Factors associated with involuntary hospital admissions in technology-dependent children

3 Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Departamento de Enfermagem Materno Infantil e Saúde Pública, Ribeirão Preto, SP, Brazil. ABSTRACT Objective: To identify the factors associated with involuntary hospital admissions of technology-dependent children, in the municipality of Ribeirão Preto, São Paulo State, Brazil. Method: A cross-sectional study, with a quantitative approach. After an active search, 124 children who qualified under the inclusion criteria, that is to say, children from birth to age 12, were identified. Data was collected in home visits to mothers or the people responsible for the children, through the application of a questionnaire. Analysis of the data followed the assumptions of the Generalized Linear Models technique. Results: 102 technology-dependent children aged between 6 months and 12 years participated in the study, of whom 57% were male. The average number of involuntary hospital admissions in the previous year among the children studied was 0.71 (±1.29). In the final model the following variables were significantly associated with the outcome: age (OR=0.991; CI95%=0.985-0.997), and the number of devices (OR=0.387; CI95%=0.219-0.684), which were characterized as factors of protection and quantity of medications (OR=1.532; CI95%=1.297-1.810), representing a risk factor for involuntary hospital admissions in technology-dependent children. Conclusion: The results constitute input data for consideration of the process of care for technology-dependent children by supplying an explanatory model for involuntary hospital admissions for this client group.


INTRODUCTION
Technology-dependent children are conceived of as being those who need some device to compensate for the loss of a vital function, such as mechanical breathing machines, peritoneal dialysis, and/or use of gastrostomy, tracheostomy, or other processes.Innumerable clinical conditions can result in the use of these technical devices, for example, cerebral palsy, myelomeningocele, genetic syndromes, congenital deformities, and others (1) .
Technology-dependent children are in the group of children with special health needs (CSHN), since they have damaged health, and need continuous attention from family members and health professionals, in excess of the care that is necessary for other children of the same age group (2) .In the literature, there are several co-existent denominations for referring to these children, such as medically fragile children -referring to those that have serious health problems and frequently need technological devices to maintain their vital functions (3) , and children with medical complexity (CMC) -those that have multi-systemic disorders of a congenital or acquired nature, require intensive care and may be dependent on technological devices (4) .
It is estimated that 15% to 20% of children in the United States up to the age of 17 have some special health need (5) .A study that aimed to estimate the number of medically fragile children, and the cost of their health services, showed that 0.25% of the children of the US State of North Carolina fitted this definition.The study also indicated that, although they represent a small portion, they were responsible for the greater part of the expenditure on the health services (3) .The high cost may be the result of accompaniment by specialists, frequent surgery, and attention given by tertiary care services (4) .In relation to Brazil, there is no estimate of the number of CSHN, but only isolated records of incidence in certain locations, of which the most significant have been studies in Rio de Janeiro, in the state of Rio de Janeiro, and Santa Maria, is the state of Rio Grande do Sul (6) .
As a result of their fragile state of health, these children need frequent admissions to hospital (7) .However, researchers suggest that the fragile state of some clinical services, associated with prolonged hospital admissions and aggressive treatments, frequently worsens the child's state of health (8) .On similar lines, a US study indicates that frequent and prolonged hospital admissions may worsen the clinical condition and generate new demands for technological devices (9) .As well as the biological dimension, frequent hospital admissions of a son or daughter can give rise to a series of family misadjustments, such as maternal overload, financial difficulties, and sadness of the healthy siblings (10) .
In view of the above, the need for this investigation is shown by the need for knowledge of the elements that contribute to prevention of hospital admissions in this population.Thus, the study aims to identify the factors associated with involuntary hospital admission among technologydependent children, in the municipality of Ribeirão Preto, São Paulo State.

METHOD
This is a cross-sectional study with quantitative approach.Investigation was carried out in the municipality of Ribeirão Preto, in the northeastern region of the state of São Paulo, Brazil.
The participants were identified through an active search, since the information relating to this group of children was not systematized in the health units.The active search took place in the health services of the Municipal Health Department, in the institutions for support for CSHN registered with the Municipal Councils for the Rights of Children and Adolescents, and in two private health institutions that provided home care, of which one refused to participate.It also benefitted from referred informants: when contact was made with one family, the investigators enquired whether they knew of other children with the same condition.
After active search, 124 children were identified as qualifying with the criteria, that is to say, aged up to 12, dependent on some technological device for maintenance of life, and resident in the municipality of Ribeirão Preto, São Paulo State.Of these, 102 technology-dependent children took part in the study, since upon contacting the families it was found that 20 children had ceased to use the technological device and three had died.Only one mother refused to take part in the survey.Home visits for collection of data were made in a single survey period, January through April 2011, with average duration of 30 minutes.We also note that five of these children lived in a philanthropic institution that provides 24-hour multidisciplinary care to children with cerebral palsy.
The data collection instrument was organized with data identifying the child and questions related to the clinical and social-demographic conditions.The instrument was filled out using the reports of the mothers or guardians as source: hence they are self-reported data.The medical records were used only for filling out the instrument of the children that were institutionalized -a total of five.
In relation to the information on hospital admissions, the mothers or guardians stated the number of admissions in the prior year, and the reasons.Based on this information the hospital admissions were categorized into voluntary and involuntary.For this study, previously programmed hospital admissions were left out of account, that is to say, those that did not correspond to a worsening of the child's clinical condition, such as voluntary surgeries and admissions for periodic administration of medication.Similarly, a US study which aimed to analyze the association between outpatient accompaniment of children with medical complexity and re-hospitalizations within the first 30 days after hospital discharge also left planned admissions out of account (11) .
The number of involuntary admissions in the prior year ( January 1 through December 31, 2010) was considered as a dependent variable or a response variable, and classified as numerical.
The following were adopted as independent variables: the age of the child in months (numerical variable) the etiology of the child's health condition (category variable: acquired The data were coded and posted in a formatted database in Excel, using double-input typing.The database was validated by a comparison of the two spreadsheets, using subtraction -after which any cells with non-zero values were checked, the original data collection instrument checked, and the due corrections made.After validation, the database was exported to the SPSS software, version 16.0, in which the analyses were carried out.The statistical tests were made by a statistician, after analysis of the empirical material.In the descriptive phase of the statistical analysis, participating children were characterized according to the variables of the study.For the category variables the measures of absolute and relative frequency were used, while for the description of the numerical variables the measures of central tendency, variability and position were used. After descriptive analysis, a comparison was made of the averages of involuntary hospital admissions among the categories of the independent variables using the Mann-Whitney test for dichotomy variables and the Kruskal-Wallis for those with more than two categories.The Spearman correlation coefficient was also calculated for the numerical variables.For the tests, a significance level of 5% was adopted (12) .
Finally, a multiple regression analysis was made using the Nelder and Wedderburn Generalized Linear Models technique (13) .This technique consists of opening the range of options for the distribution of the response variable, permitting it to belong to the exponential family of distributions, making possible a greater flexibility for the functional relationship between the average of the response variable and the independent variables (13) .Since the response (or dependent) variable of the study is a count variable, it was assumed that it follows the Poisson distribution (12) .
The process of insertion and removal of the variables in the regression model was carried out in two stages.First, all the independent variables were inserted and a first selection was made by the process known as stepwise.The Wald test was used as a selection criterion, with those variables that presented p values less than 0.05 remaining in the model.
Then, the following variables were added to the model of the first phase: Family income and etiology of the child's health condition, for the purposes of control.The final model, thus, comprised the variables that had p values less than 0.05 for the Wald test, and the control variables.For the variables of the final model chosen, the average mean increase in the number of involuntary admissions was calculated.
The study was carried out in accordance with Brazilian and internal rules of ethics in surveys involving human beings, and was approved by the Research Ethics Committee (Protocol 405/2010).

RESULTS
102 technology-dependent children took part in the study, aged between six months and 12 years, of whom 57% were male.
The characterization of the participants is presented in Table 1 (by category of variables) and Table 2 (by numerical variables).The average family income was R$ 1,700.00.Congenital conditions, such as craniofacial deformities, cardiopathies and genetic syndromes were found to be the principal causes of the need for use of technology, with a combination of more than one cause being frequent.The technological devices for feeding, such as nasal-gastric tubes and gastrostomies, were the technologies most frequently used, with the use of only one device being most common.On average, the children used approximately two medications, and the majority made continuous use of medication.Use of development activities such as physiotherapy and speech therapy were common among the participants, but the greater part of the children did not receive home care given by health professionals.
The average number of involuntary hospital admissions in the prior year, among the children studied, was 0.71 (±1.29); 67 children (65.7%) were not admitted due to involuntary causes, 19 (18.6%) were admitted once, and 16 (15.7%)had between two and six involuntary admissions in the prior year.
Table 1 also shows the averages of involuntary hospital admissions among the children participating in the study, by exploratory category variables.The average of involuntary admissions was greatest among children who used some technological device for feeding (0.89 vs. 0.29, p=0.028) or who carried out some development activity (0.81 vs. 0.47, p=0.029).In relation to the use of devices for other purposes, such as ventriculoperitoneal derivation, the average of involuntary admissions was greater among those who did not have them (0.77 vs. 0.00, p=0.039).The results of the regression analysis are given in Table 4.Only the following variables were significant in the final model: age, number of medications and number of devices used.These variables did not lose statistical significance even after the addition to the model of the variables family income and etiology of the child's health condition.It is emphasized that the effect of each variable was adjusted for the effect of all the others of the final model, including family income and etiology of the child's health condition, which were not significant, but remained in the model for the purposes of adjustment.
Age and number of devices had negative association with average number of admissions, while quantity of drugs had positive association.For each additional month of age, the figures indicated a relative reduction of 0.9% (OR=0.991) in average number of admissions; while for each drug that the child used the number of admissions increased by a relative average of 53.2% (OR=1.532).Finally, for number of devices, for each additional device used by the child, there was a relative reduction of 61.3% (OR=0.387) in the average number of admissions.

DISCUSSION
Based on the results we find that age and number of devices are characterized as protection factors, and quantity of drugs as a risk factor, for involuntary hospital admissions in technology-dependent children.From the figures, these factors appear to exercise their influence on the number of admissions even in the context of different economic conditions, and the different causes of the situation of dependence on technology, which confirms the strength of the association of these three factors (age, number of devices and quantity of drugs) with the event of interest.
A US study (14) , which aimed to identify the factors associated with hospital re-admission in the first 30 days after children had been discharged from treatment for pneumonia, presented results that corroborated the findings of this study.Children under one year old were more subject to hospital re-admissions than those in the one to four age group, reaffirming the protection factor role of increased age.The authors also pointed out that children with chronic conditions had a higher index of re-admissions compared to children who did not have chronic conditions.On this point, 20.4% of the children participating in the study, considered to have chronic conditions and dependent on some technological device, needed hospital admission within 30 days after being discharged from hospital treatment for pneumonia.
A survey to study the health conditions and use of hospital resources by children submitted to tracheotomy found that 11% of these children needed four or more admissions in the six months following the procedure.The importance of considering the child's clinical condition was emphasized, since normally children who require tracheotomy have other co-morbidities that justify the need for frequent hospital admissions, such as neurological damage or chronic lung disease.In this context, the rate of hospital re-admission increases as the degree of the child's other adverse clinical conditions increases (15) .
In counterpart, this present study found that the majority of technology-dependent children had not been to hospital for involuntary reasons in the prior twelve months.It also showed the important contribution of the use of the devices as a way of avoiding such hospital admissions: the scale of the effect was a reduction of more than 60% in the average number of admissions for each device used.This result is compatible with the professional experience of the investigators, since, in clinical practice, they observe that, in the majority of cases, episodes of frequent admissions diminish after procedures such as tracheostomy and gastrostomy, since they contribute to the clinical improvement of the child.
In this direction, a study that analyzed the occurrence of respiratory diseases before and after insertion of the gastrostomy in children with cerebral palsy corroborates with the results presented here: it identified that the use of gastrostomy makes gain in weight possible, improves the quality of life of children and family members, and significantly reduces the number of admissions for respiratory infection (16) .Clinical improvement of the child after installation of a technological device depends, however, on home care offered by the family members.According to the US literature, the period of adaptation of the parents to the therapeutic regime after the transition of a child submitted to a tracheostomy can be a factor that influences the number of re-admissions.To the extent that the family members gain experience of daily care of the child and develop the necessary skills for the care of this device, re-admissions can become less frequent (11) .The variable number of drugs used by the children of the present study represented a risk for the outcome.In the population of this study, use of drugs, although it also aims to improve clinical condition, in fact was associated with increase in the number of involuntary hospital admissions.This is in line with the result of a study in the United States which aimed to characterize healthcare actions in relation to adverse events due to use of drugs in children with complex chronic conditions, determine which drugs were associated with adverse events, and identify whether the adverse events resulted in a higher probability of hospitalization for children with complex chronic conditions than for those without complex chronic conditions.The study concluded that children with complex chronic conditions presented a greater risk than other children of needing medical care and hospitalization due to the adverse events of the drugs used.Among the drugs with the highest levels of adverse events were the psychotropics, the antimicrobials, the anticonvulsants, hormones/steroids and analgesics.Finally, the authors stated that little is known about the negative consequences of the use of these drugs in this client group, and that further studies are needed to understand the mechanisms that cause the increase in the risk of adverse events in the children with complex chronic conditions (17) .
Another point of view dealt with in the international literature refers to errors in the administration of the drugs in the context of a complex therapy regimen.On this point, one study sought to describe the frequency of errors in administration of anticonvulsants among children with epilepsy admitted to hospital for reasons not related to convulsions, and described the factors associated with the occurrence of errors.The results show that 24% of the participating children had experience with errors of administration of anticonvulsants, the most common error being non-administration of the drug due to forgetting, and errors related to the dosage.Frequency of administration of anticonvulsants, and change in the carer responsible, were the factors most strongly associated with the chance of errors (18) .

CONCLUSION
The results presented provide input information for planning of care for technology-dependent children, by identifying the factors associated with involuntary hospital admissions in this client group.Having knowledge of the risk and protection factors that are associated with hospital admissions, it is possible to propose new preventive strategies that will certainly provide a reduction in the number of admissions, and a consequent reduction in clinical deterioration and family misadjustments.
Starting from the point of view that the nursing team has a fundamental role in the handling of the therapeutic regime of these children, it is recommended that there should be effective participation in the process of transition to home and subsequent accompaniment, with priority attention for children of younger age undergoing a complex therapy regimen, especially in the use of drug therapy.Although the number of technological devices has been considered as a protection factor, implementation of education actions relating to the specific handling and care of each device also becomes necessary.
Although the results of this study find support in the literature and in the clinical experience of the investigators, it is relevant to point out some limitations.The main one relates to its being a cross-sectional study, which prevents it being possible to identify relations of cause and effect.Thus, although the effect of risk and protection is assumed, based on the associations observed, it is not possible to establish a causal relationship between the factors analyzed and involuntary hospital admissions.Also, the data were collected based on self-report by the mother or guardian, remembering the past, making the results subject to reverse causality bias and memory bias.These limitations, however, do not invalidate the results of the survey, but indicate the need for future studies, with a longitudinal structure and greater accuracy of the information collected.

Table 1 -
Characterization of technology-dependent children by category variables -Ribeirão Preto, SP, Brazil, 2011.The correlation matrix involving the numerical variables and the outcome is given in Table3.The quantity of drugs showed a weak positive correlation with the number of involuntary hospital admissions (0.30, p<0.01) and with the number of devices (0.38, p<0.01).
continued... www.ee.usp.br/reeuspFactors associated with involuntary hospital admissions in technology-dependent children * Kruskal Wallis test.† Mann-Whitney test.‡ Children institutionalized -not taken into account for carrying out of the tests.
www.ee.usp.br/reeuspFactors associated with involuntary hospital admissions in technology-dependent children