Balancing care decisions for gravely ill patients
Mayo Clinic researchers report their findings in Mayo Clinic Proceedings
ROCHESTER, Minn. -- Mayo Clinic researchers studying gravely ill intensive care unit (ICU) patients found that unrealistic family expectations resulted in the increased use of health care resources without a significant improvement in survival rate among these patients.
The February Mayo Clinic Proceedings study is important for patients who have a high likelihood of death in a hospital. Early, accurate identification of these patients when they arrive at the hospital might limit potentially futile, aggressive ICU care to such patients. However, limiting such aggressive care based on inaccurate tools might shorten potentially productive lives, says Keith Berge, M.D., a Mayo Clinic anesthesiologist who was the lead researcher.
In this study, researchers used the Acute Physiology and Chronic Health Evaluation III (APACHE III), a computerized system that is designed to prospectively predict mortality rates in "real time" for ICU patients, to identify a group of patients with a very low predicted likelihood of survival. This group of extremely ill patients was then looked at in more detail.
The researchers compared a group of these patients in which the families had unrealistic expectations of survival with a group of patients whose families' expectations were deemed appropriate. They found that patients whose families had unrealistic expectations used substantially more ICU resources. The median number of days in ICU for all patients was four, while the median number of days in ICU for patients whose families had unrealistic expectations was 11 days. While these patients survived to hospital discharge at a higher rate than others (33 percent versus 17 percent), their survival one year later did not differ much from those without documentation of unrealistic expectations (11 percent versus 6 percent). Nearly all survivors were severely disabled at discharge and at one year.
"Perhaps the best way to avoid vast expenditures of resources on patients very unlikely to survive is by improving communications between patients, their families and their caregivers. On occasion, there are expectations for recovery which far exceed what caregivers would project as a 'best case scenario,'" says Dr. Berge.
Dr. Berge suggested that increased utilization of advanced directives by patients (only 19 percent in the study had such documentation), formal patient care reviews, and assistance from ethicists and family counselors might better align patient or family expectations with reasonable therapeutic goals.
In the Mayo Clinic Proceedings study, the researchers also noted that APACHE III, a highly sophisticated and widely used computer tool for predicting outcomes, was more than five times more pessimistic than what they observed in their extremely ill subset of patients. The researchers also noted that physician insights of the likelihood of survival of some groups of ICU patients were considerably more accurate than the outcomes predicted using the computer tool.
The researchers said much more research and experience are needed before prognostication and resource allocation can be optimally improved in gravely ill ICU patients.
"Providing health care is challenged by the need to balance increasingly expensive medical resources with the needs and desires of a growing and aging population," says Dr. Berge. "One important factor that affects this balance is the care of patients in ICUs."
One approach used by hospitals is to match available resources to patients' needs by using a prognostic scoring scale to identify patients who have a meaningful chance of survival in the hospital and who have a functional recovery. By understanding the information, it might be possible to favorably shift resources toward patients with a good chance of survival and functional recovery and away from those with a minimal chance of survival or functional recovery.
In the study, the researchers noted the value of physician insights and interpretations in making decisions on care, saying "This finding also sounds a cautionary note to those who would use prognostication tools to limit resource allocation to extremely ill patients based solely on a low predicted likelihood of survival."
Source: Eurekalert & othersLast reviewed: By John M. Grohol, Psy.D. on 21 Feb 2009
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