TRAUMA OUTCOMES

Published on 10/03/2015 by admin

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CHAPTER 107 TRAUMA OUTCOMES

All surgeons who care for patients with injury are subject to increased scrutiny relative to the outcomes of their patients. In fact, all participatory physicians, nurses, technicians, hospitals, and state trauma systems should have a heightened interest in trauma outcomes. Not only does outcome analysis provide a platform for performance improvement and patient safety, but may have a significant impact on liability, cost, and reimbursement. As pay-for-performance initiatives emerge, the survival of trauma centers and systems may be at risk.

More importantly, measurement of outcomes allows comparative benchmarking of care and provides a measure of the effectiveness of current processes of care such as triage, diagnosis, treatment, and rehabilitation. Fortunately, venues for outcome analysis are maturing such as the work of the many trauma/critical care societies as well as the American College of Surgeons. Examples of this resource include the National Trauma Data Bank (NTDB) and the Office of Evidence Based Surgery at the American College of Surgeons.

OUTCOMES

Outcomes may be viewed differently from the perspective of the patient, provider, payer, and society. The standard outcome parameters are outlined in Table 1. Although survival (live/die) seems straightforward, the endpoint in time may vary considerably, including in hospital, 30 days, 6 months, 1 year, and time to death. These variations project imprecision into many of the existing severity scoring and mortality prediction models.

Table 1 Outcome Parameters in Medicine

The use of morbidity as an outcome requires distinguishing between a complication and a pre-existing condition (i.e., a comorbidity) and providing a precise definition of a complication. A wound infection requires a precise diagnosis using the NISS classification; however, many of the infections are discovered and treated as outpatients and are never recognized by registries. Distinguishing between pre-existing renal or pulmonary disease and subsequent renal or pulmonary dysfunction after trauma can be challenging.

Hospital length of stay is a gross parameter of quality or outcome because of the variety of practices in institutions relative to the use of intensive care unit, step-down, floor, and outpatient care. The effect of early discharge is widely unknown relative to the effect on the patient’s family, visiting nurses, physician’s offices, and unanticipated hospital readmissions.

As with all outcome parameters, the cost of trauma care can be in the eye of the beholder. The payer is likely to know his/her cost with some precision, which usually reflects what he/she paid plus administrative costs. The patient usually perceives the cost as out-of-pocket expenses plus lost wages. However, the cost to the providers (i.e., emergency medical services, physician, and hospital) has many confounding variables, and is much less precise. The cost to society is even more abstract and studies have revealed substantial variation in estimates.

Quality of life has been recognized by researchers as desired outcome measures. The Functional Independence Measure (FIM), Glasgow Outcome Scale (GOS), Functional Capacity Index (FCI), Quality of Well-Being Scale, Sickness Impact Profile (SIP), and the SF-36 Survey are among the most popular in trauma-related outcome studies. Some are labor intensive and become impractical except for focused studies.

Many commercially available survey tools are religiously utilized by hospital and system administrators as measures of patient satisfaction. Goals are frequently set to meet target scores, suggesting either improvement or decline in outcome.

Finally, measuring compliance with evidence-based guidelines can provide a measurement of outcomes. Studies of compliance with Advanced Trauma Live Support (ATLS) guidelines, as well as head injury guidelines, have provided several outcome studies. Using guideline compliance as an outcome itself assumes that the desired outcome is compliance, inferring improvement in other standard patient outcomes based on the evidence on which the guidelines were developed. Therefore, caution is required in interpreting this outcome parameter.

EVIDENCE-BASED MEDICINE

The discipline of evidence-based medicine has emerged over the past decade to allow investigators to quantify the power of scientific studies based on the certainty of the scientific methods employed. Although simplistic, a classification system has been well received by the medical community that allows dialog among investigators (Table 2). Fortunately, the trend of dominance of class III data in the world of trauma outcomes is slowly giving way to significant class II and class I outcome studies in trauma and critical care.

Table 2 Evidence-Based Classification of Outcome Studies

Evidence Description
Class I Prospective, randomized, controlled trials—the gold standard of clinical trials. However, some may be poorly designed, lack sufficient patient numbers, or suffer from other methodological inadequacies.
Class II Clinical studies in which the data were collected prospectively; retrospective analyses based on clearly reliable data. Types of study so classified include observational studies, cohort studies, prevalence studies, and case–control studies.
Class III Most studies based on retrospectively collected data. Evidence used in this class indicates clinical series, databases, registries, case reviews, case reports, and expert opinion.
Technology assessment The assessment of technology, such as devices for monitoring intracranial pressure, does not lend itself to classification in the format above. Thus, for technology assessment, devices were evaluated in terms of accuracy, reliability, therapeutic potential, and cost effectiveness.

In general, class I and class II studies provide the fuel for the strongest evidence-based guidelines on which to base the processes of trauma care (Table 3). The value of class III studies is to point the researcher toward an area of need and to help formulate the appropriate null hypothesis for a higher-power study. However, there are many clinical questions that have prohibitive barriers that prevent class I and class II studies, thereby augmenting the value of class III evidence.

Table 3 Trauma-Related Evidence-Based Guidelines

PERFORMANCE IMPROVEMENT AND PATIENT SAFETY

For over two decades, performance improvement (previously called quality assurance) has been a centerpiece of trauma care as promulgated by the American College of Surgeons Committee on Trauma. Recently, as a result of studies by the Institute of Medicine and the response to those studies by the Joint Commission on Accreditation of Health Care Organizations, patient safety has been added to the equation. Most health care organizations are under a mandate for demonstration of performance improvement and patient safety (PIPS) initiatives.

The Surgical Care Improvement Project (SCIP) is a national initiative to improve outcomes for patients having surgery. This project represents a coalition of 10 organizations, including the American College of Surgeons, Agency for Healthcare Research and Quality, Centers for Medicare and Medicaid Services, and Joint Commission on Accreditation of Healthcare Organizations. Although some of the initiatives are not specific to trauma care, many relate to critical care and general care of any patient, including those with injury (Table 4). Most of these initiatives are centered on evidence-based guidelines reflective of class I or II outcome studies. Therefore, it is important to understand the very strong link between trauma/critical care–related PIPS and outcome studies.

Table 4 Surgical Care Improvement Project: Process and Outcome Measures

Infection

Cardiac Venous Thromboembolism Respiratory Global

NATIONAL TRAUMA DATA BANK

In 1989, the Regents of the American College of Surgeons established the National Trauma Data Bank (NTDB) subcommittee under the aegis of the American College of Surgeons Committee of Trauma. The goal of this initiative was to develop a database that would serve as a national repository of data on trauma center care in the United States. After completing its preliminary work, including establishing the standard data set of 93 elements, the NTDB initiated a first call for data in 1997. It continues to do so annually, requesting data from the previous year. As of 2005, the NTDB has accrued over 1.4 million records from 405 U.S. trauma centers in 43 states, territories, and the District of Columbia, making it the largest aggregate of trauma data ever assembled. Table 5 outlines research studies that were at least in part based on the NTDB.

Table 5 National Trauma Data Bank–Related Research

Epidemiology

Prevention System Scoring Prehospital ShafiS, et al: Prehospital endotracheal intubation and positive pressure ventilation is associated with hypotension and decreased survival in hypovolemic trauma patients: an analysis of the National Trauma Data Bank. J Trauma, 2005. Resuscitation Operating Room Critical Care Friese RS, et al: Pulmonary artery catheter is associated with reduced mortality in severely injured patients: a National Trauma Data Bank analysis of 53,312 patients. J Trauma, 2004.

Although the sheer size of the NTDB makes it an attractive resource for trauma-related research and benchmarking, it has several significant limitations. The NTDB represents a convenience sample of trauma care provided by the participating hospitals, which are predominately trauma centers. Accordingly, it can not be used as a population-based assessment of U.S. trauma care.

The NTDB contains data originally collected using many different trauma registry programs. Because of the variability of the data definitions contained in the registry programs, there is significant data variability within the data set of the NTDB itself. In order to limit this variability, the data files are scanned to ensure that they are within valid ranges prior to entry. Presently, the NTDB Subcommittee with assistance from the U.S. Health Resources and Service Administration is engaged in a major effort to standardize the NTDB’s data set for eventual distribution to the participating hospitals.

The NTDB’s nonsystematic sampling also lends itself to a selection bias. This bias makes benchmarking problematic, as not all hospitals or trauma centers participate and certain injuries (e.g., hip fractures) are not uniformly reported. Furthermore, because of the voluntary and nonuniform nature of reporting, the NTDB participating hospitals can provide varying amounts of data within the data set. As many hospitals fail to report certain information such as complications or comorbidities, comparative analysis in these areas is impossible.