Taking healthcare where it needs (TH-WIN)
James Fleck, MD, PhD: Anticancerweb 29 (01), 2023
Primary Health Care (PHC) has a resolution rate of 85%, but when care is restricted to general practitioners, it becomes less cost-effective and, consequently, does not arouse the interest of the private market. As health is everyone's need and right, PHC becomes a tripartite responsibility, including the public, private and social sectors. The lack of administrative creativity overloads and discourages PHC, a sector of undeniable relevance in public health. General practitioners and other health professionals who work exclusively in PHC feel undervalued due to overwork and low financial return, combined with interventions classified as low complexity. However, in a well-designed interactive health system, only 15% of PHC consultations will require highly complex procedures, often associated with higher costs. Currently, High Complexity Health Centers (HCHC) are oversized, as they also offer PHC. HCHC are widely available in large urban areas and their costs are provided by public and private resources, combined with the patient's co-payment, generating an undesirable global out-of-pocket crisis imposed on the patient and family. Logistical barriers generate inadequacy and delay in referral and counter-referral, underestimating the PHC and overestimating the HCHC. TH-WIN will break this paradigm by bringing high complexity decision-making to PHC, using new generation technical inputs to fill in the gaps.
TH-WIN identifies precise and confident patient’s clinical data records as the cornerstone for a well-succeeded integration of PHC and HCHC. The record should be standardized, hopefully using a global semantics. New ontologies are in advanced stage of implementation, which would provide a healthcare paradigm shift in electronic-personal health records (www.ephr.org), which would make them globally available. Currently, INTLEKT metadata proposed the Information Economy MetaLanguage (IEML) for modelling complex human systems. It came out as a result of many years on fundamental research (https://intlekt.io/). IEML has a semantic expressive power of a natural language, has the syntax of a regular language, is unambiguous and computable. A joint effort of physicians and IT professionals would result in proper program and device implementations. The generated large amount of clinical data (Big Data) could be processed by artificial intelligence (AI), that would provide a new scientific methodology for AI-oriented algorithms, both for clinical and administrative purposes. State-of-the art medical knowledge could be universally available and a collective intelligence effort could orient point-of-care decision making, filling out the imprecise gap, currently observed in a PHC-HCHC variable intersection area (VIA) of any healthcare system. VIA work-up can be customized for different communities, states and countries fulfilling patient’s needs and rights. Referral and counter-referral would be based on telemedicine and telemetry.
TH-WIN would fight inequities, since healthcare should be universal. Recent COVID-19 pandemic showed how fragile we are. There is no geographic barriers anymore. The planet works like a small community. Everyone's safety is supported by a universal and well-balanced health care system. All communities, states and countries could be reached. The extent of interventions can be designed individually, based on local ICER/QALY criteria. Local, national and international committees would evaluate specific needs and proposed interventions. Taking healthcare to where it needs to be is a rational way of dealing with the current imbalanced distribution of the healthcare system by identifying opportunities for VIA-improvement.
* Photo by Tomasz Frankowski on Unsplash
The proposal presented by the author aims to integrate Primary Health Care (PHC) and High Complexity Health Centers (HCHC) by standardizing and analyzing patients' clinical data, with the goal of improving the quality of care and fighting inequalities in the health system. Additionally, the implementation of ontologies and artificial intelligence technologies could facilitate access to and management of this data. However, the text does not discuss the feasibility and practical challenges of implementing this proposal. It is important to consider that improving the healthcare system depends not only on technological advances but also on public policies and adequate investments to value and train the professionals involved.
A proposta de integração entre a Atenção primária e os centros de Alta complexidade possibilita que as informações clínicas dos pacientes sejam analisadas e avaliadas em prol de melhorar a assistência à saúde. Uma vez que APS são a porta de entrada para se saber da doença de uma população, o que possibilitaria que essas doenças complexas que muitas vezes são limitadas de atendimento por uma regulação, possam ser de fácil acesso. Deste modo, a implementação de ontologias e tecnologias de inteligência artificial poderiam facilitar o acesso e o gerenciamento desses dados em prol da saúde coletiva.
The proposed integration between Primary Care and High Complexity centers makes it possible for patients' clinical information to be analyzed and evaluated in order to improve health care. Since PHC are the gateway to knowing about the disease of a population, which would allow these complex diseases, which are often limited to care by regulation, to be easily accessible. In this way, the implementation of ontologies and artificial intelligence technologies could facilitate access and management of these data in favor of collective health
Given that the complexity of decision-making in primary health care depends on the specific circumstances and the needs of the patient, using Artificial intelligence (AI) in order to analyze large amounts of data and identify patterns and trends can actually increase the resolution rate of PHC. Although 85% is already a great rate, I think we can improve that by using modern technology. Moreover, technological innovations can be extremely uneven, therefore, it is great that the text defends the idea of using technology to generate more equity in the health system.
While the idea of TH-WIN is revolutionary and seems adequate in a context of inequality and overload of the primary care systems around the globe, we do have to bring up a discution that extrapolates the healthcare field. We ought to ask ourselves why did things get this way. We should consider the fact that implementing these kinds of things are subjected to all kinds of governments, politicians and financial profits, wich, I may say, are the exact reason we are where we are.
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