title: How the Frailty Index May Support the Allocation of Health Care Resources: An Example From the INCUR Study.
abstract: The Frailty Index (FI), proposed by Rockwood and Mitniski, measures the deficits accumulation occurring with aging, and can be generated from the results of a comprehensive clinical assessment. Its construct (based on pure arithmetical assumptions) may represent a unique feature for supporting unbiased comparisons among clinical facilities/services.
  
  
  
  To propose an example depicting how the FI may support health economic evaluations and provide insights for public health.
  
  
  
  Observational study.
  
  
  
  Nine nursing homes participating in the "Incidence of pNeumonia and related ConseqUences in nursing home Residents" (INCUR) study.
  
  
  
  A sample of 345 older persons living in nursing homes.
  
  
  
  A 30-item FI was generated from clinical data retrieved from medical charts. Health care expenditures that occurred over 12 months of follow-up for each participant were obtained from the Caisse Primaire d'Assurance Maladie. Descriptive analyses describing the relationships between the FI of residents with the annual health care expenditures according to nursing home are presented.
  
  
  
  Mean age of the study sample was 86.0 (SD 7.9) years. The median annual cost per patient was 27,717.75 (interquartile range, IQR 25,917.60-32,118.02) Euros. The median FI was 0.33 (IQR 0.27-0.43). Results are graphically presented to highlight clinical and economic differences across nursing homes, so as to identify potential discrepancies between clinical burden and consumed resources.
  
  
  
  In this article, an example on how the FI may support health economic analyses and promote an improved allocation of healthcare resources is presented.
authors.affiliation: Gérontopôle, Centre Hospitalier Universitaire de Toulouse, Toulouse, France; Université de Toulouse III Paul Sabatier, Toulouse, France. Electronic address: macesari@gmail.com.
authors.forename: Matteo
authors.initials: M
authors.lastname: Cesari
authors.affiliation: Département d'Information Médicale, Centre Hospitalier Universitaire de Toulouse, Toulouse, France.
authors.forename: Nadege
authors.initials: N
authors.lastname: Costa
authors.affiliation: Department of Epidemiology and Biostatistics, EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: Emiel O
authors.initials: EO
authors.lastname: Hoogendijk
authors.affiliation: Gérontopôle, Centre Hospitalier Universitaire de Toulouse, Toulouse, France; Université de Toulouse III Paul Sabatier, Toulouse, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Vellas
authors.affiliation: Memory Clinic, Department of Neurology and Psychiatry, "Sapienza" University, Rome, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Canevelli
authors.affiliation: Instituto Nacional de Geriatria, Mexico City, Mexico.
authors.forename: Mario Ulises
authors.initials: MU
authors.lastname: Pérez-Zepeda
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003695:Delivery of Health Care; D016330:Frail Elderly; D005602:France; D015577:Geriatric Assessment; D006801:Humans; D008485:Medical Audit; D009735:Nursing Homes; D040841:Resource Allocation
keywords: Aging; frailty; geriatrics; health economics