Development and validation of predictive MoSaiCo (Modello Statistico Combinato) on emergency admissions: Can it also identify patients at high risk of frailty?

Annali dell'Istituto Superiore di Sanita

Volumn 47, Issue 2, 2011, Pages 220-228

  Falasca, Pasquale ^a   Berardo, Arianna ^a   Tommaso, Francesca Di ^a  

^a Azienda USL di Ravenna   (Italy)

Author keywords

Chronic care model; Frailty; Predictive model; Score index

Indexed keywords

ADOLESCENT; ADULT; AGE; AGED; ARTICLE; COHORT ANALYSIS; EMERGENCY HEALTH SERVICE; FRAIL ELDERLY; HOSPITAL ADMISSION; HUMAN; ITALY; MIDDLE AGED; PREDICTIVE VALUE; REPRODUCIBILITY; RISK ASSESSMENT; RISK FACTOR; STATISTICAL MODEL; STATISTICS; TREATMENT OUTCOME;

ADOLESCENT; ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; COHORT STUDIES; EMERGENCY MEDICAL SERVICES; FRAIL ELDERLY; HUMANS; ITALY; LOGISTIC MODELS; MIDDLE AGED; MODELS, STATISTICAL; PATIENT ADMISSION; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; RISK ASSESSMENT; RISK FACTORS; TREATMENT OUTCOME; YOUNG ADULT;

EID: 79959341484     PISSN: 00212571     EISSN: None     Source Type: Journal    
DOI: 10.4415/ANN-11-02-15     Document Type: Article

References (42)

1. Commission of the European Communities. White Paper. Together for health. A strategic approach for the EU 2008-2013. Brussels: Commission of the European Communities; 2007. Available from: http://ec.europa.eu/health/strategy/policy/ index-en.htm.
2. Ham C. Chronic care in the English National Health Service. Progress and challenges. Health Affairs 2009;Jan/Feb;28:1.
3. United Kingdom. Department of Health. Supporting people with long term conditions: An NHS and social care model to support local innovation and integration. London: Department of Health; 2005. Available from: www.dh.gov.uk/en/Publica tionsandstatistics/Publications/ PublicationsPolicyAndGuida nce/DH-4100252.
4. Lyratzopoulos G, Havely D, Gemmell I, Good GA. Factors influencing emergency readmission risk in a UK district general hospital: A prospective study. BMC Emerg Med 2005;5:1.
5. Foster G, Taylor SJC, Eldridge S, Ramsay J, Griffiths CJ. Selfmanagement education programmes by lay leaders for people with chronic conditions. Cochrane Database of Systematic Reviews 2009;Issue 3.
6. Roland M, Dusheiko M, Gravelle H, Parker S, Follow up of people aged 65 and over with a history of emergency admissions: Analysis of routine admission data. BMJ 2005;330:289-92. (Pubitemid 40203645)
7. Hutt R, Rosen R, McCauley J. Case-managing long-term conditions. What impact does it have in the treatment of older people? London: King's Fund; 2004. Available from: www.kingsfund. org.uk/document.rm?id=90.
8. United Kingdom. Department of Health. Our health, our care, our say. London: Department of Health; 2006. Available from: www.dh.gov.uk/en/Healthcare/ Ourhealthourcareoursay/index. htm.
9. Curry N, Billings J, Darin B, Dixon J, Williams M, Wennberg D. Predictive risk project. Literature review. London: King's Fund; 2005. Available from: www.networks.nhs.uk/62.
10. Black DA. Case management for elderly people in the community. BMJ 2007;334(7583):3-4. (Pubitemid 46095429)
11. Cousins MS, Shickle, Bander JA. An introduction to predictive modeling for disease management risk stratification. Disease Management 2002;5(3):157-67.
12. Marcantonio ER, McKean S, Goldfinger M, Kleefield S, Yurkofsky M, Brennan TA. Factors associated with unplanned hospital readmission among patients 65 years of age and older in a Medicare managed care plan. Am J Med 1999;107(1):13-7. (Pubitemid 29328276)
13. Reuben DB, Keeler E, Seeman TE, Sewall A, Hirsch SH, Guralink JM, Development of a method to identify seniors at high risk for high hospital utilization. Med Care 2002;40(9): 782-93.
14. Billings J, Mijanovich T, Dixon J, Curry N, Wennberg D, Darin B, Steinort K. Case finding algorithms for patients at risk of re-hospitalisation Part 1 and Part 2. London: King's Fund; 2006. Available from: www.kingsfund.org.uk/ document. rm?id=6209.
15. Billings J, Dixon J, Mijanovich T, Wennberg D. Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients. BMJ 2006; 333(7563):327.
16. Health Dialog, King's Fund, New York University. Combined predictive model. Final Report & technical documentation. London: King's Fund; 2006. Available from: www.kingsfund. org.uk/document.rm?id=6745.
17. Billings J, Mijanovich T. Improving the management of care for high-cost medicaid patients. Health Aff (CD Millwood) 2007;26(6):1643-54.
18. Delivering for Health Information Programme. SPARRA: Scottish patients at risk of readmission and admission. edinburgh, Scotland: NHS Scotland, Information Services Division; 2006. Available from: www.isdscotland.org/isd/ files/SPARRA-Report.pdf.
19. Peter T, Donnan, David W, Dorward T, Mutch B, Morris AD. Development and validation of a model for predicting emergency admissions over the next year (PEONY). Arch Intern Med 2008;168(13):1416-22. (Pubitemid 352008423)
20. Long Term Conditions Programme. Scottish patients at risk of readmission and admission. A report on development work to extend the algorithm's applicability to patients of all ages. Edinburgh, Scotland: NHS Scotland, Information Services Division; 2008. Available from: www.isdscotland.org/isd/ servlet/FileBuffer?namedFile=2008-06-16-SPARRA-All-Ages-Report. pdf&pContentDispositionType=inline.
21. Jan De Lepeleire, Steve Iliffe, Eva Mann, Jean Marie Degryse. Frailty: An emerging concept for general practice. Br J Gen Practice May 2009.
22. Saluter.it. Emilia Romagna: Agenzia sociale e sanitaria regionale. Available from: https://siseps.regione.emilia-romagna. it/flussi/html/index. html.
23. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45(6):613-9.
24. Italia. Decreto legislativo 30 giugno 2003, n. 196. Codice in materia di protezione dei dati personali. Gazzetta Ufficiale n. 174 del 29 luglio 2003 (Suppl. ord. n. 123).
25. Shtatland, ES, Kleinman K, Cain EM. (2003). Stepwise methods in using SAS PROC LOGISTIC and SAS ENTERPRISE MINER for prediction. SUGI '28 Proceeding, Paper 258-28, Cary, NC: SAS Institute, Inc.
26. Brier GW. Verification of forecasts expressed in terms of probability. Monthly Weat Rev 1950;78(1):1-3.
27. Moons KG, Altman DG, Vergouwe Y, Royston P. Prognosis and prognostic research: Application and impact of prognostic models in clinical practice. BMJ 2009;338:b606.
28. American Nurses Association. Nursing case management. Kansas City, KS: American Nurses Association; 1988.
29. Sargent P, Boaden R, Roland M. How many patients can community matrons successfully case manage? J Nurs Manag 2008;16:38-46.
30. United Health Europe. Assessment of the Evercare Programme in England 2003-2004. Executive Summary. February 2005. Available from: www.dh.gov.uk/en/Publicationsandstatistics/ Publications/ PublicationsPolicyAndGuidance/DH-4114121.
31. Sheaff R, Boaden R, Sargent P, Pickard S, Gravelle H, Parker S, Roland R. Impacts of case management for frail elderly people: A qualitative study. J Health Serv Res Policy 2009;14:88-95.
32. Purdy S, Griffin T. Reducing hospital admissions Guidance should be evidence based and take a holistic view of patient care. BMJ 2008;336:4-5.
33. Hutt R, Rosen R, McCauley J. Case-managing long-term conditions. What impact does it have in the treatment of older people? London: King's Fund; 2004.
34. Markle-Reid M, Browne G. Conceptualizations of frailty in relation to older adults. J Advanc Nursing 2003;44(1):58-68. (Pubitemid 37352310)
35. Lally F, Crome P. Understanding frailty. Postgrad Med J 2007;83:16-20.
36. Rockwood K, Andrew M, Mitnitski A. A comparison of two approaches to Measuring frailty in elderly people. J Gerontol 2007;62A:7.
37. Abellan van Kan G, Rolland Y, Bergman H, Morley JE, Kritchevsky SB, Vellas B. On behalf of the geriatric advisory panel. The I.A.N.A. Task Force on Frailty Assessment of older people. In clinical practice J Nutr Health Aging 2008;12(1).
38. Hart JT. The inverse care law. Lancet 1971;1:405-12.
39. Watt G. The inverse care law today. Lancet 2002;360:252-54. (Pubitemid 34804658)
40. Rubin D. Propensity score methods. Am J Ophtalmol 2010;January:7-9.
41. Rosenbaum P, Rubin D. The cental role of the propensity score in observational studies for casual effect. Biometrics 1983;79(1):41-55.
42. Lyon D, Lancaster GA, Taylor S, Dowrick C, Chellaswamy H. Predicting the likelihood of emergency admission to hospital of older people: development and validation of the Emergency Admission Risk Likelihood Index (EARLI). Family Practice 2007;24:158-167. (Pubitemid 47079264)