How can you use data to identify disparities in healthcare outcomes?

One thing that I have found in my over 40 years of nursing is that the numbers may prove a known fact that health care disparities is indeed a problem, however, I’ve noticed very little follow through of any relevant solutions. Politics always play a major part, especially at election time. Let’s actually put faces with the data and do something noteworthy.

I've found keeping honest patient feedback is critical for the mission of providing healthcare equally across all platforms. When patients have a voice they have trust. That's what saves lives.

In my experience in a data driven health care system , the planners can identify the strengths and pitfalls of the existing system. One can compare their progress with other institutions both locally and internationally and prepare recommendations for planning future strategies in addition this kind of system also helps in making rationale decisions in all areas like Human Resources , training and planning subtle change management , by improving the capacities of existing employees and reducing morbidity and mortality, reducing complaints and improve patient outcomes, most of all it can reduce unnecessary departmental politics which work on personal likes and dislikes and bear no association to reality.

Honestly, the lack of data tells a story of its on as well. As far as patient feedback, surveys, and other engagement tools, we should acknowledge the demographics of patients who participate. Health literacy is also a barrier that creates disparities. There are certainly more layers than patient satisfaction.

This is particularly true in Nigeria where health indices are generally better in the south compared to the north. Factors responsible and correlated are level of education and standard of living which are generally higher in the south.

Data plays a crucial role in identifying disparities in healthcare by providing measurable insights into various aspects of healthcare delivery, including access, quality of care, outcomes, and resource allocation. By analyzing data on factors such as demographic information, health outcomes, disease prevalence, and healthcare utilization, researchers and policymakers can identify disparities in healthcare based on factors like race, ethnicity, socioeconomic status, geographical location, and gender. This information can then be used to develop targeted interventions and policies aimed at reducing these disparities and promoting health equity for all populations.

Data, especially when large and representative of the population helps detect patterns related to health disparity. Lifestyle, environmental factors are usually underlying factors within populations which result in health outcomes and most times have a greater effect on the immediate causes. For example, an area with high cases of diarrhea diseases but lacking potable water.

Data collection must be credible n honest for a study to be reliable n worthwhile. Data analysis impacts decision making in significant manner Programs educating about data analysis empowers students to have insight in their own work. National data collection is utmost requirement

Surveillance plays a crucial role especially in low and middle income countries. The integrated disease surveillance and response presents a clear strategy. Surveillance involves collection, collation, analysis, interpretation and dissemination of results to stakeholders for action. This process can be quantitative or qualitative with the use of developed tools and/or frameworks.

Collaboration is the key to advancement. However it must include basic principles of ethical communication, rationale thinking and should be non biased. Most colloborations fail due to un even contributions by the stake holder and lack of common goals. Identification of common goals to be implemented due to a certain proposed activity should be the initial priority.