Healthcare Data Collection and Labeling Market Trends

Growth Drivers

• Broadening telehealth access: Telemedicine platforms permit remote consultation, diagnoses, and continuous observations of patients, boosting the healthcare data collection and labeling market growth. It helps generate a staggering amount of patient data with accurate categorization for further analysis. For instance, in November 2022, Medcase & NTT DATA signed a definitive agreement to enable healthcare AI developers for a holistic solution to access, annotate, and label critical the vast imaging data. Moreover, as telemedicine merges with EHRs, a strong potential demand arises for standardized and accurate data labeling that shall enable interoperability while augmenting care quality.
• Increasing interest in precision medicine: To assist patients with tailored treatment strategies, personalized healthcare is predominantly gaining significance. This is further anticipated to boost the healthcare data collection and labeling market growth. Precision medicine comprises designing treatments and interventions based on individual genetic, environmental, and lifestyle factors. For instance, in July 2022, it was published that according to the Health Care Insights Study, 83% of consumers believe that coordination between all of their healthcare providers is crucial to their holistic health care. With the change in the healthcare outlook toward more customized care, the demand for healthcare data collection and labeling is expected to flourish substantially.

Challenges

• Interoperability issues: The biggest challenge with the market, is interoperability which creates a block in the sharing of information across different systems and platforms. Developing holistic patient profiles by integrating data from other healthcare providers, laboratories, and EHR systems requires seamless interoperability. Moreover, the failure of integration among different EHR systems hampers the connectivity of data, which compromises partial patient history and the quality of care. Furthermore, protocols for data introduce much complexity, with different code systems being adopted by health organizations creating a challenge for the healthcare data collection and labeling market.
• High cost and resource intensity: Gathering, managing, and labeling healthcare data requires significant investments in advanced technologies skilled personnel, and up-front training. Furthermore, medical data ranges from clinical notes to imaging results and thus requires specialized expertise for proper labeling and regulatory standards compliance. In addition, independent clinics with minimal infrastructural and resource structures working within very limited capacities fail to meet technological requirements to efficiently manage the data flow. Therefore, the data collection and labeling, which is cost consuming brings inequality to the healthcare data usage landscape.