Decision Support

Counties Manukau Health/District Health Board (DHB) in New Zealand has gone live with electronic medication management in its emergency department, aged care facilities and medical wards. CM Health clinical sponsor and director of allied health Sanjoy Nand said MedChart electronic medication management was rolled out to inpatient services from April this year. The next stage of the project is to implement across surgical, with 80 per cent of these services due to be live with electronic medication management by the end of 2019. The DXC Technology system includes an electronic medication chart, ePrescribing, pharmacy review, decision support and medication administration. Counties Manukau conducted a pilot in some aged care wards last year in order to understand the training and device needs and how much support staff needed to go live with the electronic system. “We used that information, along with a benefits analysis, to get the business case to the board for roll-out to the rest of the organisation,” said Nand. The business case was approved at the end of 2018 and the DHB chose to implement first in ED, then across the rest of inpatient services, after discussions with other DHBs that have already gone live such as Southern, Canterbury and Waitematā. “Implementing MedChart aligns with our Healthy Together Services objective of improving the delivery of safer patient care achieved through a reduction in adverse drug events and prescribing errors,” he added. Starting in ED meant the team had to look closely at patient flows throughout the hospital. “One of the biggest challenges was making sure that whenever a patient comes in, we only move from electronic to paper once, so we’re not creating a mismatch by going from electronic to paper then back to electronic,” Nand explained. “We did a lot of work to make sure staff were aware when to use paper and when to use MedChart.” He said another key challenge is ensuring there are enough devices available for staff on the floor to ensure clinical workflow is not affected. The DHB plans to go live with MedChart in maternity in 2020. This article first appeared on eHealthNews.nz.

Finding the best care for a patient can be a constantly moving target. The number of stakeholders, the constant advance of new information and treatment options and the nuanced demands of different payers make for a maze of complexities to navigate. In the field of oncology, for example, nobody but a specialist could be expected to keep up with the growing wealth of knowledge in the treatment of individual cancers. Yet most patients are treated by general oncologists who may not be abreast of every best course of action for specific conditions. These practices might not know which treatments a patient could be pre-approved for, or which payers are most likely to compensate and for what. As the practice of tailoring precision medicine plans for each patient takes hold, physicians are being asked to make more specific treatment decisions than ever before. "You have labs, you have payers, you have providers and you have pharma – and they’re all interested in what the doctor is about to do with a patient," said Clynt Taylor, CEO of Intervention Insights, which makes a tool called Trapelo that helps streamline treatment and payment options. Taylor says that giving an oncologist "an opportunity to see what they should be ordering based on the clinical scenario" empowers them to make the best decision for the patient. Information is inspiration "Most doctors have a good idea of what they want to do," said Taylor. "It’s information access that’s really holding up the process: ‘I didn’t know the lab could do that, I didn’t know these genes should be tested.’" Effective deployment of an IT system that can gather all of this information and put it at an oncologist’s fingertips, integrated into their workflow, helps align the interests of everyone involved. In precision medicine, every decision has to be tailored to the patient at hand. This requires significant knowledge about everything in a field where treatment options and knowledge about the disease are advancing rapidly. Doctors need to know their options in a way that relates to the patient and which a payer will approve. "If I order a test, will I get a treatment option that is supported by clinical evidence?" said Taylor. "Or will I get treatment options I can’t use?" Taylor notes that health plans "will pay if there’s evidence." But that puts the onus on providers to have conversations with the payer at the beginning of the care process to build a case for a specific treatment regimen. Integrating payers into the treatment option plan helps form a more granular narrative of care. "Payers not usually involved until the end of treatment selection process," said Taylor. "Docs go through the process, made treatment decisions, submitted to payer and the payer says ‘what’s going on?’ Involving them earlier in the process avoids the situation where payer prior authorization is a holdup." Having a picture at the onset of care of how to proceed and the likely outcomes enables a much better relationship with the payer and delivers the most effective care possible for an individual. Deep insights have been helping physicians predict the best treatment course in a number of fields; tying the process to the payer conversation makes for a more streamlined transition from treatment to payment. Taylor notes that as more data is amassed about precision health, the more seamless the whole process will become. "The more we can streamline communications through automation, the faster a decision can be made," he said. Benjamin Harris is a Maine-based freelance writer and former new media producer for HIMSS Media. Twitter: @BenzoHarris.

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Ping An Smart Healthcare (PASH), a subsidiary of the Ping An Group (Ping An) in China, has introduced AskBob, an artificial intelligence (AI)-based medical decision support tool, to Singapore through collaborations with SingHealth and the National University Health System (NUHS). AskBob, developed by Ping An, provides critical and up-to-date medical information to clinicians when dealing with patients at the point of care and for medical research and self-learning such as case discussions. WHY IT MATTERS At the point of care scenario, AskBob provides precise diagnosis and treatment recommendations for more than 1,500 diseases. Unlike other clinical decision support systems (CDSS), AskBob is a “knowledge + data” two-wheeled drive intelligent CDSS based on millions of anonymous patient medical records, clinical guidelines and a core medical knowledge graph covering tens of millions of medical data. The treatment recommendations AskBob provides are authoritative, personalised and patient-centric. For medical research and self-learning, AskBob makes use of Ping An’s leading medical knowledge graph and advanced natural language processing technologies (NLP) to perform more user-friendly, intuitive and precise online searches and literature analyses. AskBob can provide up-to-date literature analysis summaries and predict scientific research trends. It can also track the scholar team network in a certain research field to connect researchers around the world. COLLABORATIONS WITH SINGHEALTH AND NUHS The collaboration with SingHealth, one of Singapore’s largest public healthcare groups, started in April this year. It aims to provide doctors with personalised treatment recommendations for Type 2 diabetes patients at the point of care. Diabetes is a serious health issue in Singapore, with one in nine Singapore residents aged 18 to 69 having diabetes. AskBob’s recommendations can potentially help achieve better diabetes control and health outcomes, including reducing diabetic complications such as stroke and kidney failure. NUHS, an academic health sciences centre in Singapore, is piloting AskBob with clinicians for smart literature search and medical research trend analysis. ON THE RECORD “We are delighted to cooperate with SingHealth and the National University Health System. They are both authoritative healthcare institutions in Singapore,” said Dr. Xie Guotong, Chief Healthcare Scientist of Ping An Group in a statement. Dr. Bee Yong Mong, Head of the SingHealth Duke-NUS Diabetes Centre said: “An AI-based clinical decision support system could potentially help doctors increase the accuracy and efficiency of diabetes treatment. With the tool, we hope to better predict risks of complications and offer more personalised treatment recommendations to patients.” Prof. Ngiam Kee Yuan, Group Chief Technology Officer from NUHS, said: “More than a search engine, AskBob uses a medical knowledge graph and a natural language processing engine to empower precise literature analysis without giving you information that you don’t need. This is the power of using AskBob. I believe it will be extremely helpful for clinicians in medical research and case discussions.”

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