The time from seeking care to treatment is a good indicator of the level of service. When the helath care wait time is low there can be an excess of resources and when it is high there are not enough (in a system that is full). In theory, health care wait times can be calculated (and even better predict them going foward) for each sector of the system and resources allocated appropriately. Currently many governments are calculating wait times in the emergency rooms, monitoring patient flow and time to surgery. But wait times can be manipulated. Surgeons can limit consultation time so the actual time on the wait list for surgery is low, emergency rooms can leave the patients with the ambulance crew prior to registration.
Instead, wait times need to be considered from the patient's perspective. Not only will it better reflect the actual wait involved but it might allow for more solutions. Imagine a patient that phones the doctors office. If the wait time for the front desk is only measured as the time on-hold with the office administrator we see only half the story and consequently half the solutions. In this instance, the only option is to either hang up or keep holding. If the wait time is measured from the time the decision to call is made other options such as email, fax, etc... also become apparent. Both email and fax would potentially decrease the wait time and relieve the burden on the administrative staff.
While patients may choose to accelerate or delay treatment and inadvertantly manipulte wait times, our data suggests that the mean wait is a good predictor of availability in the clinic. Most of the patient populations have well defined normal curves with predictable variations. Since representative survey populations are already common in politics; can the same solution not be extended to health care? We don't need to record every surgery and every wait time, just a representative sample. This would significantly simplify the burden on the information technology sector in health care (who is currently trying to connect many different clinics) and potentially provide accurate data over wider sectors. To determine how many patients need be surveyed and across which sectors, it would be simple enough to look at existing data for power and size calculations. From there a uniform, automated system could be implemented for all sorts of health problems not just those choosen as priority programs.
More and more institutions are rightfully focusing on wait times and so should smaller clinics. I think we'll find that as systems evolve a universal yardstick for health care delivery will not only let us see the problems, it will let us see the solutions.
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