Dionne S. Kringos

The breadth of primary care: a systematic literature review of its core dimensions

BackgroundEven though there is general agreement that primary care is the linchpin of effective health care delivery, to date no efforts have been made to systematically review the scientific evidence supporting this supposition. The aim of this study was to examine the breadth of primary care by identifying its core dimensions and to assess the evidence for their interrelations and their relevance to outcomes at (primary) health system level.MethodsA systematic review of the primary care literature was carried out, restricted to English language journals reporting original research or systematic reviews. Studies published between 2003 and July 2008 were searched in MEDLINE, Embase, Cochrane Library, CINAHL, Kings Fund Database, IDEAS Database, and EconLit.ResultsEighty-five studies were identified. This review was able to provide insight in the complexity of primary care as a multidimensional system, by identifying ten core dimensions that constitute a primary care system. The structure of a primary care system consists of three dimensions: 1. governance; 2. economic conditions; and 3. workforce development. The primary care process is determined by four dimensions: 4. access; 5. continuity of care; 6. coordination of care; and 7. comprehensiveness of care. The outcome of a primary care system includes three dimensions: 8. quality of care; 9. efficiency care; and 10. equity in health. There is a considerable evidence base showing that primary care contributes through its dimensions to overall health system performance and health.ConclusionsA primary care system can be defined and approached as a multidimensional system contributing to overall health system performance and health.

Europe’s Strong Primary Care Systems Are Linked To Better Population Health But Also To Higher Health Spending

Strong primary care systems are often viewed as the bedrock of health care systems that provide high-quality care, but the evidence supporting this view is somewhat limited. We analyzed comparative primary care data collected in 2009-10 as part of a European Union-funded project, the Primary Health Care Activity Monitor for Europe. Our analysis showed that strong primary care was associated with better population health; lower rates of unnecessary hospitalizations; and relatively lower socioeconomic inequality, as measured by an indicator linking education levels to self-rated health. Overall health expenditures were higher in countries with stronger primary care structures, perhaps because maintaining strong primary care structures is costly and promotes developments such as decentralization of services delivery. Comprehensive primary care was also associated with slower growth in health care spending. More research is needed to explore these associations further, even as the evidence grows that strong primary care in Europe is conducive to reaching important health system goals.

The european primary care monitor: structure, process and outcome indicators

BackgroundScientific research has provided evidence on benefits of well developed primary care systems. The relevance of some of this research for the European situation is limited.There is currently a lack of up to date comprehensive and comparable information on variation in development of primary care, and a lack of knowledge of structures and strategies conducive to strengthening primary care in Europe. The EC funded project Primary Health Care Activity Monitor for Europe (PHAMEU) aims to fill this gap by developing a Primary Care Monitoring System (PC Monitor) for application in 31 European countries. This article describes the development of the indicators of the PC Monitor, which will make it possible to create an alternative model for holistic analyses of primary care.MethodsA systematic review of the primary care literature published between 2003 and July 2008 was carried out. This resulted in an overview of: (1) the dimensions of primary care and their relevance to outcomes at (primary) health system level; (2) essential features per dimension; (3) applied indicators to measure the features of primary care dimensions. The indicators were evaluated by the project team against criteria of relevance, precision, flexibility, and discriminating power. The resulting indicator set was evaluated on its suitability for Europe-wide comparison of primary care systems by a panel of primary care experts from various European countries (representing a variety of primary care systems).ResultsThe developed PC Monitor approaches primary care in Europe as a multidimensional concept. It describes the key dimensions of primary care systems at three levels: structure, process, and outcome level. On structure level, it includes indicators for governance, economic conditions, and workforce development. On process level, indicators describe access, comprehensiveness, continuity, and coordination of primary care services. On outcome level, indicators reflect the quality, and efficiency of primary care.ConclusionsA standardized instrument for describing and comparing primary care systems has been developed based on scientific evidence and consensus among an international panel of experts, which will be tested to all configurations of primary care in Europe, intended for producing comparable information. Widespread use of the instrument has the potential to improve the understanding of primary care delivery in different national contexts and thus to create opportunities for better decision making.

The Dutch health care performance report: seven years of health care performance assessment in the Netherlands

In 2006, the first edition of a monitoring tool for the performance of the Dutch health care system was released: the Dutch Health Care Performance Report (DHCPR). The Netherlands was among the first countries in the world developing such a comprehensive tool for reporting performance on quality, access, and affordability of health care. The tool contains 125 performance indicators; the choice for specific indicators resulted from a dialogue between researchers and policy makers. In the ‘policy cycle’, the DHCPR can rationally be placed between evaluation (accountability) and agenda-setting (for strategic decision making). In this paper, we reflect on important lessons learned after seven years of health care system performance assessment. These lessons entail the importance of a good conceptual framework for health system performance assessment, the importance of repeated measurement, the strength of combining multiple perspectives (e.g., patient, professional, objective, subjective) on the same issue, the importance of a central role for the patients’ perspective in performance assessment, how to deal with the absence of data in relevant domains, the value of international benchmarking and the continuous exchange between researchers and policy makers.

Is the readmission rate a valid quality indicator? A review of the evidence

Introduction Hospital readmission rates are increasingly used for both quality improvement and cost control. However, the validity of readmission rates as a measure of quality of hospital care is not evident. We aimed to give an overview of the different methodological aspects in the definition and measurement of readmission rates that need to be considered when interpreting readmission rates as a reflection of quality of care. Methods We conducted a systematic literature review, using the bibliographic databases Embase, Medline OvidSP, Web-of-Science, Cochrane central and PubMed for the period of January 2001 to May 2013. Results The search resulted in 102 included papers. We found that definition of the context in which readmissions are used as a quality indicator is crucial. This context includes the patient group and the specific aspects of care of which the quality is aimed to be assessed. Methodological flaws like unreliable data and insufficient case-mix correction may confound the comparison of readmission rates between hospitals. Another problem occurs when the basic distinction between planned and unplanned readmissions cannot be made. Finally, the multi-faceted nature of quality of care and the correlation between readmissions and other outcomes limit the indicators validity. Conclusions Although readmission rates are a promising quality indicator, several methodological concerns identified in this study need to be addressed, especially when the indicator is intended for accountability or pay for performance. We recommend investing resources in accurate data registration, improved indicator description, and bundling outcome measures to provide a more complete picture of hospital care.

The influence of context on the effectiveness of hospital quality improvement strategies: a review of systematic reviews

BackgroundIt is now widely accepted that the mixed effect and success rates of strategies to improve quality and safety in health care are in part due to the different contexts in which the interventions are planned and implemented. The objectives of this study were to (i) describe the reporting of contextual factors in the literature on the effectiveness of quality improvement strategies, (ii) assess the relationship between effectiveness and contextual factors, and (iii) analyse the importance of contextual factors.MethodsWe conducted an umbrella review of systematic reviews searching the following databases: PubMed, Cochrane Database of Systematic Reviews, Embase and CINAHL. The search focused on quality improvement strategies included in the Cochrane Effective Practice and Organisation of Care Group taxonomy. We extracted data on quality improvement effectiveness and context factors. The latter were categorized according to the Model for Understanding Success in Quality tool.ResultsWe included 56 systematic reviews in this study of which only 35 described contextual factors related with the effectiveness of quality improvement interventions. The most frequently reported contextual factors were: quality improvement team (n = 12), quality improvement support and capacity (n = 11), organization (n = 9), micro-system (n = 8), and external environment (n = 4). Overall, context factors were poorly reported. Where they were reported, they seem to explain differences in quality improvement effectiveness; however, publication bias may contribute to the observed differences.ConclusionsContextual factors may influence the effectiveness of quality improvement interventions, in particular at the level of the clinical micro-system. Future research on the implementation and effectiveness of quality improvement interventions should emphasize formative evaluation to elicit information on context factors and report on them in a more systematic way in order to better appreciate their relative importance.

Political, cultural and economic foundations of primary care in Europe

This article explores various contributing factors to explain differences in the strength of the primary care (PC) structure and services delivery across Europe. Data on the strength of primary care in 31 European countries in 2009/10 were used. The results showed that the national political agenda, economy, prevailing values, and type of healthcare system are all important factors that influence the development of strong PC. Wealthier countries are associated with a weaker PC structure and lower PC accessibility, while Eastern European countries seemed to have used their growth in national income to strengthen the accessibility and continuity of PC. Countries governed by left-wing governments are associated with a stronger PC structure, accessibility and coordination of PC. Countries with a social-security based system are associated with a lower accessibility and continuity of PC; the opposite is true for transitional systems. Cultural values seemed to affect all aspects of PC. It can be concluded that strengthening PC means mobilising multiple leverage points, policy options, and political will in line with prevailing values in a country.

Primary Care Efficiency Measurement Using Data Envelopment Analysis: A Systematic Review

There is a gap between the demand and supply of efficiency analyses within primary care (PC), despite the threatening financial sustainability of health care systems. This paper provides a systematic literature review on PC efficiency analysis using Data Envelopment Analysis (DEA). We reviewed 39 DEA applications in PC, to understand how methodological frameworks impact results and influence the information provided to decision makers. Studies were combined using qualitative narrative synthesis. This paper reports data for each efficiency analysis on the: 1) evaluation context; 2) model specifications; 3) application of methods to test the robustness of findings; 4) presentation of results. Even though a consistent number of analyses aim to support policymakers and practice managers in improving the efficiency of their PC organizations, the results indicate that DEA –at least when applied to PC- is a methodology still in progress; it needs to be further advanced to meet the complexity that characterizes the production of PC outcomes. Future studies are needed to fill some gaps in this particular domain of research, such as on the standardization of methodologies and the improvement of outcome research in PC. Most importantly, further studies should include extensive uncertainty analyses and be based on good evidence-based rationales. We suggest a number of considerations to academics and researchers to foster the utility of efficiency measurement for the decision making purposes in PC.

Living In A Country With A Strong Primary Care System Is Beneficial To People With Chronic Conditions

In light of the growing pressure that multiple chronic diseases place on health care systems, we investigated whether strong primary care was associated with improved health outcomes for the chronically ill. We did this by combining country- and individual-level data for the twenty-seven countries of the European Union, focusing on peoples self-rated health status and whether or not they had severe limitations or untreated conditions. We found that people with chronic conditions were more likely to be in good or very good health in countries that had a stronger primary care structure and better coordination of care. People with more than two chronic conditions benefited most: Their self-rated health was higher if they lived in countries with a stronger primary care structure, better continuity of care, and a more comprehensive package of primary care services. In general, while having access to a strong primary care system mattered for people with chronic conditions, the degree to which it mattered differed across specific subgroups (for example, people with primary care-sensitive conditions) and primary care dimensions. Primary care reforms, therefore, should be person centered, addressing the needs of subgroups of patients while also finding a balance between structure and service delivery.

How to achieve optimal organization of primary care service delivery at system level: lessons from Europe

OBJECTIVE To measure the relative efficiency of primary care (PC) in turning their structures into services delivery and turning their services delivery into quality outcomes. DESIGN Cross-sectional study based on the dataset of the Primary Healthcare Activity Monitor for Europe project. Two Data Envelopment ANALYSIS models were run to compare the relative technical efficiency. A sensitivity analysis of the resulting efficiency scores was performed. SETTING PC systems in 22 European countries in 2009/2010. MAIN OUTCOME MEASURES Model 1 included data on PC governance, workforce development and economic conditions as inputs and access, coordination, continuity and comprehensiveness of care as outputs. Model 2 included the previous process dimensions as inputs and quality indicators as outputs. RESULTS There is relatively reasonable efficiency in all countries at delivering as many as possible PC processes at a given level of PC structure. It is particularly important to invest in economic conditions to achieve an efficient structure-process balance. Only five countries have fully efficient PC systems in turning their services delivery into high quality outcomes, using a similar combination of access, continuity and comprehensiveness, although they differ on the adoption of coordination of services. There is a large variation in efficiency levels obtained by countries with inefficient PC in turning their services delivery into quality outcomes. CONCLUSIONS Maximizing the individual functions of PC without taking into account the coherence within the health-care system is not sufficient from a policymakers point of view when aiming to achieve efficiency.