Intensity Of Nursing Care Research Articles

Comparison of the treatment duration and nursing requirements of the EarWell infant ear correction system for different types of auricle deformities

Abstract Objective To observe whether the EarWell infant ear correction system makes any difference in terms of the treatment effect, duration, complication rate, and nursing care requirements in different types of infant auricle deformities. Methods A total of 93 infant patients with auricular deformity (age: <3 months of age) who were diagnosed and treated in Guangzhou Children and Women’s Medical Center from April 2018 to September 2020 were selected and treated with the EarWell infant ear correction system. We observed and recorded the effects of the EarWell infant ear correction system, the treatment duration, the number of rebound cases, and complications that are likely to occur during treatment, and noted the related factors causing complications and the relative requirements for nursing care. Results The Earwell infant ear correction system could effectively correct infant auricle deformities. Among the 93 cases, 90 cases had positive therapeutical outcome and the effective rate was 96.77%. The treatment duration for lop ear and protruding ear was longer than for other auricle deformities; the deformity recoil and the treatment compilation rates were much higher for these 2 deformity types, and the difference was statistically significant (P < 0.05). Conclusions The treatment suggestion for the wearing duration of the EarWell infant ear correction system for lop ear and protruding ear is a prolonged duration compared with that for other infant auricle deformities. Further, the requirements for nursing care intensity and infant patient’s guardian’s nursing knowledge and skill are obviously increased for these 2 types of auricle deformities.

Intention to use nursing care intensity as a management tool

Intention to use nursing care intensity as a management tool

Utilization of nursing care intensity in interprofessional collaboration: a literature review

Utilization of nursing care intensity in interprofessional collaboration: a literature review

How the reliability and validity of the patient classification system can be ensured in daily nursing work? A follow-up study.

This study aimed to determine the reliability and validity of the RAFAELA patient classification system (PCS) for qualified and efficient nurses. The number of patients per nurse or diagnosis-based determination of nursing workload are imprecise measures that do not consider the variation in patients' care needs. Ensuring the reliability and validity of the RAFAELA is important for the efficient allocation of nursing resources. In this study, we investigated how the maintenance (parallel classification measurement and professional assessment of optimal nursing care intensity level measurement) of the RAFAELA was done with 9 years of follow-up data. The results were analysed using quantitative methods supplemented with qualitative audit descriptions. The STROBE checklist was used. The RAFAELA was used continuously in 44 units (40%). The length of use of the RAFAELA influenced the success of parallel classification measurements. Six per cent of units passed parallel classification measurement over 75% after 1-3 years' use, 42% after 4-6 years and 83% after 7-9 years. Among the units that used the RAFAELA PCS continuously, only four (9%) passed the professional assessment of optimal nursing care intensity level measurement. This study shows that ensuring the reliability and validity of the use of the RAFAELA is laborious, requires several years of use and continuous investments in nurses' skills and motivation. Qualified use of PCS is challenging, and organisations should invest to maintenance, training, support and user motivation. Each patient should be classified comprehensively, and nursing resources should be calculated correctly. In addition, utilisation of the nursing intensity level should be maximised. Kuopio University Hospital organisation permit number 73/2014. Information regarding individual patients or nurses was not available to the researchers. All materials are in the form of summary tables.

Impact of Isolation Time of COVID-19 Patients in Intensive Care Unit on Healthcare Workers Contamination and Nursing Care Intensity.

BackgroundThe optimal isolation time of COVID-19 patients in intensive care unit (ICU) is debated. We investigated the impact of two different COVID-19 patient isolation time strategies on healthcare workers (HCW) contamination, intensity of nursing care and potential associated adverse events.MethodsWe prospectively included all consecutive COVID-19 patients and HCW in our ICU in the first two pandemic waves (March to May 2020 and August to November 2020). Specific isolation measures for COVID-19 patients were released after two negative RT-PCR assays in the first wave and 14 days after the onset of symptoms in the second wave. Contamination of HCW was assessed at the end of each pandemic wave by combining both a RT-PCR assay and a serological test.ResultsOverall, 117 COVID-19 patients and 73 HCW were included. Despite an earlier release from isolation after ICU admission in the second than in the first wave [6 (4–8) vs. 15 (11–19) days, p < 0.01], the proportion of HCW with a positive serological test (16 vs. 17%, p = 0.94) or with a positive RT-PCR assay (3 vs. 5%, p = 0.58) was not different between the two waves. Although a lower nurse-to-bed ratio, the intensity of nursing care was higher in the second than in the first wave. A longer isolation time was associated with accidental extubation (OR = 1.18, 95%CI:1.07–1.35, p = 0.005) but neither with ventilator-associated pneumonia nor with dysglycemia.ConclusionA shorter isolation time of COVID-19 patients in ICU was not associated with higher HCW contamination, while a longer isolation time seemed to be associated with higher accidental extubation.

Predicting healthcare-associated infections, length of stay, and mortality with the nursing intensity of care index.

The objectives of this study were (1) to develop and validate a simulation model to estimate daily probabilities of healthcare-associated infections (HAIs), length of stay (LOS), and mortality using time varying patient- and unit-level factors including staffing adequacy and (2) to examine whether HAI incidence varies with staffing adequacy. The study was conducted at 2 tertiary- and quaternary-care hospitals, a pediatric acute care hospital, and a community hospital within a single New York City healthcare network. All patients discharged from 2012 through 2016 (N = 562,435). We developed a non-Markovian simulation to estimate daily conditional probabilities of bloodstream, urinary tract, surgical site, and Clostridioides difficile infection, pneumonia, length of stay, and mortality. Staffing adequacy was modeled based on total nurse staffing (care supply) and the Nursing Intensity of Care Index (care demand). We compared model performance with logistic regression, and we generated case studies to illustrate daily changes in infection risk. We also described infection incidence by unit-level staffing and patient care demand on the day of infection. Most model estimates fell within 95% confidence intervals of actual outcomes. The predictive power of the simulation model exceeded that of logistic regression (area under the curve [AUC], 0.852 and 0.816, respectively). HAI incidence was greatest when staffing was lowest and nursing care intensity was highest. This model has potential clinical utility for identifying modifiable conditions in real time, such as low staffing coupled with high care demand.

Risk and Preventability of Adverse Events at a Finnish Tertiary Hospital Using Modified Global Trigger Tool

Objective: To evaluate the risk and preventability of adverse events (AEs) at a 600-bed, tertiary teaching hospital in Kuopio, Finland. Material and methods: The review of patient records was organized using the Institute for Healthcare Improvement’s Global Trigger Tool which was modified so that patient's point of view was emphasized. A bi-monthly random sample of hospital charts was selected between October 2014 and April 2016. The association with AEs of factors such as patients' age, sex, emergency vs. elective admission, multimedication, nursing care intensity raw points and categorized reasons for arrival were studied. A binary logistic regression model was employed to evaluate the risk of AEs. Result: We found 140 AEs / 1000 patient days and 91 AEs / 100 admissions. Overall, 46 % of hospital admissions (n=305) had an AE. Nursing care intensity raw points influenced the incidence of AEs (OR 1.238, P<0.001), and multimedication (OR 2.897, P=0.001) and nursing care intensity (OR 1.158, P=0.008) predicted preventable AEs. The incidence of all and preventable AEs were significantly influenced by age group (≥65-year vs younger, OR 2.303, P Conclusion: Focusing on the patient's point of view, we found a high number of AEs in the study population. The risk for AE was influenced by age group ≥65 years and high nursing care intensity, especially in internal medicine/pulmonology and oncology. Efforts should be focused on these patients to improve patient safety.

A study on the actual state of utilization by national registered dietitians of information related to assessment items of nursing care intensity

A study on the actual state of utilization by national registered dietitians of information related to assessment items of nursing care intensity

Accounting for patient heterogeneity in nurse staffing using a queueing-theory approach

ABSTRACT Evidence from observational studies suggests that inadequate nurse staffing in hospitals and heavy nurse workload may compromise patient safety and quality of care. There are recommended minimum nurse-to-patient ratios for different types of inpatient care settings. However, nursing-care intensity may vary across different patients within an inpatient unit depending on the severity of their medical condition, potentially rendering fixed nurse-to-patient ratios ineffective. This study aims at developing nurse-staffing strategies that explicitly account for patient heterogeneity. Using queueing theory, we develop a stochastic framework to model direct nursing care provided in inpatient-care units. The stochastic model is then used to measure different performance metrics that evaluate the efficiency and timeliness of inpatient-care delivery. The trade-off between those performance metrics and the nursing staff level is quantified, which can assist clinicians with determining minimum nursing staff levels that ensure timely delivery of nursing care to a given patient mix.

Evidence-Based Review and Discussion Points

Evidence-Based Review and Discussion Points

Assessing Intensity of Nursing Care Needs Using Electronically Available Data.

Although previous research has confirmed that nurse staffing affects patient outcomes, some potentially important factors have not been accounted for in tools to assess relationships between staffing and outcomes. The aim of this project was to develop and test a Nursing Intensity of Care Index using electronically available data from 152 072 patient discharges from three hospitals. Initially, 1765 procedure codes were reviewed; 69 were confirmed as directly increasing nursing workload by at least 15 minutes per shift. Two research staff independently reviewed a random sample of 5 patient days to assess interrater reliability with complete scoring agreement. To assess face validity, eight nurse clinician experts reviewed factors included in the Nursing Intensity of Care Index to assess the accuracy of the nursing time estimates in the tool. To examine concurrent validity, Nursing Intensity of Care Index scores for a random sample of 28 patients from four clinical units were compared with assessments made by a unit-based clinical nurse (low/medium/high intensity) for the same patients on the same day with a Spearman correlation of 0.94. In preliminary testing, data for the Nursing Intensity of Care Index, which accurately reflect nursing care intensity, can be obtained electronically in real time. The next steps will be a discrete-event simulation model and large-scale field trials.

Nurse staffing issues are just the tip of the iceberg: a qualitative study about nurses' perceptions of nurse staffing.

To obtain in-depth insight into the perceptions of nurses in the Netherlands regarding current nurse staffing levels and use of nurse-to-patient-ratios (NPR) and patient classification systems (PCS). In response to rising health care demands due to ageing of the patient population and increasing complexity of healthcare, hospital boards have been implementing NPRs and PCSs. However, many nurses at the unit level believe that staffing levels have become critically low, endangering the quality and safety of their patient care. This descriptive phenomenological qualitative study was conducted in a 1000-bed Dutch university hospital among 24 wards of four specialties (surgery, internal medicine, neurology, gynaecology & obstetrics and paediatric care). Data were collected from September until December 2012. To collect data four focus groups (n=44 nurses) were organized. Additionally, a total of 27 interviews (20 head nurses, 4 nurse directors and 3 quality advisors) were conducted using purposive sampling. The focus groups and interviews were audiotaped, transcribed and subjected to thematic analysis. Nurse staffing issues appear to be merely the 'tip of the iceberg'. Below the surface three underlying main themes became clear - nursing behaviour, authority, and autonomy - which are linked by one overall theme: nurses' position. In general, nurses' behaviour, way of thinking, decision-making and communication of thoughts or information differs from other healthcare disciplines, e.g. physicians and quality advisors. This results in a perceived and actual lack of authority and autonomy. This in turn hinders them to plead for adequate nurse staffing in order to achieve the common goal of safe and high-quality patient care. Nurses desired a valid nursing care intensity system as an interdisciplinary and objective communication tool that makes nursing care visible and creates possibilities for better positioning of nurses in hospitals and further professionalization in terms of enhanced authority and autonomy. The perceived subservient position of nurses in the hospital appears to be the root cause of nurse staffing problems. It is yet unknown whether an objective PCS to measure nursing care intensity would help them communicate effectively and credibly, thereby improving their own position.

Pre-implementation studies of a workforce planning tool for nurse staffing and human resource management in university hospitals.

To investigate the reliability, validity and feasibility of the RAFAELA workforce planning system (including the Oulu patient classification system - OPCq), before deciding on implementation in Dutch hospitals. The complexity of care, budgetary restraints and demand for high-quality patient care have ignited the need for transparent hospital workforce planning. Nurses from 12 wards of two university hospitals were trained to test the reliability of the OPCq by investigating the absolute agreement of nursing care intensity (NCI) measurements among nurses. Validity was tested by assessing whether optimal NCI/nurse ratio, as calculated by a regression analysis in RAFAELA, was realistic. System feasibility was investigated through a questionnaire among all nurses involved. Almost 67000 NCI measurements were performed between December 2013 and June 2014. Agreement using the OPCq varied between 38% and 91%. For only 1 in 12 wards was the optimal NCI area calculated judged as valid. Although the majority of respondents was positive about the applicability and user-friendliness, RAFAELA was not accepted as useful workforce planning system. Nurses' performance using the RAFAELA system did not warrant its implementation. Hospital managers should first focus on enlarging the readiness of nurses regarding the implementation of a workforce planning system.

The RAFAELA system: a workforce planning tool for nurse staffing and human resource management.

The RAFAELA system was developed in Finland during the 1990s to help with the systematic and daily measurement of nursing intensity (NI) and allocation of nursing staff. The system has now been rolled out across almost all hospitals in Finland, and implementation has started elsewhere in Europe and Asia. This article describes the system, which aims to uphold staffing levels in accordance with patients' care needs, and its structure, which consists of three parts: the Oulu Patient Classification instrument; registration of available nursing resources; and the Professional Assessment of Optimal Nursing Care Intensity Level method, as an alternative to classical time studies. The article also highlights the benefits of using a systematic measurement of NI.

Nurses' Experiences of Nonpatient Factors That Affect Nursing Workload: A Study of the PAONCIL Instrument's Nonpatient Factors.

In the RAFAELA patient classification system, the professional assessment of optimal nursing care intensity level (PAONCIL) instrument is used to assess the optimal nursing intensity level per unit. The PAONCIL instrument contains an overall assessment of the actual nursing intensity level and an additional list of central nonpatient factors that may increase or decrease the total nursing workload (NWL). The aim of this cross-sectional study was to assess and determine which nonpatient factors affect nurses' experiences of their total NWL in both outpatient settings and hospitals, as captured through the PAONCIL instrument. The data material consisted of PAONCIL questionnaires from 38 units and 37 outpatient clinics at 11 strategically selected hospitals in Finland, and included nurses' answers (n = 1307) to the question of which factors, other than nursing intensity, affect total NWL. The methods for data analyses were qualitative content analyses. The nonpatient factors that affected nurses' experiences of total NWL are “organization of work,” “working conditions,” “self-control,” and “cooperation.” The actual list of nonpatient factors in the PAONCIL instrument is to a reasonable extent relevant, but the list should be improved to include nurses' actual working conditions and self-control.

Development of Patient Classification System based on Nursing Intensity in Stroke Unit

Purpose: The purpose of this study was to develop a patient classification system based on nursing care intensity for patients with acute stroke-related symptoms and verify its validity and reliability. Methods: Data were collected between November, 2013 and February, 2014. The verification for content validity of the patient classification system was conducted by a group of seven professionals. Both interrater reliability and concurrent validity were verified at stroke units in tertiary hospitals. Results: The intensive nursing care for acute stroke patients consisted of 14 classified domains and 56 classified contents by adding ‘neurological assessment and observation’ and ‘respiratory care’: ‘hygiene’, ‘nutrition’, ‘elimination’, ‘mobility and exercise’, ‘education or counselling’, ‘emotional support’, ‘communication’, ‘treatment and examination’, ‘medication’, ‘assessment and observation’, ‘neurological assessment and observation’, ‘respiratory care’, ‘coordination between departments’, and ‘discharge or transfer care’. Each domain was classified into four levels such as Class I, Class II, Class III, and ClassⅣ. Conclusion: The results show that this patient classification system has satisfactory validity for content and concurrent and verified reliability and can be used to accurately estimate the demand for nursing care for patients in stroke units.

Testing Reliability and Validity of the Oulu Patient Classification Instrument—The First Step in Evaluating the RAFAELA System in Norway

Objective: To study reliability and validity of the Finnish Oulu Patient Classification instrument in Norway. Background: The Finnish patient classification system RAFAELA consists of three parts: 1) daily patient classification of nursing intensity using the Oulu Patient Classification instrument, 2) calculation of nursing resources providing bed side care per 24 hours, and 3) Professional Assessment of Optimal Nursing Care Intensity Level. The RAFAELA system has not been tested outside of Finland. Methods: A prospective, descriptive study was performed at 5 clinical units at Oslo University Hospital during 2011-2012. The interrater reliability of the Oulu Patient Classification instrument was tested by parallel classification including 100-167 patient classifications pr. unit, and analyzed by consensus in % and using Cohen’s Kappa. Convergent validity was tested by using the average Oulu Patient Classification instrument value to predict the average Professional Assessment of Optimal Nursing Care Intensity Level for the same calendar day by linear regression analysis. Results: The Oulu Patient Classification instrument consensus of parallel classifications varied between 70.1%-89%. Cohen’s Kappa within patient classes varied between 0.57 and 0.81, representing substantial interrater reliability. The Oulu Patient Classification instrument was valid as the instrument in average explained about 38% of the variation of the Professional Assessment of Optimal Nursing Care Intensity Level. Conclusions: Patient classification systems tested for psychometric properties are needed and this study provides evidence of satisfactory reliability and validity of the Oulu Patient Classification instrument as tested outside Finland, demonstrating that this instrument has international relevance within nursing.

Validation of the core elements of perioperative nursing

To define the core elements of perioperative nursing. To measure the nursing care intensity in operating departments and day surgery units, a consensus on the content of perioperative nursing is required. The core elements of perioperative nursing were initially defined based on literature and the clinical expertise of the national workgroup. Suggested core elements were verified in this study. Because healthcare systems constantly suffer from limited resources, while patients are legitimated and ethically justified good nursing care, it is essential to produce reliable information for resource allocation. Descriptive survey using Delphi technique. The purposeful sample of 55 experts was invited to participate in the Delphi panel to evaluate the suggested core elements of perioperative nursing. Two nationwide Delphi rounds were conducted. The response rates were 89% and 49%, respectively. Content Validity Index was calculated for each component. The Delphi panel accepted the suggested core elements that were seen describing the core of perioperative nursing. The initially defined core elements of perioperative nursing were verified in this study, with the core elements describing patient's safety as crucial in perioperative nursing. Those concerning patients' needs of information, communication with significant others, patients' coping mechanisms and mental well-being or administrating basic care - for example hygiene - were not seen to be as fundamental as those describing physiological needs. The results of this study can be used as an initial step when constructing an instrument for measuring the nursing care intensity in perioperative settings. In the future, the instrument may provide objective evidence of nursing care intensity and thus facilitate resource allocation. A further significance of this study lies in its potential to make perioperative nursing visible, so the nursing outcomes may be evaluated and proved.

Benchmarking by the RAFAELA Patient Classification system - a descriptive study of optimal nursing intensity levels.

The overall aim of the RAFAELA system is that the personnel resources should be in balance with the patients' caring needs, i.e. when the nursing intensity per nurse is on the optimal level of the unit. The RAFAELA system consists of three parts: the OPCq (Oulu Patient Classification Qualisan) instrument for measuring the nursing intensity, registration of the daily nursing resources and the PAONCIL (Professional Assessment of Optimal Nursing Care Intensity Level) method. The aim of this paper is (1) to describe the structure of benchmarking with the RAFAELA system and (2) to present comparisons of optimal nursing intensity levels in Finnish hospitals by using data from RAFAELA benchmarking reports in 2001. Totally 86 wards from 14 different hospitals in Finland took part in the study, the optimal nursing intensity had been decided for 53 wards. Data was analyzed using descriptive statistics. The average workload was on adult wards 25.2 NCI points per nurse. The optimal NCI was exceeded during 48% of the days and under during 22% of the days. An imbalance between nursing intensity and personnel resources clearly affects the care quality and the results. Benchmarking with the RAFAELA system provides nurse managers with many opportunities in their decision processes in human resource management.

Managing the optimal workload by the PAONCIL method - a challenge for nursing leadership in care of older people

The aim of the study was to test the ability of the professional assessment of optimal nursing care intensity level (PAONCIL)-method to establish the optimal nursing intensity (NI) per care giver within the care of older people by testing whether the method's prerequisites for hospital settings can be fulfilled within the care of older people as well. The PAONCIL method is included in the RAFAELA system as a method for calculating personnel resources based on NI. The PAONCIL assessments were collected through questionnaires (n = 3512). The data was analysed by simple linear regression analysis. It can be stated that the prerequisites for the PAONCIL method were fulfilled and that the optimal NI-level could be determined on seven participating units. It can be stated that the RAFAELA system is a useful system for measuring NI within the care of older people, but additional research is needed, especially within the home care setting. Although an instrument never provides a complete overview of the patient's care needs and need satisfaction, it provides information about the daily situation as well as gives guidelines for long-term strategic planning.