Assessment of survival in a pediatric intensive care unit In lima, peru
G Nakachi, R Shimabuku, J Cieza
intensive care unit, mortality prediction, patient outcome assessment, peru, severity of illness, survival analysis
G Nakachi, R Shimabuku, J Cieza. Assessment of survival in a pediatric intensive care unit In lima, peru. The Internet Journal of Emergency and Intensive Care Medicine. 2009 Volume 12 Number 1.
Until the last decade, poor children in Peru had limited or no access to health services. In 1997, the government established a system to deliver free health care to children attending government-run schools (children from private schools were excluded), which covered children from the age of three years until their 18th birthday. This health care system for school children from poor families lasted until January 2001, when a new, more integrated health system was established to cover children of all ages. Our research study was performed in a paediatric intensive care unit (PICU) during the period when health care services were free for poor children from their initial entry to school through secondary school. This study aimed to evaluate if the use of costly critical care to poor children was effective, as measured by outcomes, when compared to patients who were as ill in other developed countries.
Intensive care for children has contributed to the marked reduction in the rate of mortality and morbidity for certain diagnostic categories in Peru and in developed countries. Increased demand for health care, new technologies, and awareness of limited resources have become prominent issues, and intensive care paediatricians are interested in new ways to evaluate health care programs1,2,3. This has fostered the need for quantitative methods to evaluate medical activities in the paediatric population. Severity of illness scoring systems in intensive care have been developed and validated for all ages in the United States4,5,6,7, Europe8 and other settings9,10,11, and these systems have been improved and simplified12,13. Very few studies using these severity of illness scoring systems have been carried out in Latin American countries14,15,16,17,18.
When PICU was not available at our institution mortality was over 50 %. After establishing the necessity of intensive care and demonstrating that mortality could be lowered with skills, procedures and technologies proven in developed countries, paediatric mortality progressively decreased in our institution and in our country. However, we also saw that inadequate care could result in varying degrees of morbidity without necessarily resulting in death. In infants and children, poor care can have long-term effects on the dependent or independent-functioning life expectancy, and these effects are particularly important to physicians and society19,20,21. Studies assessing the performance, quality22, efficiency of paediatric intensive care23, effectiveness24, and patient outcome are relevant in our country because of the high social and economic costs of survival with disability25,26,27,28,29,30. We could not find studies measuring disability in countries comparable to our reality and since we considered important to have an approximate idea of our performance, we evaluated disability using the Pediatric Overall Performance Category (POPC) 19.
Our unit is the most important PICU in Peru. The lack of comparative analysis studies in Latin America and the need to maximize the efficiency of the scarce resources prompted us to evaluate our critical care and to compare our performance with units in other countries. In structuring our study, we considered three important aims: (1) to evaluate survival of critically ill patients and the factors related to their survival, (2) to establish the validity of the Paediatric Risk of Mortality (PRISM I) score in a Peruvian setting, and (3) to assess the effectiveness and efficiency of care in our PICU as compared to patients who were as ill in other developed countries.
Materials And Methods
for which we used PRISM I. The worst scores for the Paediatric Risk of Mortality (PRISM I)4 and Simplified Therapeutic Intervention Scoring System (STISS) scores30,31 were registered on admission or at 48–72 hours after admission. Other data collected included vital status, length of stay at the unit, and need of mechanical ventilation. To safeguard the quality of the data, the data were collected by the main researcher only. The study was approved by the Direction of Investigation and Technology Development of the Institute.
The survival curves for the patients according to the PRISM scores on admission are shown in Figure 2. To construct the curves, PRISM scores were divided into quartiles (0–6, 7–10, 11–15, and > 15 points), with larger scores showing greater physiological instability. We observed that patients with low PRISM scores (< 10 points), showing less physiological instability and had a greater probability of survival, and those with scores between 11 and 15 had a better probability of survival than patients with PRISM scores > 15.
In our population, the PRISM score performed well in predicting overall PICU mortality. The calculated SMR was 1.75 (95% confidence interval, 1.72–1.78), where the SMR by definition is the observed mortality rate divided by the expected mortality rate4,8. The stratified performance of the PRISM score in predicting the PICU mortality rate is illustrated in Figure 3; this was formally evaluated using the goodness-of-fit test, which showed that the observed and expected mortality rates were not in agreement [2 (5) = 11.07;
Children under three years of age were excluded from the study mainly to minimize any bias that might arise from the difference between government coverage of critical care and the cost assumed by the families of patients not covered by the insurance. We did this because the lack of services for children younger than three years might have delayed diagnostic procedures and treatment, or might have prevented parents from buying the medicines to treat their children, despite the help of social services and private institutions. Even though our study did not cover the full child population (i.e., none younger than three years), we believe our data are relevant to the study of health problems in school-age children because they experience a unique array of diseases and conditions (e.g., trauma), which could be useful to orient health care policies and allocation of resources.
Our country and other countries in our region are becoming increasingly concerned about the costs and questions of effectiveness and quality of care using high-technology medicine in PICUs. Until the development of the PRISM score for mortality prediction and the subsequent validation by other studies, comparing performance of different PICU settings was nearly impossible because of the wide variability in the types and conditions of the patients and the multiple factors influencing their outcomes. The PRISM score is a major step forward in standardizing these conditions.
Because of the shortage of available beds in PICUs32 and the cost of critical care borne by the families, the selection of patients has always been a factor determining patient care. Factors such as availability of beds and cost frequently delay the hospitalization and transfer of patients33 and delay the use of diagnostic procedures and therapeutic measures. Together, these factors may increase the length of stay, cause the patient’s condition to deteriorate, increase the risk of adverse events, and increase hospital costs. Government insurance for school-age children provided us with the opportunity to determine whether performance at the unit would improve once critical care was determined by factors other than family finances. We are addressing this new line of research in another work, which we hope to complete soon.
Survival curves have been used widely in cohort studies and for very specific diseases, but they have not been used in critical care studies34,35. We used survival tables and curves to evaluate the probability of patient survival during their stay in the PICU and the prognostic value of these data according to the diagnosis and physiological stability at admission. The survival curves for the PRISM score and for groups of diseases performed well in the prediction of overall PICU mortality, and, consequently, in overall survival. We found them to be useful tools to show tendencies and prognostic values in relation to mortality and when assessed with other factors related to survival. The probability of survival was better for non-medical conditions (trauma and surgery) and after the first week of admission at our unit. The probability of survival decreased for children with high PRISM scores, which indicate greater physiological instability.
We found heterogeneity in the cumulative observed and expected mortality rates, and in separate risk strata. We observed that the cumulative observed mortality rate was higher than the expected rate and that this difference was reflected in the SMR. These data indicate that the effectiveness of care in our population was equivalent to, but not better than, the reference population.
Patients most severely ill (PRISM>30) were patients with septic shock and those after cardiac interventions mainly due to congenital heart diseases. We cannot really explain why our outcomes were better in the sickest groups (PRISM >30), but we think that probably we gave more attention and we directed more efforts and resources trying to do the utmost for them than we did with the other patients (PRISM <30).
We consider that the observed mortality in our unit was considerably greater in the moderately and severely ill due to several reasons: (1) there was an asymmetry of knowledge and abilities between those intensivists dedicated to teaching and those who were not; (2) nurses were periodically rotated to other areas of the Institute according to the needs of the different services; (3) increased complications occurring during the night shifts or during the change of shifts; (4) physicians and nurses were on duty 24 hours per day on 6 and 12 hours shifts; and (5) complications due to nosocomial infections.
(6) during the study period, the medical staff at the unit were paediatricians without formal training in critical care, but with varying degrees of experience in paediatric intensive care, the same as the nurses. After this study was completed and as the need for pediatric intensivists increased, several universities started training programs for intensivists lasting two to three years. At the same time, several training programs in critical care were initiated for nurses.
The efficiency of resource allocation has been evaluated using two objective criteria in previous studies4,8. The first criterion of an arbitrary mortality risk level of 1% seemed to be an appropriate and safe lower margin; our observed mortality for this stratum was 3.57%, which is higher than that observed in these previous reports. The other criterion was the administration of at least one ICU-dependent therapy, based on the therapies found within the TISS-2830,31 and their appropriate application on the patients. Even though the turnover in our unit was good considering the perceived shortage of beds, the length of stay was somewhat longer than in other PICUs, causing an inappropriate prolongation of ICU-dependent therapies, which may have caused an artificially increased efficiency rate.
As critical care physicians, we have a duty to care for and to save children with life-threatening illnesses, as well as trying to maintain their functional status. Efficiency and effectiveness should be assessed by the final product34,35. Children have a long life expectancy, and it is important to try to increase their chances of living independently rather than with disability. In our paediatric population, more than 60% of the patients showed moderate to severe disability as measured by the Paediatric Overall Performance Category (POCP)19 , which could have been explained by the type of pathology predominant in this age group, such as trauma; infectious, congenital, and neurological diseases; adverse events before and during their stay in the unit; and previous disability before entering the unit. However, because of factors beyond our control, we could not adequately assess baseline functional status at admission or follow-up status at discharge, and we have only estimated their functional outcome at egress. Thus, these results reflect only partially the quality of care of the unit; full assessment requires further study and should be taken with caution because we do not have follow-up data after the patients left the PICU.
The risk of mortality is high in small children and infants. Having excluded from the study children younger than three years for reasons mentioned above, we acknowledge that our results may be difficult to compare with those from other units. Regardless, we still believe it important to have separate data for school-age children and adolescents, who experience a different array of diseases and risks.
We tried to compare our PICU with those in American and European reference populations (see Table 3). Because we included only school-age patients, the average age was greater in our population than in other studies. Our length of stay was longer and the PRISM score was somewhat higher, even though the risk of mortality was about the same as in other studies. Our mortality and SMR almost doubled those of Gemke
In summary, in addition to PICU mortality, other factors such as survival, long-term mortality, morbidity, and functional outcome seem to be important parameters for measuring the effectiveness and quality of care in PICUs. Our study demonstrates the validity of PRISM score-based mortality prediction in a Peruvian PICU for children between the ages of three and 18 years. The efficiency of our unit met the standards established in American and European studies, but our overall performance was lower than that in the American and European reference populations. Our study confirms that these methods are transferable to units in other countries. One important contribution of our study is that we have presented for the first time survival curves in relation to two main factors that affect survival in a PICU—the type of disease on admission and PRISM scores, which proved to be useful tools in assessing critically ill children.