Sunday, October 12, 2008

ER Crowding, physician appointment and nursing care waits

Does Michael Moore’s SiCKO do the American healthcare any justice? Is the US healthcare riddled with delays? With the increasing exposure of healthcare wait time problems on TV and other media, and with healthcare being one of the central topics of political debates and strategies, what and where are the problems, and how do we deal with them? Professor Linda Green from the Columbia Business School talks about the three critical types of waits in healthcare and their impact on one another: emergency room (ER), physician appointment (or imaging tests) and nursing care waits. She sets out to prove that there are not “too many” beds in the system, physician appointments cannot be simply Just-In-Time, and the nurse staffing level doesn’t have a one-size-fit-all solution.

When physicians aren’t surprised of seeing patients suffering from heart attacks dying while waiting to get into a bed in ER (2006 news from an Illinois emergency room), when patients leave ER without being seen due to the frustration of long waiting hours, when ambulances have to be diverted because the ER is full, one needs to ask why. Why are the ERs always full when you need it? The number one reason for this is a lack of inpatient beds – the bottleneck of the healthcare system, which causes the inability to move patients in ER to an inpatient unit and therefore releasing beds in the ER. So, why are there not enough beds? The answer is relatively simple. Healthcare is expensive, and when governments need to stay on budget, healthcare gets cut. Healthcare also happens to be largely funded by government subsidization, so such cuts have reduced the number of hospitals from 7000 to 5000 (from 1980 to now), and the number of beds available from 435 to 269 per 100,000 persons in the US. Yet, politicians cry that there are “too many” beds. Why, you ask? Because important decision makers are looking at occupancy level (or bed utilization ratio), which for ER beds the utilization currently resides at around 66% (target is 85%). Utilization looks good, but it is the wrong measuring stick. Every OR person knows variability means extra capacity (more so than the average) is needed to deal with times of heavy demand with a reasonable level of customer satisfaction. Healthcare is one such process where demand varies greatly with the day of the week and the hour of the day. Aiming at and planning for averages is not going to work. A Green’s study showed that if New York state hospitals wanted to have a less than 10% chance of not having a bed available for up to 1 hour for an ER patient, then 58% of the hospitals would be too small. If they aim for a 5% chance of not having a bed available, then 74% hospitals would be too small; and if the aim were 1%, 90% hospitals would be too small. However, the good news is performance could be improved without increasing stuffing level at the hospitals, as Green has shown in her work.

Moving onto physician appointment and nursing care waits, these two factors both contribute to the overcrowding of ERs. When physicians are asked to treat patients in a Just-In-Time fashion, the major issue is that no one knows how to balance the physician capacity with the patient demand. When physicians have too many patients, not everybody can get seen in time, and patients cancel appointments if the wait is long. When patients cancel appointments, they also ask for another one because they still needs to be seen, so it goes back and adds to the backlog for the physicians. Study shows the shorter the backlog the higher the physician’s utilization. Green’s project of recommending the right number of patients for doctors has helped over 500 clinics and organizations to find that balance of capacity and demand.

It is widely acknowledged that there is a shortage of nurses, and that the lack of nursing care is directly correlated with increasing patient safety issues (mortality included) and patient satisfaction. California has passed a legislation to ensure a 1:6 nurse-to-patient ratio for general medical-surgical wards. It is good to see actions, but is this policy more disruptive than helpful? According to Green, varying unit sizes, the level of intensity of care for differing patient types, and the length of stay (and therefore turnover of patients) at different hospitals can all mean different optimal nurse-to-patient ratios. In larger units, the California legislation could result in overstaffing at a cost of $300,000 per year per unit, says Green. That is expensive.

Overall, healthcare certainly has a lot of problems. To name a few, there is the increasing cost, quality problems, and access problems. Operations Research is needed in this field. It could mean a matter of life and death.

Credits: The talk was given at the INFORMS 2008 conference in Washington DC. The track session was SC37. Speaker is Linda Green, Armand G. Erpf Professor, Columbia Business School. The talk was titled "Tutorial: Using Operations Research to Reduce Delays for Health Care".

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