Jill Flo1, Bjørg Landmark2, Siri Tønnessen3, Lisbeth Fagerström4. 1. Faculty of Health and Social Sciences, Department of Nursing and Health Sciences, University of South-Eastern Norway, Drammen, Norway. Electronic address: Jill.Flo@usn.no. 2. Faculty of Health and Social Sciences, Department of Nursing and Health Sciences, University of South-Eastern Norway, Drammen, Norway. 3. Faculty of Health and Social Sciences, Department of Nursing and Health Sciences, University of South-Eastern Norway, Vestfold, Norway. 4. Faculty of Health and Social Sciences, Department of Nursing and Health Sciences, University of South-Eastern Norway, Drammen, Norway; Faculty of Education and Welfare studies, Åbo Akademi, Vasa, Finland.
Abstract
OBJECTIVES: To identify the patient classification systems used to classify nursing intensity in the assessment of nursing staffing resources currently used in home health care, with a special emphasis on validity, reliability and staff allocation. DESIGN: Scoping review of internationally published and grey literature, based on a methodological framework by Arksey and O'Malley. DATA SOURCES: Searches of the electronic databases Cinahl, Medline, Embase and SweMed, the websites Google and Google Scholar and hand searches of reference lists occurred. Eligibility criteria included (A) a focus on patient classification systems measuring nursing intensity and workload in home health care and (B) published in English between January 2007 and March 2019. In level one testing two team members screened titles and abstracts, in level two testing two team members determined which papers should undergo a full text review. Data were extracted using structured extraction by one team member and verified by two other members. RESULTS: Thirteen peer-reviewed articles and grey literature documents were identified, from Canada, Ireland, the UK, the USA, Scotland, Turkey and the Netherlands. Four patient classification systems had been tested for both validity and reliability. Validity was tested through face validity, predictive validity, concurrent validity or content validity index. Reliability was tested through stability, internal consistency, observer agreement or inter rater reliability. One patient classification system had been tested only for reliability, through interrater reliability and observer agreement. Two patient classification systems had been evaluated through summative evaluation; one qualitatively through focus group interviews and one through semi-structured interviews. Only one patient classification system had been validity and reliability tested and evaluated. Overall, the patient classification systems in the included papers (13) were considered to have benefits and to be appropriate for the measurement of patients' needs, workload and allocation of staff, although specific information was not always given. CONCLUSION: Little has been published on validity or reliability tested patient classification systems linked to staffing allocation in home health care in the past decade. Limited research was seen where a patient classification system was considered to be fully operational in home health care.
OBJECTIVES: To identify the patient classification systems used to classify nursing intensity in the assessment of nursing staffing resources currently used in home health care, with a special emphasis on validity, reliability and staff allocation. DESIGN: Scoping review of internationally published and grey literature, based on a methodological framework by Arksey and O'Malley. DATA SOURCES: Searches of the electronic databases Cinahl, Medline, Embase and SweMed, the websites Google and Google Scholar and hand searches of reference lists occurred. Eligibility criteria included (A) a focus on patient classification systems measuring nursing intensity and workload in home health care and (B) published in English between January 2007 and March 2019. In level one testing two team members screened titles and abstracts, in level two testing two team members determined which papers should undergo a full text review. Data were extracted using structured extraction by one team member and verified by two other members. RESULTS: Thirteen peer-reviewed articles and grey literature documents were identified, from Canada, Ireland, the UK, the USA, Scotland, Turkey and the Netherlands. Four patient classification systems had been tested for both validity and reliability. Validity was tested through face validity, predictive validity, concurrent validity or content validity index. Reliability was tested through stability, internal consistency, observer agreement or inter rater reliability. One patient classification system had been tested only for reliability, through interrater reliability and observer agreement. Two patient classification systems had been evaluated through summative evaluation; one qualitatively through focus group interviews and one through semi-structured interviews. Only one patient classification system had been validity and reliability tested and evaluated. Overall, the patient classification systems in the included papers (13) were considered to have benefits and to be appropriate for the measurement of patients' needs, workload and allocation of staff, although specific information was not always given. CONCLUSION: Little has been published on validity or reliability tested patient classification systems linked to staffing allocation in home health care in the past decade. Limited research was seen where a patient classification system was considered to be fully operational in home health care.
Authors: José A Cordero-Guevara; Naiara Parraza-Díez; Kalliopi Vrotsou; Mónica Machón; Estibalitz Orruño; Miren J Onaindia-Ecenarro; Manuel Millet-Sampedro; José Regalado de Los Cobos Journal: BMC Health Serv Res Date: 2022-05-26 Impact factor: 2.908