The Identification of Obstacles to Breast Cancer Screening Programmes Using a Health Systems Approach

Zohreh Ghomian^*
*Correspondence: Zohreh Ghomian, Department of Health in Disasters and Emergencies, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran, Email:

Keywords

Breast cancer • Screening programmes • Health systems

Introduction

It is now well-established that organised, population-based screening programmes for breast cancer are beneficial for women above a particular age. However, in reality, cancer screening programmes frequently fall short of their potential. This isn't primarily due to a lack of knowledge about breast cancer screening procedures. On the basis of solid data, the European Union (EU) has issued unambiguous guidelines on organised breast cancer screening. Instead, it is as a result of screening's shortcomings in its current form. This is due to a variety of factors. Others are outside the organisational framework of screening programmes, such to the capacity to engage target communities or technical components of screening activities, such as inadequate equipment or poorly trained employees.

Description

In this regard, breast cancer screening is not special. There are numerous well-known treatments with distinct evidence-based routes, such as the management of diabetes or the control of hypertension, yet in practise, results vary widely. Health systems research has expanded as a result of the awareness of these barriers to efficient implementation. This research aims to identify these obstacles and determine ways to overcome them. The majority of health systems involve soft systems, wherein the system in question is populated by humans who act in ways that achieve change, in spite of constraints, while being influenced by their environment and values. Although the advantages of population-based breast cancer screening are now widely acknowledged, programmes frequently fall short of their full potential in practise. In order to comprehend the elements that affect screening programmes' results, we present a conceptual model in this study that places screening programmes within the context of the larger health system. In our opinion, the overall screening system consists of several sub-systems that work together to identify at-risk populations, produce knowledge about how well they work, increase uptake, run the programme, and optimise follow-up and treatment assurance. We created the Barriers to Effective Screening Tool (BEST) based on this paradigm to analyse population-based screening programmes run by the government from the viewpoint of health systems. We tested the tool, which was designed as a self-assessment tool, with key informants in six European nations: Estonia, Finland, Hungary, Italy, and Spain [1].

Although the advantages of population-based screening for breast cancer are now well acknowledged, in reality, programmes frequently fall short of their full potential. In this article, we offer a conceptual model that places screening programmes within the context of the larger health system in order to better understand the variables affecting their results. In our opinion, the overall screening system consists of a number of sub-systems that work together to: identify at-risk populations; generate knowledge about effectiveness; maximise uptake; manage the programme; and optimise follow-up and assurance of following treatment. In accordance with this paradigm, we created the Barriers to Effective Screening Tool (BEST) to analyse population-based screening programmes run by the government from the viewpoint of health systems. We piloted the self-assessment measure, which was developed in six European nations (Estonia, Finland, Hungary, Italy, and Spain), with key informants [2].

Studies that compared a systems approach to standard care in any healthcare setting with any patient and published quantifiable data for any outcomes for both groups were included; we searched Medline, Embase, HMIC, Health Business Elite, Web of Science, Scopus, PsycINFO, and CINAHL for pertinent studies. Data was separately and duplicately extracted once they were screened. Study designs and whether they included patient or service outcomes were taken into account when stratifying study results. ORs were used in a meta-analysis with Revman software V.5.3, and I2 statistics were used to measure heterogeneity [3].

By taking into account the numerous components involved in patient care and the numerous variables affecting health, a systems approach enhances health. A systems approach can assist with the design and integration of people, processes, policies, and organisations to promote better health at a reduced cost by understanding how these aspects operate independently as well as how they depend on one another. With various tools available for the needs at various levels and across levels, these approaches can be helpful for all levels of the health system-patient-clinician interaction, health care unit, organization, community, and nation. These tools include queuing theory and operations management to ensure that resources are available when patients need them; production system methods and other management systems to help organisations continuously improve their operations and identify problems [4].

More advanced data systems and interoperable devices, a supportive culture and leadership, patient, family, clinician, and general public engagement, new incentive structures, and particular technological supports will all be needed to spread these systems concepts more widely. Although there are certain islands of brilliance in the American health system, overall performance is currently below potential due to uneven patient safety, rising costs and stagnant efficiency, and inconsistent use of scientific evidence. Despite the fact that overall health care spending has increased, some research indicate that up to 30% of those costs may be unnecessary or wasteful. Furthermore, only 50% of patients receive the evidence-based care recommended by guidelines, indicating that the application of evidence to clinical care is inconsistent [5].

Conclusion

A limited capacity for measuring is one of the implementation issues that hinder efforts to address these issues. For instance, the inability to reach consensus on what constitutes patient injury has hampered efforts to increase safety. Since several definitions are now in use, estimates of the percentage of safely given care vary. Institutions trying to enhance their care procedures and evaluate their performance against others have been hampered by the absence of defined terminology and measurements. The complexity of contemporary clinical care, which exceeds the capabilities of individual humans, makes implementation attempts more difficult. An intensive care unit (ICU) patient on average needs 200 clinical interventions per day, which is more than any one care practitioner can handle. This illustrates the level of complexity. Additionally, for these critical care patients, this same practitioner may need to monitor and respond to up to 240 vital sign inputs. Complexity is not just found in hospital settings. The average primary care physician in Massachusetts managed 370 distinct primary diagnoses, each accompanied by a set of evidence-based practises, 600 distinct drugs, and roughly 150 distinct laboratory tests, according to a 2008 study of a large multispecialty practise.

Acknowledgement

None.

Conflict of Interest

None.

References

1. Bosch-Capblanch, Xavier. "Guidance for evidence-informed policies about health systems: Rationale for and challenges of guidance development." PLoS Med 9 (2012): e1001185.

Google Scholar, Crossref, Indexed at

2. Lavis, John N. "Guidance for evidence-informed policies about health systems: Linking guidance development to policy development." PLoS Med 9 (2012): e1001186.

Google Scholar, Crossref, Indexed at

3. Lewin, Simon. "Guidance for evidence-informed policies about health systems: Assessing how much confidence to place in the research evidence." PLoS Med 9 (2012): e1001187.

Google Scholar, Crossref, Indexed at

4. Brouwers, Melissa C. "AGREE II: Advancing guideline development, reporting and evaluation in health care." CMAJ 182 (2010): E839-E842.

Google Scholar, Crossref, Indexed at

5. Kung, Justin, Ram R. Miller and Philip A. Mackowiak. "Failure of clinical practice guidelines to meet institute of medicine standards: Two more decades of little, if any, progress." Arch Int Med 172 (2012): 1628-1633.

Google Scholar, Crossref, Indexed at