Risk Factors for Polypharmacy in Elderly Patients With Cancer Pain.

OBJECTIVE: Polypharmacy (PP) is a burden in elderly patients with cancer pain; however, risk factors for PP remain unclear. The purpose of this study was to investigate the risk factors for PP in this patient population. METHODS: We retrospectively reviewed the medical charts of patients aged ≥65 years with cancer pain who were treated at Osaka University Hospital between February 2014 and June 2016 according to the World Health Organization 3-step ladder for cancer pain relief. We defined PP as ≥5 medications and conducted exploratory research to examine the association between PP and patient characteristics. Performance status (PS) was estimated according to the Eastern Cooperative Oncology Group system and is categorized as good PS (0-1) and poor PS (2-4). RESULTS: We reviewed 206 patients (122 men and 84 women) with a median age of 71 years (range, 65-89 years) and found that 174 patients (84.5%) had PP. In multivariate logistic analysis, PP was significantly associated with an increased number of comorbidities (odds ratio [OR]: 4.93, 95% confidence interval [CI], 2.57-11.42, P < .001), poor PS (OR: 4.50, 95% CI, 1.06-31.68, P = .039), and administration of an anticancer or molecular targeted drug (OR: 2.78, 95% CI, 1.13-7.16, P = .025). CONCLUSIONS: An increased number of comorbidities, poor PS, and administration of an anticancer or molecular targeted drug were considered risk factors for PP in elderly patients with cancer pain. Sharing these risk factors with medical staff will help reduce the occurrence of problems associated with PP.

A New Approach for Determining Short-Term, Objective Prognostic Predictive Methods for Terminal Cancer Patients Based on the Change Point of Laboratory Test Values.

BACKGROUND: In terminal phase cancer, predicting a prognosis precisely plays an important role for patients and their families to live meaningful lives. However, there are no established short-term, objective prognostic predictive methods. OBJECTIVE: To develop simple, short-term, objective prognostic predictive methods through detecting a change point for laboratory test values. DESIGN: A retrospective chart review. SETTING/SUBJECTS: Subjects were cancer patients aged ≥16 years and discharged dead from Osaka University Hospital in 2008. MEASUREMENTS: Using different laboratory test values, new prognostic predictive methods were determined based on either six laboratory test values (white blood cell [WBC], platelet [PLT], C-reactive protein, blood urea nitrogen [BUN], aspartate aminotransferase [AST], and lactase dehydrogenase [LDH]): the WPCBAL score, or five test values (WBC, PLT, BUN, AST, and LDH): the WPBAL score. Their utility, including sensitivity and specificity, was compared with that of Glasgow prognostic scores (GPSs). RESULTS: In total, 121 cancer patients were enrolled. WPCBAL and WPBAL scores showed higher sensitivity (0.88 and 0.91 vs. 0.68), specificity (0.79 and 0.70 vs. 0.53), negative predictive value (0.98 and 0.97 vs. 0.76), and a much larger relative risk (16.5 and 14.2 vs. 1.78) as prognostic predictors within two weeks of death than GPS as a prognostic predictor within three weeks of death. CONCLUSION: This is the first study that suggests that the objective prognostic predictive methods, through detecting the change point of laboratory test values, are useful for predicting short-term prognosis. The WPCBAL score and WPBAL score could objectively predict the remaining lifetime within two weeks of mortality.

Case Report Form Reporter: A Key Component for the Integration of Electronic Medical Records and the Electronic Data Capture System.

To improve the efficiency of clinical research, we developed a system to integrate electronic medical records (EMRs) and the electronic data capture system (EDC). EDC is divided into case report form (CRF) reporter and CDMS with CRF receiver with data communication using the operational data model (ODM). The CRF reporter is incorporated into the EMR to share data witth the EMR. In the data transcription type, doctors enter data using a progress note template, which are transmitted to the reporter template. It then generates the ODM. In the direct record type, reporter templates open from the progress note and generate narrative text to make record in the progress note. The configuration files for a study are delivered from the contents server to minimize the setup. This system has been used for 15 clinical studies including 3 clinical trials. This system can save labor and financial costs in clinical research.

Method to Identify Diagnostic Rules for Pancreatic Cancer Using Laboratory Data Based on Bayesian Estimation.

Early diagnosis and treatment of pancreatic cancer is challenging. We attempted to find diagnostic rules for pancreatic cancer from laboratory data in the Osaka University Hospital's data warehouse using Bayesian estimation. We calculated the pretest odds based on the number of laboratory tests and the cutoff value at which the diagnostic accuracy is over 20%. By this method, we identified diagnostic rules of 6 types for one item and 79 types for 2 items. Pancreatic cancer is difficult to detect from only general laboratory tests. However, this method may be promising in early diagnosis.

A Strategy for Reusing the Data of Electronic Medical Record Systems for Clinical Research.

There is a great need to reuse data stored in electronic medical records (EMR) databases for clinical research. We previously reported the development of a system in which progress notes and case report forms (CRFs) were simultaneously recorded using a template in the EMR in order to exclude redundant data entry. To make the data collection process more efficient, we are developing a system in which the data originally stored in the EMR database can be populated within a frame in a template. We developed interface plugin modules that retrieve data from the databases of other EMR applications. A universal keyword written in a template master is converted to a local code using a data conversion table, then the objective data is retrieved from the corresponding database. The template element data, which are entered by a template, are stored in the template element database. To retrieve the data entered by other templates, the objective data is designated by the template element code with the template code, or by the concept code if it is written for the element. When the application systems in the EMR generate documents, they also generate a PDF file and a corresponding document profile XML, which includes important data, and send them to the document archive server and the data sharing saver, respectively. In the data sharing server, the data are represented by an item with an item code with a document class code and its value. By linking a concept code to an item identifier, an objective data can be retrieved by designating a concept code. We employed a flexible strategy in which a unique identifier for a hospital is initially attached to all of the data that the hospital generates. The identifier is secondarily linked with concept codes. The data that are not linked with a concept code can also be retrieved using the unique identifier of the hospital. This strategy makes it possible to reuse any of a hospital's data.

Estimating the Ratio of Patients with a Certain Disease Between Hospitals for the Allocation of Patients to Clinical Trials Using Health Insurance Claims Data in Japan.

In clinical trials, investigating the ratio of patients with each disease who are treated in a hospital is important for determining the number of patients who are allocated to hospitals. The Japanese health insurance claims data includes standardized disease and medicine data. However, the disease data has some problems in terms of reliability, because the healed diseases are sometimes not deleted or because a disease that a patient does not actually have is registered to claim the cost of the examination. On the other hand, therapeutic medicines are administered to target particular diseases. In this study, we developed a system for estimating the number of patients with each disease using the disease data and the therapeutic medicine data. We converted the ICD-10 code to a 4-grade classification code so that we could predict the diseases in the shallow layer (e.g. gastrointestinal disease) when it was difficult to predict the precise diseases in the deep layer (e.g. gastric ulcers). A table showing the disease code and the corresponding therapeutic medicine code was provided by the Japan Pharmaceutical Information Center (JAPIC). We calculated the disease probability score from the diseases and therapeutic medicines and recorded the predicted disease. For the system evaluation, we used the health insurance claims data from Osaka University Hospital for January 2015. A total of 58,526 diseases were predicted from the health insurance claims data of 18,393 patients. One hundred twenty patients were randomly extracted for use in a chart review that was performed by an expert physician. Two hundred twenty-four of 329 predicted diseases, were correctly predicted; 56 were reasonably predicted, and 49 were incorrectly predicted. The main disease was correctly predicted in 71 patients. In conclusion, we could estimate the number of patients with each disease using the health insurance claims data with a certain degree of accuracy.

Cross-institutional document exchange system using clinical document architecture (CDA) with virtual printing method.

Recently one patient received care from several hospitals at around the same time. When the patient visited a new hospital, the new hospital's physician tried to get patient information the previous hospital. Thus, patient information is frequently exchanged between them. Many types of healthcare facilities have implemented an electronic medical record system, but in Japan, healthcare information exchange is often done by paper. In other words, after a clinical doctor prints a referral document and sends it to another hospital's physician, another hospital's doctor receives it and scans to store the EMR in his own hospital's system. It is a wasteful way to exchange healthcare information about a patient. In order to solve this problem, we have developed a cross-institutional document exchange system using clinical document architecture (CDA) with a virtual printing method.

Interconnection of electronic medical record with clinical data management system by CDISC ODM.

EDC system has been used in the field of clinical research. The current EDC system does not connect with electronic medical record system (EMR), thus a medical staff has to transcribe the data in EMR to EDC system manually. This redundant process causes not only inefficiency but also human error. We developed an EDC system cooperating with EMR, in which the data required for a clinical research form (CRF) is transcribed automatically from EMR to electronic CRF (eCRF) and is sent via network. We call this system as "eCRF reporter". The interface module of eCRF reporter can retrieves the data in EMR database including patient biography data, laboratory test data, prescription data and data entered by template in progress notes. The eCRF reporter also enables users to enter data directly to eCRF. The eCRF reporter generates CDISC ODM file and PDF which is a translated form of Clinical data in ODM. After storing eCRF in EMR, it is transferred via VPN to a clinical data management system (CDMS) which can receive the eCRF files and parse ODM. We started some clinical research by using this system. This system is expected to promote clinical research efficiency and strictness.

Unified Modeling Language (UML) for hospital-based cancer registration processes.

OBJECTIVE: Hospital-based cancer registry involves complex processing steps that span across multiple departments. In addition, management techniques and registration procedures differ depending on each medical facility. Establishing processes for hospital-based cancer registry requires clarifying specific functions and labor needed. In recent years, the business modeling technique, in which management evaluation is done by clearly spelling out processes and functions, has been applied to business process analysis. However, there are few analytical reports describing the applications of these concepts to medical-related work. In this study, we initially sought to model hospital-based cancer registration processes using the Unified Modeling Language (UML), to clarify functions. METHODS: The object of this study was the cancer registry of Osaka University Hospital. We organized the hospital-based cancer registration processes based on interview and observational surveys, and produced an As-Is model using activity, use-case, and class diagrams. After drafting every UML model, it was fed-back to practitioners to check its validity and improved. RESULTS: We were able to define the workflow for each department using activity diagrams. In addition, by using use-case diagrams we were able to classify each department within the hospital as a system, and thereby specify the core processes and staff that were responsible for each department. The class diagrams were effective in systematically organizing the information to be used for hospital-based cancer registries. Using UML modeling, hospital-based cancer registration processes were broadly classified into three separate processes, namely, registration tasks, quality control, and filing data. An additional 14 functions were also extracted. Many tasks take place within the hospital-based cancer registry office, but the process of providing information spans across multiple departments. Moreover, additional tasks were required in comparison to using a standardized system because the hospital-based cancer registration system was constructed with the pre-existing computer system in Osaka University Hospital. Difficulty of utilization of useful information for cancer registration processes was shown to increase the task workload. CONCLUSION: By using UML, we were able to clarify functions and extract the typical processes for a hospital-based cancer registry. Modeling can provide a basis of process analysis for establishment of efficient hospital-based cancer registration processes in each institute.