Amir Shmueli1, Charles L Sprung. 1. Department of Health Management, The Hebrew University, Jerusalem, Israel. ashmueli@md.huji.ac.il
Abstract
OBJECTIVES: For an efficient and fair allocation of medical resources, one must know which patients benefit more from medical care. The objective of this study is to assess the differential survival benefits of a general intensive care unit (ICU) by acute diagnoses and by Acute Physiological and Chronic Health Evaluation (APACHE II) scores. METHODS: The sample included all patients triaged for admission to the Hadassah-Hebrew University Medical Center ICU during a 7-month period (n = 381). The potential effect of ICU on in-hospital survival was estimated by a bivariate (admission-survival) probit model, using crowding in the unit as the identifying variable, controlling for observable patients characteristics: age, sex, acute diagnoses, and APACHE II score. Using the estimates, the differential predicted survival benefits of ICU were calculated for selected general acute diagnoses and for different APACHE II scores. RESULTS: Adjusting for age, sex, and general acute diagnoses, the average potential survival benefit of ICU is 17 percentage points (pts). The benefit of ICU for patients with central nervous system problems, with sepsis, or with respiratory failure are higher than average (23 pts). Adjusting for APACHE II scores as well increases the estimated average potential benefit to 21 pts. Over the range of APACHE II scores, the highest benefit (38 pts of potential benefit) is attained for patients with scores around 22. CONCLUSIONS: Survival benefits differ across diagnoses and APACHE II scores. Facing limited resources, admission policies should distinguish between survival probabilities (and survival maximization) and survival benefits (and maximization of ICU benefits). Actual referral and admission policies to the present ICU do not maximize the potential survival benefits of ICU resources.
OBJECTIVES: For an efficient and fair allocation of medical resources, one must know which patients benefit more from medical care. The objective of this study is to assess the differential survival benefits of a general intensive care unit (ICU) by acute diagnoses and by Acute Physiological and Chronic Health Evaluation (APACHE II) scores. METHODS: The sample included all patients triaged for admission to the Hadassah-Hebrew University Medical Center ICU during a 7-month period (n = 381). The potential effect of ICU on in-hospital survival was estimated by a bivariate (admission-survival) probit model, using crowding in the unit as the identifying variable, controlling for observable patients characteristics: age, sex, acute diagnoses, and APACHE II score. Using the estimates, the differential predicted survival benefits of ICU were calculated for selected general acute diagnoses and for different APACHE II scores. RESULTS: Adjusting for age, sex, and general acute diagnoses, the average potential survival benefit of ICU is 17 percentage points (pts). The benefit of ICU for patients with central nervous system problems, with sepsis, or with respiratory failure are higher than average (23 pts). Adjusting for APACHE II scores as well increases the estimated average potential benefit to 21 pts. Over the range of APACHE II scores, the highest benefit (38 pts of potential benefit) is attained for patients with scores around 22. CONCLUSIONS: Survival benefits differ across diagnoses and APACHE II scores. Facing limited resources, admission policies should distinguish between survival probabilities (and survival maximization) and survival benefits (and maximization of ICU benefits). Actual referral and admission policies to the present ICU do not maximize the potential survival benefits of ICU resources.
Authors: Samuel M Brown; Jason P Jones; Dominik Aronsky; Barbara E Jones; Michael J Lanspa; Nathan C Dean Journal: Respirology Date: 2012-11 Impact factor: 6.424
Authors: Frode Lindemark; Øystein A Haaland; Reidar Kvåle; Hans Flaatten; Ole F Norheim; Kjell A Johansson Journal: Crit Care Date: 2017-08-21 Impact factor: 9.097