Using AI to reduce waiting lists in hospitals

Without intervention, waiting lists for NHS patients could significantly increase In a speech ahead of the Autumn Budget on 22nd November 2018, the Chief Executive of NHS England, Simon Stevens made a stark warning. He cautioned that without extra funding the improvements made in reducing waiting times for patients over the past decade would be reversed. In fact, he stated the waiting list for elective treatment could increase to 5 million people by 2021. A tough task The NHS has some of the most challenging performance standards in the world. These standards cover a range of services including ambulance response times, new measures on access to certain mental health services and waiting times for diagnostic tests as well as the more high-profile waiting times for elective treatment, A&E and cancer services. Improving healthcare with AI The ever-increasing needs of patients and communities can only be met by finding new ways to can streamline clinical workflows. This would enable better collaboration, reduce costs and improve patient outcomes. All of which are an enabler to reduce waiting times in hospitals. This is where Artificial Intelligence (AI) comes in. AI is an enabler and can be used to free up valuable resources, which can be spent on more complex cases. This helps Healthcare Trusts meet government waiting list targets by speeding up biopsy scans, for example. More accurate and faster diagnosis Whether you want to improve diagnostic performance, engage more effectively with your patients, optimise their care or simply apply AI to your organisational performance, there are many ways to apply AI to the healthcare industry. Using extraordinary image processing and recognition capabilities, for example, means that you can reach a more accurate and faster diagnosis in areas such as: Radiology Evaluating MRI, CT scans or X-Rays Cancer Detection Cervical cancer. Skin cancer – Not all moles are the same. AI can catch the dangerous ones with a precision better than experts in the field. Lung cancer – Early detection and ruling out benign tumours. Save time on patient screening AI can help clinicians to more easily and quickly find a list of clinical trials for an eligible patient. Likewise, in clinical trial offices patients that are potentially eligible for any of the site’s trials are more easily found. The improvement in screening efficiency and more effective patient recruitment can help increase clinical trial enrolment targets. It also offers opportunities to patients and the option of a clinical trial for treatment. AI holds the key Reducing patient waiting times will inevitably improve patient experience as well as help your organisation take steps to meet government targets. Successful trusts have begun addressing the task of reducing waiting times in a systematic way much earlier than unsuccessful trusts. There are many ways of doing this, such as weekend and evening working, but AI provides a much more sustainable way. Sources: ¹marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-54679303.html ²developer.ibm.com/linuxonpower/2018/05/11/breast-cancer-classification-ibm-powerai-vision³ieeexplore.ieee.org/document/803030