The Zebra system–a new patient classification system

Journal of Nursing Management, 2002

Changes in patients' need of nursing care reflected in the Zebra system.

Journal of Advanced Nursing, 2000

Intensive and Critical Care Nursing, 2018

Intensive care units Nine equivalents of nursing manpower use score Nursing staff Nursing activities score NAS Workload NEMS a b s t r a c t Objectives: Nurse staffing costs represent approximately 60% of total intensive care unit costs. In order to analyse resource allocation in intensive care, we examined the association between nurse staffing costs and two patient classification systems: the nursing activities score (NAS) and nine equivalents of nursing manpower use score (NEMS). Research methodology/design: A retrospective descriptive correlational analysis of nurse staffing costs and data of 6390 patients extracted from a data warehouse. Setting: Three intensive care units in a university hospital and one in a regional hospital in Norway. Main outcome measures: Nurse staffing costs, NAS and NEMS. Results: For merged data from all units, the NAS was more strongly correlated with monthly nurse staffing costs than was the NEMS. On separate analyses of each ICU, correlations were present for the NAS on basic costs and external overtime costs but were not significant. The annual mean nurse staffing cost for 1% of NAS was 20.9-23.1 euros in the units, which was comparable to 53.3-81.5 euros for 1 NEMS point. Conclusion: A significant association was found between monthly costs, NAS, and NEMS. Cost of care should be based on individual patients' nursing care needs. The NAS makes nurses' workload visible and may be a helpful classification system in future planning and budgeting of intensive care resources.

Journal of Clinical Nursing, 2005

If resources are placed wrongly, the problems of daily staff management and cost control continue.

2011

Production control is an important issue for hospital management. Hospitals are faced with a growing demand for care and higher expectations for improved service delivery. For production control purposes information is required on different levels of aggregation: process resources and patient flows. Patient classification systems can be used to provide data on health care. The question is whether existing patient classification systems are suitable for production control purposes. In this paper we will elaborate on production control of hospitals and the suitability of existing patient classification systems.

Studies in health technology and informatics, 2006

Patient information systems have been available and implemented in many intensive care units for several years and still nursing research has little evidence from the use of the recorded data. One of the focus areas in Finnish nursing research is the use of information technology in evidence based nursing. The nursing intensity and patient classification assessments are important part of intensive care units data in Finnish patient information systems. Our main goal was to conduct a pilot study concerning nursing intensity and patient classification together with patient records to find out if this will provide more information on the nursing intensity.

International Journal of Technology Assessment in Health Care, 1996

A priority classification was evaluated according to a modified "Norwegian model." Many diseases do not belong to any specific priority category based only on the diagnosis. The classification also depends on the condition's type, site, and phase as well as the patient's age and overall condition. Savings cannot be achieved by the model used because 89% of the patients belonged to the priority categories l-lll, the care of which can be classified as necessary.

2017

A function of the TrendCare system: the direct care nurse reviews and updates the indicators. The 'hours predicted for nursing care' are then automatically adjusted to reflect actual nursing hours currently being worked. An update in the categorizing of patients also automatically follows. Actualization facilitates a variance measurement. This variance in the actual hours worked by the nurse that are above or below the hours predicted for nursing care and is recorded as 'Total Variance by hh: mm' in TrendCare reporting. The process of actualizing does not replace the predicted hours, they remain in the reporting formats as 'Hours required by hh: mm'. All discharges, deaths, transfers and admissions are accounted for in the actualization process. Acuity A term used in slightly different ways throughout the literature and used in this thesis to describe the relative requirements for nursing care for patients with a given medical condition or conditions. See also dependency. Acute care hospital A hospital which may provide medical, surgical, obstetric, nursing and other health care services to inpatients, most of whom have acute or temporary conditions and whose average stay is relatively short. (PSCU, 1997:14) xxii AN-DRG Australian National Diagnosis Related Group. Versions 1-3 of the Australian system were developed to classify Australian acute in-patients. AR-DRG AR-DRG-Australian Refined Diagnosis Related Group-Diagnoses classified according to relative values for distribution of costs for hospital budgets and coded alphanumerically. They include significant complication or co-morbidity severity measurements and are used for reporting casemix to Government Health Departments, Health Insurers and other funding bodies. AR-DRG Version 4.1 has been implemented in both the public and private acute hospital care sectors in Australia and New Zealand. The AR-DRG code is for an entire episode, after discharge and is unlikely to change. See Patient type. Known also as DRG in the literature and in TrendCare Reporting. Average skill mix The mix of staff by title, qualifications and grade or years of experience. The competency that comprises an overall clinical team, capable of managing a workload of 8 hours per full time equivalent across the shift. (TrendCare 2003). Benchmarks Benchmarks are used for comparison for measurement of performance and quality improvement both internal and external to the organisation. TrendCare users have provided data to the vendor for the derivation of 2001 Average Clinical Benchmarks in HPPD. The benchmark is a range of hours calculated as average, (or mean). For example, a general surgical benchmark of 4.5-4.9 HPPD in Thailand and 3.8-4.3 HPPD in Australia xxiii Care model Care models are how work is organised, delegated and evaluated. Care models are the nursing work systems in place in a ward/unit setting. Common systems include for example, team nursing, task allocation, patient allocation, case management, or nursepatient ratios. Some systems work well for a mix of junior and senior staff and others work better where the team is expert. A Nurse Unit Manager will manage the nursing resources well by selecting an appropriate care model. Further, the experienced team leader can act as a mentor or role model to the more junior team member. TrendCare allocates patients to either individuals or teams as required. Case mix The mix of different patient types in a specific ward/unit or hospital. Casemix funding A method of funding health services which is similar to output based funding. The method involves funding of health care products which are categorized using casemix classifications. Output based funding usually includes teaching and research in addition to casemix classifications (PSCU, 1997). Categorising A function of the TrendCare system: The process begins after selection of the patient type relevant to a patient's diagnosis, treatment and response to treatment, then selection of the appropriate indicators and variables within the indicators for the relevant patient type. (TrendCare 2003). The TrendCare system allocates a category. The category may change at any time throughout the shift or the episode of care. xxiv Clinical hours Clinical hours are recorded in TrendCare. Nursing care is one component of clinical care which is recorded and it includes direct and indirect nursing care. Other clinical care may be recorded such as physiotherapy, or nutrition services but non-nursing clinical hours were not recorded by hospitals in the sample for this thesis. Clinical pathways A document describing the usual method of care provision for a particular type of patient and allowing for annotation of deviations from the norm (PSCU, 1997:3). Comorbidity A secondary condition existing at the time of admission which, because of its presence with a specific principal diagnosis, causes an increase in length of stay. In the AN-DRG classification, comorbidity is expected to result in an increased length of stay of at least one day in 75% of patients (PSCU, 1997:9). Complication A secondary condition arising during the hospital stay which, when present in association with one or more specific principal diagnosis causes and increase in length of stay (PSCU, 1997:9). Convalescent days An episode of care involving the provision of maintenance nursing while the patient achieves functional gain through his or her own resources (PSCU, 1997:9). xxv Cost centre An accounting entity where all costs associated with a particular type of activity can be recorded (PSCU, 1997:9). For example, the cost of training, occupational health and safety or agency nursing hours can be recorded. Cost weight In general, the cost of one item of production relative to other items. (PSCU, 1997:9). DRG Diagnosis related groups. See AR-DRG. De-identified All information which indicates the source of the data has been removed. For example the source could be name, address, date of birth, Unit record (UR) Number or Bed number. Dependency Nurse dependency, patient dependency, nursing acuity and patient acuity are terms xxix Mandated nurse patient ratios Nurse patient ratios which are legally enforceable. Medical Illness Severity Grouping System (MedisGroups) A scoring system which involves the extraction of approximately 250 types of clinical data items and computation of a weighted measure of severity of illness. The results can be used for many purposes, including assessment of quality of care and study of variations in casemix within DRGs (PSCU, 1997:9). Medicus The Rush Medicus Patient Classification System. It contains 37 indicators that determine patient dependency. It was developed in the USA in 1976. Minimum safe staffing levels Minimum safe staffing levels are rostering strategies which may be established as 'policy' by individual hospitals. These policies override all acuity measures. For example, night duty may predict 12 hours of direct care time, based on acuity, but policy requires a minimum of 2 nurses to work in each ward or unit on night shift. Two nurses on night shift would equal, for example, 18 hours. Therefore, the night shift would have 12 hours of care time and 6 hours of safety time, to maintain minimum safe staffing levels. Night duty unproductive time The TrendCare system takes into consideration the 'down time' during the early hours of the morning on the night shift when the patient activity is low and recognises that this minimizes a nurse's opportunity to attend to patient care during this time. The unproductive value selected when setting up ward maintenance should be reflective of xxx ward activity during this time. Refer to the TrendCare Training Booklet-Clinical.

Revista do Colégio Brasileiro de Cirurgiões, 2019

Objective: to evaluate the applicability of the "Timing of Acute Care Surgery" (TACS) color classification system in a tertiary public hospital of a developing country. Methods: we conducted a longitudinal, retrospective study in a single center, from March to August 2016 and the same period in 2017. We opted for the selection of four surgical specialties with high demand for emergencies, previously trained on the TACS system. For comparisons with the previous classifications, we considered emergencies as reds and oranges and urgencies, as yellow, with an ideal time interval for surgery of one hour and six hours, respectively. Results: Non-elective procedures accounted for 61% of the total number of surgeries. The red, orange and yellow classifications were predominant. There was a significant improvement in the time before surgery in the yellow color after the TACS system. Day and night periods influenced the results, with better ones during the night. Conclusion: This is the first study to use the TACS system in the daily routine of an operating room. The TACS system improved the time of attendance of surgeries classified as yellow.

Scandinavian Journal of Caring Sciences, 1998

Patient Classification Systems (PCSs) comprise a large group of instruments which describe the condition of a patient regarding severity of disease, severity of illness, risk factors, intensity of nursing care, costs, and so on. They are advocated as an essential ingredient in outcome assessment, but the application of PCSs extends beyond research activities. The aim of this study was to investigate the use of and need for PCSs in Swedish neonatal care units as well as the need for evaluation and improvement of the systems already in use. A survey of 44 units revealed a low level of experience in the use of these systems. Among the 20 units using PCSs, only a few applied standard systems and 11 units pointed out the need for improving these systems. In addition, a second study, based on participant observation and interviews, indicated some potential applications of PCS in a specific unit, such as standard criteria for referring mothers and newborns, staff allocation, staff education and training, standard criteria for parent information, and prognostic systems for medical decision support. Evaluation and adaptation of the existing systems, which are generally developed outside the country, are necessary before they can become a tool for quality assurance, if a national programme for quality of neonatal care is to be established in Sweden.