OBJECTIVETo explore the current state and the mainly typical problems and vulnerable parts existed in the quality management systems (QMS) of local in vitro diagnostic reagent manufactures.

METHODTo statistical analyze the problems found in the quality management system of in vitro diagnostic reagent manufactures through inspection organized by CCD, SFDA during the second half year of 2011.

RESULTSThe total level of the QMS of local IVD manufacturers has risen greatly in past recent years, but a lot of problems still existed. The main vulnerable issues existed in QMS of IVD are documentation and recorder control, design control and validation, producing process control, as well as monitoring and quality control etc, to which should be paid more attention in the future improvement made by the enterprises and supervision by the administration authorities.

From the view of the potential risks of allogeneic bone products in clinical use. the key aspects of risk control and quality management for these products are discussed, as well as the general problems existing in the quality management system of their production enterprises in China are briefly introduced.
Bone Transplantation ; instrumentation ; methods ; Humans ; Quality Control ; Risk Assessment ; Transplantation, Homologous ; adverse effects ; instrumentation ; methods

The objectives of QMS for quality assurance of products are achieved by formulation, implement, and management of document system. Document (includes record) system is important constituent part of QMS. In this paper, the important issues and relative requirements of GMP on the establishment and management of documentation within quality management system (QMS) of medical device enterprises are discussed with the aim of providing reference for relative enterprises to build and improve their QMS and to implement GMP.
Equipment and Supplies ; Forms and Records Control ; methods ; Quality Control

In this paper, the procedures, logos, methods, essentials as well as notable problems for inspecting the qualification management system of in vitro diagnostic regent manufactures are discussed, with aims of promoting inspector's practical level and consequentially ensuring the quality, standard and efficacy of the inspection.
Diagnostic Techniques and Procedures ; instrumentation ; Indicators and Reagents ; standards ; Quality Assurance, Health Care ; Quality Control

Objective To analyze the massive explosions and burn at Tianjin Port in 2015 resulted in a mass casualty event,and the entire course of response of a hospital to deal with such major sudden accident in order to find a rational strategy for optimal use of medical resources and reduce the critical mortality.Methods This study was done by a retrospective analysis of data from one trauma center at an academic hospital.Data including outcome,triage,severity and pattern of injuries,patient flow,and medical resources used were obtained by the review of hospital records.Results This disaster caused 165 deaths,8 missing contact,and 797 non-fatal casualties.The Pingjin Hospital admitted 298 casualties,and 29 of them were seriously injured referred to by Tianjin Emergency Medical Center.Excessive triage rate made after transfer to another hospital was 62.07% with 11 of the 29 severely injured patients.Maximum (also the first)surge had 147 injured patients arrived around one hour after incident,the second surge had 31 seriously injured patients occurred around 4 hours after incident.Of them,17 patients needed surgery and 17 patients were admitted to the intensive care unit.Conclusions These data showed that the number of casualties in the first surge was substantially larger than predicted and those casualties had less severe trauma,whereas the number of the injured in the second surge was less but the trauma was more severe.In order to maintain the hospital surge capacity,an effective re-triage and a hospital-wide damage control principle can be used to deal with.

The objectives of QMS for quality assurance of products are achieved by formulation,implement, and management of document system. Document (includes record) system is important constituent part of QMS. In this paper, the important issues and relative requirements of GMP on the establishment and management of documentation within quality management system (QMS) of medical device enterprises are discussed with the aim of providing reference for relative enterprises to build and improve their QMS and to implement GMP.

Outpatient information management system is an important part of hospital information system,which plays an important role in hospital management,patient treatment,medical insurance reimbursement and settlement.This study integrated the application modes of big data,cloud computing,Internet of things and other cutting-edge technologies of artificial intelligence,focused on the intelligent decision support and whole-process simplified management of the diagnosis and treatment behavior of clinical TCM physicians,and developed a cloud intelligent TCM outpatient system for primary medical care.The system has intelligent medical functions such as intelligent prescription monitoring driven by the rule engine and intelligent recommendation of traditional Chinese medicine knowledge.It seamlessly connects with the intelligent four-diagnosis instrument for information collection and medical order input,and realizes the cloud storage,computing,distribution,management,service and outpatient process,multi-directional and convenient management mode.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.