Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index

Sarah J. Crane, Ericka E. Tung, Gregory J. Hanson, Stephen Cha, Rajeev Chaudhry, Paul Y Takahashi

Research output: Contribution to journalArticle

71 Citations (Scopus)

Abstract

Background. The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population. Methods. We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity. Results. The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period. Conclusions. It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

Original languageEnglish (US)
Article number338
JournalBMC Health Services Research
Volume10
DOIs
StatePublished - 2010

Fingerprint

Independent Living
Hospital Emergency Service
Hospitalization
Databases
Electronic Health Records
Logistic Models
Frail Elderly
Case Management
Tertiary Healthcare
Internal Medicine
Area Under Curve
Primary Health Care
Cohort Studies
Retrospective Studies
Demography
Sensitivity and Specificity
Population

ASJC Scopus subject areas

  • Health Policy

Cite this

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits : The elders risk assessment index. / Crane, Sarah J.; Tung, Ericka E.; Hanson, Gregory J.; Cha, Stephen; Chaudhry, Rajeev; Takahashi, Paul Y.

In: BMC Health Services Research, Vol. 10, 338, 2010.

Research output: Contribution to journalArticle

@article{0c933bae7ee0415ebd841f5a7a0ea245,
title = "Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index",
abstract = "Background. The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population. Methods. We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity. Results. The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10{\%} of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period. Conclusions. It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.",
author = "Crane, {Sarah J.} and Tung, {Ericka E.} and Hanson, {Gregory J.} and Stephen Cha and Rajeev Chaudhry and Takahashi, {Paul Y}",
year = "2010",
doi = "10.1186/1472-6963-10-338",
language = "English (US)",
volume = "10",
journal = "BMC Health Services Research",
issn = "1472-6963",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits

T2 - The elders risk assessment index

AU - Crane, Sarah J.

AU - Tung, Ericka E.

AU - Hanson, Gregory J.

AU - Cha, Stephen

AU - Chaudhry, Rajeev

AU - Takahashi, Paul Y

PY - 2010

Y1 - 2010

N2 - Background. The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population. Methods. We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity. Results. The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period. Conclusions. It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

AB - Background. The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population. Methods. We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity. Results. The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period. Conclusions. It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

UR - http://www.scopus.com/inward/record.url?scp=78649910740&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78649910740&partnerID=8YFLogxK

U2 - 10.1186/1472-6963-10-338

DO - 10.1186/1472-6963-10-338

M3 - Article

C2 - 21144042

AN - SCOPUS:78649910740

VL - 10

JO - BMC Health Services Research

JF - BMC Health Services Research

SN - 1472-6963

M1 - 338

ER -