ASIA News

Following the release of the public report by the Committee of Inquiry (COI) for the SingHealth cyberattack which occurred in July 2018 and Integrated Health Information Systems (IHiS) taking disciplinary action on staff members involved in the incident and senior management team staff, the Personal Data Protection Commission (PDPC) has imposed financial penalties on both IHiS and SingHealth, according to an official statement. The PDPC administers the Personal Data Protection Act 2012 (PDPA) in Singapore, which aims to safeguard individuals’ personal data against misuse and promote proper management of personal data in organisations. PDPC’s investigations into the data breach arising from a cyberattack on SingHealth’s patient database system, found that IHiS had failed to take adequate security measures to protect the personal data in its possession. PDPC has imposed a financial penalty of S$750,000 on IHiS. A financial penalty of S$250,000 has also been imposed on SingHealth as the owner of the patient database system. PDPC found that the SingHealth personnel handling security incidents was unfamiliar with the incident response process, overly dependent on IHiS, and failed to understand and take further steps to understand the significance of the information provided by IHiS after it was surfaced. These financial penalties (a total of S$1 million) are the highest ever imposed by PDPC to-date. PDPC took into account the fact that the data breach was the largest breach that Singapore has ever experienced, as well as the sensitive and confidential nature of the patients’ data. In addition, the penalties took into account the fact that IHiS and SingHealth were cooperative throughout the investigations and took immediate remedial actions. PDPC also recognised that both organisations were victims of a skilled and sophisticated threat actor bearing the characteristics of an Advanced Persistent Threat group, using numerous advanced, customised and stealthy tools and carrying out its attack over a period of more than 10 months.

The IHiS Board of Directors appointed an independent human resource panel to examine the roles, responsibilities and actions of the IHiS staff involved, and assess the appropriate HR actions to be taken.

The agency’s Annual Report 2017–18 identified that “42 data breaches (in 28 notifications) were reported to the Office of the Australian Information Commissioner (OAIC)… concerning potential data security or integrity breaches”, but with “no purposeful or malicious attacks compromising the integrity or security of the My Health Record system”. Of the 42 instances, one breach resulted from unauthorised access to a My Health Record as a result of an incorrect parental authorised representative being assigned to a child. Two breaches resulted from suspected fraud against the Medicare program, where the incorrect records appeared in the My Health Record of the affected individual and were viewed without authority by the individual undertaking the suspected fraudulent activity. The ADHA report also identified that 17 breaches were a result of data integrity activity initiated by the Department of Human Services to “identify intertwined Medicare records (that is, where a single Medicare record has been used interchangeably between two or more individuals)”. The remaining 22 breaches were from suspected fraud against the Medicare program involving unauthorised Medicare claims being submitted, and the incorrect records appearing in the My Health Record of the affected customers. An ADHA spokesperson confirmed that in all instances, the Department of Human Services took action to correct the affected My Health Records. “Errors of this type occur due to either alleged fraudulent Medicare claims or manual human processing errors, as was the case for the breaches reported during the 2017-2018 financial year. There has been no reported unauthorised viewing of any individual’s health information from a notifiable data breach,” the spokesperson said. “In each case, the affected individuals have been contacted and the OAIC has examined the circumstances of the breach and no unauthorised breach has been determined.” The ADHA spokesperson added that there are more than 6.3 million people with a My Health Record, but in the six years of its operations, there have been “no reported unauthorised views of a person’s health information”. “When a person’s health information is stored in different places – hospitals, doctors’ offices, filing cabinets, computers – they don’t know who is accessing it or when. In a My Health Record, every access is listed in a person’s record access history. A person can be notified by text message about who is accessing their record or restrict access to all or parts of their record,” the spokesperson said. On 26 November 2018, the Federal Parliament passed legislation to strengthen privacy protections in My Health Records Act 2012 without debate or division.   The new legislation means that Australians can opt in or opt out of My Health Record at any time in their lives. Records will be created for every Australian who wants one after 31 January and after then, they have a choice to delete their record permanently at any time. “At the time of writing, almost one quarter of all Australians have registered for a My Health Record. That figure is expected to change dramatically with the transition to an opt out system early in the 2018–19 financial year,” ADHA CEO Tim Kelsey said in the report. “Once this resource becomes almost ubiquitous across the Australian health system, clinical workflows and consumer behaviours will gradually and irrevocably change to take advantage of its many benefits. “For many people the benefits of digital health will be realised gradually, as health and medical data gradually accumulates to form a comprehensive medical history,” Kelsey said. This article first appeared on Healthcare IT News Australia.

Last week, Deqing county hospital in Guangdong Province launched free consultations featuring artificial-intelligence (AI) cameras to detect ocular fundus diseases, which are major causes of blindness, according to a report by Xinhua News. About 300 residents from Zhaoqing City in Dequing County attended the free consultation sessions. The hospital became the first to use the device, co-developed by China's search engine Baidu and Sun Yat-sen University, to serve the general public. The instrument is capable of diagnosing three types of fundus disorders -- diabetic retinopathy, glaucoma and macular degeneration. It scans the eyes and generates a report in 10 seconds, all done without the need for an ophthalmologist to be present. Baidu’s AI-powered camera was first unveiled in China in November 2018, according to a MobiHealth News article. Fundus diseases are a major cause of blindness in the developing world, where the short supply of eye doctors and instruments has stymied timely diagnosis and treatment. China, with a population of 1.39 billion, has only thousands of ophthalmologists capable of analysing fundus photos screening. “As a doctor working at the grassroots level, I believe AI can greatly help in all aspects of screening. For instance, there is so much imaging data during medical checkups and it takes up a lot of time and energy for doctors to physically look at this data, which is simply not efficient. In ophthalmology, the use of AI to verify test results from fluorescein angiography and OCT examinations can help doctors expedite their analysis, which saves time and improves their efficiency,” said Dr Honghu Xia, Director of Ophthalmology at Deqing county hospital. Xu Yanwu, a Baidu engineer developing the instrument, said the AI cameras were specifically designed to address the lack of medical instruments and ophthalmologists at grassroots health facilities. "It is easy to use and can be operated by a non-professional. Its 94-percent sensitivity and specificity at analysing photos can match a senior doctor at a tertiary hospital," Xu said. As of 10 January 2019, Baidu already has four of said AI cameras operating in four hospitals in Deqing County to assist ophthalmologists in fundus screening. It is estimated that by end of March, Guangdong Province will have 14 hospitals using the AI camera instrument.

One of the fast-growing sectors that have been identified in Thailand is healthcare and it is expected to be a key driver of the country’s economy. Deloitte estimates that the health care spending in Thailand would have reached $18.7bn last year, growing by 8% between 2014 and 2018. The consultancy added that total spending was $12.8bn in 2013. The medical equipment market is growing quickly as well, having risen in value from BT25.92bn ($780.2m) in 2010 to BT38bn ($1.1bn) in 2015. Nearly 80% of this medical equipment is imported. The government’s share of sector spending is the second highest in the region, at 77%, yet private sector spending is on the rise. In 2008, the Thai government spent BT8.2bn ($246.8m) on health care while the private sector spent BT2.6bn ($78.3m). By 2015, the government was spending BT12.5bn ($376.3m) for health care, while the private sector spent BT4bn ($120.4m). Private hospitals have benefited from government efforts to provide universal health care. Local hospitals report having experienced sharp increases in patient numbers, and this has led patients with the financial means to seek treatment at privately run establishments. Private sector growth According to the data from the Health Service Support Department at the Ministry of Public Health in 2015, there were 343 private hospitals operating in Thailand, up from 321 in 2011. Around 40% of these were in the Bangkok Metropolitan Area. The private hospital sector has been undergoing structural change and the effects of this are becoming increasingly clear. Large hospitals which are able to expand rapidly are doing so through mergers and acquisitions and by expanding their commercial networks both in the Bangkok Metropolitan Area and in important regional centers, especially those in border regions. Thailand’s Medical tourism industry is largely driven by private hospitals. Some of the well-known private hospital groups in the country include: (i) Bangkok Dusit Medical Services, the largest private hospital group in Thailand which consists of six major hospital groups – Bangkok Hospital, Samitivej Hospital, BNH Hospital, Phyathai Hospital, Paolo Hospital and The Royal Hospital and (ii) Bumrungrad International Hospital, one of the largest private hospitals in Southeast Asia and the first hospital in Asia to receive Joint Commission International (JCI) accreditation in 2002. The above-mentioned private hospitals are also continually looking to expand their international reach through Memorandum of Understanding (MoUs) with foreign online health platforms or companies. For instance, Bangkok Dusit Medical Services signed an MoU with China’s Ping An Good Doctor in November 2018 and Bumrungrad International Hospital signed an MoU with Malaysia’s BookDoc in June 2018. New players such as huge conglomerate companies in Thailand are also increasingly interested in investing in healthcare. These investments are huge and tend to be concentrated in the Bangkok Metropolitan Region. Examples of investors include Pruksa Holdings (Vimutti Hospital, scheduled for opening in 2020), RSU Group (RSU International Hospital, also scheduled for opening in 2020), CP Group, and TCC Group. Convergence of public initiatives and private sector developments Through a number of incentives, the Thai government wants to capitalise on the market development of medical tourism. Thailand is shifting public policy towards creating an environment wherein medical tourists can access the country’s services with ease. Part of the government’s strategic plan to become a global medical hub involves the loosening of visa restrictions and the creation of smart visas. Extending visas from 30 days to 90 days for citizens of China along with those of Cambodia, Laos, Myanmar and Vietnam (CLMV) will increase treatment options and draw customers with the promise of quality facilities. The private healthcare sector will be expected to grow and become more competitive due to the entry of non-traditional players such as huge conglomerate companies. Additionally, some public hospitals have also noticed the potential opportunities and have developed services (e.g. specialist treatments or providing services outside regular working hours) that match the standards of the private hospitals. Piyamaharajkarun Hospital, part of the Siriraj Hospital network and the Somdech Phra Debaratana Medical Centre at Ramathibodi Hospital are examples of public hospitals which have followed this path. Challenges and conclusion Thailand provides universal health coverage to its citizens, which is great but comes with several challenges. Some of these big challenges include fiscal sustainability in the long term, maintaining healthcare service quality and the shortage of healthcare professionals to meet the demands of universal health coverage. There is also the existing urban-rural divide in terms of the provision and quality of healthcare. The clever and practical use of technologies could address some of these issues, but this also requires significant buy-in and commitment from the policy makers and public sector.

The Committee of Inquiry, which was convened on 24 July 2018, identified five key findings and a total of 16 recommendations for SingHealth and IHiS to improve its cybersecurity defences.

The Australian Institute of Health and Welfare (AIHW) built the tool and said it provides a new way of comparing Australia’s performance across a range of health-related measures from the data of 36 Organisation for Economic Co-operation and Development (OECD) member countries. Some of these countries include Japan, Spain, Italy, Switzerland, Canada, New Zealand, the UK, the US, France, Korea, Israel, Norway, Germany and Denmark. The data tool, International health data comparisons 2018, gives users interactive data visualisations of snapshot comparisons of key health indicators such as life expectancy, health risk factors and causes of death. It also aims to give insights into how Australia’s healthcare system compares, including data on the pharmaceutical market, health insurance coverage and waiting times for elective surgery. All data is sourced from the OECD Health Statistics 2018 website and results are for 2017 or the nearest available year of data for countries with available data. According to the AIHW, the tool was built to aid local healthcare professionals compare health and healthcare data between countries and get a better understanding of how the market compares to other countries. "This new data tool is an important resource, facilitating international comparative reporting, supporting policy planning and decision-making and enabling new types of research and analysis," AIHW spokesperson Claire Sparke said. How does Australia’s health compare to other OECD countries? The AIHW data presented some key findings for Australia, as compared to the rest of these 36 OECD member countries, including: Australia has the 6th lowest proportion of daily smokers (12 per cent) across OECD countries, below the OECD average of 18 per cent.  Australia has the 9th highest rates of overweight and obesity (63 per cent). This is even more notable for men, with Australian men having the 3rd highest rate of overweight and obesity, behind the US and Chile. Waiting times for most elective surgery procedures in Australia are below the OECD average. For example, Australians waited a median of 13 days for coronary bypass compared to the OECD average 22 days. “The data show that Australia performs relatively well across most of the indicators. For example, Australia has a life expectancy at birth of 82.5 years – above the OECD average of 80.6 years, and 6th highest among OECD countries,” Sparke said. “However, the data show that there are some areas where Australia could be doing better, such as rates of overweight and obesity”. This article first appeared on Healthcare IT News Australia.

“I think the biggest trend (in healthcare) is towards greater integration. Traditionally, healthcare has been very fragmented, where many different groups serve specific clinical needs without necessarily coordinating with each other. But going forward, the trend is towards integration – not just of things like databases and systems, but integration of the way we process the data and how this influences the clinical workflow,” said Prof Ngiam Kee Yuan, Group Chief Technology Officer of National University Health System (NUHS) in Singapore, in response to what he thought would be the key trends that will impact healthcare systems in future. It was with the same motivation and mission to best use the healthcare data for research at NUHS that led to the building and development of the DISCOVERY AI platform, which started about four years ago and the platform was officially announced in July 2018. The platform is what Prof Ngiam describes as a ‘sandbox’ that allows the staff at NUHS to develop AI tools in a safe and equitable way – the platform is scalable and can be applied to more than one system within the organisation. “We saw the opportunity because we had datasets which were large enough to support the development of these AI tools. And one of the advantages we have at NUHS is that we have clinicians and allied health professionals who understand, and are willing to develop these tools. I cannot emphasise enough the importance of having the clinicians onboard throughout the development process.” Currently, a randomised control trial of a system as part of the platform is a free-text diagnosis machine at the Accident & Emergency (A & E) department. When doctors input a certain set of findings as part of clinical documentation, the machine would automatically provide a suggestion for a diagnosis. The team is exploring diagnosing appendicitis for a start. The trial is slightly under halfway through and Prof Ngiam hopes by the later part of 2019, they would be able to have results, which would be the basis for them to operationalise the AI tool. One of the early milestones for the NUHS DISCOVERY AI platform is its ability to sustain multiple proof-of-concept projects. With the platform, individual projects are no longer fragmented and there is the ability to aggregate, link and share large data sets. “It took us four years to get to this point and the next milestone for us is to finish our trials and to actually launch them as “software as medical devices”. Again there are some hurdles to get through before we get there but seeing where we are right now, it is very likely we should be able to get through them.” Prof Ngiam also pointed out that as the platform is unlike anything they had before and behaves like an advanced form of clinical decision support system (CDSS), which are not based on a set of rules but based on a set of complex trained weights and multiple factors that affect a certain outcome. Despite its complexity, the AI tools need to be thoroughly trialed before it can be used in routine clinical practice. “This is why we are running it as a trial now in the hospital. In essence, the platform is run under the ambit of a trial to mature the workflow and test the system under real world conditions. Operationally, what the doctors are doing during the trial is no different from what they would have done, except that we collect the data on the basis of the trial,” he added. Looking to the future, Prof Ngiam and his team is working towards completing the trials in 2019 and hopefully heading towards registration in terms of the platform being used as a medical advisory device.

The project, a joint collaboration between Intel and GE Health, is promising to offer physicians automated diagnostic alerts for some conditions within seconds of medical imaging being completed. It leverages the Intel Distribution of OpenVINO toolkit, running on Intel processor-based X-ray systems to help prioritise and streamline patient care. Using this system, X-ray technologists, critical care teams and radiologists will be immediately notified to review critical findings that may accelerate patient diagnosis. Intel Internet of Things Group Health and Life Sciences Sector General Manager David Ryan explained that the AI imaging models are optimised for inference and deployment using the model optimiser component of OpenVINO. The optimised models are then integrated into the GE application with the OpenVINO inference engine APIs. As X-ray images are acquired by the machine, the inference engine runs them for clinical diagnosis. GE Healthcare Senior Vice-President of Edison Portfolio Strategy Keith Bigelow said medical imaging is the largest and fastest-growing data source in the healthcare industry. But, even though it accounts for 90 per cent of all healthcare data, more than 97 per cent of it goes unanalysed or unused. “Before now, processing this massive volume of medical imaging data could lead to longer turnaround times from image acquisition to diagnosis to care. Meanwhile, patients’ health could decline while they wait for diagnosis,” he said. “Especially when it comes to critical conditions, rapid analysis and escalation is essential to accelerate treatment.” According to Bigelow, a key implementation of this technology is providing earlier detection of a potentially life-threatening event – a collapsed lung, also known as pneumothorax. He said radiologists can now deploy optimised predictive algorithms that scan for and detect pneumothorax “within seconds at the point of care”, allowing rapid response and reprioritisation of an X-ray for clinical diagnosis. “Deploying deep learning solutions on existing infrastructure delivers the potential to power more efficient and effective care, enhance decision-making, and drive greater value for patients and providers,” he said. "For the more than 12,000 Australians diagnosed with lung cancer each year, this means a higher chance of survival.” Ryan said deep learning was a promising approach for radiology because its models can be trained to recognise desired features in an image, such as tumors or anatomies.   “Furthermore, training is done by giving numerous labeled example images to the models, without having to specify the exact features to look for. Deep learning can identify details that can be missed by the human eye,” he said. According to Ryan, in future applications, deep learning models can be used to identify incidental findings, as well as help radiologists manage their workload, enhance quality of scans, and reduce ‘retakes’, which can cause unnecessary exposure to radiation. “Deep learning is also showing promising results in image reconstruction from the imaging modalities. Future applications of deep learning can extend beyond imaging data to include electronic health records, pathology, cellular microscopy data, etc. to help develop targeted drugs and achieve precision in medicine,” Ryan added.  Ryan also said deep learning was a promising approach for radiology because its models can be trained to recognise desired features in an image, such as tumours or anatomies. “Furthermore, training is done by giving numerous labeled example images to the models, without having to specify the exact features to look for. Deep learning can identify details that can be missed by the human eye,” he said. According to Ryan, in future applications, deep learning models can be used to identify incidental findings, as well as help radiologists manage their workload, enhance quality of scans, and reduce ‘retakes’, which can cause unnecessary exposure to radiation. “Deep learning is also showing promising results in image reconstruction from the imaging modalities. Future applications of deep learning can extend beyond imaging data to include electronic health records, pathology, cellular microscopy data, etc. to help develop targeted drugs and achieve precision in medicine,” Ryan said.  This article first appeared on Healthcare IT News Australia.

The report, tabled by the Queensland Audit Office (QAO), highlighted the benefits of the digital hospital program in Queensland, while making recommendations to improve governance of the future rollout. Key findings from the report identified that as a result of the digital hospital program, Queenslanders face improved health service delivery and patient outcomes, as well as a reduction in unplanned readmission rates. It found that medical staff can access clinical information faster and that patient records are more legible. Minister for Health and Ambulance Services Steven Miles said the digital hospital program is “one of the most significant health advances in decades”. “Digital hospitals are making Queensland hospitals safer than ever before. Doctors and nurses have told me when I’ve visited hospitals that the digital system helps them do their jobs and helps patients,” Miles said. Miles brought up the example of Metro South Health’s digital program, which he said contributed to a “significant increase” in early identification of deteriorating patients, as well as a decrease in emergency patient readmissions, less incidents linked to drug administration, monitoring, dispensing and supply and a significant drop in infections. As part of its move to digital, the healthcare provider most recently embarked on a journey to enable people living with progressive neurological conditions like Motor Neuron Disease (MND) to use mobile digital assistants daily. The report also identified the benefits that Princess Alexandra Hospital has faced and how it has become a template for the rest of the state following its adoption of an integrated electronic medical record (ieMR) system. “We can see digital hospitals are reducing the average length of stay and unplanned readmissions,” Queensland Chief Clinical Information Officer Dr Keith McNeil said. “Doctors are telling us the new system means they can spend more time on patient care and less time on paperwork. “Nurses are saying that the system means they have a huge amount of readily available information and they are not having to waste time searching for notes. This means the system is working.” He added that the increasing focus on technological advances and continuing improvements will continue to provide new opportunities. “Our increased focus on ieMR’s clinical capability will ensure our patients can access these opportunities, now and in the future.”   The report also found that while implementation costs exceeded initial expectations, it was often because hospitals spent more to go beyond the planned scope of their digital hospitals, bought extra devices to increase utilisation of the systems and invested more resources to reduce disruption on patient flow when new systems were introduced. Queensland Health Director-General Michael Walsh has reviewed the status of the system rollout and has made a number of changes relating to report recommendations. Walsh said the system was in place in 10 hospitals across the state’s Hospital and Health Services and that the department would continue to focus on ensuring the system delivered on benefits. He said Queensland Health has expanded the responsibility for managing the relationship with the digital hospital system provider and commenced an independent assessment to confirm that, as per the contract, the prices being paid for the system were no less favourable than those being paid by other health service providers in Australia. “The people of Queensland expect and deserve the very best care when they are treated in the state’s hospitals,” Walsh said. “The report confirms the system is helping us deliver that and we accept the system-oversight recommendations the QAO has made. They are not difficult to implement because they are not major adjustments.” This article first appeared on Healthcare IT News Australia.