With cMDX SSIS, it is feasible to generate heat maps of the spread patterns of PCa from routine data. The analysis tool enables the analysis of graphical data to obtain a resulting image file with the heat map and CSV files containing clinical data and analysis results. The data analysis is performed in compliance with data privacy regulations. The applied tools are user-friendly and well-accepted by physicians. Therefore, cMDX SSIS is a practical approach to obtain timely heat maps and results from the current data without any major preparation. Previously, the physicians had to fit data from routine documentation to perform analysis. This procedure is time-consuming and can cause systematic errors during data fitting. The goal of improving the primary information system is well known, but the implementation of single source systems is not common . We conducted a PubMed search using the key words “heat map and prostate cancer”, “heat map and documentation” and “map and prostate cancer”. Here, we did not find any similar approaches to the implementation of this form of documentation in the HIS that can provide timely heat maps.
The anatomical representation of the prostatic gland enables the collection and analysis of the spread pattern of PCa as well the status of the surgical margins. Such information is necessary to optimize the biopsy strategy, so that the detection rate of PCa can be increased [18–20]. In addition, the status of the surgical margins plays an essential role in treatment and quality management assessments, which is one of the important conditions for certification of prostate centers . The tumor volume is presumably an important prognostic indicator for predicting prostate cancer recurrence following surgery and therefore must be mentioned in the pathologic reports . The pathology report can be denoted as a supportive tool for decision-making in cancer management and therefore must be clearly structured and informative for physicians. With cMDX SSIS, we have achieved the creation of pathology reports within a short turnaround time.
The measured data quality, especially the completeness of the documented items per form, is high. The completeness of the electronic forms in the HIS (current documentation) was found to be 100%. We presume that clinical routine data are documented regularly in each patient. By contrast, the clinical data not related to the clinical routine are commonly not documented; however it is this kind of data that is regularly acquired for research purposes. Furthermore, the retrospective study seems to have lower data completeness than the prospective study because in a retrospective study, patients with missing or incomplete data may be present. According to Chan et al., the data completeness varied considerably across studies and that even in the same organization, the amount of missing data was variable . Nahm et al. concluded that medical record abstraction is the most significant source of errors and should be controlled and managed during the course of clinical trials; the acceptance criteria for analytical variables were 10 errors per 10,000 fields and zero errors per 10,000 fields . The source-to-database error rate in the documentation process is acceptably low (on average, 10.3 errors per 10,000 fields). We assume that the regular evaluation of pathology reports during the tumor conference is the main reason for the low error rate. Since applying the automatic file naming of cMDX reports, the source-to-database error rate was decreased significantly. Therefore, the automation of standardized well-defined procedures may reduce the error rate in the documentation process. Nevertheless, further investigations are needed to validate this statement.
The transformation of paper-based documentation to electronic form is time consuming and mostly associated with data incompleteness. Furthermore, additional data sources, if available, are necessary to achieve data completeness.
cMDX SSIS was implemented in a commercial HIS and is therefore applicable to all other customers using the same HIS. In addition, cMDX supports standard document formats such as HL7 and CDA (clinical document architecture) and can store pictures and images . The pathological information in prostatectomy specimens is now available in the HIS for many patients. Attributes such as tumor staging, Gleason score, and tumor extension are documented in a structured way, which can be used as inclusion or exclusion criteria for patient recruitment in clinical trials. The supplementary cMDX Editor tool is not currently available for public download, but the interested reader can contact the corresponding author to obtain a copy of the tool for use.
This article focused primarily on pathology reports of prostatectomy specimens. The statement of transferability of cMDX SSIS to other clinical fields is therefore limited. The technical approach described here may be accompanied by technical failures, which requires appropriate handling to keep the system working without interruption. Any technical interruption could result in data incompleteness and disrupted workflows in clinical routines. Thus the system requires continual monitoring and periodic maintenance.