Informatization is the process of transforming information into numbers, while data analysis is the process of transforming numbers into information, and it is the process of using data to extract useful information, provide decision-making basis, and play the role of data.
The premise of data analysis is data, the premise of data is informatization, the premise of informatization is the scene, and the premise of the scenario is the individual needs of the service object.
The data comes from the scenario-based individual needs, and the numbers created and generated based on the scenarios of individual needs will continue to create value for individual needs and will be more meaningful for analysis.
Scenarios are divided into systematic scenarios and institutional scenarios, the systematic scenarios are vertical general scenarios, the institutional scenarios are parallel general scenarios, the systematic scenarios support institutional scenarios, and the institutional scenarios are connected to the systematic scenarios, and the digital quality formed on this basis has more prerequisites for data analysis.
Data comes from the demand individual and its demand driven, after all, it is necessary to serve the individual needs as the fundamental purpose, so the data analysis should be based on the demand standard, and the data analysis should be described through data analysis, and the degree of demand satisfaction and improvement opportunities should be verified, and the data analysis without this core will lose its most important value.
Over the years, health informatization is only the informatization of replicating the inherent process within the boundaries of the institution, and the original application scenario has not had a pulling effect on the transformation and upgrading of the institution, not only there is no connection between the upstream, middle and downstream of the service chain, but also the internal structure, process, and relationship have not changed, and the spontaneous supply and demand relationship between individual needs and individual institutions has not been touched, although the numbers come from individual needs but are not "born" for individual needs, and the data analysis lacks a basic quality basis.
Even if the data has the value of analysis, due to the lack of full consideration of the continuum between data and individual needs at the beginning of informatization, and due to the lack of statistical technology of system developers, there is no built-in analysis function in the system in terms of purpose and tools, especially the lack of improved data analysis capabilities. The first generation of informatization only accumulates data for the internal management of the institution, and only conducts simple statistics on the data for internal management, and does not have a standardized data analysis foundation and data analysis ability. From the perspective of individual needs, all data occupies large-capacity storage resources and is basically unusable, and no matter how it is "washed", there is a problem of disconnection with individual needs.
Without fundamentally changing the relationship between the system and institutions, and failing to establish a relationship between demand and supply, there is no way to build a new generation of information application scenarios, there is no digital ecology from demand for demand, and there is no solid foundation for data analysis, and the value of digital as a resource cannot be brought into play. It seems to be a data analysis problem, but behind it is a service model, a management model, and a data problem.
Digitalization and intelligence based on data analysis, especially the formation of artificial intelligence, will eliminate intermediate management links and directly serve individual needs. Without numbers that are connected to individual needs, how to "feed" artificial intelligence that serves individual needs. From the perspective of development, the new generation of informatization is only to prepare digital resources for intelligence, and the use of digital training artificial intelligence is the terminal of informatization, and this process needs data analysis to judge and guide from beginning to end.
The biggest difference between the new generation of informatization and the first generation of informatization is whether the final generation of data can become an intelligent digital resource.
Aiming at the development direction of digital intelligence, the management of single-disease groups establishes an information conversion chain of demand-scenario-digital-demand, "generates" useful numbers according to demand, uses numbers to serve demand, realizes digital health governance, and lays the foundation for intelligent development.