{"id":17705,"date":"2022-09-29T10:46:21","date_gmt":"2022-09-29T10:46:21","guid":{"rendered":"https:\/\/globalhealthintelligence.com\/?p=17705"},"modified":"2026-02-16T12:17:39","modified_gmt":"2026-02-16T18:17:39","slug":"hospital-spotlight-with-hospital-italiano","status":"publish","type":"post","link":"https:\/\/globalhealthintelligence.com\/pt-br\/ghi-analysis\/hospital-spotlight-with-hospital-italiano\/","title":{"rendered":"HOSPITAL SPOTLIGHT with Hospital Italiano"},"content":{"rendered":"\n

By\nDaniela Chueke Perles<\/strong><\/p>\n\n\n\n

Currently a variety of converging healthcare technologies are being created for healthcare, some proven and others that are still under development. According to Dr. Daniel Luna\u2014chief of the Healthcare IT department at Hospital Italiano in Buenos Aires and a pioneer in this area in Latin America\u2014the technology with the greatest potential to revolutionize healthcare in the future is algorithmic medicine. <\/p>\n\n\n\n

\"Dr.<\/figure><\/div>\n\n\n\n

Dr. Luna spoke with Global Health\nIntelligence about his work and made some interesting predictions. \u201cA big\nchallenge is on the way: we still don\u2019t know how algorithmic oracles will be\nintegrated into the processes of healthcare, but there is no doubt that this\nwill be the future of medical treatment. Right now, there are so many varied\nfields emerging in the computerization of health that a bubble is being\ncreated. At some point that bubble will burst and within five or six years\nwe\u2019ll see the fields with real staying power,\u201d he says.<\/p>\n\n\n\n

Dr. Luna defines his specialty area as\nan ecosystem whose greatest challenge is sustaining excellence and permanently\ninnovating; the most important thing is changing the mindset of health\nprofessionals and the main challenge is anticipating changes. His perspective\noffers a glimpse of profound changes in the roles of doctors and healthcare systems,\nbut it\u2019s not pessimistic. Instead of fearing that (AI) will nullify people\u2019s confidence\nin their own judgment, as seen in the recent film Don\u2019t Look Up<\/em>, Dr.\nLuna believes that medical algorithms will restore some of the lost humanity\nbetween doctors and patients. \u201cThe algorithms will improve decision making but\nwon\u2019t supplant the role of the doctor; the doctor will transform into an\nintermediary between the algorithm and the patient,\u201d he says. <\/p>\n\n\n\n

Below we offer some of Dr. Luna\u2019s more\ndetailed answers during our interview, using a Q&A format to make them\neasier to follow.<\/p>\n\n\n\n

What kind of research is the healthcare IT field focused on right now?<\/strong><\/p>\n\n\n\n

Currently innovation is focused on\nartificial intelligence (AI) and machine learning, the medicine of precision\nand bio-information technology. Healthcare and medicine are now overlapping\nwith all the emerging fields of IT: social\nmedia, wearables, mobile health, telemedicine, shared economies, quantum\ncomputing, omic sciences, automatic speech recognition (ASR), data analytics,\nvirtual reality, 3D printing, PNL, 5G, blockchain, AI. Over the next 20 years\nthis tech landscape will transform all the areas of healthcare. But I think\nthat the most promising field is algorithmic medicine, and that\u2019s why we are\nfocused on an AI project. <\/p>\n\n\n\n

What is involved with the AI project and how is your team developing it?<\/strong><\/p>\n\n\n\n

The project has been under development\nfor the past five years, when we put together an AI program that now has more\nthan 15 active lines, 4 of which are in the process of production within the Healthcare\nIT Department of the hospital.  <\/p>\n\n\n\n

\u201cThe algorithms will improve decision making but won\u2019t supplant the role of the doctor.\u201d<\/p><\/blockquote>\n\n\n\n

What are the challenges and application possibilities with this type of research field? <\/strong><\/p>\n\n\n\n

What we\u2019ve been doing for the past five\nyears is the genesis of the transformation of computerized medicine into\nalgorithmic medicine. The big challenge is resolving how we will integrate the\nalgorithmic oracles into healthcare processes. Today they\u2019re all like islands;\nthere is a lot of promise and expectations of the development of all kinds of technological\nsolutions, and the market is trying to        recoup\nits investments. A bubble is being created that will someday burst and we\u2019ll\nsee which will be the lasting technologies in five or six years. At that point we\u2019ll\nbe able to see real change.<\/p>\n\n\n\n

What\u2019s needed to achieve the transformation of computerized medicine into algorithmic medicine? <\/strong><\/p>\n\n\n\n

In the first place, we need to define a criterion for what is understood as AI. Because these days, it\u2019s a random mix where any definition can be included [as part of AI]. But we are generating a taxonomy to understand that AI is first a field of knowledge and then afterwards, you must strip away different aspects of AI: on one hand, the automatic learning of machine learning and rule-based learning. Up until now, we only have evidence of the application of AI in the support of making decisions; that is what really must be used. But in the long term [AI] will other applications, based on the fact that the algorithm doesn\u2019t do anything by itself. The algorithm must reach the user through an alert system based on rules to become integrated into the process. At this point, the connection between the algorithm and reality has not yet been made. I think that we\u2019ll find that many of the developments that are being made are not ready to make that step.<\/p>\n\n\n\n

But will there finally be a day in which all doctors will be replaced by bots? <\/strong><\/p>\n\n\n\n

I doubt it, at least not by much. We must\nunderstand how much time will pass until the patient won\u2019t want to have a human\nin front of them. This will depend a great deal on the type of patient. I think\nthat there are five large\u2014and very different\u2014groups in terms of how they relate\nto healthcare providers. And the largest group is healthy people. If someone is\ndiagnosed with a terminal illness, their worldview changes and surely, they\nwill need to trust in someone who will mostly give them support and affection.<\/p>\n\n\n\n

The character Baymax* comes to mind\u2026<\/strong><\/p>\n\n\n\n

But it\u2019s very difficult for an algorithm\nto simulate human emotions, at least it hasn\u2019t been achieved up to now, though maybe\nthis will be possible in the future. But it won\u2019t happen that quickly. Instead,\nwhat will end up happening in not so many years from now\u2014as algorithmic\nmedicine is adopted\u2014is that doctors will use algorithms as contributory tools,\nthe same way that 150 years ago, some of them used stethoscopes and some didn\u2019t.\nThe doctor that uses algorithmic medicine will be more current and will advance\nmore rapidly and will take away work from the more old-fashioned providers that\ndon\u2019t use it. But it won\u2019t be that algorithms will replace doctors. In any\nevent, [these doctors] will be like centaurs, with medical knowledge augmented\nby computer knowledge that is capable of processing millions of data points at\na faster rate than the human mind. <\/p>\n\n\n\n

*Baymax\nis a robot nurse who is the star of the animated Disney movie <\/em>Big Hero 6.<\/em><\/p>\n\n\n\n

Next Steps<\/h2>\n\n\n\n

Contact us<\/a> to learn more about HospiScope, GHI’s database that includes the\nHospital Italiano de Buenos Aires and more than 20,000 other Latin American\nhospitals. This database was created as a resource for medical equipment\nmanufacturers by showing them the installed base equipment that hospitals have,\nproviding propensity-to-purchase analysis and other types of strategic planning\ntools for sales and marketing. <\/p>\n\n\n\n

GHI’s databases also use hospital data, including SurgiScope<\/a>, which tracks surgical procedures performed in Latin American hospitals, and ShareScope<\/a>, which indicates the market share of manufacturers in different Latin American countries for a wide range of medical equipment categories.<\/p>\n\n\n\n

\"Hospital<\/figure>\n\n\n\n

About the Hospital Italiano de Buenos Aires (HIBA) and the Healthcare IT Department<\/h2>\n\n\n\n

The Healthcare\nIT Department, headed by Dr. Luna, employs around 200 people. One of the main\nfocuses is the training of healthcare professionals in ICTs, with a\npostgraduate course in Medical IT at the hospital’s University Institute and\nthe Healthcare IT Conference that has been held every year since 2003. <\/p>\n\n\n\n

HIBA is one of\nthe best-equipped hospitals in Latin America according to GHI’s HospiRank<\/a>. It is also the first hospital in Argentina and second in Latin America\n(after Unimed in Recife, Brazil) to be fully computerized, certified in 2017 by\nthe Healthcare Information and Management Systems Society (HIMSS) of the\nElectronic Medical Record Adoption Model 7 (EMRAM 7, the highest level) scale.\nSince 2015, it has been certified by the Joint Commission International, which\naccredits patient safety and quality. <\/p>\n","protected":false},"excerpt":{"rendered":"

The challenges in implementing artificial intelligence in healthcare IT and key takeaways for hospitals<\/p>\n","protected":false},"author":14,"featured_media":17706,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[32],"tags":[],"class_list":{"0":"post-17705","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-ghi-analysis"},"_links":{"self":[{"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/posts\/17705","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/comments?post=17705"}],"version-history":[{"count":2,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/posts\/17705\/revisions"}],"predecessor-version":[{"id":29798,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/posts\/17705\/revisions\/29798"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/media\/17706"}],"wp:attachment":[{"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/media?parent=17705"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/categories?post=17705"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globalhealthintelligence.com\/pt-br\/wp-json\/wp\/v2\/tags?post=17705"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}