Cost of Care Drivers

Last week I listed what I believe are the main factors contributing to capacity constraints in the healthcare system in Germany. Some of those are being already addressed in various ways, while others remain an open field (or shall we call it a blue ocean?):

Reimbursement incentives: Until recently, hospitals were incentivised to maximise the volume of patients and minimise their stay. While the out-patient centres and practices were incentivised to maximise the volume of procedures up to a quarterly budget limit. This led to high-admission rates in the former and general avoidance of chronic and time-consuming cases in the latter. The new healthcare reforms are changing those incentives in significant ways, so that the two sectors will now be paid the same rate for treating the same patient, which creates all kinds of interesting dynamics. A subject of another post.
High manual work: Doctors typing notes by hand, receptionists cross-checking calendars, controlling departments reviewing DRG codes, GPs entering EBM codes, etc. The obvious solution here is increasing automation. There are three layers here - the clinical IT layer (documentation, admission, reporting, billing, etc. - no regulatory approval required), the diagnostic layer (hardware and software) and the treatment layer. Potent startup ground.
Various system inefficiencies and silos: within the in- and out-patient sectors you have duplicated diagnostics, and lack of IT and data interoperability. But you also have those silos within each sector individually. This is as much of a collaboration problem as it is a design and ownership one. The patient journey is not designed with the patient in mind; or in tech terms - there is no “patient owner”. It’s not designed with the workflow in mind either.

I can’t help but wonder if all of this couldn’t have been modelled with the help of a generative AI, but given the human nature and the nature of human systems, the accuracy of such model would have probably been rather suboptimal. Well, isn’t that encouraging?

Tomorrow I'll zoom in on the increasingly dwindling clinician supply. And the day after - on the demand drivers.

Healthcare Demand Drivers

This is the third point I want to address as part of my effort to explore the capacity constraints in the German healthcare system. Part one was looking at cost of care and part two from yesterday was about the origins of the physicians shortages in Germany. 200 years ago

Clinicians Shortages, Drivers

To continue the cost of care thread from yesterday, the second big capacity constraint is around clinicians. Here is a quick recipe for how to think about this problem: 1. First we take specialists such as radiologists and dermatologists (in-patient care) vs GPs (out-patient care). 2. Second we

Capacity Constraints

There are three main problems with the healthcare system in Germany: 1. Bad economics: cost of care is too high. This is driven by many factors, including reimbursement incentives, high manual work, various system inefficiencies and silos, and the medical field simply developing further and finding ever more cures for

AI Drug Development Bottlenecks, The Workflow Middleware Layer

From a16z: To understand where AI fits, it helps to decompose drug discovery into its three essential stages: 1.Disease-to-mechanism: Identifying a biological mechanism — a pathway, a target, a molecular interaction — where therapeutic intervention will alter the course of disease in humans. 2.Mechanism-to-drug: Creating a

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Healthcare Demand Drivers

Clinicians Shortages, Drivers

Capacity Constraints

AI Drug Development Bottlenecks, The Workflow Middleware Layer