Quality of care is of prime importance to patients, health-care providers, governments, and third-party payers. In addition to major concerns in some areas such as access, costs continue to climb, raising concerns about sustainability of health-care systems and the ability of society to continue to pay for health care. Rising health-care costs are due to many factors, including administrative costs, inefficient care, litigation, an aging population requiring advanced care, and technological advances. There have been many calls for health-care reform, mostly stemming from reports about unsustainable rises in costs of care.
The Institute of Medicine published Crossing the Quality Chasm: A New Health System for the 21st Century, showing that many gaps exist in quality1. In that document, the Institute of Medicine recommended systematic approaches to implement change, including appropriate incentives, evidence-based practice, and strong clinical information systems. For many in the health-care system, improving quality has become a rallying cry. However, it is still unclear as to exactly what is meant by “quality care.” Should the focus be reducing complications after treatment, improving pain relief, improving patient satisfaction, increasing life expectancy, or improving functional outcomes? There is no easy answer about what topic should take priority over others, which has led to disagreement about how to focus improvement efforts.
Quality does not necessarily improve by spending more money; in fact, quality could be a means to save money, as better coordinated care can lead to lower complication rates, improved patient and staff satisfaction, and shorter lengths of stay2,3. The challenge is to improve quality of care and still meet the increasing volumes and expectations of orthopaedic patients. While improving outcomes is the ultimate aim, many factors other than the care, such as patient comorbidities, influence outcomes and adjust risk. Therefore, process measures are often chosen as the outcome of interest.
Defining, measuring, and reporting value in health care is not a new concept. Ernest Codman was the first to advocate for tracking and reporting patient outcomes, and he used that information to modify processes of care and improve patient outcomes4. Recently, concerns over rising health-care costs and lack of accountability among health-care providers have led to an increased demand for measuring and reporting the cost and quality of health-care services. Yet, questions remain regarding the clinical relevance, reliability, and actionability of this information. Specifically, experts have debated about the merits and drawbacks of using structural, process, outcomes, and efficiency measures, as well as patient satisfaction, as a proxy for the “value” of health-care services5.
Structural measures, including nursing ratios and adoption of electronic health records, have the qualities of being easy to define and difficult to manipulate, but they are rarely actionable by providers. Process measures, including administration of prophylactic antibiotics and postoperative venous thromboembolism prophylaxis, are easier to measure, are actionable, and furnish feedback to providers. However, the clinical relevance of process measures is often questioned, and it is unclear how process measures correlate with outcomes and quality of care. Outcomes measures, such as infection rates and functional status, are the most direct measure of quality. However, they are difficult to measure, must be risk-adjusted, provide limited feedback, and are subject to time lags between care delivery and outcomes. Patient experience measures, such as Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey scores, are the most “patient-centered” measures of value, but they are influenced by patient expectations and their understanding of treatment alternatives. Finally, efficiency measures include utilization of services and total cost of care. Although utilization and cost of health-care services are frequently reported by payers using administrative claims data, true costs across the episode of care are very difficult to measure accurately. Furthermore, their correlation with quality of care has not been established.
In this article, we review the current quality and performance-improvement activities, policy implications and their impact on quality-improvement programs, and the ways in which the effectiveness of quality-improvement programs is being measured in some of the English-speaking countries. We also describe how to leverage information technology to guide clinical practice and how to make maximum use of data-tracking systems to effect continuous improvements in health care.
The United States has a continued health-care cost escalation, now at 17% of gross domestic product, with no clear strategy for reining in costs. The recent focus of U.S. health care has been on value, which is defined as the ratio of quality to cost. Regional variability differs greatly in practice patterns, which was defined by Wennberg et al. and demonstrated with the Dartmouth Atlas publications6. Higher interventional rates do not correlate with improved patient outcomes; thus, the relationship between cost and quality is not congruent7.
One of the largest issues within orthopaedics is to clearly define quality in terms that are meaningful to patients and practitioners. The American Academy of Orthopaedic Surgeons (AAOS) has taken a leadership role with a resource-intensive effort to define best practice. Many of the recommendations are limited by a paucity of well-conducted Level-I evidence studies, a condition common to the surgical specialties. Nevertheless, this commitment to systematic analysis of the best evidence available, as well as making the information available to orthopaedic surgeons and their patients, will help to set future research agendas while improving the quality of care for patients managed by practitioners who follow the evidence-based guidelines.
There are, however, various stakeholders’ perspectives regarding the measurement of quality in orthopaedic surgery. The data sources differ for these various perspectives and primarily focus on process measures. For example, HealthGrades, which uses publicly available data sets to analyze rates of infection and readmission and makes those rates publicly available on the Internet, looked at the percentage of cases that resulted in various complications after total hip replacement (Fig. 1)8. This perspective is based on readily available administrative data that are not routinely risk-adjusted and presents an oversimplified view of quality of care.
The patient perspective is an important one with regard to measuring quality because patients are the ultimate consumers of health care. Patients care about complications, reoperations, and, most importantly, results such as pain and function. There have been past efforts to measure patient outcomes with use of patient-oriented self-report measures. The AAOS established the Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) program in the early 1990s9. The program ultimately failed because it was voluntary and the costs of staff time and obtaining access to the computerized database proved to be too high9.
However, times have changed. The public and health-care payers are demanding cost-effective care, while informed patients are demanding convenience and often unnecessary tests and treatments, which drive costs higher. Therefore, the motivation to document and publicly report the results of care is becoming economically based. There is motivation to suggest that the public is responding to this type of data in the post-acute-care market and, with time, a response to acute-care data is expected. Withholding payment for care until quality results are reported is becoming a more frequent occurrence—and one that will most assuredly increase over time.
In some of the English-speaking countries, there are various quality initiatives that have been or are currently being undertaken. Only a few quality initiatives are highlighted. The number of initiatives, given the many elements of quality and the number of stakeholders, is overwhelming.
United States
In the U.S., pay-for-performance has been enacted by the Centers for Medicare & Medicaid Services (CMS), which pays hospitals and surgeons, as part of the Physician Quality Reporting Initiative, as much as a 2% premium on allowed expenses. The pay for reporting is linked to predetermined quality measures, including a mixture of process and outcome measures. The issues include concerns about exclusions, risk adjustment, and process measures that may not be linked to outcomes. While the context and the specific incentives are critical, overall-pay-for-performance programs have, at best, demonstrated modest improvements in quality10,11. Accountable-care organizations, offering financial incentives to both physicians and organizations with the intent of improving quality and lowering cost, are another mechanism of pay-for-performance that has not yet been proven to be effective12.
Many surgically focused performance-improvement programs have been introduced over the past decade. The Surgical Care Improvement Project (SCIP), which is a national quality partnership dedicated to reducing the rate of surgical complications, includes twenty evidence-based process measures covering various elements of surgical care. Nine of these twenty process measures are publicly reported, while six measures focus on surgical site infections13. Evidence varies regarding whether or not compliance with SCIP measures improves clinical outcomes. In a study of 491 consecutive patients undergoing colorectal resections, Pastor et al. reported that, despite an increase in compliance with SCIP measures from 40% to 68% following the introduction of a multidisciplinary task force, there was no change in infection rate14. In a retrospective cohort study of 405,720 surgical patients, Stulberg et al. found no correlation between individual process measures and the risk of postoperative infection15. However, they found a decreased adjusted risk of postoperative infection associated with compliance consisting of a composite set of process measures15.
Similarly, Bozic et al. evaluated the independent contributions of four SCIP measures, which included administration of appropriate perioperative antibiotic prophylaxis, beta-blockade, venous thromboembolism prophylaxis, and outcomes in 182,146 patients who underwent total joint arthroplasty16. Their results indicated that there are inconsistent and weak correlations between individual SCIP measures and outcomes16. However, Bozic et al. found a strong correlation between composite measures and outcomes, even after controlling for volume effects16. Results from Stulberg et al., Bozic et al., and other authors suggest that although individual process measures may not correlate with improved surgical outcomes, process standardization may play a role in improving surgical outcomes15-17.
The World Health Organization (WHO) has developed a surgical safety checklist that confirms a prespecified list of tasks at three time points: before the induction of surgery (“sign in”), before the skin incision (“time out”), and before the patient leaves the operating room (“sign out”)18. Several investigators have reported a reduction in postoperative morbidity and mortality with implementation of the WHO checklist. In a study of 7688 patients undergoing noncardiac surgery, Haynes et al. reported a decrease in mortality and complications following introduction of the WHO checklist19. In a study of 1750 patients undergoing urgent noncardiac surgery, Weiser et al. found that adherence to safety steps increased and complication and mortality rates decreased following implementation of the WHO checklist20.
The Institute for Healthcare Improvement works to accelerate improvement in health care by building the will for change, cultivating promising concepts for improving patient care, and helping health-care systems put those ideas into action. The main focus of the Institute for Healthcare Improvement is to overcome challenges in translating evidence into practice21. Dellinger et al. evaluated the impact of redesign of care processes on the incidence of surgical site infection at fifty-six hospitals22. They reported a 23% reduction in surgical site infection in association with increased compliance with evidence-based processes of care22.
“Value-based” payment methodologies, such as episode-of-care payments and pay-for-performance, may have an influence on not only the cost but also the overall quality of care. The goal of the Medicare Acute Care Episode (ACE) Demonstration Project, which provides a single bundled payment to physicians and hospitals for inpatient services for certain procedures including total joint arthroplasty and coronary artery bypass grafting, is to facilitate improved quality and reduced costs through better coordination of care among providers23. Early results for total joint arthroplasty procedures have shown a 10% cost savings in year one, with no change in complication and readmission rates23.
However, not all “value-based” payment methodologies have been associated with improved patient outcomes. Bozic and Chiu evaluated the impact of adherence to “quality” measures on outcomes and costs in total joint arthroplasty patients enrolled in a commercial health plan’s Premium Designation Program24,25. The authors reported no correlation between adherence to “quality” measures and outcomes, complications, reoperations, or total cost of care25. Bozic and Chiu suggested that the “quality” measures that were used in this program were a surrogate for utilization of health-care services25.
The AAOS has developed several strategies to help surgeons in delivering care, such as evidence-based guidelines and elimination of wrong-site surgery. To eliminate wrong-site surgery, surgeons are encouraged to sign the surgical site, not the side, with their initials, and to confirm the operative site and procedure with the patient. In addition, just prior to the onset of the surgical procedure, the surgical team should pause to confirm the patient, surgery, and site. The effectiveness of these procedures is controversial and wrong-site surgery is an extremely rare event, hampering conclusive proof of their effectiveness.
Canada
Countries that have a single-payer system have the potential to improve quality of care in a more unified fashion. Although Canada has universal health coverage, timely access to health care as one Institute of Medicine element of quality has been a major issue. The federal government provided $4 billion from 2004 to 2011 to the provinces responsible for health care to provide additional services in five areas: hip and/or knee replacement, the use of magnetic resonance imaging and/or computed tomography, sight restoration, cancer, and cardiac care26. While most provinces have reported a reduction in wait times, many patients who previously were not on lists are now on the wait lists.
Many Canadian provinces have ongoing demonstration projects to enhance the evaluation, triage, and treatment of arthritis and back pain. Operative candidates are directed to “next-available” surgeons27. The impact of these programs remains to be seen, although it is known that they limit patient choice.
United Kingdom
The National Health Service in the United Kingdom (U.K.) has created an organization called the National Institute for Health and Clinical Excellence, which is mandated to develop practice guidelines28. While supporting many aspects of care, the implementation of practice guidelines has had mixed success at best10.
The U.K. has also invested heavily in reducing wait times by developing feasible targets and obtaining additional funding. The current target of eighteen weeks from referral to surgery has dramatically reduced waits. Yet, the major concerns relate to when the additional funding is reduced29.
The U.K. is preparing major initiatives in equity and excellence, with a heavy emphasis on measurement, quality standards, and public reporting. However, there is concern that this information will lack completeness and data quality and will have an overwhelming amount of proposed measures30. For example, it is anticipated that there will be 150 proposed measures over the next five years.
Australia
In Australia, there are several commissions active in quality. The Australian Commission on Safety and Quality in Healthcare is using best evidence to influence practice31. Another commission, the Australian Safety and Efficacy Register of New Interventional Procedures—Surgical (ASERNIP-S), performs health technology assessments but lacks the enforcement necessary to resolve their negative findings32. Finally, while the National Institute of Clinical Studies develops guidelines, the National Health Priority Action Council develops health priorities and the National Health Performance Committee sets national performance standards. Among these three commissions, there is a lack of coordination and thus a lack of overall impact.
While Canada, the United Kingdom, and Australia all have a single-payer system, the delivery of health care is quite different among these three countries. Furthermore, the potential advantage of a single-payer system in addressing quality of care is unknown.
To achieve highly reliable, quality-based care delivery, some think that there must be a paradigm shift that allows providers to transition away from the traditional practice models to patient-focused, data-driven integrated delivery systems. Success in health care, therefore, is achieved by balancing growing burdens of care with diminishing resources33-35. Data-driven management on the organizational and patient levels can be accomplished through leveraging technology and is the key to achieving cost-effective quality now and into the future.
The current state of health information technology and electronic health-record vendors is not adequate to singularly influence this transition. Although many government regulatory measures were put in place with the hopes of emphasizing quality, they often serve to assess process and may redirect the emphasis away from clinically oriented outcomes. It is hoped that health information technology can assist organizations and physicians in reaching their goal of redesigned, quality-focused care.
The pluralistic, fractionated electronic medical-record and electronic health-record vendor community still lacks interoperability. Although health-information exchanges offer the promise of increasing this communication, reality is still years away. The key to improved communication and better quality is patient-centric data aggregation36. For this to be realized, there must be more reliable, accurate, and efficient flow of health information technology between providers. Additionally, health-information technology systems must become more intelligent, with clinical decision support and a bidirectional flow of information37. Today, clinical decision support is mostly pop-up reminders that alert the clinician or surgeon to specific care issues. Often, these lead to alert fatigue and can decrease the safety and efficiency of care delivery.
Governmental regulations and initiatives exist throughout the world. The stated intention of these regulations is often improved quality. Unfortunately, the reality is that many of these regulations focus on process issues and cost containment. Typically reported through abstraction from governmental billing systems, private insurance payers, and laboratory systems, the information used for these measures is easier to track and thus should be used to grade clinicians and hospitals. However, government regulation measures do not focus on the patient-oriented clinical outcomes that truly drive an improved quality health-care system. When using government regulations effectively in an overall quality and safety-related initiative, hospitals and providers can partner together for a health-care delivery system that truly meets the triple aim of health care, as championed by the Institute of Medicine and the Institute for Healthcare Improvement38. The triple aim of health care focuses on improved experience of care, population health, and cost of care.
Physicians and hospital systems are also barriers in advancing to a data-driven, patient-focused quality health-care delivery system. Often, physicians and care-delivery systems anticipate that the patient will get better with time, and thus they do not initiate or intensify therapy; this behavior is termed clinical inertia. Another common explanation for the lack of improved outcomes is lack of patient compliance. While patient factors do contribute to slower improvement of current quality, many leading institutions have demonstrated that advanced patient outreach systems, guided by health-information-technology decision support, improve patient engagement and lead to higher quality, patient-focused outcomes. These outcomes often come at a lower cost to the health-care delivery system39. Lack of active management of clinical problems contributes to a delivery system that remains lower in quality.
Many factors contribute to lower-quality health-care delivery systems throughout the world. Improved health information technology offers the opportunity for data-driven, evidence-based, patient-focused improvements to be made to the health-care delivery system. Providers must continue to influence vendors of health-information technology so as to improve the reliability, efficiency, accuracy, and interoperability of health-information technology systems. Coordinating the information regarding health-information technology across physicians and hospital systems will further magnify the positive benefit of the implementation of electronic medical record and electronic health record systems.
Despite these challenges, exemplary organizations continue to excel at achieving ever-improving clinical, fiscal, and efficiency outcomes. We offer a couple of examples to illustrate the power of a focus on continuous improvement with enabling technology and data-rich tracking in place:
A pediatric specialty hospital had a long history of paperless ordering through computer-based provider order entry. To reduce alerts while increasing efficacy, the hospital implemented advanced clinical decision support through “intelligent order sets.”40 Intelligent order sets included recommended drugs with route and dosing reflecting the patient’s disease process or care needs, recalculated automatically incorporating weight, age, and the pertinent documented characteristics41. The adoption of intelligent order sets was voluntary, providing concurrent treatment-versus-control statistical analysis capability. Severity-adjusted, “with-versus-without” analyses were conducted for twelve consecutive months of medication orders (496,105 from intelligent order sets versus 497,604 from computer-based provider order entry alone)42. No significant demographic and/or descriptive differences were found between prescribers in the two groups.
The results revealed the following:
31.2% fewer alerts for providers who leveraged intelligent order sets as compared with providers who used computer-based provider order entry alone (p < 0.0001) (Figs. 2, 3, and 4).
122.8% higher response rate to alerts for clinicians who used intelligent order sets in addition to computer-based provider order entry as compared with clinicians who used computer-based provider order entry alone (p < 0.0001); the clinicians who used intelligent order sets were more than twice as likely to respond to alerts versus “clicking past.”
59.2% fewer medication-related errors reached patients when intelligent order sets were used in addition to computer-based provider order entry, as compared with when computer-based provider order entry alone was used (p < 0.0001); restated, children treated without use of the intelligent order sets were more than twice as likely to experience a medication-related error.
Years before requirements, incentives, or penalties, a teaching hospital undertook rate reduction for deep venous thrombosis through a computer-based provider order entry-enabled deep venous thrombosis prophylaxis order set. Time-series data were analyzed, which included forty consecutive weeks with implementation at fourteen weeks (Fig. 5)43.
The analyses revealed the following:
A 62.6% decrease in mean rates of deep venous thrombosis from the time before implementation of the technological-based clinical decision support assistance to the time after implementation, falling from 0.431 to 0.161 (p < 0.001).
An estimated 302 fewer patients suffered from the short-term and long-term effects of deep venous thrombosis annually thereafter.
An estimated $739,000 dollars in reduced cost.
These examples illustrate how a drive to improve health care, coupled with enabling technology, lead to better safety, clinical outcomes, and organizational performance. Computer-based provider order entry alone is not as effective as “intelligent,” “teachable” health-information-technology systems that have been trained or programmed to make a real difference, not just capture information.
Quality is a hallmark of health care, although it is difficult to come to a consensus on who gets to define what “quality health care” is. Most health-care workers enter this field with the goal of improving the health of their patients (and the community), and while everyone tries to do the best job possible, we must continuously seek better methods and techniques for achieving better outcomes. The passion for continuous improvement is fundamental, but passion is not sufficient by itself.
There is substantial opportunity to improve quality and reduce cost in health care. Multidisciplinary teams that include physicians, nurses, and other ancillary care providers have led to decreased waiting times to see specialists and have also led to better management of chronic disease44. By including ancillary care, providers can increase cancer-screening rates and have the potential to decrease readmissions45-47. Moreover, the addition of hospitalists and physician assistants can produce quality and efficiency outcomes that are commensurate with those enjoyed by traditional house staff48. However, truly improving performance is difficult due to questions about how we define “quality,” design care processes, measure inputs and outputs, develop multi-stakeholder collaborations, and develop incentive programs for delivering “good” care.
There is a definite need for more thorough and robust studies of the impact of pay-for-performance programs, with the inclusion of ancillary care providers. Current research has not shown that there is not enough evidence to be able to determine what incentive structure might “work” in a particular health-care system49,50. Payment systems will continue to evolve to incentivize greater collaboration among providers to yield higher-quality, lower-cost care. Future efforts will necessitate the need for strong physician leadership in helping to develop an optimal care team that is as patient-centered as possible.
Technology adds dimensions of capability to making improvement real and systematic, as well as providing safer care with fewer errors and better adherence to proven best practices. The drive for quality with technology produces better clinical outcomes and maximizes efficiencies and financial metrics of organizational performance. Technology also adds capabilities for capturing key metrics and reporting them back to clinicians and others. Improved data transparency informs those who can actually do things differently to produce better results and outcomes.
While health-care entities strive to focus on quality of care, measuring and reporting such care in a meaningful way are difficult. The best chance of improving overall care for patients is through the adoption of systems that improve coordination and continuity, not by health-care staff working harder. Only through collaboration and integration can health care incorporate a culture for improving quality and patient safety.
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Disclosure: None of the authors received payments or services, either directly or indirectly (i.e., via his or her institution), from a third party in support of any aspect of this work. One or more of the authors, or his or her institution, has had a financial relationship, in the thirty-six months prior to submission of this work, with an entity in the biomedical arena that could be perceived to influence or have the potential to influence what is written in this work. Also, one or more of the authors has had another relationship, or has engaged in another activity, that could be perceived to influence or have the potential to influence what is written in this work. The complete Disclosures of Potential Conflicts of Interest submitted by authors are always provided with the online version of the article.