scholarly journals Clinical Pathway Generation from Hospital Information System

2018 ◽  
Vol 139 ◽  
pp. 545-553
Author(s):  
Shusaku Tsumoto ◽  
Tomohiro Kimura ◽  
Haruko Iwata ◽  
Shoji Hirano
2021 ◽  
Vol 182 (2) ◽  
pp. 181-218
Author(s):  
Shusaku Tsumoto ◽  
Shoji Hirano ◽  
Tomohiro Kimura ◽  
Haruko Iwata

Data mining methods in medicine is a very important tool for developing automated decision support systems. However, since information granularity of disease codes used in hospital information system is coarser than that of real clinical definitions of diseases and their treatment, automated data curation is needed to extract knowledge useful for clinical decision making. This paper proposes automated construction of clinical process plan from nursing order histories and discharge summaries stored in hospital information system with curation of disease codes as follows. First, the system applies EM clustering to estimate subgrouping of a given disease code from clinical cases. Second, it decomposes the original datasets into datasets of subgroups by using granular homogenization. Thirdly, clinical pathway generation method is applied to the datasets. Fourthly, classification models of subgroups are constructed by using the analysis of discharge summaries to capture the meaning of each subgroup. Finally, the clinical pathway of a given disease code is output as the combination of the classifiers of subgroups and the the pathways of the corresponding subgroups. The proposed method was evaluated on the datasets extracted hospital information system in Shimane University Hosptial. The obtained results show that more plausible clinical pathways were obtained, compared with previously introduced methods.


1974 ◽  
Vol 13 (03) ◽  
pp. 125-140 ◽  
Author(s):  
Ch. Mellner ◽  
H. Selajstder ◽  
J. Wolodakski

The paper gives a report on the Karolinska Hospital Information System in three parts.In part I, the information problems in health care delivery are discussed and the approach to systems design at the Karolinska Hospital is reported, contrasted, with the traditional approach.In part II, the data base and the data processing system, named T1—J 5, are described.In part III, the applications of the data base and the data processing system are illustrated by a broad description of the contents and rise of the patient data base at the Karolinska Hospital.


1987 ◽  
Vol 26 (04) ◽  
pp. 189-194
Author(s):  
S. S. El-Gamal

SummaryModern information technology offers new opportunities for the storage and manipulation of hospital information. A computer-based hospital information system, dedicated to urology and nephrology, was designed and developed in our center. It involves in principle the employment of a program that allows the analysis of non-restricted, non-codified texts for the retrieval and processing of clinical data and its operation by non-computer-specialized hospital staff.This Hospital Information System now plays a vital role in the efficient provision of a good quality service and is used in daily routine and research work in this hospital. This paper describes this specialized Hospital Information System.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jinyao Ni ◽  
Junwu Zhang ◽  
Yanxia Chen ◽  
Weizhong Wang ◽  
Jinlin Liu

Abstract Background Good's syndrome (GS) is a rare secondary immunodeficiency disease presenting as thymoma and hypogammaglobulinemia. Due to its rarity, the diagnosis of GS is often missed. Methods We used the hospital information system to retrospectively screen thymoma and hypogammaglobulinemia patients at the First Affiliated Hospital of Wenzhou Medical University from Apr 2012 to Apr 2020. The clinical, laboratory, treatment, and outcome data for these patients were collected and analyzed. Results Among the 181 screened thymoma patients, 5 thymoma patients with hypogammaglobulinemia were identified; 3 patients had confirmed diagnoses of GS, and the other 2 did not have a diagnosis of GS recorded in the hospital information system. A retrospective review of the clinical characteristics, laboratory results, and follow-up data for these 2 undiagnosed patients confirmed the diagnosis of GS. All 5 GS patients presented with pneumonia, 2 patients presented with recurrent skin abscesses, 2 patients presented with recurrent cough and expectoration, 1 patient presented with recurrent oral lichen planus and diarrhea, and 1 patient presented with tuberculosis and granulomatous epididymitis. In the years after the diagnosis of hypogammaglobulinemia with mild symptoms, all 5 patients had received irregular intravenous immunoglobulin (IVIG) treatment. As the course of the disease progressed, the clinical symptoms of all patients worsened, but the symptoms were partly resolved with IVIG in these patients. However, 4 patients died due to comorbidities. Conclusion GS should be investigated as a possible diagnosis in thymoma patients who present with hypogammaglobulinemia, especially those with recurrent opportunistic infections, recurrent skin abscesses, chronic diarrhea, or recurrent lichen planus.


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