In my Data-Driven Innovation in Services course, I learned the role of customer data in businesses: services and products. Customer data is one of the most essential details for businesses, as it provides insights into business operations, influencing marketing, sales, and innovations. It also serves as a valuable resource for improving services. However, I found that it does not really provide all the solutions, even though it could.

In healthcare specifically, customer data can be defined as clinically relevant data obtained on a patient, client, service user, customer, or consumer for use in the healthcare setting. Looking into the NHS case study I worked on gives some handy examples of how these data help improve healthcare services. The NHS provides a wide range of healthcare services, like general practice, hospital inpatient and outpatient appointments, clinic appointments, and laboratory diagnosis, to millions of patients across the UK For instance, according to NHS England, 31 million people accessed healthcare services in September 2023 alone (NHS England, 2023). Handling this large customer base necessitates a high level of efficiency and adaptability within the healthcare system, and to provide efficient services, data is very useful (Asri, 2015).

Across the UK, the various NHS directorates use patient data to improve their services. These can range from simple activities to complex ones. Clinical professionals at the NHS use biological data, medical history, and test results of patients to understand new diseases and therapies, predict outcomes at earlier stages, and make real-time decisions. In doing these, they come across large data sets, which are not called big data. These data can inform decisions as well as referrals. Essentially, these growing data sets make it necessary for institutions to find better ways of managing them (Afolabi and Erhum, 2003). One way this is done in the NHS is through the introduction of Electronic Health Records Systems (EHR), which store these data in a way that is easy to use. The EHRs also help in collaboration between different health facilities. In this case, hospitals under the same Trust will have similar EHRs, which allows them to exchange patient data. All these are aimed at improving patient care seamlessly. 

Beyond these, the EHRs help in the planning and management of other activities. They allow tracking patient attendance, planning and managing their finances, and estimating items needed for stocking the pharmacy and its stores to reduce wait times. These are combined with ethnographic studies as well. By collecting structured and unstructured customer data, NHS Trust can address customer concerns and improve the patient experience (Black et al., 2021). Despite all of the data that are being collected, it is still not enough to provide solutions for clinical trials. While working on the essay for this course, I found that clinical trials faced challenges ranging from low turnout of volunteers to no compensation to volunteers (Bickman et al., 2021). I could recall saying that all these were data issues. The low turnout negatively impacted the trial exercises because of the insufficient participants, which will prove lower statistical power. I am wondering if, with these whole datasets, these challenges could be handled. While this is my thought, I am quite aware that there are challenges, such as accessibility to health services, that could restrict this, however, I think this can be a solution for most trials, especially whenever there is a pandemic and a pressing need for a vaccine.

Well, I may just be dreaming, but I think there is a close relationship between imagination and reality.

Customer Data: opportunities and limitations / Onyebuchi Enechukwu / Knowledge Integration and Project Planning: Data, Inequality and Society (2023-24) by is licensed under a