Along with the development of information system, various information systems of hospitals has been set up quite perfectly, such as HIS, CIS, PACS, LIS, EMR, charge management system, pharmacy management system, bed management, blood bank management and public health, etc.

But utility ratio of more advanced applications such as auxiliary therapy, superintendent decision support system, clinical decision support system, performance appraisal system, etc., is very low even in developed areas.

But utility ratio of more advanced applications such as auxiliary therapy, superintendent decision support system, clinical decision support system, performance appraisal system, etc., is very low even in developed areas.

The management or executives facing numerous fixed reports provided by information department and statistics department every day are difficult to really find out value behind data.

1. Mass data

Mass data generated from hospital business systems and growing faster and faster result in low efficiency and low utilization rate of data query and report generation, is it garbage or value? How to manage and use it?

2. Data cognition

Available in most traditional HIS, the simple analytic statistics charts are in sole data format, with poor flexibility and low interactivity, so that managers hardly make proper cognition of data.

3. Management decision

When Management Decisions, key data cannot be quickly extracted from the big data of a hospital to drive smart health care by data, and Management Decisions have to be made only through statistical statements provided by statistics section and information section or from various discrete systems.

The whole system covers three levels

1. Data layer: integrate hospital information system, break information island and realize data sharing.

2. Modeling layer:establishing different analysis topic marts for decision-making layer, management layer of data and indicators concerned by executive layer.

3. Business layer: sort the hospital business process and push the analysis results to the display layer.

A. Around doctors, data analysis and exploration from the views of doctors' medication, doctors and specific diseases and doctors' own habits, etc., to optimize doctors' decision-making and improve service level.

B. Around patients, data analysis and exploration from the views of the patient's personal factors, medical history and drug dependence relationship, etc.,to improve the core competitiveness of the hospital and optimize the management of doctors and patients.

C. Around disease, data analysis and exploration from the views of drug resistance, doctor's disease treatment methods, disease abnormal index and relationship between doctors and patients, etc., to deal with "abnormal" diseases confidently.

D. Around drugs, data analysis and exploration from the views of the influence of drugs on examination or laboratory index, effects of drugs on specific disease, the influence of the drugs on patients, etc., to assist doctors to use drugs rationally.

E. Around medical practitioners, data analysis and exploration from the views of problem-focused, scientific payoffs, etc., to improve the level of clinical research.

F. Around the management of doctors and patients, it helps with information asymmetry of doctors and patients and to effectively solve "three-long-and-one-short"problem, i.e., three long queues respectively for registration, waiting to see a doctor and paying fees, short period for diagnosis.

G. Around the hospital, real-time warning and monitoring from the views of core concern indicators, KPI performance assessment and scorecard,etc., to improve the core competitiveness of the hospital.

4. Display layer, in rich and beautiful chart, by flexible way of interaction, the analysis results are presented to decision-making level.

1. Basing on Yonghong medical big data analysis platform, decision-makers and management may have insight into the operation of the whole hospital.

2. Confidently deal with rapidly growing data of the hospital and respond to the calculation and presentation of any business on the basis of detailed data at the second level.

3. The business department can carry out some self-service analysis to meet the needs of medical exploration and analysis.

4. Capability to quickly respond to new analysis needs and changes, and improve work efficiency.