In 2023, negative growth in the number of Chinese population will become the new normal, and behind this major turning point is the dual impact of rapid aging and extremely low fertility rate. This long-term demographic change has not only had a profound impact on the size of the healthcare services market and the health industry, but has also created new opportunities.
A few days ago, Yikai Capital released a white paper to discuss the changes and market performance brought about by the negative growth of Chinese population in 2023, and forecast the market opportunities in 2024. According to the China Health Statistical Yearbook and the statistics of the National Health Commission, the overall size of the medical service market in mainland China in 2022 is estimated to be around 8.3 trillion yuan. However, the white paper believes that the overall growth rate of the medical service market is roughly around 4.5%, so the medical service market size in 2023 will be close to 9 trillion yuan, slightly lower than the 9.1 trillion yuan mentioned in the "Healthy China 2030" planning outline issued by the National Health Commission in 2017.
The problem of "one old and one young" has caused long-term changes in the demographic structure, affecting the scale of the medical service market and even the extension of the entire health industry, and at the same time bursting out new business opportunities.
One
The healthcare industry is being reshaped
1. Negative population growth and the problem of "one old and one young".
China's demographic development is showing a new trend. The negative population growth for two consecutive years has undoubtedly brought new challenges to society. This trend requires us to pay close attention to the issue of "one old and one young", that is, pension services and fertility optimization. With the deepening of the aging population, the pension service industry is ushering in the first year of its development, and how to provide high-quality and diversified pension services has become the key. At the same time, the issue of fertility has also risen from a family affair to the level of a national affair, and how to optimize the fertility environment and increase the fertility rate has become an urgent problem to be solved.
2. The operation and capital market of medical service enterprises
Although the performance of medical service companies has improved after the epidemic, the downward trend of the capital market and the impact of medical insurance reform policies such as centralized procurement and DRGS in the medical industry have made investment institutions more cautious in terms of investment and exit. This change has had a profound impact on the business strategy of medical service companies, and enterprises need to pay more attention to their profitability and risk control. At the same time, the positive effect of "medical anti-corruption" has begun to appear, which is undoubtedly a profound baptism for the medical industry, which objectively delays the growth of the operating performance of ToB medical service enterprises. The reshaping of the system is not achieved overnight, and requires the joint efforts of all parties and the precipitation of time.
3.AI application of technology in the field of medical services
With the advent of ChatGPT, a "thousand model war" has been set off, and AI medical care is entering a new stage of development. Leading companies have turned their perspectives to the implementation of medical vertical models at the first time, and AI medical has entered a new investment cycle and ushered in a boom.
Since 2023, domestic medical models have been in full bloom, with traditional Internet giants led by Baidu, Huawei, and Tencent, medical information platform companies represented by Weining Health and Neusoft, and Internet medical rookies represented by Yidu and Left-handed Doctors, and many other companies gearing up, with nearly 40 large models coming out in the past year. Multimodal large models are fully empowering the development of industrial ecosystems such as services, diagnosis and treatment.
Two
New demands are emerging
Based on the above changes, the white paper believes that under the "silver economy", investment opportunities in medical services involving the concept of pension are becoming more and more apparent. At present, the elderly care service system in mainland China is gradually shifting from institutional pension to community home care, focusing on the construction of the pension service system, elderly supplies, rehabilitation aids, talent education, age-appropriate construction, smart pension, elderly finance and other fields have gradually started. Medical treatment, medicine, medical equipment, rehabilitation and other forms of business are gradually becoming the focus. At the same time, the rise of "new consumption" among the middle-aged and low-aged elderly groups has led to a growing demand for intelligent, technological and intelligent products.
In addition, the white paper mentions that the recovery of consumer medical care in the post-epidemic period, the development of the new obstetrics and gynecology and assisted reproduction industry driven by the number and structural changes of newborns, and the "new Chinese medicine" that integrates ophthalmic chain services, traditional Chinese medicine and modern medical consumption concepts, will attract market attention.
More importantly, generative AI and the large model technology behind it have a disruptive impact on the B-side, G-side, and C-side, which is expected to give rise to a new round of medical digitalization. The white paper points out that large models may play a significant role in assisting diagnosis/treatment/protocol generation, patient services, hospital management/quality control, medical research, public health and other fields.
For example, in the field of auxiliary diagnosis/decision-making/protocol generation, compared with the traditional CDSS (clinical decision support system), the training data of large models is more extensive, and the self-purification ability is more efficient, so it can bring a significant improvement to CDSS. In addition, in terms of interaction and autonomous assistance, it can also improve the experience of doctors. At the same time, large models can quickly generate treatment plans after receiving patients in emergency pharmacy services, orthopedics, bacterial infections, and other fields.
Three
The industry needs vertical models more
The white paper also emphasizes that due to the particularity and high standards of medical scenarios, the existing general large models are often difficult to meet the specific needs of the medical industry, which requires the development of vertical models specifically for the medical field to meet the specific needs and challenges of the field.
First of all, the scenarios in the medical industry require a high degree of professionalism and technology, and a very low tolerance for errors, which requires large models to have higher accuracy and professionalism when providing medical advice. AI systems need to rely on a wealth of medical professional data to generate high-quality recommendations that meet medical standards.
Second, the multimodal nature of medical data requires large models to be able to process and analyze multiple data types, including medical images, text, speech, and video. To enable effective decision support in healthcare, large models must be able to synthesize these different types of data to provide comprehensive healthcare solutions.
Furthermore, considering the actual operating environment of the hospital and the requirements for data security, the large model needs to be balanced in terms of scale and implementability. Larger models are not better, but rather to ensure that they can be deployed and run effectively in a hospital environment.
In terms of training data, the diversity and complexity of medical data poses additional challenges for the training of large models. In order to realize the effective application of large models in the medical field, a large amount of high-quality medical image data is required. At the same time, with the development of computer vision and privacy protection technologies, computing power allocation and data management have become the key factors to promote the development of models. Therefore, it is necessary to further build and improve the relevant infrastructure, and build cross-hospital datasets to promote the effective integration and utilization of medical data.
Finally, in terms of application objects, medical models mainly serve medical institutions and government departments, and these users have extremely high requirements for the accuracy and reliability of the models. Therefore, when providing decision support, medical large models must ensure the accuracy of their conclusions and be able to provide sufficient evidence to support their recommendations to meet the strict requirements of the medical field.
Four
epilogue
The new normal of negative growth of Chinese population has brought unprecedented challenges and opportunities to the medical service industry, and new investment booms have emerged in various segments of the medical field. It is worth noting that generative AI and the large model technology behind it have had a subversive impact on the digitalization of the medical industry. Pay attention to the official account of the big health faction, reply to the keyword [medical and health services] to download the full text of the white paper.
Source | Big Health, 2024 CEC Capital China Health Industry White Paper - Medical and Health Services
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