6. Healthcare

6.4 Workload of Doctors

Since doctors are paid based on the quality of their work, it is not worthwhile for them to perform unnecessary treatments. Because both patient satisfaction and their competence assessment would suffer as a result. If the state determines that every other treatment by a doctor was unnecessary, the worth of their effort points diminishes by half.40

If a doctor is fully booked and therefore has to turn away some patients, it is worthwhile for him to work more efficiently and shift a larger portion of the workload to nurses. As long as competence and patient satisfaction don't suffer too much, he will be paid better for it (since he collects more effort points). Which is right and important. After all, the goal is to treat every patient without them having to wait a long time for an appointment.

If the doctor is not fully occupied (which should be the default case), then he can take a little more time for each patient. It doesn't cost him any revenue from lost effort points (since no one is waiting), and the extra time should improve patient satisfaction and competency assessments (as long as he doesn't perform unnecessary treatments). Which in turn means a better income for the doctor.

To ensure that doctors are not fully utilized on average and that the entire system functions as it should, an average utilization rate of 80% for doctors is the goal. We have set the target number of doctors (one doctor per 100 inhabitants), and it cannot be changed in the short term. Instead, there will be a list of the treatments covered by the public health system, meaning that all others are not. This list is sorted by efficiency for each field of medicine (How much additional quality of life does this treatment enable on average, for how long, in relation to its costs?). If a field’s utilization rate exceeds 80%, its least efficient treatments are removed from the list. If utilization is below 80%, the next most efficient treatments are added. By comparing the efficiency of treatments that are just barely/no longer covered in different fields, the state can determine the need for doctors: If general practitioners have to forgo useful treatments because there is a shortage of doctors, while dentists are gold coating their patients teeth because they have so much time—then we need more general practitioners and fewer dentists. Since the state employs and pays the doctors, it has all levers of control at its disposal here.

Limiting capacity to 80% in normal times ensures competition in the system (patients can choose a good doctor and get an appointment there) and is necessary for it to function well. Having this reserve is actually very desirable for the state. If the workload of doctors and nurses is only 80% in normal times, then in a crisis situation, such as a severe flu epidemic, a coronavirus pandemic, a natural disaster, or a war, it can exceed 100% without immediately risking burnout. If, on the other hand, the system is always running at its limit, as is currently the case for large parts of the German healthcare system, then this reserve is simply not available, and the system is much less able to cope with crisis situations.

The system design presented here, on the other hand, adheres to what I stated at the end of Chapter 3: futurities should be resilient.

If patients want a treatment not included in the list of paid services, that is possible. Either by paying for the treatment themselves, or by having a private supplementary insurance cover those costs. They can either go to a private clinic that has nothing to do with the state healthcare system, or a state-funded doctor can perform it. These treatments are paid less well (importance < 1), so for the doctor the effort is less worthwhile than treatments from the list of services paid for by the state (a reversal of the current state, where private patients are treated preferentially). The payment for this treatment goes to the state and is significantly higher than the money the doctor receives (undeclared work and bribery has to be prevented!). The state uses this money to pay additional doctors to compensate for the time spent on these privately funded treatments.

A brief word about state-funded medications: Only medications that have passed the state approval process (see 5.2 “Patent System”), and have thus proven their effectiveness, are paid for by the statutory health insurance. Similar to treatments, medications are also sorted according to efficiency. If the total expenditure on medication rises to an excessive level, the state will no longer pay for the least efficient ones. Then it is once again up to the citizens whether they pay for the medication themselves, can cover it through additional insurance, or have to forgo it.

Here, the abolition of the patent system described in 5.2 helps enormously, since it simplifies the production of generic drugs. Generic drugs are much cheaper than the original brand-name medications. And cheaper drugs equals significantly more medications being on the state-funded list.

This is yet another example of the predicted difficult ethical decisions. There isn't enough money for everything. All the state can do is decide as objectively as possible how to use the limited funds most efficiently.

The doctors' appointment scheduling is organized through the health app.

Each doctor indicates the maximum number of hours per week they want to fill with patient appointments. He specifies his work and vacation days. For workdays, he selects suitable time slots (he can also specify a preference, so that other appointment slots are only filled once the preferred time slots are full). The health app then automatically reserves time slots for patients seeking a doctor. The referring doctor or the patient himself selects the category describing the reason for the doctor’s visit.41 The doctor determines how much time the system should reserve for an appointment for each of these categories.

For the state, all this appointment data is incredibly useful for noticing problems in the system (such as a localized overload) early on. For patients it is very convenient to be able to organize doctor's appointments centrally via the health app.

Every doctor is obligated to offer a certain amount of time as open consultation at the end of their workday. Time during which he is available for patients but does not schedule appointments. If no patient arrives, he can use the time for office work. This is intended for general practitioners to address acute patient problems, thereby relieving the burden on hospital emergency rooms. With specialist doctors in polyclinics, it allows for follow-up examinations or treatments directly on the day of the annual checkup or as a result of an appointment with another specialist.

Determining the current workload of doctors simply as a percentage of appointment slots filled is not good enough—we need a computer simulation of the healthcare system for that.42
While this is a lot of work initially, it allows us to test many aspects of the overall system (salary formula, target utilization, demand from specialist fields, ...). Any adjustment help we can glean from the simulation, any indication of an impending problem, is extremely helpful.

In addition to defining the treatment catalog and payment of specialist departments, these calculated utilization values have another important application: the state uses them to decide where to deploy the available doctors. The counties are a suitable administrative unit for this purpose: their populations in Germany is in the order of 100,000. With one doctor per 100 citizens, there are approximately 1,000 doctors in a county.

Which counties are allowed to offer positions to doctors of which specialties? After all, it is the state paying the doctors' salaries.

On the one hand, we want to afford doctors freedom of choice. It doesn't sound fair if the state, as monopolist, can order doctors to any location in the country. On the other hand, we can't let them choose freely: There would be too many doctors in the capital and too few in the countryside.

One could come up with many rules here. I propose the following simple logic: For each specialty, only counties with a currently above-average workload for their doctors in that specialty should be allowed to recruit (this should be roughly half of all counties for each specialty). Each county is allowed to recruit as many doctors as necessary to reach an average capacity utilization (which will cause other counties to fall below the average and become eligible to recruit new doctors).

The decision of whether and where doctors can work in the county is made by the county and the heads of the polyclinics (who are selected by the county). So, if a county doesn't offer any or any attractive job opportunities for doctors: that's something voters can influence by electing more competent politicians in their county!43

42 If one simply uses the proportion of unfilled appointment slots, a target utilization rate of 80% leads to a vicious cycle: Because many doctors, as intended, still have free capacity, they take more time per patient (good!), thereby increase their satisfaction and competence level (also good!), in order to earn more money. In this way, they have used some of their free capacity after all though. The measured utilization is therefore higher. Which means that now further treatments are getting cut (in order to reach 80% capacity again). Which means that doctors have even more free time and can spend even more time with their patients, as a result of which the next treatments are removed from the list... →
A computer simulation can solve this dilemma. As the number of treatments increases, how does the quality of healthcare change (as measured by wait times, as well as satisfaction and competency ratings of individual doctors)?We feed a neural network with historical data until it predicts the past development as accurately as possible. Then we query the future behavior for various percentage increases in treatments. For every specialty and location, the highest possible increase without a noticeable loss of quality is the 100% local utilization of the healthcare system.