Overall, the results show that the RSV in Germany on Google Trends for cataract surgery, DMEK surgery and laser refractive corneal surgery has increased in recent years. On the other hand, the RSV for corneal transplantation as a general search term and specifically for LASIK tends to be constant or even decrease in Germany. Furthermore, the RSV on Google Trends showed a low to high statistical correlation with the number of procedures performed in Germany during a specific time period.
The results presented here allow drawing the following conclusions. (1) The RSV for certain cataract and corneal refractive surgery procedures correlates both geographically and temporally with the actual surgeries performed. (2) The correlation is strongly dependent on the search term used for the specific surgical procedure.
With that in mind, future studies should investigate which linguistic terms are actually used by patients. Furthermore, it is still not clear which age group actually uses Internet search engines to obtain general information about their illness or about an upcoming operation. This could lead to an even greater correlation between the number of operations performed and the actual search volume and thus increase the discriminatory power. Another important limitation is that different age groups and different end device users use divergent platforms (eg Twitter, LinkedIn, Facebook, Instagram). This can lead to bias as different platforms address different target groups. However, GoogleTrends is a particularly attractive platform because it addresses a broad spectrum of age groups and the data is easily accessible.
However, the use of certain search terms can also vary depending on the age of the patient and often over time or even geographically. Furthermore, with a decrease in the RSV of, for example, refractive surgery procedures, but at the same time a significant increase in the number of surgeries performed, it is noticeable that, hypothetically, a general acceptance and disclosure of a surgical procedure leads patients to become less informed about it on the internet (e.g., friend-to-friend disclosure) and later post their experiences more on social media channels. However, access to this data is now severely limited, so unfortunately no statements can be made about this in this study.
Until now, planning and distribution at the microeconomic level (ie, the individual hospital) as well as at the macroeconomic level (ie, the entire health care system) has been based only on retrospectively collected case numbers and past costs. The adaptation of strategic health issues based on data collected in real time is rare or non-existent so far. However, due to the fast pace of today’s world, which is partly caused by a multitude of disruptive processes, as well as increased international mobility, a quick adaptation to current developments or technologies is essential to achieve an adequate health economic outcome. Furthermore, as the SARS-CoV-19 pandemic currently illustrates, it is advantageous to ensure health system flexibility and react in a timely manner to national and global developments. For such plasticity in the health system, it is crucial to be able to collect and evaluate structural health data in real time and, in addition, to know how to react appropriately to them. Due to the decentralized structure of the German healthcare system, but also due to the orientation of data from previous years, it is very difficult in Germany compared to the UK, for example, to generate real-time data on geography and time -occurrence depending on diseases, the current number of surgical procedures performed or the demand for certain services in the health system and being able to react to them in the short term. A dataset of enormous size is generated in real time every day in the form of queries on search engines and social media by millions of people in Germany. Alternatives are large online registries maintained by large proportions of health care providers, such as IRIS in the US (by the AAO) or OREGIS (by the German Ophthalmological Society; www.oregis.de) in Germany.
The main limitation in validating the above hypothesis is the general lack of availability of official health data. In many countries where data are available, they often consist of large time intervals (eg annual data). Making it difficult to analyze and predict diseases and outbreaks13🇧🇷 A similar limitation exists in our study in terms of official health data that are based on each quarter of the year, neither real-time nor monthly data. On the other hand, despite the fact that data acquired from google trends, i.e. RSV, are not absolute data, which in turn are difficult to statistically correlate with real data from official authorities, using Pearson’s correlation in our study for the available data was an objective statistical methodology to prove, ie H1 or disprove H0 a correlation between RSV and actual data. We assume that other correlation projects can be resolved with more data available in future studies.
Also, as a limitation, it cannot be clearly distinguished whether the search terms were entered by physicians or patients. Furthermore, the search terms used could have been indirectly linguistically specified by the patients’ physicians. As the input device in the form of a smartphone is almost ubiquitous and always linked to the geographic position of the respective input. In the future, data acquired in real time related to eye diseases, treatments and surgical interventions may be crucial for immediate and short-term planning and even strategic guidance of public and private health practices.
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