In the healthcare sector, communication amongst the members of the medical team is very less due to the lack of medical knowledge amongst administrators and difficulty in analyzing the accurate and meaningful clinical data. In recent times, a paradigm shift has taken place in the healthcare landscape providing novel techniques to eradicate the communication gap amongst the physicians, administrators, and patients. Patient engagement techniques have been deployed to monitor health changes and provide accurate information with highly satisfying health experiences. A survey carried out at Lumere with 276 respondents has shown that effective communication helps physicians to achieve better organizational quality and cost metric results by frequently updating the clinical data along with evidences.
Furthermore, the data analysts have recommended certain measures to achieve communication amongst patient data and physicians. Evaluation of the process involved in enabling communication amongst the physicians plays a key role during this process. In numerous health care systems, the data communication takes place in an irregular and inconsistent manner.
During medical analysis, numerous data is collected such as patient biography, past health records, and data obtained from the administration section. Mining the required data effectively along with evidence helps both physicians and patients to select cost-effective drug and other device alternatives that can be used to achieve an effective medical solution cost-effectively. The effective approach to mine medical data is to deploy a machine-learning algorithm. There are numerous algorithms such as artificial neural network, support vector machines, naïve Bayes algorithm, and decision tree classifier. Algorithm selected should be on the basis of the application and its previous analysis results.
The final process will be concerning data classification. Before the data is being classified or submitted to the physicians, the health system administrators should ensure that the data follows the medical standards and is in a well-organized manner with high-quality details.
In summary, the advanced healthcare systems are transforming their medical services from cost-based to value-oriented services. Since communication is the critical barrier, which still exists in many medical systems, organizations are striving to overcome the limitations. Moreover, certain critical metrics such as success, identity champ, and build consensus along with trust factor should be ascertained in the future to achieve efficient data communication.