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In Sweden GPs are going extinct, but can we expect AIs to help save the GP function?

It is now quite common in the Swedish health system where all specialists sit in their own silos that nobody actually has the responsibility for taking a holistic view of a patient. Specialists are primarily looking to hand their patients over either to the the pre-defined “next care giver” or to send them home. No specialist seems to have any particular responsibility to peek across specialisation boundaries. I miss my old-fashioned General Practitioner (GP) but wonder if the species is going extinct.

(My own recent experience with the health service may not be representative and may only be anecdotal. Nevertheless, I believe that this lack of holistic responsibility in the health service has led to medication from one specialisation leading to interference with medications prescribed by other specialisations and with nobody actually having the responsibility to check that they could work together. In my case, detecting and resolving these interferences between different medications is still ongoing and has been extremely frustrating and uncomfortable).

It seems to me that not only are doctors forced to work primarily to these hand-over criteria rather than patient well-being, but that even care institutions (clinics, hospitals, departments) seem to set their priorities on fulfilling hand-over conditions. It is probably policy that fulfilling a handover protocol is more important than a patient’s well-being. Each institution or department is looking to hand over responsibility to the next health-care station. The lack of a GP type of role as the primary care giver means that there is often little continuity in who a patient first meets at the primary care station. There is no one any longer, it seems, who has the responsibility for taking a holistic view of the patient.

I have a gut-feeling – perhaps just wishful thinking – that the use of AI will facilitate the possibility of every patient in any public health system having a primary care giver (human + AI) who actually does take a holistic view and who takes responsibility for the well-being of a patient.

So I put some questions to ChatGPT:

ktwop: Can neural networks be used for medical diagnostics?
 
ChatGPT: Yes, neural networks can be and are being used for medical diagnostics. Neural networks, particularly deep learning models, have shown great promise in various medical applications, including image analysis, pathology detection, and disease diagnosis. Here are some ways in which neural networks are being utilized in medical diagnostics:

  1. Medical Imaging:

    • MRI and CT Scans: Neural networks can analyze medical images such as MRI and CT scans to detect abnormalities, tumors, or other medical conditions.

    • X-rays: Deep learning models have been employed to interpret X-ray images for conditions like fractures, lung diseases, and more.

  2. Pathology and Histology:

    • Neural networks can assist pathologists in analyzing histopathology slides, identifying cancerous cells, and providing more accurate and efficient diagnoses.

  3. Disease Diagnosis:

    • Neural networks can be trained to recognize patterns and features in patient data, helping in the diagnosis of diseases based on symptoms, lab results, and other clinical information.

  4. Drug Discovery:

    • Neural networks are used in drug discovery processes to analyze biological data and predict potential drug candidates.

  5. Predictive Analytics:

    • Neural networks can be employed for predicting patient outcomes, disease progression, and the likelihood of complications based on historical patient data.

  6. Genomic Data Analysis:

    • Neural networks can analyze genomic data to identify genetic markers associated with certain diseases and predict susceptibility to particular conditions.

  7. Telemedicine:

    • Neural networks can play a role in remote patient monitoring and telemedicine by analyzing data from wearable devices to assess a patient’s health status.

  8. Natural Language Processing (NLP):

    • NLP techniques, often integrated with neural networks, can be used to analyze and extract information from medical literature, clinical notes, and patient records.

It’s important to note that while neural networks and other machine learning approaches show promise, they are not a replacement for professional medical expertise. They should be used as tools to assist healthcare professionals in making more accurate and timely diagnoses. Additionally, ethical considerations, data privacy, and regulatory compliance are crucial aspects when deploying such technologies in the medical field.

 
ktwop: Can a neural network based AI take over the functions of a general practitioner.
 
ChatGPT : As of my last knowledge update in January 2022, while neural networks and artificial intelligence (AI) have made significant advancements in various medical applications, a neural network alone is unlikely to completely replace the functions of a general practitioner (GP). General practitioners perform a wide range of tasks that go beyond the capabilities of current AI systems. Here are some reasons why:

  1. Complex Decision-Making:

    • General practitioners often deal with complex cases that require a holistic understanding of a patient’s medical history, lifestyle, and other contextual factors. They need to integrate information from various sources to make nuanced and individualized decisions.

  2. Patient Interaction:

    • A significant part of a GP’s role involves interacting with patients, understanding their symptoms, providing explanations, and addressing concerns. Building a rapport with patients and considering their subjective experiences is a crucial aspect of healthcare that AI lacks.

  3. Diagnostic Challenges:

    • Many medical diagnoses involve intricate decision trees and require a deep understanding of diverse symptoms. GPs use their clinical expertise to navigate through these complexities, often relying on intuition and experience.

  4. Ethical and Emotional Considerations:

    • GPs often deal with ethical dilemmas and emotionally charged situations. They provide support and guidance to patients, taking into account not only medical factors but also the patient’s emotional and psychological well-being.

  5. Preventive Care and Health Promotion:

    • GPs play a vital role in preventive care, health promotion, and patient education. They offer advice on lifestyle changes, vaccination schedules, and early detection of risk factors.

While AI, including neural networks, can augment the capabilities of healthcare professionals by assisting in diagnosis, analyzing medical images, and processing large datasets, a comprehensive and empathetic approach to patient care remains a distinctive feature of human healthcare providers.

The integration of AI in healthcare is more likely to involve collaboration between AI systems and healthcare professionals, with AI serving as a valuable tool to support decision-making rather than replacing the human element. Additionally, regulatory and ethical considerations will continue to shape the role of AI in healthcare. It’s essential to stay updated on the latest developments in this rapidly evolving field.

A pretty good summary but not entirely satisfactory or optimistic.

Perhaps AIs will come and GPs will return – but not anytime soon.

 

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This entry was posted on December 24, 2023 at 10:14 pm and is filed under Health. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.