Identifying patients with good results in communities with unsatisfactory care can be the key to finding success factors.
There are several initiatives that advocate a high value care in order to contribute to greater efficiency and sustainability of health systems. This value is interpreted as obtaining better health gains relative to the costs, which translates into better use of available resources (1). The more traditional approach to detect this potential value was based on the identification of patients with poor health in order to establish subsequent remedial measures that lead to a good result.
In an article published in The New England Journal of Medicine, Sequist and Taveras (2) propose to analyze the problem from a different perspective:
- Identify patients who are doing good (“positive outliers“)
- Analyze what factors may influence their good health
- Disseminate the identified success factors and expand them to the rest of the system
To accomplish this, the authors propose a new approach to measure and analyze information. It’s about relating the supply system, the community and the patient in an effort integrated as a strategy with the aim of improving population health. This type of approach strengthens assessment models that AQuAS is applying in areas such as attention to chronicity and integrated health and social care in our country (3-5).
Health determinants and social determinants
According to the authors, the population’s health status is the result of a complex web of interactions between individual patient characteristics and other determinants of health dependent of the area of residence (community). The more evident is that most determinants that affect the health of people would be generated outside the health service delivery system. These factors, that some studies estimated constitute about 80%, have a profound effect on how the patients interact with the system and consequently, the quality of care they receive and their health outcomes.
Thus, the policies and the actions in areas such as housing, employment or social welfare can not be decoupled from assessments on health and from the health system. We must emphasize the need of introducing in the context of public and social policies, the concept of health as an item to be referred to in all its dimensions and evaluated in an integrated manner, together with other social determinants besides the health system (6).
The challenge of evaluating integrated care
Given this new approach it’s necessary to analyze the performance at the community level, usually focused on the area of residence. This analysis will allow provision system to obtain a better understanding of its population and identify where patients are grouped within communities, as well as what are the environmental factors that can affect health outcomes. This represents a quality leap beyond traditional analysis of each service providing system units (hospitals, primary care, care teams, etc.). Among the advantages of this new strategy we must specify the identification of patients who reside in communities where the quality of care and the results are not satisfactory, the detection of promising approaches for patients in these communities and integrating these successful strategies into care plans for the patients.
The definition of the community and the analysis of data for evaluation
To perform this type of assessment it’s necessary to first have a good working definition of “community” as well as a robust infrastructure for data analysis. The second step consists in identifying positive outliers – extreme values with good results- in communities with poor performance or with a high burden of disease – hotspot communities– more specifically, the identification of treated patients with good health outcome in an environment of unsatisfactory service provision and, in particular, those who historically had poor results and who recently improved. Once the success factors are identified, we would move on to the phase of climbing or extending the strategies in the rest of the territory.
In the precise case of the project assessment of the care for chronic diseases, the territories with programs or models of care to chronic diseases seeking greater care integration have been identified, given the large impact on morbidity and mortality and the use of resources caused by a complex chronic population. Consequently, the analysis from this territorial or community vision -taking into account the various healthcare resources and interventions in the territory- has allowed us to identify programs or models that perform better in relation to a number of health result indicators of various quality of care dimensions. This way we can select those that are “outstanding” (good outcomes for patients) and then identify good practices and success factors.
The last step is the integration of these strategies or models with the plans of patient care. Sequist and Taveras cite some other examples of community initiatives that relate to clinical practice (care or welfare services provision) as communicating vessels between the data analysis and the interventions that can be made in various areas.
This analytical approach can have several potential uses and can also be a powerful tool for addressing socioeconomic inequalities in health outcomes; as long as they focus on the differences at the context level, on patients’ membership to a community, on differences in gender, income, or education. Finally the authors mention that, as a prerequisite for a successful implementation, it’s necessary to have a well-defined operational infrastructure in which funding is aligned with the approach of linking the community and the health care.
Similarly, sustainability challenges also occur, as it may be that the service providing system “buys” this concept of factors that historically have been considered outside the area of influence or responsibility of health care. We must also ensure that resources and community interventions are safe and reliable if we want to have the support of professionals to refer patients to these resources as well as determining the most appropriate information updating intervals.
To conclude, we’re looking at an approach that instead of focusing on the “non-compliant” patients, it’s based on the observance and analysis of the best, especially in disadvantaged areas, with the purpose of applying the same keys to success to other territories.
(1) Porter ME. What is value in healthcare?. N Engl J Med. 2010;26:2477-81.
(2) Sequist TD, Taveras EM. Clinic-community linkages for high-value care. N Engl J Med. 2014;371(23):2148-50.
(3) Desenvolupament d’un marc conceptual i indicadors per avaluar l’atenció a la cronicitat. Primer informe. Barcelona: AQuAS; 2013.
(4) Consens i selecció d’indicadors per avaluar l’atenció a la cronicitat. Segon informe. Barcelona: AQuAS; 2013.
(5) Serra-Sutton V, Montané C, Pons JMV, Espallargues M. Avaluació externa de 9 models col•laboratius d’atenció social i sanitària a Catalunya. Barcelona: AQuAS; 2014 (en premsa).
(6) Determinants socials i econòmics de la salut. Efectes de la crisi econòmica en la salut de la població de Catalunya. Barcelona: Observatori del Sistema de Salut de Catalunya. AQuAS; 2014.