Incisional hernia repair in a high-fidelity silicone model for open retro-muscular mesh implantation with preparation of the fatty triangle: validation and educational impact study

BACKGROUND

Incisional hernia repair requires detailed anatomic knowledge. Regarding median subxiphoidal hernias, the proper preparation of the fatty triangle is challenging. To foster proficiency-based training, a cost-efficient model for open median retromuscular mesh repair resembling the human body was developed, including the main anatomical structures related to the procedure. The aim is to create and validate a high-fidelity model on open retromuscular mesh repair suitable for "training before doing".

MATERIALS AND METHODS

Different types of fabrics for imitation of connective tissue and 2-component silicones were used to construct the incisional hernia model. Sample size for validation of the model was determined by a triangular testing approach. Operations from six beginners and six experts were assessed by three blinded-raters. Reliability and construct-validity were evaluated on a behaviorally anchored rating scale (highest score: 4) for the criteria: "instrument use", "tissue handling", "near misses and errors", and "end-product quality".

RESULTS

The model authentically mimicked an open median retromuscular mesh repair. Participants considered the procedure realistic. Reliability was excellent, ranging from 0.811 to 0.974 for "end-product quality", and "tissue handling" respectively. Construct-validity was confirmed with experts significantly outperforming beginners in the "use of instruments" (M_beg. = 2.33, M_exp. = 3.94, p < 0.001), "tissue handling" (M_beg. = 2.11, M_exp. = 3.72, p < 0.001), "near misses and errors" (M_beg. = 2.67, M_exp. = 3.67, p < 0.001), and "end-product quality" (M_beg. = 2.78, M_exp. = 3.72, p < 0.001). Criterion-validity revealed a paradox effect: beginners performed significantly better than experts (p < 0.05) when preparing the fatty triangle.

CONCLUSIONS

The model covers all relevant aspects involved in median-open retromuscular incisional hernia mesh repair. Performance differences between beginners and experts confirm construct-validity and thereby realism of the model. It enables to efficiently improve and practice technical skills of the demanding surgery.

A Knowledge Representation Concept Facilitating Construction and Maintenance of Large Knowledge Bases

Since diagnostic competence cannot be easily divided, the practical value of diagnostic consultation systems increases considerably with the diversity of problems they can handle. However, since initial construction and subsequent maintenance of large knowledge bases are extremely time-consuming, few have been built so far.

The knowledge representation concept we developed (implemented in the expert system shell MED2) to help resolve this dilemma contains as its main structural element the Question/ Finding-Set as a representational unit comprising findings usually collected and interpreted together. It allows representation of findings at multiple levels of detail and their local interpretation by data base reasoning, thereby supporting simulation of two powerful human problem-solving strategies: Symptom analysis at greater detail and stepwise formation of conceptual abstractions. Resulting knowledge base modularity facilitates initial knowledge base building by multiple cooperating teams and later easy refinement and extension.

Evaluating Four Diagnostic Methods with Acute Abdominal Pain Cases

Contemporary work in medical decision support is characterized by a multitude of methods. To investigate their relative strengths and weaknesses, we built four diagnostic expert systems based on different methods (Bayes, case-based classification, heuristic classification) for analysis of the same set of 1254 cases of acute abdominal pain previously documented in a prospective multicenter study. The results of the comparative evaluation indicate that differences in overall performance are relatively small (statistically not significant). The performance depends more on the quality of the knowledge base and the case data than on the inference methods of the expert systems. Methods relying exclusively on empirical knowledge (Bayes, case-based classification) tend to have slightly higher overall performance scores due to a diagnostic bias toward ordinary and common diseases. By contrast, methods operating with expert knowledge (e. g., heuristic classification) perform slightly worse overall, but are more sensitive toward uncommon (serious) diseases.

EuraHS: the development of an international online platform for registration and outcome measurement of ventral abdominal wall hernia repair

BACKGROUND

Although the repair of ventral abdominal wall hernias is one of the most commonly performed operations, many aspects of their treatment are still under debate or poorly studied. In addition, there is a lack of good definitions and classifications that make the evaluation of studies and meta-analyses in this field of surgery difficult.

MATERIALS AND METHODS

Under the auspices of the board of the European Hernia Society and following the previously published classifications on inguinal and on ventral hernias, a working group was formed to create an online platform for registration and outcome measurement of operations for ventral abdominal wall hernias. Development of such a registry involved reaching agreement about clear definitions and classifications on patient variables, surgical procedures and mesh materials used, as well as outcome parameters. The EuraHS working group (European registry for abdominal wall hernias) comprised of a multinational European expert panel with specific interest in abdominal wall hernias. Over five working group meetings, consensus was reached on definitions for the data to be recorded in the registry.

RESULTS

A set of well-described definitions was made. The previously reported EHS classifications of hernias will be used. Risk factors for recurrences and co-morbidities of patients were listed. A new severity of comorbidity score was defined. Post-operative complications were classified according to existing classifications as described for other fields of surgery. A new 3-dimensional numerical quality-of-life score, EuraHS-QoL score, was defined. An online platform is created based on the definitions and classifications, which can be used by individual surgeons, surgical teams or for multicentre studies. A EuraHS website is constructed with easy access to all the definitions, classifications and results from the database.

CONCLUSION

An online platform for registration and outcome measurement of abdominal wall hernia repairs with clear definitions and classifications is offered to the surgical community. It is hoped that this registry could lead to better evidence-based guidelines for treatment of abdominal wall hernias based on hernia variables, patient variables, available hernia repair materials and techniques.

Checking concordance between findings and diagnoses in sonographic reports by a knowledge-based documentation system

PURPOSE

Sonographic reports are examiner-dependent and may not always be reliable. We investigated concordance between documented findings and diagnostic conclusions--not the objective correctness of both--with the help of a knowledge-based documentation system.

MATERIALS AND METHODS

The knowledge-based documentation system SonoConsult (SC) is routinely used in the ultrasound unit of a gastroenterological clinic for more than four years. Physicians documented findings with goal directed questionnaires, and diagnostic conclusions with free text. The consistency of documented findings and diagnoses was checked with the help of SC in a two-step process: 1. the diagnoses inferred by SC based on the documented findings were compared to the diagnoses of the physicians stated as free text. 2. In case of discrepancies, a more thorough comparison was performed manually by the medical authors of this study. For judging the practical relevance of discrepancies, diagnostic codes were pre-classified as a) being presumably of higher and lower relevance for the clinician and b) requiring simple or complex inference rules from the findings.

RESULTS

In a first series of 250 consecutive cases with 934 diagnoses (3.7 diagnoses per case), 71.1% showed agreement between diagnoses of the physicians and of SC and were judged as consistent compared to the documented findings. 24.4% of the diagnoses suggested by the documented findings, however, were not mentioned by the physicians (false negative) and 4.5% were mentioned by the physicians but not suggested by the documented findings (false positive). From the 24.4% missing diagnoses, 40% were pre-classified as being of higher relevance for the clinician. In a second series of 161 consecutive cases with 501 diagnoses (3.1 diagnoses per case), 61.1% were judged as consistent compared to the documented findings, 36.1% false negative and 2.8% false positive. In this study, we differentiated the missing diagnoses due to their inferential complexity: From the 152 complex diagnoses, 44% were missing, while from the 349 simple diagnoses, 32.7% were missing.

CONCLUSION

As shown for a sonographic department of a clinic of internal medicine, in sonographic reports, one has to be aware of discrepancies between question-set-based documentations of findings and diagnostic conclusions of the examiners. While a detailed documentation of findings is the basis of quality control, consistency checks between documented findings and diagnostic conclusions, which might be done automatically in an electronic patient record, would considerably improve the quality of the reports.

HepatoConsult: a knowledge-based second opinion and documentation system

HepatoConsult is a publicly available knowledge-based second opinion and documentation system aiding in the diagnosis of liver diseases. The positive results of a prospective diagnostic evaluation study encouraged its use in clinical routine, although the available hardware infrastructure was not optimal. The comments of the physicians who used the system confirmed the results of the study and showed that the time for data entering is acceptable and the implicit standardization of terminology and documentation is welcome. Suggestions for improvement included the interface to enter data more easily, the scope to be usable for more patients and the additional capability to generate medical reports from the data.

Learning at the computer: evaluation of an intelligent tutoring system

The aim of the study was to test the efficacy of a new courseware. In a pre and post test frame, students were given the software to be used during one semester. A significant increase in the students' general study motivation was shown at the end of the semester. A change in the use and attitudes towards computers could not be observed. In a follow-up survey at the end of the semester, the students stated that the program was indeed helpful and useful but that they have had difficulties with the program's technical aspects and the general use. Furthermore, the results show that the majority of the participating students accepted the program's content, the general study motivation was high and the students showed a significant increase in learning gains, determined by the differences from pre and post test values. Especially students with low pre test values seemed to profit from the additional use of learning material, resp. the presented courseware. At the end of the semester the students with low and middle pre test results showed an increase in performance as well as an alignment in the performance for diagnosing rheumatological diseases to the students of the upper third pre test results.

Evaluating four diagnostic methods with acute abdominal pain cases

Contemporary work in medical decision support is characterized by a multitude of methods. To investigate their relative strengths and weaknesses, we built four diagnostic expert systems based on different methods (Bayes, case-based classification, heuristic classification) for analysis of the same set of 1254 cases of acute abdominal pain previously documented in a prospective multicenter study. The results of the comparative evaluation indicate that differences in overall performance are relatively small (statistically not significant). The performance depends more on the quality of the knowledge base and the case data than on the inference methods of the expert systems. Methods relying exclusively on empirical knowledge (Bayes, case-based classification) tend to have slightly higher overall performance scores due to a diagnostic bias toward ordinary and common diseases. By contrast, methods operating with expert knowledge (e.g., heuristic classification) perform slightly worse overall, but are more sensitive toward uncommon (serious) diseases.

Graphical knowledge acquisition for medical diagnostic expert systems

Like many textbook authors use text systems for writing their books, expert system authors should have easy to use knowledge acquisition systems for entering and testing their knowledge bases by themselves without much help from 'knowledge engineers'. In this paper, we report on a graphical knowledge acquisition tool (CLASSIKA) based on an expert system shell for heuristic classification (MED2) and designed for direct use by domain experts. We demonstrate how the system has been used for building a rather large expert system for diagnosing rheumatology diseases which is now being tested in clinical use.

MED1: an intelligent computer program for thoracic pain diagnosis

MED1 is a fully implemented, medical expert system providing assistance in the diagnosis of patients complaining of chest pain. Its reasoning strategy combines efficient mechanisms for hypothesis generation and hypothesis evaluation in a model simulalting the basic features of the hypothesize-and-test approach found to be applied by diagnosing physicians. The knowledge acquisition facility of the program is comfortable enough to allow the expert physician to alter the knowledge base without understanding the basic code (LISP) of the program.