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Healthcare | Technology

Data analytics: the next frontier in medication management

1 Feb 2021, by Amy Sarcevic

Right patient, right time, right method, right dose and – last but not least – the right medication. When it comes to administering pharmaceuticals in health care settings, there are many different avenues for clinical error – especially when visual checks are used to inspect product labels, eMARs, and NMICs.

These errors occur in around 9 percent of medication administrations and, in Australia alone, cause an estimated 230,000 hospital admissions each year – costing taxpayers $1.2 billion annually. With this in mind, barcodes on unit dose packaging have arguably been one of the sector’s most important recent innovations – reducing medication errors by an estimated 41 percent.

However, while barcodes are still being celebrated as the next best eMedication technology, Jarrod Yip of Alfred Health said it’s important the sector does not get complacent. With the dust created by this digital shift beginning to settle, he says it’s time to think about the next frontier of medication management: data analytics.

“There’s no doubt that the introduction of barcodes has been a really positive development for Australian healthcare. However, it’s important we realise that barcodes, on their own, are not a silver bullet,” said Jarrod ahead of the eMedication Management Conference.

“Barcodes are meant to assist with providing a safe, standardised medication administration process, but there is still a lot of clinician variability in terms of how they are used. When you have a ‘hit and miss’ situation – with sometimes only one in four, or one in five, medications being scanned – there is still a large potential for people to administer the wrong meds inadvertently,” he added.

To this end, data analytics is expected to become a valuable tool – helping identify areas to improve medication management across an organisation – without relying on surrogate markers.

“Data analytic tools can help you prove your implemented processes are consistently being done, and if they’re not, measure how far that gap is to what is considered the gold standard,” Jarrod continued.

“With these tools, you could feed back to a nursing group and say, ‘these are the scanning rates on your ward, this is your trend, this is how you measure up against the top ten wards in terms of patient identification and med barcode scanning.”

“With that information, we could start to generate really big improvements, helping individual wards see where they need to get better, so that safe medication practices are consistently performed throughout the organisation.”

While the rationale for data analytics in medication management may be clear, Jarrod admits putting it into practice may take time and resources: two things health care organisations don’t have in surplus.

“There will likely be a large investment of time needed for this. Redesigning data is hard. You need to develop insights – extract and present them in a way that can be clinician intuitive,” Jarrod said.

“It will need to talk to physicians, governance and other clinical groups, respectively. Each of these groups has their own focus but, at the same time, doesn’t necessarily know what data exists or how to extract the data they want. Moreover, a lot of organisations may not have the time or resources to invest in this process” he said.

Challenges aside, Jarrod believes the rewards for getting it right are worth it.

“Based on the trends captured, we could do KPI measurements, audits, and address some hard-hitting issues within healthcare. We can change what people are doing based on higher level insights,” he said.

“We are only just exploring this now, but it’s an exciting direction to be heading. The system is already there, and we’re now trying to build on it – developing a more mature approach to feeding information back to the clinician.”

The benefits of data analytics don’t stop with closing the loop in medication management.

Jarrod highlights how data analytic tools may also help with Venous thromboembolism (VTE) prophylaxis – helping feed information back to medical units as part of regular governance groups or audits. This would allow live information to be accessed at any time and fed back to the clinicians that are delivering patient care.

“Utilising our data warehouse and extracting the relevant information for each patient each day, we could see whether a VTE assessment has been done; whether a form of anti-coagulation has been prescribed; whether the patient is not a suitable candidate for anti-coagulation. All of this in combination with patient factors such as age, renal function and weight,” Jarrod said.

“Being able to consolidate this data into a dashboard means that everyone is accessing and seeing the same set of data; which provides transparency on seeing close to real-time information on prescriber behaviour so that we can identify and address potential issues before it results in patient harm,” he concluded.

Hear more from Jarrod Yip about how data analytics is set to transform healthcare in Australia at the eMedication Management Conference – due to take place 29-30 March 2021 at the Swissotel Sydney.

Learn more and register.

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