George Yacoub – Group Director of IT / Group Chief Information Officer at Abu Dhabi Health Services Company (SEHA) talks about how data drives individual patient experience and impacts the larger healthcare industry
Data has already transformed the healthcare industry and patient experience in various ways. From proactive health predictions to supply chain optimisation, data has immense potential. However, it’s crucial to maintain data compliance while encouraging data democracy within organisations. Collaborative cross-functional teams and strategic technology investments are key.
“A cross-functional approach to utilising and processing data means focusing on team-to-team collaboration on data strategy, collection, validation, and other activities rather than leaving these responsibilities to a single individual or team,” says George Yacoub – Group Director of IT / Group Chief Information Officer at Abu Dhabi Health Services Company (SEHA).
Here are insights from SEHA’s CIO on leveraging data for healthcare success.
Excerpts from the interview;
How can data impact the healthcare industry, and the individual patient experience?
Data has already had a significant impact on healthcare across various areas. Here are some examples:
- Data can be utilised to analyse a patient’s lab results and electronic medical records (EMR) over a period of time, predicting potential health problems in the future and recommending proactive action plans.
- Data can be used to recommend changes in the supply chain and procurement of medications based on recent consumption trends.
- Data can help expand or scale down certain healthcare services to meet the demand of the local market in a specific geographical area, considering the demographics of that locality.
Tell us about the cross-functional teams you work with, how can data and analytics add value across the organisation?
A cross-functional approach to utilising and processing data means focusing on team-to-team collaboration on data strategy, collection, validation, and other activities rather than leaving these responsibilities to a single individual or team.
This leads to the question of why cross-functional collaboration is essential for data analysis. It is because cross-functional collaboration forces different groups from different parts of an organisation, with diverse experiences, expectations, and goals, to agree on a plan to achieve the best results. This collaborative approach improves communication, enhances customer services, and provides an effective platform for decision support and other benefits. This would not be possible if the entire approach is designed by a single individual or team with only their business goals in mind, without considering the larger view of the many groups within an organisation.
How do you encourage data democracy while maintaining safeguards for data compliance within the organisation?
Many groups, departments, and individuals require access to certain data elements in order to perform their work, conduct analysis, research, and more. The gold standard for handling such data is following the guidelines for Patient/Protected Health Information (PHI). PHI includes demographic information, medical histories, test and laboratory results, mental health conditions, insurance information, and other data elements pertaining to a patient.
The Health Insurance Portability and Accountability Act (HIPAA) is the primary law in the US that governs the use of, access to, and disclosure of PHI. Similar laws and versions of HIPAA have been adopted in many other countries as a general guideline for governing access to and protection of patient data.
Adhering to these laws and guidelines ensures that individuals and groups have appropriate access to perform their work while remaining in compliance with relevant regulations.
What advice would you give data leaders when it comes to investing in a technology stack and choosing partners?
Many market researchers have provided recommendations, such as Gartner and KPMG. The advice is to ensure proper structure within the data team, establish clear ownership of individual data sources within the organisation, clearly understand the organisation’s plan to utilise and benefit from their data assets and select the appropriate technical solutions (which is the easier part).
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