Discussion 

The number of missing cases is very high (53,5%) which already shows a failure in MTS application since there was no record of medical observation in all the cases as it should be. Moreover, in some cases in which there was record of medical observation, it was made in an incorrect way (58 errors and 21 possible errors).

It would be expected that the time would be exceeded predominantly in less urgent cases. However with the results obtained it is possible to see the opposite. Several factors may explain this fact. First, for less urgent cases, in which the maximum waiting time suggested by MTS is higher, it is easy to see that the probability of this being exceeded is smaller than in the cases in which the suggested time is very tight. Secondly, it mustn’t be overlooked the fact that the priority of doctors is the care of patients and not the record of the observation. For this reason, the immense interval of time experienced between the time of entry into the U.S. and the time of medical observation may be explained by the fact that doctors tried to ensure the necessary health care to the patients first and just then they registered the case.

Figure 10 – Relations between rate of death.

There are two tight relationships involving rate of death with the waiting time and with the urgency of cases. Just like we expected the rate of death increases as the situation’s urgency increases too. In the same way, the behavior is similar when we talk about the time patients waited. According to table 3 and 4, in the more serious cases, the death rate was superior in the cases that waited more than the time suggested by MTS. This fact is easily understood if we make the following thought: if they need care and if they don’t get it on time is normal that the probability of death become higher. However, the elevated rate of death in red colour must be mainly related to the urgency of the cases and not to the waiting time.

We can also conclude that in the colours green and blue there were no differences in the different groups. On the other hand, the yellow cases were an exception being the death rate superior in the group that didn’t waited more than it was supposed to. We believe this could be an interesting subject for future approaches.

It is important to emphasize that, according to the results; the MTS’s efficiency was higher by the beginning of its implementation, because the percentage of the exceeded waiting time increased in the most recent trimesters in comparison to the first ones. A possible explanation for this fact is that in the beginning nurses and doctors gave special attention to all the procedures related to MTS as it was new in the urgency services (US). Along the time, MTS is becoming an ordinary routine and so is possible that it is less strict and respected. About the possible relationship between the rate of death and the efficiency of MTS, as it was seen in the results (figure 5), we can conclude that there is no evidence which confirm that the decrease of MTS’s efficiency is a probably cause for the number of deaths occurring along the time.

About the returns to US it remains as an open question to further approaches: how do the lower urgent colours have more returns? And also, why all patients that reentered after 48 hours, showed again after 72 hours of the first triage moment?

In the beginning of our study we’ve mentioned some studies that might reach a certain level of comparison with this one. For a brief analysis between results and conclusions we’ve selected one of those and another study proceeded on Netherlands. Starting with Martins H. ⁽⁵⁾, they have focused work on observing how priority given to patients by MTS could affect their outcome, especially concerned on admission and death (on the A&E department). Their statistical analysis came from a database with 321 539 episodes of urgency, all of them collected between January 2004 to the end of June 2007 but, as we’ve done, they’ve excluded cases with white colour (4917; 1,53%), thus analyzing 316 622 patients. The other patients submitted to MTS were categorized into Red (0,74%), Orange (24,78%), Yellow (50,65%), Green (20,28%) and Blue (2,00%): resulting on a median of 65 226 patients in each MTS code. When comes to outcome death, there’s the need to say that they hadn’t estimated percentages, only presenting the global median (6) and the absolute frequencies – however we needed to obtain some valid percents to compare with our results. Concerning to colour red they’ve obtained 10% of deaths, while in this study there was 29% of deaths with the red colour assigned -  a great difference which can led people doubt about the efficiency of the emergency department of Hospital Santa Maria da Feira concerning to high urgent cases. On the other hand, there are presented one death on green colour and zero on blue colour, while we could obtain zero deaths in both colours. Concerning to colours orange and yellow, they’ve obtained 0,04% and 0,003 % of deaths, respectively; one more time a number that were substantial lower than our results (0,7% and 0,1%). As conclusions, it was found that risk of death seemed to increase exponentially from lower to higher urgency categories. From our analysis, it comes clear the relationship between rate of death and urgency level. Another aspect tights with the outcome admission where high priority ranks (such as red and orange) have four times more propensity to be admitted.

                The other article (13), involved the study of four US databases between 1 January and 18 July of the year 2006 to predict mortality and admission on MTS and another triage method (ESI – Emergency Severity Index). About MTS they were able to analyze 34 258 urgency episodes, already with missing categories excluded; with patients triaged mostly in yellow (37,7%) and green (44,5%) categories, while red occurred a few times (0,6%) – thus we can consider these ones similar to our results. Paying attention on outcome death, there was observed 29 deaths on MTS system, in which 75,9% corresponded to red colour cases. We could consider this number of deaths substantially under ours but, in this case, the database used in our study has a high number of cases. But, they’ve also drawn the hypothesis of higher rates of death on most serious and urgent cases, showing a close relation between urgency categories and mortality. An interesting point comes from the variable age, which is considered a significant predictor of urgency, once data comes from different populations. The mean age and standard deviation (SD) from these are 42,4 and 23,5 years, while in our database we obtained 46,5 as mean age, with 19,8 years as SD; however, we can consider our results as more precise ones because our sample have a higher number of urgency episodes. Finally authors remember that after a patient being triaged, his condition may deteriorate in the period between triage moment and medical assessment, which can lead to unexpected outcomes.

                Unfortunately we couldn’t find and article which studied the efficiency on the apply of MTS concerning recommended waiting times, to see if these results can be accepted even if major times it didn’t respect those minutes categorized for each colour.

For summarize, comparing the expected results to the observed ones we have:

Figure 11 – Comparison between the expected results and the observations.

- We thought that the waiting time would correspond to the colour given to the patient. However, there were significant differences, especially in the orange and red cases where the waiting time exceeded in a large scale the expected one;

- Another observation, and even more surprising, was that some patients waited more time then the recommended for colours which represent less urgent cases. For example, 6.8% of the oranges exceeded the limit of waiting time for the yellow cases. This situation shows, in fact, an enormous failure in the application of MTS in this hospital;

- It was expected that the mortality rate will correspond to each colour; for example, the mortality rate should be higher in the patients that are given the red colour, and what we observed was completely in agreement with this idea;

- It was also expected that the cause for the death of some patients was the urgency of the case and not, directly, the fact of these patients waited more than the expected. Nevertheless it was not what we see, in fact, 80,5% of the cases which waited more than the standard waiting time of the correspondent colour, the patient ended up dying. This is, probably, the most serious consequence of the malfunction of MTS in this hospital;

- Although it was expected that the efficiency rate of MTS increased along the time, we observed the opposite, since the percentage of the exceeded waiting time increased in the most recent trimesters in comparison to the first ones.

From these results, we can conclude that the application of MTS is failing in practice. Despite the fact that the triage system is still possible of improving, the flaws that we present in this report are due mainly to its application in daily life in a big hospital. And so, we believe that its application should be more rigorous, accurate and effective, in order to obtain better results in the future and the most suitable and correct system of triage.

Finally, although the limitations: as the great number of missing cases in the database and the fact data only belonged to one hospital all along the country (making possible exist other scenarios of how is MTS being applied) and these were collected possibly for some other purposes, we think that main aims of our work were achieved, since we were able to evaluate what we proposed to.

For further studies we recommend more analysis of how recommended waiting times are being respected, not only in our country but all over the hospitals who have relied on MTS, and even pay attention to some factors such as age and social status (graffar).