How is data-driven healthcare impacting patient care?
Digital healthcare is a broad, multidisciplinary concept that bridges the intersection between technology and healthcare. Digital transformation in the field of healthcare stretches across many different aspects of software, devices, services and infrastructure, including mobile health (mHealth) apps, electronic health records (EHRs), electronic medical records (EMRs), wearable devices, telehealth and telemedicine, as well as personalised medicine.
The emerging challenge is, therefore, how to use the data from these systems and initiatives to enhance the delivery and outcomes of frontline services and patient care. Let’s look at some of the areas in which data-driven healthcare is transforming patient care.
1. New research opportunities
Digital healthcare makes it possible to collect and combine big datasets to create new research opportunities. Collected data includes DNA, proteins, metabolites, tissues, cells, organs, etc. Combining this wealth of data with new machine learning and artificial intelligence (AI) technologies makes it possible to capture new insights and explore new research opportunities to improve treatment and identify new treatment options. In the long term, it is hoped that the resulting breakthroughs will lead to better patient outcomes.
2. Improved diagnoses
The power of data is also being felt in the field of medical imaging. AI-powered algorithms can analyse medical images such as X-rays, MRI and CT scans with remarkable precision. This can help to speed up diagnostics and reduce error, leading to improved patient outcomes.
3. Administrative efficiency
Data-driven solutions are helping to improve many aspects of healthcare administration, streamlining effort and optimising and automating processes, including with the aid of AI. In this way, by releasing cost from the back office, money and resources can be released to frontline care. Ultimately, this will lead to improved patient care and improved patient outcomes.
4. Data-driven strategic planning
By analysing health needs, treatment and outcomes among different demographic groups, data-driven healthcare analysis can inform strategic planning, directing resources to where they are needed most and can have the best impact. This data can come from for example Electronic Health Records, or now with advances of AI and Machine Learning (ML) it can be curated from real world feedback from Patients and Health Care Professionals. Patients talk to each other, and they talk to their Doctors online. There has been a phenomenal growth in the volume of online conversations about medicines and health, driven in part by the pandemic with systematic changes as healthcare moved online. This data is unstructured and difficult to decode, however, using AI and ML to curate and classify the information unlocks valuable clues about the real treatment journey that patients experience. This has significant value to the healthcare system in understanding and addressing the $250Bn gap in adherence where medicines are prescribed but not taken by patients.