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International Journal for Quality in Health Care Advance Access originally published online on October 18, 2007
International Journal for Quality in Health Care 2007 19(6):334-340; doi:10.1093/intqhc/mzm049
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© The Author 2007. Published by Oxford University Press on behalf of International Society for Quality in Health Care; all rights reserved

Designing national quality reforms: a framework for action

Sheila Leatherman1,2 and Kim Sutherland3

1 School of Public Health, University of North Carolina, NC, USA
2 London School of Economics, University of Cambridge, UK
3 Judge Business School, University of Cambridge, UK

Address reprint requests to: Sheila Leatherman, School of Public Health, University of North Carolina, NC, USA Tel: +1 612 922 0220; E-mail: sheilaleatherman{at}aol.com


   Abstract
Top
 Abstract
Background and Overview
 QEI: a taxonomy to...
 Conceptual framework for...
 Conclusion
 Funding
 References
 
Healthcare systems worldwide strive to improve the quality of care they provide. Securing predictable systemic improvement is, however, a complex task. The imperative to be evidence-based is often constrained by the literature, which is of uneven scientific rigour and neither well-synthesized nor contextualised. This article provides a conceptual framework to guide the translation of the available evidence into policy and managerial decisions for improving quality. The framework has three aspects: a taxonomy to organize the available evidence of potential quality-enhancing interventions; a multi-tier approach to selecting and implementing interventions in a healthcare system; and a model to guide the adoption of professional, governmental and market levers for change.


   Background and Overview
Top
 Abstract
 Background and Overview
QEI: a taxonomy to...
 Conceptual framework for...
 Conclusion
 Funding
 References
 
Worldwide health-care systems, although diverse in structure, resources, accountabilities, history and priorities, generally share a common objective to improve quality of health care. This objective appears straightforward and simple. However, conceptualizing and organizing a reform agenda for predictable systemic improvement is a difficult and daunting task.

In this article, we propose a conceptual framework to guide the translation of the available evidence into policy and managerial decisions to improve quality. The framework has three aspects:

  1. A taxonomy to organize the available evidence of potential quality enhancing interventions (QEI).
  2. A multi-tiered approach to select and implement interventions in a health-care system at four levels: national, regional, institutional and the patient–clinician encounter.
  3. A model to guide the adoption of a balanced portfolio approach to quality improvement—recognizing the prudence of simultaneously employing professional, governmental and market levers for change.

Literature from health services research, clinical medicine and social sciences refers to a huge number of interventions designed to improve quality of health care. The interventions vary widely in terms of underlying assumptions, resources required and the context in which they have been implemented. Although the number of publications that discuss quality improvement is huge and ever increasing, the empirical evidence about the effects on health-care processes and outcomes is sparse and difficult to synthesize. This is a significant obstacle to those who make managerial and policy decisions and is in stark contrast to the case in clinical decision-making, where there has been a concerted effort over the past two decades to synthesize and disseminate evidence to guide practice [1–3].

In an era, when evidence-based decision-making is highly valued, policymakers and managers lack an easily accessible portal to the evidence-base about quality improvement interventions. Further, there is no common framework, generically relevant in multiple countries, to guide the design and implementation of quality improvement reforms. This article outlines an approach that aims to address these problems by presenting a conceptual framework for designing health system reforms and developing a taxonomy of available options for quality improvement based on structured reviews of the evidence made available as an online resource that acts as a searchable database.


   QEI: a taxonomy to organize and assess the evidence-base
Top
 Abstract
 Background and Overview
 QEI: a taxonomy to...
Conceptual framework for...
 Conclusion
 Funding
 References
 
The QEI project seeks to provide an authoritative summary of the available evidence to inform decision-making and policy analysis. The QEI project is a key component of a wider initiative known as Quest for Quality and Improved Performance (QQUIP), a 5-year research project conducted by a consortium of researchers at University of North Carolina, School of Public Health, LSE, University of York, and University of Cambridge, funded by The Health Foundation (UK). The website is at: www.health.org.uk/qquip.

The taxonomy of QEIs is based on a broad conceptualization of quality, encompassing issues of effectiveness, access, equity, patient responsiveness and safety [4]. At the highest level of differentiation, we have identified six categories of interventions.

  1. Patient-focused interventions’ recognize the role and contribution of patients as active participants in securing appropriate health care at both an individual and collective level. Increasingly regarded as the proper and respectful mode of providing health services, patient-focused interventions can also contribute to better outcomes in certain clinical conditions, and constructively influence health system reforms. The evidence review report [5] examines and classifies the literature by interventions designed to improve health literacy, clinical decision-making, self care, safety, access and the patient experience.
  2. Regulatory interventions’ address three key functions: to improve health care, to guarantee minimum acceptable standards and to reassure the public about quality of care. The evidence review [6] classifies regulatory interventions according to the target of the regulation: health-care delivery institutions; the professions (individually and collectively); and health-care markets.
  3. Incentives’ focus on various motivators to improve quality and include both rewards and sanctions. Financial and non-financial incentives can be differentiated in terms of their focus on professions, patients or institutions.
  4. Data-driven and IT-based interventions’ are those that seek to harness information to improve quality of care. The interventions are broadly classified into two categories:
    1. Health Information Technology (HIT) which includes knowledge management initiatives across delivery of health-care services, policymaking, administration and the training/education of health sector workforce.
    2. Performance/quality reporting systems that provide feedback to providers of care at systemic, institutional or individual levels; and information to users and payers of services for accountability and choice.

  5. Organizational interventions’ focus on improving managerial, professional and institutional behaviours. They include initiatives that are concerned with personnel and institutional capacity (e.g. skill mix, staffing levels, facility layout and design); changing organizational culture and professional behaviour (e.g. opinion leaders, clinical audit); the use of Continuous Quality Improvement (CQI) techniques and learning collaboratives for improved performance; and the provision of reliable quality assurance and controls (e.g. infection control, risk management).
  6. Health-care delivery models’ are innovative interventions in the resourcing, organization and delivery of health-care services, often focused by specific clinical condition or disease in the research literature. The evidence reviews encompass different stages along the continuum of care including: prevention and promotion, acute, chronic, long term and palliative care.

The classification recognizes that there are a number of broad categories of generic activity that are applicable worldwide. Within these categories there is a range of interventions, some widely used across many countries and others more specific to particular contexts. Within each of the six main QEI categories, multiple branches represent specific interventions that have been developed and applied in health-care systems. To illustrate, Table 1 shows a partial depiction of the taxonomy with sub-classification.


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  		Table 1 . An abridged depiction of the QEI taxonomy

 
Using the taxonomy as an organizing principle, we are leading an international team of researchers undertaking structured reviews of the available literature. To date, the QEI project has commissioned work from RAND; Research Triangle Institute; University of Minnesota in the USA; AWL in the Netherlands and drawn on expertise of Centre for Reviews and Dissemination at the University of York.

There are a number of similar synthetic research projects underway around the world, most notably the Closing the Quality Gap series published by Agency for Health-care Research and Quality (AHRQ) in the USA [7]. Most existing projects adopt disease groups as the primary organizing principle. We have used the type of intervention as the basis for our typology and search strategies. Adopting an intervention-based, rather than a disease-based approach, has two main benefits. First, it captures generic interventions that may improve quality at a system level (e.g. inspection), which may be missed by traditional disease-based reviews. Second, it allows for comparisons about the impact of various interventions in different disease and population group contexts (e.g. does telemonitoring work equally well in improving diabetes care and heart failure care?). Providing a more generic perspective on quality improvement interventions in this way should facilitate decision-making of those concerned with macro-system improvement, who have little comprehensive, comparative information available to them to inform decisions [8].

The syntheses are made available in two main forms: a traditional document, organized around themes of quality improvement; and a searchable database (www.health.org.uk/qquip).

Assembling the evidence-base: strategy and process
The QEI project takes an inclusive approach to evidence—acknowledging the sparseness of available evidence and the difficulties in undertaking experimental studies in organizational research. Hence the syntheses draw on existing systematic reviews; experimental and quasi-experimental studies; and observational studies. In organizational and policy research, there are far fewer studies conducted and reported than in clinical medicine and the research designs are more diverse. Therefore, the QEI project has used inclusion and exclusion criteria that are less rigid than those used in many systematic reviews but is explicit regarding the methodological and design features, allowing decision-makers to see the strength and extent of information available.

Limitations of the taxonomy and evidence-base
The lack of rigorous research design means that many published studies entail multiple interventions or are affected by mediating variables for which there have been no, or insufficient, controls. It is therefore difficult, and sometimes impossible, to determine the contribution of a discrete intervention to the observed changes in quality and performance. There are also some elements of bias in the available literature. Just as in clinical research, success is much more likely to be written up than failure, resulting in a publication bias. More fundamentally, it is difficult to control for contextual confounders in studies; therefore it is hard to ascertain whether impact in one context will translate into a different health-care environment.


   Conceptual framework for applying evidence in the ‘real world’
Top
 Abstract
 Background and Overview
 QEI: a taxonomy to...
 Conceptual framework for...
Conclusion
 Funding
 References
 
A multi-tiered approach to building predictable systemic capacity for improvement
Although reference to an accessible evidence-base may facilitate prudent selection of interventions, a robust quality reform agenda cannot be built on the basis of a disjointed ‘pick and mix’ approach. Predictable systemic improvement requires a coherent overarching view; with coordination of interventions at all levels of the health-care system. In a decade of work evaluating quality reforms in the UK, we have developed a conceptual framework that guides the complex process of choosing and applying interventions that are appropriate to context and combine or complement to construct a comprehensive set of reforms. The framework is built around a holistic approach to quality improvement that considers three key factors:

  1. The way in which different types of approaches interact; for example are patient engagement strategies aligned with systemic incentive structures? We refer to this as ‘horizontal coherence’.
  2. The application and interaction of improvement interventions across multiple levels of a health-care system; for example are national strategies supportive of and well integrated with health service delivery at the front lines? We refer to this as ‘vertical coherence’.
  3. The balance and complementarity between three key mechanisms for improving quality and accountability; for example are professionalism, the power of government and market forces used in a coordinated, symbiotic way? We refer to this as ‘coherence in accountability’.

Decision-makers can use the model to select discrete interventions from the six intervention catagories shown in Table 1 and consider their application within different vertical levels in their health-care system (Fig. 1).


Figure 1
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  		Figure 1 Levels for building systemic capacity for quality.

 
Fig. 1 displays four levels of activity within any country's health-care system and can be used to plan and implement an overall quality improvement strategy. For example, in the broad category of information and data, interventions might range from the building of an IT infrastructure for the health sector at the national level, to the use of comparative performance indicators for monitoring regional variation, to the development of clinical decision support systems at the institutional level and the use of shared decision-making models at the level of the clinical encounter with the patient.

A balanced portfolio approach
In addition to vertical and horizontal integration of quality improvement interventions, decision makers often need to consider the relative importance, both current and desired, of three broad approaches to improve performance and provide accountability in health-care systems (see Table 2) [9]..These approaches are

  1. ‘The professional model’, which has historically dominated health-care systems, is founded on the underlying assumption that health care is a transaction between the patient and the professional, influenced by and regulated through traditional instruments such as professional licensure and peer review with newer tools emerging such as hospital credentialing and physician certification. Reliance on conventional forms of professionalism is decreasing as evidence grows of widespread quality deficiencies and less frequent, but often politically compelling, cases of individual egregious conduct.
  2. ‘The market model’ has a fundamentally different foundation, where health care is viewed as a commodity and relies on mechanisms that encourage competition among ‘suppliers’ for market share (individual and institutional providers). In theory, consumers act as arbiters, exercising choice and exit to improve quality and accountability. The assumption is that if competition and choice are available, consumers and payers will use their ‘purchasing power’ to discipline the health-care system to perform better. Regulation of the market may occur through such requirements as mandatory publicly reported performance metrics and controls to maintain a ‘level playing field’ to deter unfair or anti-competitive behaviour.
  3. ‘The governmental (or political) model’, where health care is viewed primarily as an essential service or public good rather than as a private good or commodity. Control is exerted via centralized bureaucracies operating in the public interest and on patients' behalf. In this model, instruments to improve performance are government reforms that take various forms including legislation, regulation, infrastructure building such as IT, performance-based contracting and public policies that shape the health-care environment.


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  		Table 2 Three broad approaches to accountability and improving performance in health care

 
None of these approaches has been demonstrated to be sufficiently robust to operate alone. In the USA, where reliance on market forces has been the key strategy for several decades, government at the state and federal levels is now playing a larger role through regulation. In the UK, where reliance has been on the government and professional models historically, market forces are increasingly being introduced.

Moving from blunt strategies to more refined interventions
A number of interventions are now common to the quality improvement agendas of multiple countries (see Fig. 2). This configuration of interventions is partially supported by the growing body of research but also includes interventions that have become trendy in the quality field and for which the evidence-base is either sparse and equivocal or questionable in its research rigour.


Figure 2
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  		Figure 2 Improving quality circa 2007.

 
As the evidence-base has grown quickly over the past 5 years and will inevitably continue to do so over the next decade, it is reasonable to expect that the rather blunt instruments we are currently using for payment, regulation, public reporting, knowledge management etc will become more highly refined and targeted.

On the basis of some of the evidence emerging from our early reviews in the taxonomy categories of regulation, patient engagement and health delivery models, a set of more focused and nuanced interventions begins to emerge (Fig. 3). The well-intentioned but often blunt instrument of public reporting for all potential consumers as patients may evolve into a more refined strategy of developing excellence in data reporting for those clinical conditions or events where evidence indicates patients or families are more likely to exercise choice in terms of providers, and health outcomes are affected. Increasingly, we should see health-care regulation and payment reform focus on enforcing and rewarding the concentration of clinical services to high volume providers where the evidence supports volume as a determinant of patient outcome. Though highly controversial and dependent on workforce issues for implementation, the evidence-base is beginning to identify what types of physicians predictably achieve better compliance with guidelines or better patient outcomes in particular clinical conditions and settings. Targeted interventions at high-risk groups—either in the form of literacy campaigns or offsetting cost for health promotion and preventive care (e.g. nicotine replacement therapy) also show promise. In terms of technology, discrete yet powerful initiatives such as shared decision support systems and telemonitoring programmes have been shown to work.


Figure 3
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  		Figure 3 Examples of refined reforms for quality improvement 2007–10

 

   Conclusion
Top
 Abstract
 Background and Overview
 QEI: a taxonomy to...
 Conceptual framework for...
 Conclusion
Funding
 References
 
Basing policy and managerial decisions on evidence seems both prudent and rational, however, there are at least four obstacles to evidence-based health reforms for quality improvement.
  1. the paucity of rigorous studies that evaluate the impact of interventions seeking to improve quality,
  2. the available evidence is often dominated by studies from the USA, which is in many ways a unique health-care system, thus raising questions about applicability and transferability of research findings,
  3. the difficulty of relating the evidence-base to the complexity of ‘real world’ problems and varying country contexts,
  4. insufficient information about costs versus benefits of implementing quality interventions.

Nevertheless there is growing recognition of the potential benefits that could accrue from systematic, evidenced-based approaches to managerial decision-making and policy formulation focused on reforms for predictable quality improvements in health care [7, 8].

A common challenge unifying all countries is the imperative to develop predictable capacity for quality improvement in health services. The evolution of the field of quality measurement provides useful and sobering lessons. It has taken about three decades for quality measurement to move from an art to what could now be defended as a newly emerging science, which is adopted and adapted worldwide. Our collective task is to move from the art to the science in quality improvement, and much more rapidly than over three decades. International collaborations do exist for common measurement but still need to be developed to work towards a consensus on conceptual frameworks, and decision support for designing national reforms.

A commentary about the conduct of policy and government in respect to health care in England in ‘The Times’ of 1876 observed that ‘science is held to be superfluous.... at best regarded as a reserve force for the rectification of blunders, or as a means of securing, in a dignified and imposing manner, the door of a stable from which the steed has already been stolen’ [10]. More than 100 years later, science continues to be underused. Evidence has an important role to play in guiding decisions of policymakers, clinical leaders and managers. It is undoubtedly true that applying evidence in complex decisions is rarely straightforward. Decision makers have to juggle competing claims for resources and effort; incorporate some value judgements into their considerations; and integrate new initiatives both with processes already in place and within the context of the wider health-care system in which they operate. These difficulties notwithstanding, easier access to and greater reliance on evidence proffers considerable rewards in improving quality.


   Funding
Top
 Abstract
 Background and Overview
 QEI: a taxonomy to...
 Conceptual framework for...
 Conclusion
 Funding
References
 
The models and approaches described in this article represent work over the past decade funded by several organizations including The Commonwealth Fund, The Health Foundation and The Nuffield Trust. The findings and conclusions are those of the researchers and do not reflect the views of the Foundations.


   References
Top
 Abstract
 Background and Overview
 QEI: a taxonomy to...
 Conceptual framework for...
 Conclusion
 Funding
 References
 

  1. Cochrane Database of Systematic Reviews (2007) London: John Wiley & Sons, Ltd. http://www3.interscience.wiley.com/cgi-bin/mrwhome/106568753/HOME?CRETRY=1&SRETRY=0.

  2. Sackett DL, Rosenberg WMC, Muir Gray JA, Haynes RB, Richardson WS. Evidence-based medicine: what it is and what it isn't. BMJ (1996) 312:71–2.[Free Full Text]

  3. Oxman AD, Sackett DL, Guyatt GH. Users' guides to the medical literature. I. How to get started. The Evidence-Based Medicine Working Group. JAMA (1993) 270:2093–5.[Abstract/Free Full Text]

  4. Kilpatrick KE, Lohr KN, Leatherman S, Pink G, Buckel JM, Legarde C, Whitener L. The insufficiency of evidence to establish the business case for quality. Int J Qual Health Care (2005) 17:347–55.[Abstract/Free Full Text]

  5. Coulter A, Ellins J. The Effectiveness of Patient-Focused Interventions. (2006) London: The Health Foundation.

  6. Sutherland K, Leatherman S. Regulation and Quality Improvement: A Review of the Evidence (2006) London: The Health Foundation.

  7. Shojania KG, McDonald KM, Wachter RM, Owens DK. Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (2005) Rockville, MD: Agency for Healthcare Research and Quality.

  8. Clancy CM, Cronin K. Evidence-based decision making: global evidence, local decisions. Health Affairs (2005) 24:151–62.[Abstract/Free Full Text]

  9. Emanuel EJ, Emanuel LL. What is accountability in health care? Ann Intern Med (1996) 124:229–39.[Abstract/Free Full Text]

  10. Sheard S, Donaldson L. The Nation's Doctor (2006) Oxon: Radcliffe. 14.

Accepted for publication September 4, 2007.


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