Introduction
Healthcare disparities present a significant problem surrounding the delivery of medical services. Inter-group differences related to access to care or the quality of treatment run counter to the principle of equality. Considering this problem’s significance and impact, the purpose of the paper is to expand on disparities, contributing factors, potential solutions, and the details of their implementation.
Elements of the Problem
The problem is recognized both in modern research and at the governmental level. “Systematic, unfair, and avoidable differences” in the outcomes of treatment and the details of care provision exist in any country and relate to multiple characteristics, including social position (Penman-Aguilar et al., 2016, p. S34). Some inequalities are associated with discrimination on the basis of unchangeable demographic characteristics – ethnicity, gender, and sexual orientation (Penman-Aguilar et al., 2016; Young, Pollack, & Rutkow, 2015). It takes place when prejudiced attitudes to some group lead to the unjust and unfair treatment of its members. In healthcare, it can be manifested in different outcomes, ranging from refusal to provide services to varying mortality rates.
Apart from that, health disparities can be caused by the inequality of opportunity. As is concluded by Thompson, Molina, Viswanath, Warnecke, and Prelip (2016), the unequal distribution of power and wealth contributes to disparities. Some groups of the population are statistically more likely than others to have access to financial resources and better job opportunities, which impacts health outcomes. Low-income individuals and those with low educational attainment have less access to qualified specialists compared to wealthier and more educated fellow nationals (Pinto et al., 2016). Thus, financial opportunities that are linked to education heavily affect healthcare consumers’ ability to receive high-quality treatment on time.
Analysis
Relevance/Importance
In general, the problem of healthcare disparities is extremely broad and requires significant changes at the systemic level to be solved or at least reduced. As a nurse, I would like to promote equality and just attitudes toward patients. Also, to demonstrate the commitment to nursing values, it is critical for me to make sure that my clients are not discriminated against on the basis of age, gender, ethnicity, and socio-economic position.
The context for the Problem
Unlike many other problems, disparities are not caused by the growth of care processes’ complexity. It is not a new healthcare issue – inequalities between large groups of patients have probably existed for many decades. However, they came to the attention of the U.S. public less than thirty-five years ago when the Department of Health revealed significant differences in racial and ethnic groups’ health outcomes (Penman-Aguilar et al., 2016). In the broad context, the selected problem takes place due to global processes beyond the scope of the healthcare system, including income distribution. However, in some aspects of the issue, for instance, healthcare specialists’ prejudices towards particular populations, the problem is easier to reduce.
Affected Populations
For different medical conditions and situations, it is possible to single out specific disparity groups. However, based on research, it is possible to list some categories of patients that are more likely to experience disparities. Among them are low-income/uneducated/homeless populations, racial/ethnic minorities, LGBT people, and individuals with disabilities (Penman-Aguilar et al., 2016; Pinto et al., 2016). Thus, when it comes to health inequities, there are many high-risk categories.
Considering Options
Potential solutions that can decrease healthcare disparities include strategies for community empowerment, targeted screenings based on socio-demographic data, and provider education to eliminate implicit bias. The first option involves working with particular communities and encouraging people to identify their specific health problems and collaborate with healthcare providers (Thompson et al., 2016). This idea gives rise to many experimental interventions, including the creation of task forces that work with disparity groups, patient education targeted at specific populations, and community-based research projects (Thompson et al., 2016). To me, the methods above are time-consuming and do not allow for countrywide improvement.
The second option that can be found in the modern peer-reviewed literature is the collection of socio-demographic data that is automatically uploaded to patients’ EMRs. Using patient data and research results concerning health disparities in particular populations, it is possible to identify high-risk groups for specific conditions and conduct targeted screenings (Pinto et al., 2016). The practice allows making screening and treatment decisions that are informed by data on disparities. In my opinion, apart from the listed options, it is also possible to reduce the problem by eliminating prejudice in healthcare specialists with the help of ethical education. This idea is not widely discussed in the selected literature, and it is possibly seen as unnecessary because the principle of non-discrimination is already taught to professionals in the field.
Solution
The solution that is based on the collection and use of patients’ socio-demographic information can be chosen as the most appropriate and practically relevant. Concerning its benefits, the decision proposed by Pinto et al. (2016) allows uploading clients’ survey responses to their EMRs automatically and in a prompt manner. Therefore, it is easy to use, and the procedure is not time-consuming. However, its potential disadvantages relate to the threats of data breaches and patients’ unwillingness to reveal some information resulting from stigma.
Ethical Implications
Despite its numerous advantages, the selected solution has some ethical implications, such as patients’ reactions to questions and potential data privacy issues. Firstly, since some demographic characteristics, for instance, belonging to sexual minorities, are still stigmatized, it is pivotal to formulate questions in a professional way (Pinto et al., 2016). For instance, terms with any negative connotations that can be found offensive should be excluded (Pinto et al., 2016). Secondly, to avoid discontent, the aims of data collection and privacy concerns need to be discussed with patients in some way. From an ethical point of view, the advantages of implementing the solution include the use of secure servers for data storage and transfer to EMRs. Also, it eliminates the need to ask sensitive questions directly (Pinto et al., 2016). At the same time, as it has been said, potential disadvantages are presented by patients’ negative perceptions of the collection of data that will not be de-identified.
Implementation
To implement the solution, a healthcare organization would need to select, purchase, and install EMR software or use already installed programs. Then, to organize the data collection process, it would be essential to define the main patient characteristics associated with disparities, develop clear and professionally formulated questions, and create an online questionnaire. Moreover, it would be critical to find and install equipment for data gathering. For example, Pinto et al. (2016) use iPads, but less expensive options are also available. Then, patients would need to use their medical record numbers to answer questions, and new data will be added to their EMRs. After that, socio-demographic details would be used to conduct statistical analysis or propose interventions to ensure disparity groups’ access to needed care.
Conclusion
Finally, healthcare disparities can be caused by numerous factors, including discrimination, biases, and unequal distribution of resources. Potential solutions are presented by measures to eliminate bias in healthcare professionals, community empowerment, and adding socio-demographic data to patients’ EMRs to organize targeted screenings or conduct research. Ethical implications of the options have to be considered prior to implementation, which involves ensuring data protection and proper formulation of questions.
References
Penman-Aguilar, A., Talih, M., Huang, D., Moonesinghe, R., Bouye, K., & Beckles, G. (2016). Measurement of health disparities, health inequities, and social determinants of health to support the advancement of health equity. Journal of Public Health Management and Practice, 22(Suppl. 1), S33-S42. Web.
Pinto, A. D., Glattstein-Young, G., Mohamed, A., Bloch, G., Leung, F. H., & Glazier, R. H. (2016). Building a foundation to reduce health inequities: Routine collection of sociodemographic data in primary care. The Journal of the American Board of Family Medicine, 29(3), 348-355. Web.
Thompson, B., Molina, Y., Viswanath, K., Warnecke, R., & Prelip, M. L. (2016). Strategies to empower communities to reduce health disparities. Health Affairs, 35(8), 1424-1428. Web.
Young, J. L., Pollack, K., & Rutkow, L. (2015). Review of state legislative approaches to eliminating racial and ethnic health disparities, 2002–2011. American Journal of Public Health, 105(Suppl. 3), S388-S394. Web.