Advanced illness index: Predictive modeling to stratify elders using self-report data.
OBJECTIVE
Develop a prediction model to identify persons who have an increased risk of dying within the next 36 months, in order to focus additional resources and assessment in areas related to advanced care planning.


METHODS
Retrospective study with a 3-year observation period.


METHODS
Integrated, not-for-profit managed care organization.


METHODS
Beneficiaries aged 65-105 responding to an annual survey (n = 4888).


METHODS
Survey instrument includes physical function, geriatric syndromes, health care utilization, special equipment use, self-care deficits, caregiving responsibilities, and general health problems.


RESULTS
An 11-variable model changed the baseline chi2 from 315.71 (df = 1) to 742.511 (df = 11). The percent of subjects correctly classified was 74.3% and the negative predictive value was 92.2%.


CONCLUSIONS
Advanced Illness Index (AII) model is stable. Characteristic variables used are not easily reversed: the 1997 cohort classified as at-risk consistently remained at risk or died in the subsequent years (1998, 92%; and 1999, 96%) and 92% of those not at-risk survived the next 36 months. Persons at high risk should at a minimum be made aware of the types of integrated home and community-based services available to them should it be needed. They also should be targeted for elicitation of treatment preferences, values, designation of health care proxy, planning, and advanced care directives.
Brody
Kathleen K
KK
Center for Health Research, Kaiser Permanente, Portland, Oregon, USA.
Perrin
Nancy A
NA
Dellapenna
Richard
R
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005544:Forecasting; D006306:Health Surveys; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D012189:Retrospective Studies; D018570:Risk Assessment; D012650:Self Disclosure; D012720:Severity of Illness Index; D019452:Terminally Ill