UPDATE IN PREDICTIVE SCORING SYSTEMS IN THE INTENSIVE CARE UNIT
Gamal Ali Ali Hussein;
Abstract
Intensive care has developed over the past 30 years with little
scientific evidence about what is, or is not, clinically effective.
Without these data, doctors delivering intensive care often have to decide which patients can benefit most. Scoring systems
have been developed in response to an increasing emphasis on
the evaluation and monitoring of health services. These
systems enable comparative audit and evaluative research of intensive care.
Scoring systems have been employed in ICU settings since
the 1980s, and are intended to help inform decisions related to
treatment and prognosis and used to measure ICU quality, the
most accepted and used models are the Acute Physiology and
Chronic Health Evaluation (APACHE), the Simplified Acute
Physiology Score (SAPS) and the Mortality Prediction Model
(MPM). The APACHE system incorporates measures of
physiologic derangement and co-morbidities, SAPS includes
many of the same physiologic variables as APACHE but adjusts
for co-morbidities to a more limited extent, and the MPM
system uses fewer physiologic measures than either APACHE or SAPS and includes several process variables.
Important characteristics of these instruments are
calibration and discrimination. Calibration reflects the
agreement between individual probabilities and actual
outcomes, whereas discrimination is the model’s ability to separate patients who die from those who survive.
The scoring system chosen depends on the proposed use
there are five major purposes of severity-of-illness scoring
systems. First, scoring systems have been used in randomized
controlled trials (RCT) and other clinical investigations The
second purpose of severity-of-illness scoring systems is to
quantify severity of illness for hospital and health care system
administrative decisions such as resource allocation. The third
purpose of these scoring systems is to assess ICU performance
and compare the quality of care of different ICUs and within the same ICU over time. Severity-of-illness scoring systems
could be used to assess the impact on patient outcomes of
planned changes in the ICU, such as changes in bed number,
staffing ratios, and medical coverage the fourth purpose of
these scoring systems is to assess the prognosis of individual
patients in order to assist families and caregivers in making
decisions about ICU care. Finally, scoring systems are now being used to evaluate suitability of patients for novel therapy.
The main criteria for selection of a good scoring system should be:
1- Simple, reliable, easily obtainable.
2- Wide patient applicability (Different diagnoses - All age groups - All levels / types of ICU’s)
3- High sensitivity/specificity.
4- Stimulates improvement in outcomes.
5- Independent of treatment.
6- Physiological parameters.
7- Optimal time is unclear.
8- Number of criteria is unclear.
Scoring systems in intensive care can be either specific or
generic. Specific scoring systems are used for certain types of
patient whereas generic systems can be used to assess all, or
nearly all, types of patient. The scoring system may be either anatomical or physiological. Anatomical scoring systems assess
the extent of injury whereas physiological systems assess the
impact of injury on function. Scores from anatomical scoring
systems, once assessed, are fixed whereas physiological scores
may change as the physiological response to the injury or disease varies.
All existing models aim to predict an outcome based on a given set of variables. Although death before discharge from hospital is the usual measure of outcome, disability, functional
health, and quality of life should not be ignored. Quality of life
after a critical illness has been measured by various methods.
The results differ according to the method used and the types of
patient studied. Age and pre-existing severe clinical conditions seem to greatly affect quality of life after intensive care.
The prediction of outcome is very important for:
1- Prognosis.
2- Cost-benefit analysis.
3- Withdrawal of treatment.
4- Comparison between different centers.
5- Monitoring/assessment of new therapies.
6- Population sample comparison in studies.
scientific evidence about what is, or is not, clinically effective.
Without these data, doctors delivering intensive care often have to decide which patients can benefit most. Scoring systems
have been developed in response to an increasing emphasis on
the evaluation and monitoring of health services. These
systems enable comparative audit and evaluative research of intensive care.
Scoring systems have been employed in ICU settings since
the 1980s, and are intended to help inform decisions related to
treatment and prognosis and used to measure ICU quality, the
most accepted and used models are the Acute Physiology and
Chronic Health Evaluation (APACHE), the Simplified Acute
Physiology Score (SAPS) and the Mortality Prediction Model
(MPM). The APACHE system incorporates measures of
physiologic derangement and co-morbidities, SAPS includes
many of the same physiologic variables as APACHE but adjusts
for co-morbidities to a more limited extent, and the MPM
system uses fewer physiologic measures than either APACHE or SAPS and includes several process variables.
Important characteristics of these instruments are
calibration and discrimination. Calibration reflects the
agreement between individual probabilities and actual
outcomes, whereas discrimination is the model’s ability to separate patients who die from those who survive.
The scoring system chosen depends on the proposed use
there are five major purposes of severity-of-illness scoring
systems. First, scoring systems have been used in randomized
controlled trials (RCT) and other clinical investigations The
second purpose of severity-of-illness scoring systems is to
quantify severity of illness for hospital and health care system
administrative decisions such as resource allocation. The third
purpose of these scoring systems is to assess ICU performance
and compare the quality of care of different ICUs and within the same ICU over time. Severity-of-illness scoring systems
could be used to assess the impact on patient outcomes of
planned changes in the ICU, such as changes in bed number,
staffing ratios, and medical coverage the fourth purpose of
these scoring systems is to assess the prognosis of individual
patients in order to assist families and caregivers in making
decisions about ICU care. Finally, scoring systems are now being used to evaluate suitability of patients for novel therapy.
The main criteria for selection of a good scoring system should be:
1- Simple, reliable, easily obtainable.
2- Wide patient applicability (Different diagnoses - All age groups - All levels / types of ICU’s)
3- High sensitivity/specificity.
4- Stimulates improvement in outcomes.
5- Independent of treatment.
6- Physiological parameters.
7- Optimal time is unclear.
8- Number of criteria is unclear.
Scoring systems in intensive care can be either specific or
generic. Specific scoring systems are used for certain types of
patient whereas generic systems can be used to assess all, or
nearly all, types of patient. The scoring system may be either anatomical or physiological. Anatomical scoring systems assess
the extent of injury whereas physiological systems assess the
impact of injury on function. Scores from anatomical scoring
systems, once assessed, are fixed whereas physiological scores
may change as the physiological response to the injury or disease varies.
All existing models aim to predict an outcome based on a given set of variables. Although death before discharge from hospital is the usual measure of outcome, disability, functional
health, and quality of life should not be ignored. Quality of life
after a critical illness has been measured by various methods.
The results differ according to the method used and the types of
patient studied. Age and pre-existing severe clinical conditions seem to greatly affect quality of life after intensive care.
The prediction of outcome is very important for:
1- Prognosis.
2- Cost-benefit analysis.
3- Withdrawal of treatment.
4- Comparison between different centers.
5- Monitoring/assessment of new therapies.
6- Population sample comparison in studies.
Other data
| Title | UPDATE IN PREDICTIVE SCORING SYSTEMS IN THE INTENSIVE CARE UNIT | Other Titles | الجديد في أنظمة التقييم والتوقع في وحدة العناية المركزة | Authors | Gamal Ali Ali Hussein | Issue Date | 2014 |
Recommend this item
Similar Items from Core Recommender Database
Items in Ain Shams Scholar are protected by copyright, with all rights reserved, unless otherwise indicated.