Sizing in hospital nursing: implications of the 2017 regulatory update for 2024Abstract
Objective To size nursing teams in hospital inpatient units based on the Federal Nursing Council’s 2017 and 2024 proposals.
Methods This is a cross-sectional, retrospective and quantitative study. All patient classifications from 11 adult medical and/or surgical inpatient sectors of a large hospital in southern Brazil were extracted from a management database for the year 2023. The stages and descriptive statistical parameters of the class entity’s regulations proposed in 2017 (Resolution No. 543) and updated (Technical Opinion No. 01) in 2024 were respected.
Results 17.134 patient classifications were analyzed, with emphasis on the semi-intensive degree of dependency, except in two surgical units that concentrated intermediate care. In all units, the sizing carried out using the 2017 parameters was higher than the 2024 proposal. The smallest difference between the staffing levels projected by the proposals was one and the largest was 17 professionals. Units with lower occupancy rates had the biggest differences, as the current method doubled this factor.
Conclusion Nursing teams sized according to the current/vigilant rule by the regulatory body are discrepant and lower than the previous standard. Considering the occupancy rate factor repeatedly in the method is counterproductive for the category, signaling the need for a new review.
Keywords:
Personnel downsizing; Nursing staff, hospital; Workload; Nursing, team; Nursing administration
Resumo
Objetivo Dimensionar equipes de enfermagem em unidades de internação hospitalar com base nas propostas de 2017 e 2024 do Conselho Federal de Enfermagem.
Métodos Estudo transversal, retrospectivo e quantitativo. A totalidade de classificações de pacientes de 11 setores de internação em clínica médica e/ou cirúrgica para adultos de um hospital de grande porte do Sul do Brasil foi extraída de uma base de dados gerencial, referente ao ano de 2023. As etapas e parâmetros estatísticos descritivos da normativa da entidade de classe proposta em 2017 (Resolução nº 543) e atualizada (Parecer técnico nº 01) em 2024 foram respeitados.
Resultados 17.134 classificações de pacientes foram analisadas, com destaque para o grau de dependência semi-intensivo, exceto em duas unidades cirúrgicas que concentraram cuidados intermediários. Em todas as unidades, o dimensionamento realizado com os parâmetros de 2017 foi superior à proposta de 2024. A menor diferença entre os quadros de pessoal projetados pelas propostas foi de um e a maior de 17 profissionais dimensionados. Unidades com menores taxas de ocupação tiveram as maiores diferenças, pois o método atual duplicou este fator.
Conclusão Equipes de enfermagem dimensionadas à regra atual/vigente pelo órgão regulador são discrepantes e inferiores à norma anterior. Considerar o fator taxa de ocupação repetidamente no método é contraproducente para a categoria, sinalizando necessidade de nova revisão.
Descritores:
Dimensionamento de pessoal; Recursos humanos de enfermagem no hospital; Carga de trabalho; Equipe de enfermagem; Administração em enfermagem
Resumen
Objetivo Dimensionar los equipos de enfermería en unidades de internación hospitalaria con base en las propuestas de 2017 y de 2024 del Consejo Federal de Enfermería.
Métodos Estudio transversal, retrospectivo y cuantitativo. Se extrajo de una base de datos gerencial del año 2023 un total de clasificaciones de pacientes de 11 sectores de internación en clínica médica o quirúrgica para adultos de un hospital de gran tamaño del sur de Brasil. Fueron respetadas las etapas y los parámetros estadísticos descriptivos de la normativa de la entidad de clase propuesta en 2017 (Resolución n° 543) y actualizada en 2024 (Informe Técnico n° 01).
Resultados Se analizaron 17.134 clasificaciones de pacientes, con énfasis en el nivel de dependencia semi-intensivo, excepto en dos unidades quirúrgicas que concentraron cuidados intermedios. En todas las unidades, la dotación realizada con los parámetros de 2017 fue superior a la propuesta de 2024. La menor diferencia entre las plantillas de personal proyectadas por las propuestas fue de un profesional y la mayor diferencia de 17 profesionales asignados. Las unidades con menores índices de ocupación tuvieron las mayores diferencias, ya que el método actual duplicó este factor.
Conclusión Los equipos de profesionales de enfermería dotados según la normativa actual/en curso del ente regulador son discrepantes e inferiores a la norma anterior. Considerar el factor del índice de ocupación repetidamente en el método es contraproducente para la categoría, lo que indica la necesidad de una nueva revisión.
Descriptores:
Reducción de personal; Personal de enfermería en hospital; Carga de Trabajo; Grupo de enfermería; Administración de Enfermería
Introduction
Although the search for the right composition of nursing teams has been a long-standing concern, the methods for achieving this still require greater instrumentation(1) This is due to the multiple variables involved in the numerical definition, the balance of professional experience among team members and the level of training of workers, which also has repercussions on the multiplicity of methods available for estimating nursing staff numbers.(2)
In professional practice and scientific dissemination, the knowledge that the composition of nursing teams has a direct impact on the quality of care is increasingly unquestionable.(3,4) However, this does not mean that the means of predicting the composition of these teams are unanimous.(2,4)
The planning of teams in terms of numbers and professional qualifications can be understood as nursing staff sizing (NSS). In work dynamics, NSS is not always a systematized process, since managerial intuition is sometimes decisive in estimating the nursing workforce.(5) This intuitive thinking does not guarantee assertiveness in forecasting nursing staff, but it should be taken into account, since nurses’ knowledge of the reality of care work adds reasonableness to the allocation of human resources.(6)
Different methodological approaches to carrying out NSS in the same context can produce different results.(7) Findings of this nature support the position that regulatory bodies in the nursing profession, and even governmental bodies, should invest in determining sensitive NSS methods that are compatible with contemporary professional practice environments.(2,8)
In Brazil, the Federal Nursing Council (COFEN) has promulgated resolutions that set standards for NSS for decades, which attests to the entity’s commitment to the matter. This is corroborated by researchers who alluded to the updating of the NSS parameters from 2004 to 2017 as an important step forward for Brazilian nursing.(9)
Recently, COFEN Resolution No. 743/2024(10) revoked COFEN Resolution 543/2017,(11) which was the standard in force for planning the nursing workforce until then. The new resolution replaces the previous one and, instead of establishing parameters, recommends them through a technical opinion. Thus, on March 15, 2024, Normative Opinion No. 1/2024 was published by COFEN, which provides guidance on the new parameters and methods for NSS.(12)
Although most of the previous parameters have been preserved and even improved in the aforementioned revocation and update, one significant change for hospitalization units caught the attention of the researchers. This is the inclusion of the occupancy rate of the units in the estimation of nursing hours, in addition to the sum of the patients classified by stratum of a given Patient Classification System (PCS). Taking the occupancy factor into account was a practice in 2004,(13) and, more than a decade later, it fell into disuse in 2017.(11) In 2024, in Annex II of the technical opinion describing the methodological procedures of the NSS, the occupancy factor is once again referenced.(12)
Although updates are compatible with the advancement of knowledge, we believe that resuming the aforementioned practice in the NSS equation could be counterproductive to the profession, as it tends to undersize teams. In view of this, the justification for this study lies in the problematization of a standard with an obvious influence on the distribution of the workforce on the national scene, leading us to the problem: does the revocation of the 2017 NSS parameters and COFEN’s new 2024 proposal influence the estimation of hospital nursing staff? To answer this question, the aim of this study was to size nursing teams in hospital inpatient units based on COFEN’s 2017 and 2024 proposals.
Methods
This is a retrospective, descriptive, documentary study with a quantitative approach. It was carried out in 11 inpatient units for adult patients at a large public university hospital located in southern Brazil. Of the units, six were for surgical patients, while five were clinical units.
The hospital caters mainly for patients linked to the Unified Health System (SUS), but also provides supplementary health care. In this case, only three units served health insurance plans. The total operational capacity of the 11 units was 396 beds. In this study, the units were identified by clinical or surgical service followed by a letter.
The clinical units have the following profile: “Clinic A”: 32 beds for health insurance and private individuals. It treats clinical and surgical patients in general and has an iodine therapy bed; “Clinic B”: 45 SUS beds and focuses on clinical oncology care; “Clinic C”: 34 SUS beds and is an institutional reference in the care of patients with multidrug-resistant germs; “Clinic D”: 45 SUS clinical beds, including cardiology and cardiac telemetry beds. It also includes the special care sector for pulmonology and stroke care. Finally, the “Clinic E” unit also has 45 exclusive SUS beds and, in addition to clinical beds, is an institutional reference in geriatrics.
The surgical inpatient sectors assist with pre- and post-operative patients for a wide range of procedures, including general, digestive system, cardiovascular, peripheral vascular, thoracic, plastic, traumatology, coloproctology, neurology, urology, gynecology, otorhinolaryngology, mastology and ophthalmology. Surgical units “A” and “B” have 17 and 20 supplementary health beds respectively. They treat general clinical and surgical patients. The “Surgical C” unit has 34 SUS beds for surgical patients, with a focus on general surgical care. The sector now called “Surgical D” also has 34 SUS beds and stands out for being a reference in the care of patients undergoing solid organ transplants, as well as serving patients in the Transdisciplinary Gender Identity Program and those undergoing bariatric surgery. The “Surgical E” unit has 45 SUS beds and focuses on orthopedic-trauma care. Finally, the “Surgical F” unit, with 45 SUS beds, treats general surgery patients, as well as heart surgery and other major procedures.
A census was taken of all patient classifications recorded during the selected period. The eligibility criterion was the presence of records in the hospital’s electronic system. Therefore, indirect participants were patients admitted to the units during the established time frame whose levels of dependence on nursing care had been assessed. No personal information was collected beyond the level of dependence on nursing care.
Two variables were extracted in the study: the level of care complexity, measured by the Patient Classification System (PCS), and the occupancy rate of the units. The other measures were consequential and are described below.
Patient classifications are carried out by nurses in each hospitalization unit. It is understood that there may be discrepancies in individual nurses’ perceptions/interpretations of the classification criteria, as well as differences in levels of experience with this assessment. However, it should be noted that all the institution’s nurses are properly trained to apply the PCS, and that there is a standard operating procedure (SOP) for this purpose.
Data was collected between July and August 2024, exclusively digitally, through a report generated by the institutional system Business Analytics Strategic Intelligence (Base)®. This software combines information to support decision-making, as well as contributing to research, reports and statistical analysis. The data in Base® is fed in by the professionals who work directly in care, i.e. it is data migrated from the electronic medical record. After that, managers can access dashboards that show information in real time, as is the case with inpatient classification data. The entire patient classification for each of the inpatient units was extracted from Base® for the period January to December 2023. The same software also provided information on the annual occupancy rate of the units for 2023.
Based on previous research carried out at the hospital itself,(14) patient classification is carried out by the unit nurses and, according to institutional routine, takes place in the last week of each month, from Monday to Friday. The study period therefore included 60 days of classification in each of the 11 sectors.
The institution uses Perroca’s validated PCS,(15) one of the instruments endorsed by COFEN(11,13) for classifying hospitalized adults. This PCS covers nine areas/indicators of nursing care: Planning and coordination of the care process; Investigation and monitoring; Body care and eliminations; Skin and mucous membrane care; Nutrition and hydration; Locomotion and activity; Therapy; Emotional support; and Health education.(15)
Each patient must be classified in all the indicators, choosing one of the four levels/points that describe their needs in relation to nursing care. The degree of complexity of the care is defined by the sum of the points from all the indicators and is stratified into: minimal care (PMC) 9 to 12 points; intermediate care (PIC) 13 to 18 points; semi-intensive care (PSIC) 19 to 24 points; and intensive care (PIntC) 25 to 36 points.(15)
All of the study’s analysis was based on the methodological recommendations and parameters governing NSS in Brazil. The methodological path of these analysis procedures is detailed in chart 1.
The project that led to this study was approved by the Research Ethics Committee, under opinion no. 6.794.451/2024. As the research did not involve the direct participation of human beings, nor the disclosure of any sensitive data, the requirement for an Informed Consent Form was waived (Certificate of Submission for Ethical Appraisal: 79035824.9.0000.5327).
Results
A total of 17,134 patient classifications were analyzed. In all clinical inpatient units, the demand for semi-intensive care prevailed. In two surgical units, dependence on intermediate care was higher (Table 1).
Level of dependence on nursing care according to the strata of the Patient Classification System, by clinical or surgical hospitalization unit
The units for supplementary healthcare had lower occupancy than those for SUS services. Considering the occupancy factor and the average daily number of patients according to the PCS strata, Table 2 shows the nursing hours required in each unit, segregated by the 2017 and 2024 parameters. In all units, the lower demand for nursing hours projected according to the 2024 parameters compared to the previous ones is evident, to a greater or lesser extent.
In view of the Total Nursing Hours, the staff sizing for each sector is shown in table 3, following the comparative demonstration between the 2017 and 2024 parameters. In all the inpatient units, the sizing carried out using the 2017 parameters was higher than the 2024 proposal. When comparing the proposals, the smallest difference between the projected staff was one (Clinical Unit B) and the largest was 17 professionals (Clinical Unit A).
Discussion
The provision of nursing human resources is a relevant and challenging issue for managers, given its direct relationship with the quality and safety of care, team workload, patient experience during the therapeutic journey, job satisfaction, among others. This is borne out by studies of various nationalities which allude to the fact that ensuring adequate staffing to meet the demands of care is essential for the efficiency of services and the achievement of positive results, helping to minimize failures or undesirable events that place a burden on patients, professionals and institutions.(1,3,16)
This study revealed a concentration of semi-intensive dependency levels in most of the hospitalization units, which illustrates the care provided to clients with greater morbidity and a demand for advanced therapeutic and technological resources. According to a study that validated parameters for filling in Perroca’s PCS,(17) activities such as: the nurse’s involvement with multidisciplinary teams; transportation by the nursing team outside the hospitalization unit; telemetry monitoring; antimicrobial and/or chemotherapy therapies; and assistance with bedside examinations, are examples of care needs that require more nursing hours. These activities have a direct impact on the classification of patients into more complex levels of dependency, such as semi-intensive care, which was prevalent in this study.
Research carried out in Turkey has shown that the Perroca PCS is sensitive to discriminating between patients in terms of dependence on care,(18) Therefore, the standardization of its application should be considered, guaranteeing the assertiveness and consistency of the data. For this to happen, it is essential that the classification procedure is agreed between the nurses, with a clear understanding of all the instrument items, as well as the client’s needs and profile.(19)
When comparing the 2017 and 2024 parameters recommended by COFEN, discrepancies were observed both in the required nursing hours and in staff sizing. Thus, it can be inferred that the current recommendation,(12) when considering the occupancy rate in the calculation, tends to underestimate the number of nursing workers. This inference is confirmed by the discrepancy between the staff scaled to the rule of the two methodologies, which led to a difference of up to 17 professionals in the overall composition of one of the clinical units. Although the numerical difference is substantial and there is a clear trend towards smaller nursing teams in the 2024 methodology, studies using inferential statistical analysis are needed to confirm this trend.
Significant differences were found in the estimate of nursing staff between sites with the same number of beds and common care characteristics. The occupancy rate is an indicator that should be taken into account by leaders when planning and distributing staff. However, it is necessary to give some thought to its use, considering the dynamic nature of the indicator itself and the high variability of health work. Thus, it is crucial to consider the profile of labor demands, which includes factors such as the complexity of clinical conditions, the level of care required, as well as the specifics of the sector of work. Some of these aspects can be visualized using tools such as the PCS, which, when used systematically, help to measure workload, identify and prioritize needs, and identify and prioritize workload.(8,15,18)
We reiterate that the occupancy rate was a variable recommended by COFEN regulations in 2004,(13) but was discontinued in the subsequent 2017 resolution,(11) perhaps due to the fact that this factor is already deduced by the act of classifying the clientele. In contrast, in the current normative opinion of 2024, the occupancy rate factor is once again mentioned and recommended in the methodological procedures for sizing nursing teams in uninterrupted care units.(12) It is not up to this study to judge the reasons why this recommendation has been taken up again; however, in keeping with the social role of science, we make the constructive proposition that taking it up again is counterproductive, as well as being mathematically wrong: it is a question of considering a proportion of a proportion.
This is supported by the results of this study, as there was a clear discrepancy in the calculation of nursing hours when the occupancy rate factor was used to measure hours, especially in units with lower occupancy rates, a group made up mostly of surgical units. In practical terms, this was because the occupancy of these units, which had already been indirectly taken into account by adding up the average number of patients classified by each level of the PCS, was put back into effect, in other words, doubled.
In other words, when we apply the PCS tool, it already predicts the number of nursing and professional hours needed based on the occupancy rate of each area. When the same tool is used, but the average occupancy rate is taken into account, this procedure involves proportionally reconsidering the results of the initial classification, which explains the discrepancies found.
When applying the PCS to forecast the number of nursing hours and the number of professionals, it is understood that the calculation already takes into account the occupancy rate of each area. This is because the PCS aims to assess all patients who have been hospitalized for at least 24 hours,(8,15) which tends to approximate the actual occupancy of the sectors. We speak of approximation because of the authors’ empirical knowledge of possible losses in patient classification, such as: users who are discharged from hospital before being classified by the nurse; patients temporarily allocated to diagnostic-therapeutic support units (operating room, hemodialysis, hemodynamics, among others) within the shift planned for their classification, followed by non-information for the subsequent shift; as well as failures related to the patient’s computerized medical record.
The resumption of the recommendation of the occupancy rate factor can be attributed to different reasons. There may be a lack of knowledge and/or familiarity with the procedures in the current regulations. Professionals and managers may not be fully aware of the implications of the occupancy rate factor, especially given the changes in recommendations over time. It is necessary to consider that the reintroduction of the occupancy rate factor in the 2024 regulations may reflect an attempt to adjust the number of staff to the economic reality (or interests) of healthcare institutions. In other words, the inclusion of this factor may be aimed at reducing institutions’ budgets for human resources.
Regarding the projection of nurses, the most recent standard (2024) considers the established minimum number of one nurse per shift, so there is no requirement for professionals to guarantee coverage for absences.(12) In other words, it is possible to deduce that, in practice, stipulating a minimum of one nurse per shift goes back to what the TSI presupposes, which is to consider a number of professionals in the staff estimate capable of covering absences, which are inevitable in nursing work.
In the 2017 resolution, it was established that, for minimum and intermediate care, teams should be made up of 33% nurses - with at least six professionals - and the rest of the team should be made up of technicians/nursing assistants.(11) The 2024 normative opinion, on the other hand, establishes that, for the same categories of care, there should be 33% nurses - with a minimum of one professional per shift - and the rest made up of technicians/assistants. In other words, it is possible to deduce that, in practice, stipulating a minimum of one nurse per shift goes back to what the TSI presupposes, which is to consider a number of professionals in the staff estimate capable of covering absences, which are inevitable in nursing work.(12) This change represents a significant reduction in the minimum requirements for the presence of nurses, since the new parameter does not provide for the technical safety index (TSI), i.e. a percentage to cover absences (vacations, time off, absenteeism), which is a recommendation of the regulatory body itself.(10-13) Therefore, in addition to being counterproductive, the repeal followed by the “update” seems contradictory.
A study carried out at a hospital in the Midwest showed that this number of professionals may not be taken into account in work schedules, as it represents workers who are absent for various reasons.(19) Thus, COFEN’s new recommendation represents a step backwards, given that absences by nurses will occur, as they are provided for by law, in the case of time off and vacations, and the high rates of absenteeism observed among nurses must also be taken into account.(20,21)
There is the natural limitation of the possible inconsistency of electronic records on which this study was based, as well as the absence of inferential statistical analysis. However, it is believed that the research is necessary to demonstrate that the updating of the regulations governing NSS, recommended by the profession’s regulatory body, requires careful review. This has a high potential for practical implications, because it concerns the composition of hospital nursing teams in Brazil.
Conclusion
There are discrepancies in the dimensioning of nursing staff in hospitalization units based on the methodological parameters of the professional association proposed in 2017 and updated in 2024. The current parameters underestimate staffing levels, as they replicate the occupancy rate factor already considered in the average number of classified patients. In practice, this means considering a proportion of a proportion. Units with lower occupancy rates and/or higher bed turnover, such as surgical sectors, tend to be more impacted by the new proposal. It is considered prudent to review the methodological proposal regarding the occupancy factor in defining the average number of inpatients and the consequent nursing hours required. Furthermore, recommending a minimum of “one nurse per shift” in certain cases seems to contradict the regulatory body’s own recommendations, as this would extinguish the coverage provided by the technical safety index.
Data availability
The authors did not make the data from this article available in repositories prior to submission.
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Edited by
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Associate Editor:
Alexandre Pazetto Balsanelli (https://orcid.org/0000-0003-3757-1061) Escola Paulista de Enfermagem, Universidade Federal de São Paulo, São Paulo, SP, Brazil
