To enhance the clinical thinking of laboratory personnel and their capability to interpret clinical results, this study proposes a new working model known as the "Systemic Disease Diagnosis Team" mode. Drawing inspiration from the guiding principles of "Organ-oriented Teaching" and "PBL Teaching," this mode organizes laboratory physicians and laboratory technicians with clinical medical backgrounds to engage in learning through disease diagnosis and treatment guidelines and typical case diagnostic pathways. Through various channels and forms, they actively participate in clinical communication and collaboration. The objective of this model is to break down the boundaries of laboratory sub-specialties, emphasizing the integration of laboratory expertise and the accumulation of relevant clinical diagnostic and treatment knowledge. Ultimately, the aim is to develop the ability to effectively translate laboratory results into diagnostic and treatment information. Having been in operation for over two years, eight systemic disease diagnosis teams have been established within the department. Members of these teams have experienced a significant improvement in their awareness and abilities to participate in clinical diagnosis and treatment. The number of invitations to clinical consultations and involvement in multidisciplinary treatment models (MDT) has notably increased. Attempts to create laboratory analysis reports with diagnostic significance and disease clinical diagnostic pathways have been well-received in the clinical community. However, during the operational process, challenges persist, including the need to develop personalized training plans for team members and to refine the working and management systems of the systemic disease diagnosis teams.

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.