by Point of care (POC) data management systems integrate all medical testing devices, monitors, and other medical equipment at the point of patient care to provide rapid access to patient data in electronic health records. POC data management systems enables clinicians to seamlessly and efficiently share patient information across care settings. They facilitate real-time clinical decision-making by compiling diagnostics test results, patient vitals, clinical notes, and other patient data into a single platform accessible throughout hospitals, clinics, and other healthcare facilities. Moreover, POC data management systems offer streamlined workflows and centralized management of medical devices and instruments. They automate the uploading of patient test results to electronic health records for easy sharing with physicians, medical staff, and across departments.
The global Point of Care (PoC) Data Management Systems Market is estimated to be valued at US$ 5.2 billion in 2023 and is expected to exhibit a CAGR of 12% over the forecast period 2023-2033, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics
Growing Adoption of Electronic Health Records: Electronic health records (EHR) are digital versions of paper-based patient medical charts that facilitate real-time, team-based care. EHRs improve quality of care, reduce healthcare costs, and enhance healthcare operations and compliance. Government initiatives and incentives to promote adoption of EHRs among healthcare providers is driving demand for POC data management systems that help populate and integrate EHRs with near-patient testing data. Additionally, rising healthcare costs have necessitated more efficient management of patient information and improved clinical workflows which is boosting adoption of POC data management systems across care settings.
Segment Analysis
The point of care (POC) data management systems market is dominated by the infectious disease testing sub segment. Rapid diagnosis and quick decision making is critical in case of infectious diseases like HIV, hepatitis, influenza etc. POC data management systems help in faster reporting of test results to physicians, thus enabling immediate commencement of correct treatment. This increases the demand for such systems from diagnostic centers, hospitals and clinics which deal with large infectious disease patient loads on a daily basis.
PEST Analysis
Political: Guidelines mandating electronic healthcare records and connectivity between POC devices and central data servers laid down by regulatory bodies promote adoption of POC data management systems.
Economic: Rising incidence of infectious diseases coupled with increasing healthcare expenditures drives the need for cost-effective POC testing and management of test data for improved patient outcomes.
Social: Growing awareness among general public about benefits of timely diagnosis and need for integrated healthcare services boosts demand.
Technological: Advancements enabling wireless data transfer, integration of EMR with external systems, innovations to make systems user-friendly and customizable as per end-user needs expand the market scope.
Key Takeaways
The global point of care (POC) data management systems market is expected to witness high growth.
Regional analysis: North America currently dominates the market due to presence of major players and rapid adoption of healthcare IT solutions. Europe and Asia Pacific are fastest growing regions on back of rising infectious disease burden, government initiatives to digitize healthcare systems and growing medical tourism.
Key players operating in the point of care (POC) data management systems market are Siemens Healthineers, HemoCue AB, F. Hoffmann-La Roche Ltd., Abbott Laboratories, Becton, Dickinson and Company, Quidel Corporation. Key players focus on launching integrated platforms, partnerships with diagnostic instrument manufacturers and geographic expansion to strengthen market position.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
