How Hospital Authority Hong Kong is working towards sustainable healthcare

How Hospital Authority Hong Kong is working towards sustainable healthcare

Hospital Authority has made significant achievements over the past years in digitising its processes and ways of delivering care to patients and communities. For over 30 years, it has invested in developing its clinical management system, which is now considered one of the most advanced systems in the world. Recently, it also began working on projects that contribute to its vision of a smart hospital.

However, its digital transformation journey is far from over.

In her case study presentation titled, “Towards Sustainable Healthcare with Digital Health in Hong Kong,” Dr Joanna Pang, Chief Medical Informatics Officer, Hospital Authority Hong Kong, shared how they are going to further digitise following the release of the HA Strategic Plan 2022-2027 late last year.

The plan provides an outline of organisation-wide directions over the coming five years and covers strategic goals in providing smart care. 

Under this plan, Dr Pang said they will adopt a new service model and new technologies to improve patient outcomes.

“We will continue to develop the smart hospital concept by adopting AI, digital technology, and other advanced technologies that can enable smart care and nurture a smart workforce… We hope that we can work towards sustainable healthcare,” she added.

In becoming a “Digital HA”, the organisation seeks to become more decentralised so it can be more engaged with communities and empower more patients. Dr Pang also hopes that by going digital, they will be able to decongest the outpatient traffic and enable patients to become more active in managing their own healthcare and staying connected with its care services.

Assessing strengths and weaknesses

“There are so many things that we want to deliver and things we want to do. We have to identify all those key digital actions in the short term and also find a way how to help us prioritise investments in certain activities in the future,” Dr Pang said.

In 2020, HA engaged HIMSS to be assessed for its progress toward building a digital health ecosystem. It became one of the first organisations to be assessed under the Digital Health Indicator (DHI) model, which helped HA identify its strengths and weaknesses. HA scored 358/400 in the DHI assessment, which is considerably high. It scored high in three areas: governance and workforce, interoperability, and predictive analytics.

“The assessment helped us mobilise our data across multiple sources and share them in a very secure environment. It also found our care providers and care teams to be providing digitally-enabled services and that we have set up a good platform, which could bring along predictive analytics to drive insights for improving outcomes,” Dr Pang shared.

Following the DHI assessment, HA worked towards getting all its 43 hospitals validated for Stage 6 EMRAM. 

Working collectively in AI deployment

“The difficult task is not coming up with some AI solutions; it’s how you operate them,” Dr Pang claimed. “It can’t be just simply plug and play. You need to do quite a lot of engagement with your clinicians, and you need to identify your pain points and key issues that you want to address, instead of just simply switching on something called AI. You need to identify the issue or problem and see where AI can be helpful.”

From here, working alone will not cut it, she stressed. “We should work with others.” 

HA has formed an internal community working on some AI initiatives. It is also collaborating with local and international communities to exchange ideas and ways to work on AI projects for healthcare.

At present, HA has implemented three AI projects across its hospitals, one of which is an imaging solution that helps doctors prioritise chest x-ray reports. The same AI model was later developed to assist clinicians to spot abnormal findings in chest x-rays. So far, it has analysed 740,000 cases, cutting down the need for doctors to make second notes or readings. A third AI solution reads Hepatitis B reports to identify and alert for positive cases. After a year’s pilot, this tool was able to prevent the development of liver failure in 21 patients.

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