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The cycle of quality as a model for improving health outcomes in the treatment of hypertension

Robert M. Califf
DOI: http://dx.doi.org/10.1093/eurheartj/sum002 B8-B12 First published online: 11 May 2007

Abstract

Considerable progress has been made in diagnosing and treating chronic diseases such as hypertension. However, ongoing improvements in methods for characterizing the impact of long-term diseases provide strong evidence that a substantial gap still exists between knowledge and its successful application. We have developed a conceptual model for improving healthcare outcomes, known as the ‘cycle of quality’, which enables clinicians, researchers, and administrators to develop new knowledge bases and put new treatment strategies into practice, while also allowing continuous feedback and education from measurement of the results of these therapeutic approaches. We discuss the application of the cycle of quality to the treatment and prevention of hypertension in the specific context of a programme exploring a community-oriented approach to healthcare.

  • Hypertension
  • Quality
  • Outcomes
  • Cycle of quality

Introduction

Considerable progress has been made in the diagnosis and treatment of chronic diseases such as hypertension. Simultaneously, however, improvements in our methods for characterizing the impact of chronic diseases provide compelling evidence that a huge gap still exists between what we know and what we are presently achieving.1,2 The acknowledgment of this gap among healthcare providers has led to an emerging consensus; specifically, that a systematic approach to successfully implementing therapies known to be effective would have a major impact on the number of people who suffer premature death and disability. We have developed a conceptual model, the ‘cycle of quality’, (Figure 1) that allows researchers, clinicians, and administrators in each component of the medical system to examine their priorities and actions, and in doing so to foster development of new knowledge bases and implement beneficial diagnostic and treatment strategies in practice.3 In this discussion, we will examine the components of the cycle of quality and its application to treatment and prevention of hypertension, specifically in the context of a community-oriented approach to healthcare.

Figure 1

The cycle of quality: 12 steps. Adapted from Califf et al10. Copyrighted and published by Project HOPE/Health Affairs in: Califf RM et al. Curbing the cardiovascular disease epidemic: Aligning industry, government, payers, and academics. Health Aff (Millwood) 2007;26:62–74. Published article archived and available online at www.healthaffairs.org.

Cycle of quality

The US Institute of Medicine has defined healthcare quality in terms of six key dimensions.4 According to this definition, healthcare should be safe, effective, patient-centred, timely, efficient, and equitable. Such a demanding array of qualities requires an understanding that medicine should be based on best practices as determined by empirical evidence. Further, these best practices should be coupled with effective means of delivery, as well as measurement systems to determine whether constant improvements in health are being achieved. Thus, the centre of the cycle of quality is a measurement system geared to provide continuous feedback and education to the practice community. However, undue focus on a single component of the cycle can actually impede progress, as every element is linked to every other element.

An appreciation for the integrated whole can be gained by examining the important issue of safety and medical errors. A medical error is defined as either (1) a mistake in implementation of a correct plan or (2) having an incorrect plan in place. This definition, however, begs the question of how to define ‘the right plan’. After much trial and error, there is now a consensus that the right plan can only be defined by empirical evidence developed through high-quality research, typically a well-designed randomized controlled trial.5 Indeed, when such trials are done, development of clinical practice guidelines representing a distillation of professional consensus is relatively straightforward.

Adherence to professional guidelines thus forms a relatively impervious definition of having ‘the right plan’. Measuring components of the plan, such as giving the correct dose of a drug recommended by a guideline, enables systems to measure error rates in a manner useful for improving practice. Thus, errors of judgement (having the wrong plan) and errors of execution (mistakes in carrying out the right plan) can be accurately measured in a quality improvement system only if the proper studies, resulting in robust clinical practice guidelines, have been done, and if adequate measurement systems are in place.

Overcoming the first translational block

As hypertension is considered to be the leading cause of death globally,6 implementing the cycle of quality in the context of hypertension treatment and prevention should be considered an essential priority. An examination of each phase of the cycle could suggest strategies to improve the ultimate outcomes.

Discovery science remains the starting point of a science-based medical culture. In the case of hypertension, major advances in vascular biology and neural control of the vascular system continue to be made, with almost $3 billion per year in research funding directed to the National Heart, Lung and Blood Institute (NHBLI) in the United States alone. Yet despite this investment, there is a relative paucity of new and highly effective antihypertensive medicines.7 Many governments, including that of the United States, are making major efforts to upgrade the organization of discovery science efforts in this new era of ‘big science’,8 but it will be years before a return on this investment is seen.

A major problem has been identified in the transition between developing a scientific concept and performing the initial studies in humans. This problem, termed the ‘first translational block’, is classically visualized as a set of impediments in going ‘from bench to bedside’.9 As the science of drug development has evolved from simple animal models to transgenic animals, one constant has been the fact that animal models are not reliable predictors of human outcomes. New drug failure most often occurs at some remove from the pathway identified as the target of drug discovery; these off-target effects are more often the rule than the exception. Tragic examples of off-target effects include the angioedema caused by omapatrilat, the drug interactions leading to excessive sudden death rates with mibefradil, the excess rate of heart failure seen with alpha adrenergic blocking agents, and the late thrombosis seen with drug-eluting stents.

Attempts aimed at overcoming this first translational block include a portfolio of new approaches. First, it is hoped that the new ‘omics’ technologies (genotyping, gene expression, transcriptomics, proteomics, metabolomics) combined with advanced functional imaging methods will enable early detection of off-target effects in both animal and human studies. By measuring the composite output of gene expression, proteomic patterns, and metabolite patterns, it is evident that most drugs affect multiple known and unknown pathways simultaneously. Direct imaging of tissue effects also could provide early clues.

Second, the creation of public–private partnerships10 is critical to the aggregation of complex data that will allow the identification of empirical patterns in biological data that can predict outcome. Without the development of new ground rules in what has been termed the ‘precompetitive’ space, drugs that fail due to toxic effects at any point during the chain of development will continue to be abandoned without any presentation of the research data that led to the decision. If key data about failures are not shared, progress cannot be made in understanding the predictive value of findings.

Improving the clinical trials system

Assuming that new drugs are developed, improvements to the current system of clinical trials and outcomes research are needed. Much has been written about how to perform clinical trials with drugs and behavioural approaches in the treatment of hypertension. The present system permits new drugs to be marketed after modest numbers of subjects have been enrolled in short-term randomized clinical trials, usually placebo-controlled. A public–private partnership allowed the FDA to determine the precise risk of short time periods on placebo in these trials by enabling the aggregation of previously proprietary data in a composite analysis of data submitted to the FDA.11,12 The more troublesome aspect has been the question of how to conduct adequate longer-term comparative trials necessary for understanding the balance of risk and benefit for each drug when compared with alternatives. The enormous expense associated with current methods demands a transformation of the existing clinical trials system, one that will permit clinical trials to be performed with an order of magnitude more patients at a fraction of the current cost per patient.

This transformation can only occur in the setting of wide-scale implementation of electronic health records that incorporate interoperable standards for health data and common nomenclature. If health systems are then connected through informatics networks, much of the cost of data collection and auditing could be circumvented. The data used in clinical practice would be accessible for clinical trials, thus dramatically reducing the burden of redundant data collection, entry of data into computers, and unnecessary research clinic visits to document phenomena already measured as part of the routine provision of health care.

Clinical practice guidelines and performance indicators

Given appropriate clinical trials that define the comparative risks and benefits of drugs, clinical practice guidelines are developed to place these research findings in perspective. The guidelines for the treatment of hypertension have served as prototypes for other fields, but have themselves been somewhat controversial. When guidelines can be derived directly from well-conducted trials, dissension is typically minimized, but when they depend on a consensus of expert opinion, public disagreement is more likely to occur. One particularly contentious issue is how best to handle conflicts of interest in guideline development. Fortunately, US hypertension guidelines have emanated from the NHLBI with input from multiple professional societies, with the result that appearance of bias is minimized. Recent accusations of heavy-handed direct influence on professional guidelines in the treatment of sepsis13 and erythropoietin administration in nephrology14 have created broad public concern about the veracity of specialty society guidelines. Improving practices in dealing with conflicts of interest in guideline development is considered a high priority by generalist practitioners who rely on these guidelines in the course of routine decision-making.

When clinical practice guidelines are considered definitive, they lend themselves to development of performance indicators, which are measures of practices for which one can calculate a numerator and denominator, thus making measurement of adherence to best practice possible. A major controversy in the development of performance indicators for hypertension hinges upon whether they should be based on process or outcomes. For instance, process could be measured by counting how often a practitioner follows JNC7 guidelines15 for both choice of therapy and for dosing of drugs (when drugs are chosen) in clinic visits. Another important process measure is simply whether blood pressure is measured, and if so, whether it is done properly and with adequate equipment. Key outcome measures in this therapeutic area are blood pressure itself and the sequelae of hypertension, including stroke, ischaemic heart disease events, renal dysfunction, heart failure, and peripheral vascular events.

The problem that arises with using outcome measures as performance indicators is that differences in patient mix, both biologically and behaviourally, are more important determinants of outcome than the treatment itself. A practitioner with a clinic full of engineering professors (who tend to graph their own blood pressure on spreadsheets for the doctor) is likely to see much better adherence to therapy and avoidance of risk among his or her patients than a practitioner in a clinic in an impoverished area. There is also continuing controversy over whether statistical methods used to adjust for these imbalances are adequate. My opinion is that current methods are indeed inadequate. Thus, outcomes are vital to internal quality improvement within a practice or health system, but should not be used to make publicly available comparative judgements about individuals or groups of practitioners.

Delivering best practices: overcoming the second translational block9

The delivery of best practices in the treatment of hypertension deserves considerably more creativity than is typically seen in practice. The growing disparities in outcome as a function of economic and social differences are disturbing on both a global and national basis. Globally, heterogeneity can be seen from country to country in rates of hypertension diagnosis and treatment. Within a country such as the United States, substantial heterogeneity can likewise be seen, with a significant amount of this variability attributable to differences in ethnic backgrounds and socioeconomic status.

Quality of individual practitioners in dealing with hypertension is affected both by their practices and habits, and by the environment created by the medical practice or health system in which they work. At the very least, all types of practitioners should be responsible for screening patients who see them in the office or clinic. In the United States, these guidelines are clearly outlined by the US Health Services Preventive Services Task Force. Additionally, given proper screening, the practitioner should be accountable for adhering to JNC7 guidelines, except in specific identifiable situations in which alternative approaches are justified.

Practices and health systems are increasingly responsible for creating the field on which the practitioner operates. Remarkably, 30% of doctors are still in solo practice in the United States, in which case, the practice and practitioner are the same entity. The remainder of providers, including the many generalist and specialist groups, nurses, and physicians' assistants who treat hypertension, can choose from an array of systems to enhance proper screening and treatment.

Integrated health systems provide special opportunities for linking providers in a manner that in theory could provide seamless, tiered care for the individual patient, based on preferences, finances, and capabilities. Specifically, in the diagnosis and treatment of hypertension, algorithms based on standardized criteria can be used for most patients to initiate and sustain blood pressure control. This is of particular importance, because if available dollars are spent on more expensive encounters and drugs, little money will be left to pay for critical functions such as patient education and frequent follow-up visits (to keep up with issues related to adherence and side effects). This concept of medication management is rapidly evolving to develop a knowledge base regarding systematic approaches to maintaining adherence and optimizing choice of medications and dosing.

Community-oriented perspectives in healthcare

A community-oriented perspective in the provision of healthcare is potentially quite different than that of a practice or health system. In the United States, practices and health systems have obligations to their customers or patients, who are defined by the fact that they actively enter the clinic or health system (or are brought in by a particular employer- or government-sponsored coverage plan).

A community in the United States might best be defined at the county level. The tactics to reduce death and disability from hypertension in a community are different from standard approaches at the clinic practice level, in which patients routinely are scheduled for follow-up measurements and adjustment of medications, dosages, and behavioural advice. In a community, the highest rates of poor outcomes are observed in people who do not receive medical care, whether because of limited access or avoidance behaviour. Reaching such people necessarily requires strategies that use low-cost providers linked by effective systems management who can go into the community to provide fundamental diagnostic and treatment strategies.

Community-based healthcare in Durham County, NC

We are embarking on an ambitious project to improve the health status of Durham County, NC, the location of our university-based academic health centre. With a population of 300,000 people, Durham County displays a remarkable diversity: 40% of its citizens are black, 40% are white, and the remaining represents a mixture of Hispanic, Asian, and other backgrounds. Hypertension and its sequelae exact a huge toll of death and disability in this community, as manifested by rates of cardiovascular death, stroke, renal failure, heart failure, and peripheral vascular disease that exceed US averages by large margins. Our thesis is that through the development of a community-wide electronic health records, geospatial mapping of electronically recorded blood pressures, and targeted interventions in the community, we can lower average blood pressure and thereby reduce death and major disease morbidity rates. We believe that reducing disparities by providing low-cost care in the community (including the schools, churches, and homes), rather than building clinics with more specialty care, will have a measurable positive impact on outcomes in Durham County. By obtaining more frequent blood pressure measurements, transmitting them electronically, and allowing all providers to have access to the same record in the community, we hope to provide frequent dose titrations to better maintain better blood pressure control.

Conclusions

The community project described earlier affords an opportunity to test the cycle of quality outside the specific settings where it has previously been shown to be so powerful. In doing so, we hope to be able to assess impacts on healthcare outcomes, as well as management of practical and logistical issues, on a broader scale than has previously been examined. The results of this project could have extremely important implications for wider implementation of the cycle of quality, particularly if the benefits observed at the practice or system level are also seen in this ‘real-world’ setting.

Conflict of interest: R.M.C. is Director of the Duke Translational Medicine Institute and the former Director of the Duke Clinical Research Institute, which has contracts with, and/or receives research grants from, multiple pharmaceutical and medical device companies. These projects are vetted through the institutional sponsored research agreement program. All personal income outside of university-based salary for specific research projects is donated to Duke University for research and training programs.

References

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