙𝑖𝑛𝑔 𝑎𝑛𝑑 𝑏𝑒𝑛𝑒𝑓𝑖𝑡 𝑣𝑒𝑟𝑖𝑓𝑖𝑐𝑎𝑡𝑖𝑜𝑛 𝑑𝑎𝑡𝑎.

→ No feedback loop from billing back to scheduling on which service-payer combinations produce the largest estimate-to-bill variance.

𝑁𝑜𝑡 𝑎 𝑟𝑒𝑣𝑒𝑛𝑢𝑒 𝑐𝑦𝑐𝑙𝑒 𝑝𝑟𝑜𝑏𝑙𝑒𝑚.
𝐴 𝑚𝑖𝑠𝑠𝑖𝑛𝑔 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑎𝑙 𝑙𝑜𝑜𝑝.

Price transparency is a care access design problem.

The answer isn't a better widget on the website.

📩 Start the conversation: [link in bio]

09/10/2026

Telehealth programs that underperform have these things in common:
• low adoption rates
• patient experience gaps
• clinical quality inconsistency
• volume projections not materializing

These are the most universally diagnosed as technology problems, physician resistance, or patient preference for in-person care.

The platform is rarely where the gap lives.

Telehealth underperformance is an operating model design problem rooted in care pathway integration, scheduling architecture, clinical protocol design, and billing infrastructure that were never rebuilt to support a different mode of care delivery.

Here are the five structural failure points that explain why telehealth programs don't deliver what they projected.

Swipe through. 👇

If two or more appear in your environment, the performance gap has an operational design address.

The free 15-Point Operational Readiness Assessment is pinned to the Malloy & Co. Featured section for systems ready to look past the technology narrative.

09/08/2026

The transfer center is one of the most operationally consequential functions in a health system, and one that should be treated as a function that needs an operating model.

When transfer centers underperform, slow acceptance decisions, high refusal rates, patients landing in receiving units that weren't ready, the standard response is staffing adjustments, physician communication training, and capacity management dashboards.

Transfer center performance is an operational design problem, not a communication or staffing problem within the center.

𝐓𝐡𝐞 𝐫𝐞𝐚𝐬𝐨𝐧 𝐟𝐫𝐮𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐞𝐱𝐢𝐬𝐭𝐬:
→ No single owner of transfer acceptance criteria by service line, producing real-time negotiation between the transfer center coordinator, receiving physician, and charge nurse — each working from different information. Not a communication failure. A missing decision rights design for a time-sensitive call.

→ Real-time capacity visibility limited to what the capacity management dashboard was built to show two hours ago, creating information risk in every acceptance decision. Not a process efficiency problem. A data architecture that wasn't designed for the speed of the decision it needs to support.

→ No standard post-acceptance protocol for notifying, preparing, and confirming the receiving unit, so each transfer runs a different sequence with variable outcomes. Not a bed management problem. A missing operating model for the workflow between acceptance and patient arrival.

→ Transfer coordinator decision authority that doesn't match the clinical and capacity information required to use it, producing hesitation, escalations, and delay at the point of acceptance. Not a staff capability problem. A role design that assigned authority without the information infrastructure to support it.

→ Transfer center performance measured by volume and turnaround without tracking post-transfer readmission rates, adverse events, or receiving unit experience.

Not a measurement gap.
A performance framework that stops at the handoff.

Transfer center performance is a patient flow hub design problem.

The operating model is what needs redesign, not the staff inside the center.

📩 Start the conversation: [link in bio]

09/03/2026

𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐚𝐝𝐦𝐢𝐧𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐯𝐞 𝐛𝐮𝐫𝐝𝐞𝐧 is the ratio of time clinicians spend on documentation, regulatory compliance, and administrative tasks versus direct patient care.

It is one of the most consequential and most persistently misdiagnosed operational problems in hospital systems.

The standard response when the ratio worsens: EHR optimization training, scribes in high-burden departments, efficiency coaching.

Clinical administrative burden isn't produced by how clinicians use their systems.

Documentation burden is an operating model output built into workflow architecture, role design, and regulatory compliance layering.

It is not a clinician performance variable.

Here are the five failure points that drive clinical administrative burden.

Swipe through. 👇

If two or more appear in your environment, the clinical time problem has an operational design address — one that EHR training and scribe deployment alone won't resolve.

The free 15-Point Operational Readiness Assessment is pinned to the Malloy & Co. Featured section for systems ready to look past utilization data.

09/01/2026

Hospital operations dashboards are built around throughput: door-to-doctor time, discharge by noon rate, admit decision time, transfer center turnaround, left without being seen percentage.

These metrics get reviewed, escalated, and driven with significant operational energy.

They don't measure whether the workflow is producing the right thing at the end.

𝐖𝐡𝐚𝐭 𝐡𝐚𝐩𝐩𝐞𝐧𝐬 𝐰𝐡𝐞𝐧 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐚𝐠𝐠𝐫𝐞𝐬𝐬𝐢𝐯𝐞𝐥𝐲 𝐟𝐨𝐫 𝐭𝐡𝐫𝐨𝐮𝐠𝐡𝐩𝐮𝐭:
→ Discharge by noon improving while 30-day readmissions hold flat or worsen, because the metric stops at the process step and never reaches whether the transition plan was built before the speed target was hit.

A discharge that happened on time and produced a patient who returned in 22 days is not a throughput success with a downstream problem.

𝐼𝑡'𝑠 𝑎 𝑚𝑒𝑡𝑟𝑖𝑐 𝑡ℎ𝑎𝑡 𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝑡ℎ𝑒 𝑤𝑟𝑜𝑛𝑔 𝑡ℎ𝑖𝑛𝑔.

→ Door-to-doctor time improving while diagnostic accuracy drifts, because the metric measures the speed of the first clinical handoff, not the quality of clinical decision-making it produced.

𝐹𝑎𝑠𝑡𝑒𝑟 𝑓𝑖𝑟𝑠𝑡 𝑐𝑜𝑛𝑡𝑎𝑐𝑡 𝑖𝑛 𝑎 𝑑𝑒𝑝𝑎𝑟𝑡𝑚𝑒𝑛𝑡 𝑤𝑖𝑡ℎ 𝑎 𝑟𝑖𝑠𝑖𝑛𝑔 𝑚𝑖𝑠𝑠 𝑟𝑎𝑡𝑒 𝑓𝑜𝑟 𝑠𝑒𝑟𝑖𝑜𝑢𝑠 𝑑𝑖𝑎𝑔𝑛𝑜𝑠𝑒𝑠 𝑖𝑠 𝑎 𝑠𝑝𝑒𝑒𝑑 𝑖𝑚𝑝𝑟𝑜𝑣𝑒𝑚𝑒𝑛𝑡 𝑎𝑝𝑝𝑙𝑖𝑒𝑑 𝑡𝑜 𝑎 𝑝𝑟𝑜𝑏𝑙𝑒𝑚 𝑡ℎ𝑎𝑡 𝑛𝑒𝑒𝑑𝑒𝑑 𝑎𝑐𝑐𝑢𝑟𝑎𝑐𝑦 𝑤𝑜𝑟𝑘 𝑓𝑖𝑟𝑠𝑡.

→ Admit decision time hitting target while admitted patients board in the ED for six hours after the decision, because the metric measures the decision, not what happens to the patient after it.

→ Transfer center turnaround improving without tracking transfer appropriateness or receiving-unit outcomes optimizes decision speed without the quality guardrails a faster decision still needs.

→ Left without being seen percentage dropping because registration got faster, not because care delivery capacity grew

𝐴 𝑑𝑎𝑠ℎ𝑏𝑜𝑎𝑟𝑑 𝑛𝑢𝑚𝑏𝑒𝑟 𝑡ℎ𝑎𝑡 𝑚𝑜𝑣𝑒𝑑 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑡ℎ𝑒 𝑢𝑛𝑑𝑒𝑟𝑙𝑦𝑖𝑛𝑔 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑎𝑙 𝑝𝑟𝑜𝑏𝑙𝑒𝑚 𝑚𝑜𝑣𝑖𝑛𝑔 𝑤𝑖𝑡ℎ 𝑖𝑡. 𝑆𝑝𝑒𝑒𝑑 𝑡ℎ𝑟𝑜𝑢𝑔ℎ 𝑎 𝑤𝑜𝑟𝑘𝑓𝑙𝑜𝑤 𝑎𝑛𝑑 𝑣𝑎𝑙𝑢𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑑 𝑏𝑦 𝑎 𝑤𝑜𝑟𝑘𝑓𝑙𝑜𝑤 𝑎𝑟𝑒 𝑛𝑜𝑡 𝑡ℎ𝑒 𝑠𝑎𝑚𝑒.

The operating models that outperform on both quality and efficiency are the ones that track throughput and output in the same conversation.

📩 Start the conversation: [link in bio]

08/27/2026

Healthcare-associated infection rates are one of the most financially and reputationally consequential performance indicators in hospital operations — and one of the most persistently misdiagnosed.

The standard response when HAI rates climb: audit hand hygiene compliance, retrain EVS staff on terminal cleaning protocols, add observation rounds.

Compliance monitoring is rarely where the structural gap lives.

HAI performance isn't primarily a compliance problem. It's an operating model design problem — built into EVS staffing architecture, room turnover workflow, and environmental design long before any individual cleaning event.

Here are the five structural operating model failure points that drive chronic HAI performance gaps.

Swipe through. 👇

If two or more appear in your environment, the trend has an operational design address — one compliance audit cycle alone will not resolve it.

The free 15-Point Operational Readiness Assessment is pinned to the Malloy & Co. Featured section for systems ready to look past hand hygiene scores.

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