Similarities and differences between physician and non-physician acupuncturists in using diagnostic methods - an explorative study

Purpose: Acupuncture is one of the complementary medicine therapies with the greatest demand in Switzerland and many other countries in the West and in Asia. Over the past decades, the pool of scientific literature in acupuncture has markedly increased. The diagnostic methods upon which acupuncture treatment is based, have only been addressed sporadically in scientific journals. The goal of this study is to assess the use of different diagnostic methods in the acupuncture practices and to investigate similarities and differences in using these diagnostic methods between physician and non-physician acupuncturists. Methods: 44 physician acupuncturists with certificates of competence in acupuncture – traditional chinese medicine (TCM) from ASA (Assoziation Schweizer Ärztegesellschaften für Akupunktur und Chinesische Medizin: the Association of Swiss Medical Societies for Acupuncture and Chinese Medicine) and 33 non-physician acupuncturists listed in the EMR (Erfahrungsmedizinisches Register: a national register, which assigns a quality label for CAM therapists in complementary and alternative medicine) in the cantons Basel-Stadt and Basel-Land were asked to fill out a questionnaire on diagnostic methods. The responder rate was 46.8% (69.7% non-physician acupuncturists and 29, 5% physician acupuncturists). Results: The results show that both physician and non-physician acupuncturists take patients’ medical history (94%), use pulse diagnosis (89%), tongue diagnosis (83%) and palpation of body and ear acupuncture points (81%) as diagnostic methods to guide their acupuncture treatments. Between the two groups, there were significant differences in the diagnostic tools being used. Physician acupuncturists do examine their patients significantly more often with western medical methods (p<.05) than this is the case for nonphysician acupuncturists. Non-physician acupuncturists use pulse diagnosis more often than physicians (p<.05). A highly significant difference was observed in the length of time spent with collecting patients’ medical history, where nonphysician acupuncturists clearly spent more time (p<.001). Conclusion: Depending on the educational background of the acupuncturist, different diagnostic methods are used for making the diagnosis. Especially the more time consuming methods like a comprehensive anamnesis and pulse diagnosis are more frequently employed by non-physician practitioners. Further studies will clarify if these results are valid for Switzerland in general, and to what extent the differing use of diagnostic methods has an impact on the diagnosis itself and on the resulting treatment methods, as well as on the treatment success and the patients’ satisfaction.

Stricture prevention after extended circumferential endoscopic mucosal resection by injecting autologous keratinocytes in the sheep esophagus

During the past decades, endoscopic mucosal resection (EMR) has been developed to treat early intramucosal esophageal cancers and dysplastic Barrett's esophagus. The primary drawback of this method is severe postsurgical esophageal stricture formation. The purpose of this preclinical study was to assess strategies for prevention of this major complication by injecting autologous keratinocytes in the EMR mucosal defect in the sheep model.

The application of medical informatics to the veterinary management programs at companion animal practices in Alberta, Canada: a case study.

Companion animals closely share their domestic environment with people and have the potential to, act as sources of zoonotic diseases. They also have the potential to be sentinels of infectious and noninfectious, diseases. With the exception of rabies, there has been minimal ongoing surveillance of, companion animals in Canada. We developed customized data extraction software, the University of, Calgary Data Extraction Program (UCDEP), to automatically extract and warehouse the electronic, medical records (EMR) from participating private veterinary practices to make them available for, disease surveillance and knowledge creation for evidence-based practice. It was not possible to build, generic data extraction software; the UCDEP required customization to meet the specific software, capabilities of the veterinary practices. The UCDEP, tailored to the participating veterinary practices', management software, was capable of extracting data from the EMR with greater than 99%, completeness and accuracy. The experiences of the people developing and using the UCDEP and the, quality of the extracted data were evaluated. The electronic medical record data stored in the data, warehouse may be a valuable resource for surveillance and evidence-based medical research.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.