Identificação de um método estatístico como instrumento da qualidade: tempo da presença do doente na sala de operação

Introducao: A organizacao do trabalho cientifico atraves da logica e experimentos, a estrutura do estabelecimento de pesquisa individual ou aos diferentes aspectos da vida da comunidade cientifica foram o eixo de mudancas na relacao ciencia e tecnologia. A Universidade, dentro deste contexto, se constitui em uma fonte de criacao permanente, sistematizacao e difusao do conhecimento cientifico e tecnologico. A estatistica como instrumento da qualidade se constitui em apoio as acoes que visem a otimizacao dos recursos disponiveis e melhoria da prestacao de servicos com qualidade. Objetivo: O estudo proposto, junto a especialidade de Cirurgia Cardiaca/Hospital de Clinicas/Unicamp tem como objetivo identificar um metodo estatistico que expresse o tempo da presenca do doente na sala de operacao e construir uma "matriz de relacao" de otimizacao deste tempo, o tempo exato e real da operacao. Metodo: O metodo de analise de sobrevivencia aplicada utilizando o estimador nao parametrico de Kaplan-Meier, permite calcular as curvas de sobrevivencia para os tempos em estudo, e com o resultado obtido criar uma "matriz de relacao" da otimizacao do tempo da presenca do doente na sala de operacao por meio de dez hipoteses que auxiliam na escolha da nova operacao, e melhor ocupacao da sala. Este estudo tem como parâmetro de referencia para o tempo de limpeza da sala de operacao, o que a literatura estabelece em aproximadamente 30 minutos, alem do tempo de cada tipo de procedimento cirurgico. A amostra aleatoria simples para estimar a curva de sobrevivencia constitui-se de 71 pacientes, das operacoes eletivas de adultos da Cirurgia Cardiaca/Hospital de Clinicas/UNICAMP, durante o ano de 2008. Resultados: Nos resultados encontrados observou-se que os tempos que sobram das operacoes em media estao em um intervalo de 140 minutos a 200 minutos e excedem de 5 minutos a 90 minutos, para realizacao de novas operacoes. No geral, realizou-se em media diariamente uma operacao dentro de 520 minutos, para um tempo disponivel de 720 minutos. No ano de 2008 foram suspensas 39% das operacoes, sendo que 81% dos motivos foram "fatores hospitalares extrapacientes" e 19% "relativos ao paciente". Em suma com os resultados obtidos pela metodologia de analise de sobrevivencia, metodologia tradicional, e metodologia de gestao da qualidade, e possivel cruzar informacoes e construir passo a passo o conhecimento cientifico e tecnologico. Conclusao: (1) O tempo do doente na sala de operacao e um tempo que tem nele incluso, o tempo de aprendizado pelo aluno, em um hospital escola, universitario. (2) Com o tempo maximo disponivel de 720 minutos nao e possivel realizar outra operacao, a nao ser utilizando da "matriz de relacao", sendo que o tempo maximo disponivel varia entre 660 minutos e 690 minutos, considerando-se intervalo de limpeza da sala. (3) Ao otimizar o tempo do doente na sala de operacao, atraves da "matriz de relacao", mais doentes serao beneficiados, acarretando uma diminuicao da fila de espera para novas operacoes, garantindo uma eficiente relacao custo beneficio. (4) A "matriz de relacao" fornece dados que permitem visualizar, opinar e decidir qual e a melhor operacao a ser realizada e se ha tempo disponivel para tal 
Abstract


INTRODUCTION
The constitutional principles of the Health Care System (SUS) together with the Brazilian nosological situation and technological evolution and increase of its costs, as a result of scientific progress, make the prioritization of health interventions a critical issue. Citing Fourez [1], "For many of our contemporaries, it seems clear that science and technology are connected". According Bittar [2], citing Sloan and Valcona, "the more precise and rapid diagnosisdue to the development of complementary services -have brought, as a result, a decrease in length of stay. Also, one should not forget the technological development occurred with drugs, orthoses, prostheses and procedures that directly influence on the length of stay required for recovery of patients".
Hospital processes constantly need to be improved. The search for tools that can measure the processes and activities, make possible the improvement of the quality of services provided. Combined with a high-technology, professionals who always are well prepared for the management of such services, are an important factor in the relationship of medical care with patients, as well as the time the procedures are performed is an essential variable to be measured -from the waiting list of the patient to be treated up to his effective treatment. As a result we can mention the effective and efficient use of resources, indicators measuring the quality and quantity of what is done in terms of programs and health services, such as structure, processes and outcomes; by avoiding waste, such as cancellation of surgeries, time in waiting list, among others that should be pursued by the manager, otherwise the Hospital not may survive. Such subjects are approached by Aranha [3], Bittar [4], Duarte and Ferreira [5], Perroca et al. [6] and Haddad et al. [7].
The aim of this study is to identify a statistical method that expresses the time of the presence of the patient in the Resultados: Os tempos das operações em média sobram em um intervalo de 140 a 200 minutos e excedem de 5 a 90 minutos. No geral, realizou-se em média diariamente uma operação dentro de 520 minutos, para um tempo disponível de 720 minutos.
Conclusão: 1) Com o tempo máximo disponível de 720 minutos não é possível realizar operação, a não ser utilizando da "matriz de relação", sendo que o tempo máximo disponível varia entre 660 e 690 minutos, considerando-se intervalo de limpeza da sala. operating room and build a relationship matrix of optimization of this time, the exact and real time of the operation.

METHODS
The research on the literature guided to a path that could approach the improvement in the optimization and quality of service. In this study we applied the method of survival analysis to assess the times: Real Time of Surgery (T1), the Exact Time of Surgery (T2) and Time of the Presence of the Patient in the Operating Room (T3). The classification of heart surgeries is in Chart 1 and are part of this study of the times T1, T2 and T3. After classifying the times of operating room and the types of operation, we identified the schedule of the operating room for heart surgery, which has an exclusive room, with two periods of 360 minutes, totaling 720 minutes available daily. Next, we used the method of applied survival analysis, according to Colosimo and Giolo [8], which seemed to be the most appropriate for this type of study. The records collected came from a random sample of 71 patients, whereas eight of aortic aneurysm, six of ischemic heart disease, six with congenital heart disease, two of other procedures (pericardiectomy and surgical debridement) and 49 valve disease patients, at a confidence level of 95% during the year 2008, noting that at the time of collection of this sample there was no aortic surgery. The data are only related to adult patients undergone heart surgeries at the mentioned period and were performed at the Clinics Hospital of UNICAMP, and the software used for analysis was the SAS.
In survival analysis, the dependent variable is the time when the event occurs, or that is, when the surgery is performed. This time is counted from the time of entry into the operating room, which is the "time of entry into the operating room" until the discharge from the operating room, which is the "time of discharge from the operating room". The dependent variable, time, is the "failure time", that in this case, is the time when the surgery was not accomplished and it refers to the initial time, the measurement scale and the occurrence of the event. The aim of this statistical analysis is to identify factors that may influence the processing time. The time in which the event of interest occurs is specified by its "survival function" or "risk function". The first is the probability that an observation does not fail until a specified time. The second is the probability that the failure occurs in a period of time. The procedure adopted is to find an estimate for the survival function and, from such function, to estimate these measures.
The most widely known technique for this purpose is the Kaplan-Meier nonparametric method, where: S (t) = number of observations that have not failed until a specified time/ total number of observations in the study. The estimator considers both time intervals as the number of distinct failures. To assess the accuracy of this estimator it can be built confidence intervals and hypothesis test for S (t). The survival curves for this study and further analysis were calculated for: T1 -Real Time of Surgery, T2 -Exact Time of Surgery and T3 -Time of the Presence of the Patient in the operating room. The data collected do not have any missing time, and there is therefore no variable without values.

RESULTS AND DISCUSSION
Surgeries and cardiac hospital stay are shown in the Table 1.
Regarding the cancellation of surgeries, there were many different reasons, such as administrative reasons or "extra-patient hospital factors", 190 surgeries suspended; reasons related to patients, 46 surgeries suspended, totaling 236 surgeries suspended; and two reasons mainly due to "inadequate surgical time", 92 suspended surgeries; and "lack of beds available", 70 suspended surgeries, totaling 162 suspended surgeries due to the maximum time available for daily surgeries at the Surgical Center, which could be better controlled, reducing the waiting list.  (Fig. 1).
-Time (T2) -Exact time of Surgery (minutes). By the time 265 minutes, in about 51% of surgeries their T2 times were not completed, and so until the time of 420 minutes on average, all surgeries had their T2 time completed (Fig. 2).
-Time (T3) -Time of the Presence of the Patient in the Operating Room (minutes). By the time of 340 minutes, in about 51% of surgeries their T3 times were not completed, and so until the time of 520 minutes on average, all surgeries had their T3 completed (Fig. 3). about 50% of surgeries their T3 times were not completed, and so until the time of 520 minutes on average, all surgeries had their T3 times completed (Fig.4).    (Fig. 7).

Other procedures: pericardiectomy and surgical debridement
-Time (T1) -Real Time of Surgery (minutes). By the time of 190 minutes, in about 50% of surgeries their T1 were not completed, and so until the time of 250 minutes on average, all surgeries had their T1 times completed.
-Time (T2) -Exact Time of Surgery (minutes). By the time of 167 minutes, in about 50% of surgeries their T2 times were not completed, and so until the time of 225 minutes on average, all surgeries had their T2 times completed.
-Time (T3) -Time of the Presence of the Patient in the Operating Room (minutes). By the time of 225 minutes, in about 50% of surgeries their T3 times were not completed, and so until the time of 310 minutes on average, all surgeries had their T3 times completed (Fig. 8).
Calculating the probability of surgeries using the survival analysis and buiding a "relationship matrix' for optimizing the time of the presence of the patient in the operating room (T3), it is shown in Chart 2 the main time limits in general and by specialty to: T1, T2 and T3, the maximum time available, the difference of these times between the T3 time and the difference between the maximum time available and the T3 considering the minimum   and maximum times of assepsy according the type of surgery and the assepsy time described in the literature, according Nepote [9]. In Chart 3, the "relationship matrix" is a crossanalysis of informations obtained by the survival analysis and contains the difference of maximum times with respect to T3, the 10 hypotheses aiding in re-operation, spare time and over time of the possible new surgeries, and, in general and in the average, the spare time is of 140 minutes to 200 minutes, and over time of 5 minutes to 90 minutes and no new surgery to be performed. For example, if it is used H1, Tmax difference (12)-T3 (=200) and considering the rule of H1: "performing another surgery of the same type", it seems that another surgery of aortic aneurysm, which uses an average of 520 minutes, is not possible. Since it spares 200 minutes (720 -520 = 200), it is not possible to perform another surgery of the same type, and does so with the other cases in accordance with its rules and the maximum available time at the Surgical Center, and one should also consider that the assepsy time of the operating room should vary from 10 minutes to 60 minutes according to the assepsy time for each type of surgery. It was established as a rule in this study, a possibility of exceeding the time for new surgeries in up to 90 minutes.

CONCLUSION
In short, the method of survival analysis allows to cross informations and build step by step, the scientific and technological knowledge, resulting in a quality instrument, as is the "relationship matrix" for optimizing the time of the patient in the operating room, concluding that: 1) The time of the patient in the operating room is a time that includes the time of learning by the student in a teaching or university hospital. 2) With the maximum available time of 720 minutes is not possible to perform other daily surgery, except for predicting the average times of surgeries obtained by the analysis of survival and establishment of the "relationship matrix", as it became evident that the time is "not" 720 minutes daily and should be lower, due to the time of assepsy of the operating room between a surgery and another. 3) By optimizing the time of the patient in the operating room through the "relationship matrix" it will be chosen the hypothesis with better convenience, because it increases surgeries, allowing that the spare time of the previous surgery may be occupied, decreasing the waiting list.