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Print version ISSN 0103-2100
Acta paul. enferm. vol.25 no.3 São Paulo 2012
Nursing staff absences in the emergency room of a university hospital*
Flávio Trevisani FakihI; Luiza Hiromi TanakaII; Maria Isabel Sampaio CarmagnaniIII
IMaster of Science. Advisor to the Director of Nursing, São Paulo Hospital, Federal University of São Paulo - UNIFESP - São Paulo (SP), Brazil
IIDoctor of Nursing. Guest Professor, Federal University of São Paulo - UNIFESP - Assistential Coordinator of the Nursing Board of São Paulo Hospital - UNIFESP - São Paulo (SP), Brazil
IIIDoctor of Human Communication Disorders. Associate Professor of the Course in Public Health Nursing and Administration Applied to Nursing , of the school of nursing "Escola Paulista de Enfermagem", Federal University of São Paulo - UNIFESP - São Paulo (SP), Brazil. Director of Nursing of the São Paulo Hospital - São Paulo (SP), Brazil
OBJECTIVE: To verify and analyze absences of nursing staff of the adult emergency room (AER) of a university hospital.
METHODS: A study using a quantitative approach, observational and prospective, conducted between January and December, 2009, involving the nursing staff of a AER.
RESULTS: The AER had, on average, 96.8 employees per month. Expected absences corresponded to 30.1% of working days. The absenteeism rate was 11.7%. There was a greater incidence of unplanned absences during the periods of May (15.3%) and August (13.3%).
CONCLUSION: There was a correlation between the variables: professional category, employment contract and shift work, and the distribution of expected and unexpected absences. Absenteeism was considered high and motivated, mainly, by allowances for health care greater than 15 days. The monthly deficit of staff also contributed to the work overload of the team.
Keywords: Absenteeism; Nursing staff, hospital; Emergency nursing
Absenteeism from work has great economic impact, as it interferes with production, increases operational cost and reduces the efficiency of work, in addition to resulting in overload on workers who remain in the work environment and need to perform the absent workers' tasks. This overload may lead to the appearance of health problems and possible need to grant sick-leave(1).
Absenteeism refers to employees' absences at times during which they should be working normally(2). Foreseen absences comprise days off and vacations. Unpredicted absences are the sum of failure to turn up, sick leave for the purpose of health treatment, leave supported by law and other situations, such as dispensation to attend courses or congresses, or disciplinary suspension. These behave as random variables, and may occur on any day of the year(3).
Absenteeism may reflect both on workers' conditions of health and on those of life and work, which must be analyzed, and undergo interventions, so that absences may be prevented(4). In order to enable a health service to perform interventions in absenteeism, it is necessary to have knowledge of its quantitative dimension, and then identify its causes(5).
The causes of absenteeism may be related to the work itself, such as the lack of organization, deficient supervision, impoverishment of work tasks, lack of motivation, poor working conditions and inadequate organizational policy. Among other causes include proven illnesses, family reasons, involuntary late arrival and voluntary absences(2).
Nursing consists of the major portion of human resources in hospital establishments. It constitutes the group of workers that most suffer under poor working conditions in an insalubrious environment, as well as measures of cost containment that favor absenteeism(6).
The urgency and emergency sectors present situations that expose workers to suffering and work overload, among others(7). It is known that not only stress, but also factors of the work environment are responsible for the appearance of disease in these sectors(8).
Although it is not systematically controlled, absenteeism among nursing staff at the Adult Emergency Department of the São Paulo Hospital, university hospital of the Federal University of São Paulo, has been considered high by the nursing management of this service. Being off work due to illness, particularly absences of long duration, are presumably pointed out as being the main cause of absences and as a factor over overload of the work team.
In view of the foregoing discourse, the purpose was to conduct this study with the aim of verifying and analyzing predicted and unpredicted absences of the nursing staff at the mentioned first aid station, based on the following specific objectives: Verify the distribution of predicted and unpredicted absences, their associations with the professional category, the employment tie and work shift; verify the monthly distribution of unpredictable absences and the respective proportions of time lost, and verify the distribution of absence dueto leave in order to undergo health treatment, in accordance with the chapters of the International Statistical Classification of Diseases - 10th revision (ICD 10)(9) and period of the year.
This was a study with a quantitative, observational and prospective approach. The research was conducted at the Adult Emergency Department (AED) of a University Hospital (UH), located in the Municipality of São Paulo. The AED attends the spontaneous demand by adult patients for general clinical and surgical urgency and emergency, 24 hours a day, totaling a mean daily number of 1,200 patients.
The study population was composed of a monthly mean number of 96.8 nursing staff members, allocatedto the Hospital's AED, in the months from January to December, 2009.
The weekly work hours of nursing staff at UH, hired under Consolidation of Labor Laws (CLL))(10) regime, and statutes in accordance with the Single Juridical Regime (SJR)(11) are 36h a week. The daily hours of work vary according to the professional category, job performed, employment tie (SJR or CLL) and the work shift, so that there are the following possibilities: 6h, 6h15, 7h and 12x36h.
The distribution of nursing staff monthly days off from the AED is made according to an annual time schedule, in addition to one day off per month (or bimonthly, for nurses with 12 x 36h work hours). This concession was made by the institution as an incentiveto workers allotted to this sector. The dependent vari ables of the study were defined as follows: Predicted absences (paid time off for weekly rest, public holidays that do not coincide with Sundays and vacation) and unpredicted absences (not showing up; sick leave to undergo health treatment; legal time off and other leave), as characterized in the proposed method for sizing staffing requirements (3), also used by other authors(5,12-14) and in accordance with the corresponding legislation(11,15). Absences due to maternity leave were considered unpredictable (within the legal leaves of absence), because there is no replacement of staff in this case.
The independent variables of the study consisted of occupational characteristics such as: Professional categories (nurses and technicians/nursing assistants), employment ties (CLL and SJR) and morning, afternoon, night work shift 1 (NS1) and night work shift 2 (NS2).
Data were collected by means of documents, such as monthly time off scales, and medical certificates, and from secondary data in electronic timecard control spreadsheets and records of sick leave for health treatment.
For monthly record of nursing staff absences, an electronic spreadsheet was drawn up, using an adapted model(12) and Microsoft Excel software®. The time clock data from 1,162 clock cards punched by employees were transcribed onto electronic spreadsheets and checked against the monthly time off scales.
The distribution of predicted and unpredicted absences and their correlations with independent variables, the proportion of time lost (PTL), according to the unpredicted type of absence, and the monthly distribution of sick leave for health treatment (SLHT), according to the chapters of ICD 10(9) were verified.
The rate of PTL, considered the indicator of absenteeism in the present study, was calculated by means of the equation standardized by the Subcommittee on Absenteeism of the International Association of Industrial Medicine(16), in which:
For statistical analysis of the data collected, STATA SE 9.1 software (StataCorp, College Station, Texas, USA) was used.
The qualitative variables were described by means of frequencies (simple and relative) and means. Comparisons between the proportions of absences, according to the independent variables, were presented as relative risks (risk ratios) and the respective 95% intervals of confidence were calculated by Cornfield approximation. One considered p-Values < 0.05, calculated by the non parametric Chi-square test.
The research project was approved by the Research Ethics Committee of the Federal University of São Paulo (UNIFESP), Protocol CEP No. 0127/09.
In the year 2009, the staff of the AED was, on an average, composed of 96.8 nursing staff members, distributed as follows: 17.7% nurses, 82.3% nursingtechnicians and nursing assistants; 47.5% CLL-tie employees and 52.5% SJR-tie employees; 27.0% on morning shift, 24.3% on afternoon shift, 24.8% on night shift NS1 and 23.9% on night shift NS2.
Among the nursing staff of the AED, it was found that there was a monthly deficit of 12.0% in relation to the sized staff requirement, caused by delay in replacement or because of their non replacement. In the months of June and July the highest staff shortages occurred, being: 18.2% and 16.4% respectively.
The total number of days of time off (8,227) and vacation (2,390) found corresponded to 23.3% and 6.8% work days respectively. Thus the predicted absences compromised 30.1% of the work days. Each staff member had, on an average, 85 days off (1.6 days a week) weekly work hours of 32 hours and 13 minutes. The SJR-tie employees on the morning and afternoon shifts had one or two extra days off in comparison with the CLL-tie employees.
The distribution of predicted absences and their correlations with the independent variables are presented in the data in Table 1
It was verified that SJR-tie employees had a higher number of days off (mean of two days off per week). Nursing staff in night shifts NS1 and NS2 had 11.0% [RR = 0.89, IC 95% (0.85 to 0,94) and p <0.0001] fewer days off in comparison with the morning shift. On an average, each staff member had 24.7 days of vacation in the year, and each SJR-tie employee, 30.3 days and each CLL-tie employee 18.5 days. SJR-tie employees had 63.0% [RR = 1.63, IC 95% (1.50 to 1.77) and p <0.0001] therefore more days of vacation in comparison with the CLL-tie employees.
The distribution of unpredicted absences and their correlations with the independent variables are presented in the data in Table 2.
After excluding the predicted absence, each staff member, on an average, had 255 work days. The number of 2,898 unpredicted absences were verified, these being: 569 (19.6%) failure to turn up, 732 (25.3%) due to SLHT less than 15 days, 1,127 (38.8%) for SLHT longer than 15 days, 340 (11.7%) for maternity leave and 130 (4.5%) for other types of leave.
The monthly distribution of predicted absences of AED nursing staff and the respective proportions of time lost (PTL) are presented in the data in Table 3.
The 2,898 unpredicted absences found repre sented 11.7% of the scheduled work days. This rate signifies PTL due to unpredicted absences, or absenteeism of AED nursing staff due to unpredicted absences or absenteeism of the AED nursing staff, in the studied period.
The SLHT for longer than 15 days referred to only five staff members, for the following reasons: - mental and behavioral disorders - Chapter V, osteomuscular system disease - Chapter XIII and pregnancy - Chapter XV. Mental and behavioral disorders represented 78.9% of the days away from work.
The distribution of absences due to SLHT for periods shorter than 15 days, according to chapters of ICD 10, is shown in the data in Table 4.
The data in Figure 1 illustrate the monthly distribution of absences due to SLHT shorter than 15 days, according the most frequent chapters of the ICD 10.
With regard to predicted absences, a strong association was verified between the employment link and the mean number of days of vacation, and between the professional category and the distribution of days off.
The daily working hours of the SJR-tie employees (6h15 or 7h daily) determined a higher mean number of days off, in comparison with the CLL-tie employees (6h daily), on the morning and afternoon shifts. The lower number of days off of the employees of night shift NS1 and NS2 was due to their 12 hour working hours per shift, attributing to them a lower number of hours of time off in comparison with the other shifts.
The difference between the mean number of days of vacation of SJR-tie and CLL-tie employees was due to the peculiarities of the respective labor contracts, such as deductions for absences from their vacations and the right to monetary bonuses among CLL-tie employees, resulting in a reduction in the mean number of days of vacation in the year per employee.
The proportion of predicted absences (30.1%), in relation to scheduled work days was higher than that found in another study (23.3%)(17). This difference was attributed to days off, especially those granted to AED employees. On the other hand, the proportion of days of vacation was discretely lower in the present study, because of the reduced mean number of days of vacation of the CLL-tie employees.
The predicted absences, particularly days off, had great impact on the AED nursing staff. Although the concession of additional time off results in a reduction in the weekly hours worked, this is not considered in the AED staff sizing calculation, in which the standard work time of 36 hours per week is considered.
The accumulated time lost of over 1.2% was considered high, indicating that the work situation should be evaluated(16). Thus, the absenteeism rate (PTL) verified in this study (11.7%) was considered very high.
It was verified that the independent variables influenced the distribution of the unpredicted absences and respective PTL. These absences were significantly more numerous for the category of nursing technicians and assistants, for the SJR-tie and night shifts (NS1 and NS2).
The higher prevalences of unpredicted absences in the categories of middle level educational formation was also observed in another study(7), which explained that the more qualified groups, with higher education, are less exposed to poor working conditions, become ill less frequently, and thus are absent less frequently.
PTL verified due to failure to turn up (2.3%) was significantly higher to the value found in another study (0.5%)(17), which attributed its low incidence to professionals' commitment to their . An increase was observed in the occurrence of failure to turn up in the months between March and May, the period in which there was also an increase in the employees granted sick leave for SLHT. This may have generated work overload, andthus, encouraged absences in the corresponding period. Absences for health reasons were proportion ally the main causes of days lost due to unpredicted absences. The PTL verified for these reasons (7.6%), was 2.3 times higher than that found in a study conducted in a public hospital specialized in urgency and emergency (3.28%)(7).
Respiratory and osteomuscular system-related problems figure among the main causes of taking sick leave. In a large portion of urgency and emergency situations, professionals perform mobilization techniques on dependent patients, in addition, they are insufficient in number, and act in an area that is physically demanding(7). Incorrect body postures, excessive activity, spending a long time on their feet and the unsuitability of furniture are pointed out as factors for ergonomic risk, fatigue as well as being harmful to health(18). Therefore, in the AED, these factors can be related to the main cause of taking sick leave for SLHT shorter than 15 days.
Infirmities such as stress, depression anxiety have raised concern in authorities world-wide, and have been attributed to changes in organization of the work and productive processes (19). Adverse working conditions and variables that characterize the urgency and emergency sectors may also cause alterations in the workers' psychological balance(7).
Mental and behavioral disturbances were the cause ranked second for taking sick leave shorter than 15 days and the main cause of sick leave taken for periods longer than 15 days, corresponding to 78.9%, This situation reflects probably maladjustments of the workers to the organization and working conditions.
Corroborating the results of another study(7), respiratory system affections were the third most frequent cause of taking leave for SLHT for less than 15 days. The winter period is directly related to the increase in the incidence of diseases and infections that compromise the respiratory system. The months of June and August, 2009 were marked by the influenza A (H1N1) epidemic. Therefore, workers allotted to first aid stations were more exposed to this type of infection. The AED nursing staff with this infection confirmed or suspected, and pregnant women were given off work.
The fourth cause of absence for less than 15 days due to SLHT was found to be taking time off work dueto pregnancy, birth or puerperal problems. Maternity leave, counted as unpredicted absence, corresponded to 11.7% of unpredicted absences. The higher inci dence of this type of leave may be attributed to the fact that the female gender predominates in the Nursing profession(18).
High incidence was found of days lost for health reasons (14.1%), for which the certificates did not contain the ICD 10 code or diagnosis explained on the medical certificate. Although this is a legal right the patient has, this omission compromised the ability to find the reasons for the respective absences.
The peak occurrence of SLHT shorter than 15 days found in the month of March was mainly generated by leave granted due to mental and behavioral disturbances alone, and there were no justifications for associating these periods of leave granted and the period of the year in which they occurred. However, these periods of leave corresponded to periods which preceded or intermediated the periods of leave of long duration of these same employees, also for mental and behavioral disturbances.
Another peak occurrence of SLHT of less than 15 days occurred between the months of July and August due to osteomuscular and respiratory system diseases. The monthly variation in absences due to osteomuscular diseases was probably the overload of work generated by the other types of absences and by the high mean staff shortage observed.
The main causes of high rates of PTL due to un predicted absences found between the months of May and August were the absences due to respiratory system diseases in the months of June and July, and due to osteomuscular system diseases in the months of July and August. The monthly peaks of staff shortages found in the months of June and July probably contributedto the work overload on the nursing professionals, and thus, to the absences.
Although the PTL rates found were higher thanthose presented in other studies conducted in urgency and emergency services, it would still be necessary to verify other characteristics of these services, such as being generalist or specialized, referenced or whether they meet spontaneous demand and the number of personnel they have, in order to evaluate whether the employees were exposed to the same working conditions.
The high monthly staff shortages found in the AED probably contributed to generating overload on the work team. Staff replacement due to turnover is difficult to solve in public institutions, into which personnel entry occurs by means of sporadic public contests.
The scarcity of publications about absenteeism in nursing in the international literature limited compari son of the results of the present study to comparison with other Brazilian researches.
There would be significant reduction in the high rate of unpredicted absences found if the prolonged absences from work, such as maternity leave and SLHT longer than 15 days were covered by staff replacements.
Unless one considers the real values of the weekly work hours in the calculations for sizing staff requirements, instead of the contractual values (36h per week), the numbers of staff will not correspond to the demands of the services and will contribute to work overload.
The present study confirmed the correlation between the variables: Professional category, employment-tie and work shift, and the distribution of predicted and unpredicted absences and their respective PTL.
There was strong association between the employment link and the mean number of days of vacation, and between the professional category and the distribution of days off.
The granting of additional time off had great impact on the predicted absences of AED nursing, particularly because these are not considered in the calculations for sizing the staff requirements of this sector.
The unpredicted absences and their respective PTL were significantly more numerous for the category of nursing technicians and assistants, for the SJR-tie and night shifts (NS1 and NS2).
Absenteeism was considered high and motivated above all by SLHT longer than 15 days. The most frequent causes of SLHT shorter than 15 days were: Diseases of the osteomuscular system and conjunctive tissue; mental and behavioral disturbances, and respiratory system diseases. The highest rates of PTL due to unpredicted absences occurred in the period from May to August in the studied period.
The study also pointed out the high monthly nursing staff shortage of the AED, motivated by the delay in or non replacement of staff members, which also contributed to generating work overload on the nursing professionals.
Although this study has not exhausted the factorsthat competed for absenteeism, it pointed out important aspects that need to be analyzed with the executive body of UH, in order to promote effective changes in the policy of personnel management and work processes, as well as in promoting the health and safety of employees, increasing their work satisfaction and commitment to the institution.
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Corresponding Author: Received article 10/02/2011 and accepted 27/09/2011 * Article extracted from Master's thesis "Absences of nursing staff from first aid station of a university hospital and their impact on staff sizing.", presented to the Post-Graduation Program in Nursing of the Federal University of São Paulo - UNIFESP - São Paulo (SP), Brazil.
Flávio Trevisani Fakih
Rua Tenente Gomes Ribeiro, 58 - apto 133 - Vila Mariana
São Paulo (SP), Brasil CEP: 04038-040
Received article 10/02/2011 and accepted 27/09/2011
* Article extracted from Master's thesis "Absences of nursing staff from first aid station of a university hospital and their impact on staff sizing.", presented to the Post-Graduation Program in Nursing of the Federal University of São Paulo - UNIFESP - São Paulo (SP), Brazil.