H E A L T H I N S I G H T S
Five ways to support staff in successfully adopting new tech
1 . Addressing misconceptions
By encouraging open dialogue in the workplace , leaders can learn more about the fears and concerns that might lie behind a reluctance to use new technologies . If , for example , the staff are concerned about data breaches and complications during CQC inspection , leaders can put in place mechanisms for users to check the security credentials and verifications of the technology for themselves .
Automation technologies are designed to improve patient safety and reduce the risk of CQC penalty . If there are fears about new technologies ‘ replacing ’ staff , educate your employees on how these tools have been introduced to support – not replace – workers .
2 . Onboarding and training
A very common reason why staff don ’ t feel confident using automation software is that they ’ ve never been shown how to access login details , navigate the platform or use it to its full potential . This scenario can be avoided by ensuring that new tools are comprehensively rolled out in the organisation and that they are carefully selected to have an excellent user experience . They should also be easy to navigate and ensure that all users receive comprehensive training resources .
3 . Work with early adopters in the team
Peers are more influential than managers when it comes to encouraging the adoption of new working practices . Leaders can lean into this when rolling out a new tech tool by encouraging team members to spread the news to others . These evangelists can support and inspire colleagues to engage with new technologies and may even help with training and troubleshooting in the early stages of the rollout .
4 . Promote the advantages and benefits
The most impactful way to help colleagues overcome anxiety is to showcase how automation software can save them time , reduce their workloads and significantly cut down onerous paperwork . For example , on account of the litany of checks and verification processes that healthcare HR teams and new candidates must complete , it can take up to 60 days for hires to start working . Not only does this process pile a huge volume of work on the plate of administrative staff but candidates often drop out of the process in frustration , opting to work for competitor organisations instead . However , simply by introducing a software platform that automates the credential and reference checking process , hundreds of hours are instantly saved for admin teams and frustration is eliminated for everyone involved in the process .
5 . Make adoption the default
Humans are hardwired to prefer the status quo , which is why the most successful tech rollouts are those where the new process is established as the standard , default option . Choosing not to use new tech then becomes the harder , less preferable option . To make this work , all new technologies must be able to be integrated into existing workflows and ‘ talk ’ to systems already in place .
Automation anxiety is a natural human reaction to change and modernisation in the workplace , and managing its impact is part and parcel of any successful transformation process . Although it requires effort , it ’ s certainly worth it .
When proven automation tools are deployed to reduce the excessive administrative workloads fanning the flames of the burnout crisis , capacity will be increased , staff retention will improve , time and money will be saved , and ultimately , patients will benefit from safer , betterquality treatment . �
About
Dr Kit Latham , Co-founder and CEO of Credentially
Dr Kit Latham studied medicine ( specialising in surgery ) in the UK at The University of Leeds . After attending London Business School and completing a master ’ s degree in Technology Entrepreneurship at University College London ( UCL ), he worked as an Emergency Physician in England ’ s NHS . In 2016 , he founded Credentially , a global company revolutionising HR processes and delivering efficiencies for healthcare organisations with machine learning and computer vision technology .
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