Hospital discharge: testing the “Blaylock Risk Assessment Screening Score” in a surgical department

Main Article Content

Sara Colognesi
Cristina Fagnani
Federica Panceri
Manuela Ruggero
Filomena Di Florio
Chiara Passoni
Valentina Fantini
Patrizia Boracchi
Annalisa Orenti
Maria Adele Fumagalli
Marco Vergani

Keywords

Discharge planning – BRASS Index – Validation study – Nursing care - Surgical nursing

Abstract

Background and aim of the work

Standardizing patients’ assessment to identify individuals at greater risk in encountering difficulties at discharge may help to assist healthcare professionals in clinical decision making and address the gaps in quality that negatively affect continuity of care. We analyzed the predictive validity and the test-retest reliability of the BRASS index in surgical inpatients. Moreover, we evaluated the association between other variables and length of stay or location at discharge.


Methods


A prospective observational study was conducted. Four hundred twenty-eight patients (≥18 years old) hospitalized in the surgical department of Vimercate hospital were recruited. Data were collected using BRASS index within 48 hours from admission and before discharge.


Results

We found a high specificity for BRASS in identifying patients discharged to their home with assistance or to residential care. The hospital stay for medium and high-risk patients was significantly longer than those in the low-risk group. There was no statistically significant difference of the BRASS scores during hospitalization. Type of admission, pressure ulcers, ASA score, multidrug-resistant bacterial infections, medical complications and Intensive Unit Care stay showed a significant correlation with longer hospitalization and increased probability to be discharged to their home with assistance or to residential care.


Conclusions

The BRASS Index may support healthcare professionals to identify surgical inpatients requiring a discharge planning and needs to be completed just once at admission. The inclusion of other patient-specific factors in the assessment process could be valuable for targeting the at-risk population.


 

Downloads

Download data is not yet available.
Abstract 67 | PDF Downloads 52

References

1. Italian National Institute of Statistic Annual report 2019. Retrieved from https://www.istat.it/it/files//2019/12/Asi-2019.pdf.
2. OECD Health at a Glance 2019: OECD Indicators. Retrieved from https://doi.org/10.1787/4dd50c09-en.
3. OECD The Future of Families to 2030. Projections, policy challenges and policy options. A synthesis report. 2011 Retrieved from https://www.oecd.org/futures/49093502.pdf.
4. Rorden J.W. and Taft E. Discharge planning guide for nurses. W.B. Suanders Company: Philadelphia 1990.
5. Saiani L., Palese A., Brugnolli A. & Benaglio C. La pianificazione delle dimissioni ospedaliere e il contributo degli infermieri [Self-instruction. Hospitals discharge planning and the nurses' contribution]. Assist Inferm Ric 2004; 23: 233-49.
6. Registered Nurses' Association of Ontario Clinical best practice guidelines: Transitional Care. 2014 Retrieved from https://rnao.ca/sites/rnao-ca/files/Care_Transitions_BPG.pdf.
7. Gonçalves-Bradley D.C., Lannin N.A., Clemson L.M., Cameron I.D. & Shepperd S. Discharge planning from hospital. Cochrane Database of Systematic Reviews 2016; 27:CD000313.
8. Hwabejire J.O., Kaafarani H.M., Imam A.M., Solis C.V., Verge J., Sullivan N.M., DeMoya M.A., Alam H.B., Velmahos G.C. Excessively long hospital stays after trauma are not related to the severity of illness: let's aim to the right target! Jama Surg 2013; 148: 956-61.
9. Lenzi J., Mongardi M., Rucci P., Di Ruscio E., Vizioli M., Randazzo C., Toschi E., Carradori T., Fantini M.P. Sociodemographic, clinical and organizational factors associated with dealyed hospital discharges: a cross-sectional study. BMC Health Serv Res 2014; 14 https://doi.orgv/10.1186/1472-6963-14-128.
10. Boult C., Dowd B., McCaffrey D., Boult L., Hernandez R. & Krulewitch H. (1993) Screening elders for risk of hospital admission. J Am Geriatr Soc 1993; 41: 811-7.
11. Sager, M.A., Rudberg M.A., Jalaluddin M., Franke T., Inouye S.K., Landefeld C.S., Siebens H., Winograd C.H. Hospital admission risk profile (HARP): identifying older patients at risk for functional decline following acute medical illness and hospitalization. J Am Geriatr Soc 1996; 44: 251-7.
12. De Jonge P., Bauer I., Huyse F.J., Latour C.H. (2003). Medical inpatients at risk of extended hospital stay and poor discharge health status: detection with COMPRI and INTERMED. Psychosom Med 2003; 65: 534-41.
13. Holland D.E., Harris M.R., Leibson C.L., Pankratz V.S. & Krichbaum K.E. Development and validation of a screen for specialized discharge planning services. Nurs Res 2006; 55: 62-71.
14. Blaylock A. & Cason C.L. Discharge planning predicting patients' needs. J Gerontol Nurs 1992; 18: 5-10.
15. Chaboyer, W., Kendall E. & Foster M. Use of the 'BRASS' to identify ICU patients who may have complex hospital discharge planning needs. Nurs Crit Care 2002; 7: 171-5.
16. Mistiaen P., Duijnhouwer E., Prins-Hoekstra A., Ros W. & Blaylock A. Predictive validity of the BRASS index in screening patients with post-discharge problems. Blaylock Risk Assessment Screening Score. J Adv Nurs 1999; 30: 1050-6.
17. Saiani L., Zanolin M.E., Dalponte A., Palese A. & Viviani D. Valutazione della sensibilità e specificità di uno strumento di screening dei pazienti a rischio di dimissione difficile [Sensibility and specificity of a screening instrument for patients at risk of difficult discharge]. Assist Inferm Ric 2008; 27: 184-93.
18. Dal Molin A., Gatta C., Derossi V., Guazzini A., Cocchieri A., Vellone E., Alvaro R., Rasero L. Hospital discharge: results from an Italian multicenter prospective study using Blaylock Risk Assessment Screening Score. Int J Nurs Knowl 2014; 25: 14-21.
19. Panella L., La Porta F., Caselli S., Marchisio S. & Tennant A. Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS Index. Eur J Phys Rehabil Med 2012; 48: 443-54.
20. Cammilletti V., Forino F., Palombi M., Donati D., Tartaglini D. & Di Muzio M. BRASS score and complex discharge: a pilot study. Acta Biomed 2017; 88: 414-25.
21. Cunic D., Lacombe S, Mohajer K., Grant H. & Wood G. Can the Blaylock Risk Assessment Screening Score (BRASS) predict length of hospital stay and need for comprehensive discharge planning for patients following hip and knee replacement surgery? Predicting arthroplasty planning and stay using the BRASS. Can J Surg 2014; 57: 391-7.
22. World Medical Association Declaration of Helsinki: ethical Principles for Medical Research Involving Human Subjects. JAMA 2013; 310: 2191-4.

Most read articles by the same author(s)