Abstract
Over the past 2 decades, there has been a renewed focus on improving the quality of health care both in the United States and worldwide. The ultimate goal of this movement has been to increase the use of evidence-based practices and improve patient outcomes across the health-care continuum. In the surgical disciplines, one of the primary goals has been to reduce the incidence of short- and long-term complications following an operative procedure. In order to do this, one must have standardized methods for identifying and reporting outcomes in addition to tested approaches to improving the quality of care when sustained patterns of poor outcomes are identified. In this chapter we present a contextual framework for understanding how surgical complications are classified and include descriptions of some of the most commonly used reporting systems for surgical complications. We also provide a brief overview on various commonly used approaches to quality improvement in surgery. By presenting these topics, we hope to inform the urologists on how best to improve outcomes for their patients and how to navigate the emerging value-based health-care environment.
Keywords
Outcomes assessment, Quality of care, Process improvement
Chapter Outline
Quality Improvement Strategies
[CR]
Key Points
- 1.
A surgical complication is any event that deviates from the normal or expected course of action either during or after surgery.
- 2.
The Common Terminology Criteria for Adverse Events system is a comprehensive set of criteria for the standardized classification of complications after cancer therapy and has been broadly accepted and extensively used by cooperative research and industry groups.
- 3.
The Clavien-Dindo classification system is centered around the risk and invasiveness of the therapy required to resolve the complication.
- 4.
The International Continence Society and the International Urogynecological Association classification system is extraordinarily complex and incorporates site, timing, and category of complications into six- or seven-digit code (with three numbers and three to four letters) to cover any conceivable complication after graft or prosthetic placement.
- 5.
Despite the lack of unanimity in how surgical complications should be classified, significant strides have been made in national outcome registries such as the National Surgical Quality Improvement Program and the American Urological Association Quality registry.
- 6.
Plan-Do-Study-Act, also known as rapid cycle improvement, is an iterative, four-stage, problem-solving model aimed at making positive changes in health-care processes.
- 7.
Statistical process control is a set of methods for assessing ongoing quality improvement measures in real time and relies on the early identification of special cause variation. Alternatively, a process that displays only common cause variation may be stable and predictable and yet still unacceptable.
- 8.
Root cause analysis is a formalized investigation and problem-solving method focused on identifying and understanding the underlying cause of an untoward event.
- 9.
Lean methodologies – used in the manufacturing of Toyota cars – aims to improve processes by removing activities that are nonvalue-added through retrospective investigations of errors that interrupt the sequence of efficient operations.
- 10.
Failure mode effects analysis aims to prevent errors through proactive risk assessment – that is, to prevent errors by identifying all the ways a process could fail, estimating the predicted probabilities and consequence of failures, and then taking action to prevent the potential failures from occurring.
- 11.
The key factors necessary for success in quality improvement are strong and committed senior leadership, buy-in from rank-and-file members of the organization, and open lines of communication between leadership and involved stakeholders.
Introduction
Since the publication of Crossing the Quality Chasm, there has been a renewed interest in improving outcomes after surgery in the United States. However, it remains unclear what constitutes a “bad” outcome after surgery as some complications are inherent to the procedure and expected to occur. Despite this uncertainty, the rate of surgical complications remains one of the most commonly used surrogate measures of surgical quality. In an effort to guide the systematic measurement and reporting of surgical complications for quality improvement purposes, several different classification systems for surgical complications have been developed despite none having emerged with universal acceptance. In this chapter, we provide a contextual framework for understanding how surgical complications are classified and how these reporting systems can be leveraged for quality improvement. Specifically, our objective is to review the available reporting systems used for complications after urologic surgery, to highlight deficiencies in these reporting systems, and to review how these classifications systems can be conceptualized within the framework of one or more prevailing quality improvement paradigms.
Definition of Complications
Before a classification system for surgical complications can be adopted, a standardized definition of what exactly constitutes a surgical complication is needed. In broad terms, a surgical complication is any event that deviates from the normal or expected course of action either during or after surgery. While many patient-, provider-, and system-level factors contribute to variations in surgical complications, a standardized reporting system is the sine qua non of effective surgical quality–improvement initiatives. There are several different proposed classification systems for reporting and classifying surgical complications, and these are summarized below.
Common Terminology Criteria for Adverse Events
The Common Terminology Criteria for Adverse Events (CTCAE) system is a comprehensive set of criteria for the standardized classification of complications after cancer therapy and has been broadly accepted and extensively used by cooperative research and industry groups since its introduction in the early 1980s. Now in its fourth version, the CTCAE system uses a range of grades from 1 to 5 to classify surgical complications, ranging from mild complications to death ( Table 8.1 ). In general, one advantage to the CTCAE system is that it is a relatively simple classification system, at least with respect to surgical complications. While this makes it ideally suited for NCI-sponsored trials where the focus is on unexpectedly serious and/or life-threatening surgical complications, it does not have the granularity needed to be used for comparative effectiveness research or quality improvement.
| 1 | Asymptomatic or mild symptoms; clinical or diagnostic observations only; intervention not required |
| 2 | Moderate; minimal, local, or noninvasive intervention indicated; limiting age-appropriate instrumental activities of daily living (ADL) |
| 3 | Severe or medically significant but not immediately life threatening; hospitalization or prolongation of existing hospitalization indicated; disabling; limiting self-care ADL |
| 4 | Life-threatening consequences; urgent intervention indicated |
| 5 | Death |
Clavien-Dindo System
In an attempt to standardize surgical outcome reporting with increased precision, Clavien et al. published a grading system for the severity of surgical complications. This new system, published in 1992, was centered on the risk and invasiveness of the therapy required to resolve the complication ( Table 8.2 ). In theory, this minimizes the influence of subjective interpretation on complication scoring because it is rooted in objective outcomes. Initially, four grades of complications were described; however, in 2004, Dindo et al. introduced a modification to the Clavien classification system using five grades contained within seven levels. This revision added further precision by characterizing whether an intervention required general anesthesia or whether a complication led to organ failure and/or admission to an intensive care unit. This reporting system, known as the Clavien-Dindo classification system, has been extensively validated and evaluated for interobserver variability.
| Grade | Definition |
|---|---|
| Grade I | Any deviation from the normal course without the need for pharmacological treatment or surgical, endoscopic and radiologic interventions. Allowed therapeutic regimens are: drugs as antiemetics, antipyretics, analgesics, diuretics and electrolytes, and physiotherapy. This grade also includes wound infections opened at the bedside. Example: wound infection, postoperative ileus not requiring total parenteral nutrition (TPN) |
| Grade II | Requiring pharmacological treatment with drugs other than such allowed for grade I complications. Example: blood transfusion, urinary tract infection, ileus requiring TPN |
| Grade III | Requiring surgical, endoscopic or radiological intervention. Grade IIIa complications do not require anesthesia. Grade IIIb complications require anesthesia Example: take back to the OR for any reason, stent placement for ureteral injury |
| Grade IV | Life-threatening complication (including CNS complications) * requiring IC/ICU management. Grade IVa is single organ dysfunction. Grade IVb is multi-organ dysfunction. Example: sepsis, stroke, cardiopulmonary event |
| Grade V | Death of a patient. If the patient suffers from a complication at the time of discharge, the suffix “d” (for “disability”) is added to the respective grade of complication. This label indicates the need for a follow-up to fully evaluate the complication |
* brain hemorrhage, ischemic stroke, subarachnoidal bleeding, but excluding transient ischemic attacks (TIA)
While this classification method has increased in popularity in recent years, it is not without its limitations. First, many of these complications remain susceptible to subjective interpretation, which may create variability within the grading assignments. For example, urologists may grade a recognized rectal injury during a radical prostatectomy differently: grade I for prolonged hospital stay versus grade III for intraoperative repair under general anesthesia. Second, some interventions may be performed under local anesthesia at one institution but general anesthesia at another, which introduces inter-rater variability within grades III and IV. Third, this system may not capture patients who have multiple complications within the same grade. Last two patients with the same complication may be managed differently at two separate institutions (e.g., IVC filter versus heparinization alone for DVT). Because of these challenges, the utility of the Clavien-Dindo classification system for national quality-improvement initiatives has been limited.
The International Continence Society and the International Urogynecological Association Classification of Complications Related Directly to the Insertion of Grafts and Prosthetics
In an effort to clarify terminology and to promote a registry for the improvement of pelvic-floor surgical procedures, the International Continence Society (ICS) and International Urogynecological Association (IUGA) have established a joint working group for classifying complications related to the insertion of prosthetics and grafts for female pelvic floor surgery. The article recommends precise definitions for specific complications by distinguishing among local systemic complications. Novel terms such as exposure, compromise, perforation, extrusion, separation, contraction, and prominence are described in this report. The classification system itself is extraordinarily complex and incorporates anatomic site, timing, and category of complication into a six- or seven-digit code (with three numbers and three to four letters) to cover any conceivable complication after graft or prosthetic placement. By way of example, the code 1AaT1S1 would indicate asymptomatic vaginal prominence with no epithelial separation in the area of the suture line within 48 hours of surgery. While the complexity of this system may limit its use in daily practice, this system may be useful for comparative effectiveness research or surgical registries. A user-friendly calculator can be found online at the ICS website.
National Quality Registries
Despite the lack of unanimity in how surgical complications should be classified, significant strides have been made in national outcome–based surgical-quality assessment. The National Surgical Quality Improvement Program (NSQIP), for example, has been measuring outcomes for many types of surgeries and, for a small subset of institutions, publically reporting them. Originally established in 1994, the goal of NSQIP was to prospectively collect surgical outcome data at Veterans Affairs (VA) hospitals and compare observed outcomes to risk-adjusted, model-based predictions. In 1999, it began expanding to include private hospitals to test the feasibility of implementing the system outside the VA. However, participation in NSQIP has not necessarily resulted in improved outcomes compared with nonparticipating hospitals. While initially showing promise for the VA system, recent data have challenged the association between hospital participation in NSQIP and improvement in outcome measures over time. Furthermore, many important patient-centered outcomes are not captured by NSQIP such as margin status, return to work, and survival beyond 90 days.
With the aim of improving quality of care for urologic patients, the American Urological Association (AUA) established the AUA Quality registry (AQUA) in the summer of 2014. The AQUA registry is a national urologic disease registry designed to measure and report quality and patient-centered outcomes after urologic surgery. Using data directly extracted from commercially available electronic medical records, AQUA aggregates and organizes clinical and patient-reported data on diagnostic and therapeutic interventions, outcomes, and resource utilization. While still in its infancy, data generated from AQUA will be used to support evidence-based decision support mechanisms and will provide feedback to urologists regarding their individual and/or practice-level performance on a range of quality measures benchmarked against their peers at the national and regional levels.
Quality Improvement Strategies
With an understanding of the basic principles of performance measurement and quality improvement, the next question is how to actually improve the quality of care. Unfortunately, the answer is often not simple. The overall goals of measuring health care are to ascertain whether the delivery of health care results in desired outcomes and to determine the degree to which health care adheres to processes that are rooted in scientific evidence, professional consensus, and patient preference. The theoretical framework that underlies successful quality-improvement programs emphasizes strategic vision, an understanding of organizational culture, streamlined data management, and infrastructure for efficient dissemination of results. As such, it is important to understand many different process-improvement techniques that can identify inefficiencies, ineffective care, and preventable errors that arise from system or process failures. The remaining portion of this chapter will focus on strategies and tools for quality improvement, including failure modes and effects analysis, plan-do-study-act (PDSA), statistical process control, Lean methodologies, and root cause analysis.
Plan-Do-Study-Act Cycle
PDSA, also known as rapid cycle improvement, is an iterative, four-stage problem-solving model aimed at making positive changes in health-care processes ( Fig. 8.1 ). This approach has been widely used by the Institute for Healthcare Improvement. This strategy invokes a cyclic approach to assessing the impact of successive changes in the process. The basic structure of PDSA is:
- 1.
Plan. Assemble a team that has knowledge of the problem, describe the problem, and identify and analyze causes.
- 2.
Do. Implement the action plan in a trial or small test group, collecting data prospectively.
- 3.
Study. Analyze the data collected, and assess whether the new process has a level of performance and/or random variation that is superior to that displayed by the old process.
- 4.
Act. If deemed successful, standardize the improvement and begin to use it regularly. If not successful, either modify it and test it again or discard it.
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