Patent ID: 11966374
Assignee: SERV MEDICAL PTE. LTD.
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A medical clinical data quality analysis system based on big data, comprising a clinical data acquisition module, an admission data analysis module, a course data analysis module, a medical record quality inspection module, an operating quality inspection module, and a medical big data server, wherein the clinical data acquisition module is configured to acquire authenticity data and compliance data of a patient in each clinical department at admission within a fixed period of time and authenticity data and compliance data of the patient after the fixed period of time, and send the authenticity data and the compliance data to the admission data analysis module and the medical big data server, and the clinical data acquisition module is further configured to acquire process data and conclusive data of the patient in each clinical department during hospitalization and at discharge within a fixed period of time and process data and conclusive data of the patient after the fixed period of time, and send the process data and the conclusive data to the course data analysis module and the medical big data server;
the admission data analysis module is configured to perform authenticity analysis and processing on the authenticity data of the patient in each clinical department at admission within the fixed period of time and the authenticity data of the patient after the fixed period of time to obtain an authenticity factor for the clinical department, and send the authenticity factor to the medical record quality inspection module, and the admission data analysis module is further configured to perform compliance analysis and processing on the compliance data of the patient in each clinical department at admission within the fixed period of time and the compliance data of the patient after the fixed period of time to obtain a compliance factor for the clinical department, and send the compliance factor to the medical record quality inspection module,
wherein a specific process of the authenticity analysis and processing is as follows:
in step 1, comparing the authenticity data of the patient in each clinical department at admission within the fixed period of time with the authenticity data of the patient after the fixed period of time, to obtain a frequency of occurrence of mistakes, an average time for rectifying mistakes for qualification, and a number of completions mistakes are rectified for qualification of the authenticity data; and
in step 2, marking the frequency of occurrence of mistakes, the average time for rectifying mistakes for qualification, and the number of completions mistakes are rectified for qualification of the authenticity data as Zpi, Zgi, and Zci, respectively, wherein i=1, . . . , n, and n is a positive integer greater than 1; and
performing processing according to a formula
Zsi=aV(alxZpi)2+(a2xZgi)2+(a3xZci)2×(Zpi+Zgi+Zci) to obtain an authenticity factor Zsi for each clinical department, wherein alpha is a correction factor and alpha=0.957, a1, a2, and a3 are all preset weight coefficients, a1>a2>a3>0, and a1+a2+a3=3.189; and
a specific process of the compliance analysis and processing is as follows:
in step 1, comparing the compliance data of the patient in each clinical department at admission within the fixed period of time with the compliance data of the patient after the fixed period of time, to obtain a frequency of occurrence of violations, an average time for rectifying violations for qualification, and a number of completions violations are rectified for qualification of the compliance data; and
in step 2, marking the frequency of occurrence of violations, the average time for rectifying violations for qualification, and the number of completions violations are rectified for qualification of the compliance data as Hpi, Hsi, and Hci, respectively, wherein i=1, . . . , n, and n is a positive integer greater than 1; and performing processing according to a formula Hgi=/JV(b1xHpi)2+(b2xHsi)2+(b3xHci)2×(Hpi+Hsi+Hci) to obtain a compliance factor Hgi for each clinical department, wherein beta is a correction factor and beta=0.986, b1, b2, and b3 are all preset weight coefficients, b1>b2>b3>0, and b1+b2+b3=4.219;
the course data analysis module is configured to perform process analysis and processing on the process data of the patient in each clinical department during hospitalization and at discharge within the fixed period of time and the process data of the patient after the fixed period of time to obtain a process factor for the clinical department, and send the process factor to the operating quality inspection module, and the course data analysis module is further configured to perform conclusive analysis and processing on the conclusive data of the patient in each clinical department during hospitalization and at discharge within the fixed period of time and the conclusive data of the patient after the fixed period of time to obtain a conclusion factor for the clinical department, and send the conclusion factor to the quality inspection module,
wherein a specific process of the process analysis and processing is as follows:
in step 1, comparing the process data of the patient in each clinical department during hospitalization and at discharge within the fixed period of time with the process data of the patient after the fixed period of time, to obtain a total number of occurrences of errors, a total time for rectifying errors for qualification, and a number of completions errors are rectified for qualification of the process data; and
in step 2, marking the total number of occurrences of errors, the total time for rectifying errors for qualification, and the number of completions errors are rectified for qualification of the process data as Gci, Gsi, and Ghi, respectively, wherein i=1, . . . , n, and n is a positive integer greater than 1; and performing processing according to a formula to obtain a process factor Gzi for each clinical department, wherein delta is a correction factor and delta=0.925, c1, c2, and c3 are all preset weight coefficients, c1>c2>c3>0, and c1+c2+c3=6.284; and
a specific process of the conclusive analysis and processing is as follows:
in step 1, comparing the conclusive data of the patient in each clinical department during hospitalization and at discharge within the fixed period of time with the conclusive data of the patient after the fixed period of time, to obtain a total number of occurrences of problems, a total time for rectifying problems for qualification, and a number of completions problems are rectified for qualification of the conclusive data; and
in step 2, marking the total number of occurrences of problems, the total time for rectifying problems for qualification, and the number of completions problems are rectified for qualification of the conclusive data as Jci, Jsi, and Jhi, respectively, wherein i=1, . . . , n, and n is a positive integer greater than 1; and performing processing according to a formula J*_(Jci)2 (Jsi)2 (Jhi)2 ZI−c3−d1+−d2+−d3 to obtain a conclusion factor Jzi for each clinical department, wherein epsilon is a correction factor and epsilon=0.937, d1, d2, and d3 are all preset weight coefficients, d1>d2>d3>0, and d1+d2+d3=4.876; the medical record quality inspection module is configured to process the authenticity factor Zsi and the compliance factor Hgi of the clinical department according to a formula A Cn−n ZH=n I·JCelxZsi)+Ce2xHgi) i=I to obtain a medical record quality coefficient ZH, and compare the medical record quality coefficient ZH with a threshold thereof, and output a medical record qualification signal when the medical record quality coefficient is greater than the threshold thereof, and output a medical record disqualification signal and send the medical record disqualification signal to the medical big data server when the medical record quality coefficient is less than or equal to the threshold thereof, wherein lambda is a correction factor and lambda=1.387, e1 and e2 are both preset weight coefficients, e1>e2>0, and e1+e2=1.843;
the operating quality inspection module is configured to process the process factor G zi and the conclusion factor Jzi of the clinical department according to a formula GJ=---μ_Cn−1)_n I−JCflxG zi)+Cf2xJzi) i=I to obtain an operating quality coefficient GJ, and compare the operating quality coefficient GJ with a threshold thereof, and output an operating qualification signal when the operating quality coefficient is greater than the threshold thereof, and output an operating disqualification signal and send the operating disqualification signal to the medical big data server when the operating quality coefficient is less than or equal to the threshold thereof, wherein mu is a correction factor and mu=1.185, f1 and f2 are both preset weight coefficients, f1>f2>0, and f1+f2=2.527; and
the medical big data server is configured to multiply the medical record quality coefficient corresponding to the medical record disqualification signal by the operating quality coefficient corresponding to the operating disqualification signal to obtain a comprehensive quality coefficient, and compare the comprehensive quality coefficient with a preset range thereof, and perform no processing when the comprehensive quality coefficient is greater than a maximum value in the preset range thereof, output a second-level quality control signal when the comprehensive quality coefficient is within the preset range thereof, and output a first-level quality control signal when the comprehensive quality coefficient is less than a minimum value in the preset range thereof.