@article{RamserBaurKelleretal.2021, author = {Ramser, Michaela and Baur, Johannes and Keller, Nicola and Kukleta, Jan F. and D{\"o}rfer, J{\"o}rg and Wiegering, Armin and Eisner, Lukas and Dietz, Ulrich A.}, title = {Robotic hernia surgery I. English version}, series = {Der Chirurg}, volume = {92}, journal = {Der Chirurg}, number = {Suppl 1}, doi = {10.1007/s00104-021-01446-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323934}, pages = {S1-S13}, year = {2021}, abstract = {The treatment of inguinal hernias with open and minimally invasive procedures has reached a high standard in terms of outcome over the past 30 years. However, there is still need for further improvement, mainly in terms of reduction of postoperative seroma, chronic pain, and recurrence. This video article presents the endoscopic anatomy of the groin with regard to robotic transabdominal preperitoneal patch plasty (r‑TAPP) and illustrates the surgical steps of r‑TAPP with respective video sequences. The results of a cohort study of 302 consecutive hernias operated by r‑TAPP are presented and discussed in light of the added value of the robotic technique, including advantages for surgical training. r‑TAPP is the natural evolution of conventional TAPP and has the potential to become a new standard as equipment availability increases and material costs decrease. Future studies will also have to refine the multifaceted added value of r‑TAPP with new parameters.}, language = {en} } @article{PamirSzyszkaScheineretal.2014, author = {Pamir, Evren and Szyszka, Paul and Scheiner, Ricarda and Nawrot, Martin P.}, title = {Rapid learning dynamics in individual honeybees during classical conditioning}, series = {Frontiers in Behavioral Neuroscience}, volume = {8}, journal = {Frontiers in Behavioral Neuroscience}, number = {313}, issn = {1662-5153}, doi = {10.3389/fnbeh.2014.00313}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-115365}, year = {2014}, abstract = {Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.}, language = {en} } @phdthesis{Bauer2023, author = {Bauer, Carsten}, title = {Learning Curve Effects in Hospitals as Highly Specialized Expert Organizations}, doi = {10.25972/OPUS-32871}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-328717}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2023}, abstract = {The collection at hand is concerned with learning curve effects in hospitals as highly specialized expert organizations and comprises four papers, each focusing on a different aspect of the topic. Three papers are concerned with surgeons, and one is concerned with the staff of the emergency room in a conservative treatment. The preface compactly addresses the steadily increasing health care costs and economic pressure, the hospital landscape in Germany as well as its development. Furthermore, the DRG lump-sum compensation and the characteristics of the health sector, which is strongly regulated by the state and in which ethical aspects must be omnipresent, are outlined. Besides, the benefit of knowing about learning curve effects in order to cut costs and to keep quality stable or even improve it, is addressed. The first paper of the collection investigates the learning effects in a hospital which has specialized on endoprosthetics (total hip and knee replacement). Doing so, the specialized as well as the non-specialized interventions are studied. Costs are not investigated directly, but cost indicators. The indicator of costs in the short term are operating room times. The one of medium- to long-term costs is quality. It is operationalized by complications in the post-anesthesia care unit. The study estimates regression models (OLS and logit). The results indicate that the specialization comes along with advantages due to learning effects in terms of shorter operating room times and lower complication rates in endoprosthetic interventions. For the non-specialized interventions, the results are the same. There are no possibly negative effects of specialization on non-specialized surgeries, but advantageous spillover effects. Altogether, the specialization can be regarded as reasonable, as it cuts costs of all surgeries in the short, medium, and long term. The authors are Carsten Bauer, Nele M{\"o}bs, Oliver Unger, Andrea Szczesny, and Christian Ernst. In the second paper surgeons' learning curves effects in a teamwork vs. an individual work setting are in the focus of interest. Thus, the study combines learning curve effects with teamwork in health care, an issue increasingly discussed in recent literature. The investigated interventions are tonsillectomies (surgical excision of the palatine tonsils), a standard intervention. The indicator of costs in the short and medium to long term are again operating room times and complications as a proxy for quality respectively. Complications are secondary bleedings, which usually occur a few days after surgery. The study estimates regression models (OLS and logit). The results show that operating room times decrease with increasing surgeon's experience. Surgeons who also operate in teams learn faster than the ones always operating on their own. Thus, operating room times are shorter for surgeons who also take part in team interventions. As a special feature, the data set contains the costs per case. This enables assuring that the assumed cost indicators are valid. The findings recommend team surgeries especially for resident physicians. The authors are Carsten Bauer, Oliver Unger, and Martin Holderried. The third paper is dedicated to stapes surgery, a therapy for conductive hearing loss caused by otosclerosis (overflow bone growth). It is conceptually simple, but technically difficult. Therefore, it is regarded as the optimum to study learning curve effects in surgery. The paper seeks a comprehensive investigation. Thus, operating room times are employed as short-term cost indicator and quality as the medium to long term one. To measure quality, the postoperative difference between air and bone conduction threshold as well as a combination of this difference and the absence of complications. This paper also estimates different regression models (OLS and logit). Besides investigating the effects on department level, the study also considers the individual level, this means operating room times and quality are investigated for individual surgeons. This improves the comparison of learning curves, as the surgeons worked under widely identical conditions. It becomes apparent that the operating room times initially decrease with increasing experience. The marginal effect of additional experience gets smaller until the direction of the effect changes and the operating room times increase with increasing experience, probably caused by the allocation of difficult cases to the most experienced surgeons. Regarding quality, no learning curve effects are observed. The authors are Carsten Bauer, Johannes Taeger, and Kristen Rak. The fourth paper is a systematic literature review on learning effects in the treatment of ischemic strokes. In case of stroke, every minute counts. Therefore, there is the inherent need to reduce the time from symptom onset to treatment. The article is concerned with the reduction of the time from arrival at the hospital to thrombolysis treatment, the so-called "door-to-needle time". In the literature, there are studies on learning in a broader sense caused by a quality improvement program as well as learning in a narrower sense, in which learning curve effects are evaluated. Besides, studies on the time differences between low-volume and high-volume hospitals are considered, as the differences are probably the result of learning and economies of scale. Virtually all the 165 evaluated articles report improvements regarding the time to treatment. Furthermore, the clinical results substantiate the common association of shorter times from arrival to treatment with improved clinical outcomes. The review additionally discusses the economic implications of the results. The author is Carsten Bauer. The preface brings forward that after the measurement of learning curve effects, further efforts are necessary for using them in order to increase efficiency, as the issue does not admit of easy, standardized solutions. Furthermore, the postface emphasizes the importance of multiperspectivity in research for the patient outcome, the health care system, and society.}, subject = {Lernkurve}, language = {en} } @article{NedopilDhaliwalHowelletal.2022, author = {Nedopil, Alexander J. and Dhaliwal, Anand and Howell, Stephen M. and Hull, Maury L.}, title = {A surgeon that switched to unrestricted kinematic alignment with manual instruments has a short learning curve and comparable resection accuracy and outcomes to those of an experienced surgeon}, series = {Journal of Personalized Medicine}, volume = {12}, journal = {Journal of Personalized Medicine}, number = {7}, issn = {2075-4426}, doi = {10.3390/jpm12071152}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281842}, year = {2022}, abstract = {After starting an orthopedic practice, a surgeon with a fellowship in mechanically aligned (MA) TKA initiated this study to characterize their learning curve after they switched to unrestricted kinematic alignment (KA) TKA using manual instruments. Accordingly, the present study determined for the inexperienced (IE) surgeon the number of cases required to achieve consistent femoral resections and operating times, and whether the femoral resection accuracy, patient-reported outcome measures (PROMs), and component alignment were different from an experienced (E) surgeon. This prospective cohort study analyzed the IE surgeon's first 30 TKAs, all performed with KA, and 30 consecutive KA TKAs performed by an E surgeon. The resection accuracy or deviation was the calipered thickness of the distal and posterior medial and lateral femoral resections minus the planned resection thickness, which was the thickness of the corresponding condyle of the femoral component, minus 2 mm for cartilage wear, and 1 mm for the kerf of the blade. Independent observers recorded the femoral resection thickness, operative times, PROMs, and alignment. For each femoral resection, the deviation between three groups of patients containing ten consecutive KA TKAs, was either insignificant (p = 0.695 to 1.000) or within the 0.5 mm resolution of the caliper, which indicated no learning curve. More than three groups were needed to determine the learning curve for the operative time; however, the IE surgeon's procedure dropped to 77 min for the last 10 patients, which was 20 min longer than the E surgeon. The resection deviations of the IE and E surgeon were comparable, except for the posterolateral femoral resection, which the IE surgeon under-resected by a mean of -0.8 mm (p < 0.0001). At a mean follow-up of 9 and 17 months, the Forgotten Joint Score, Oxford Knee Score, KOOS, and the alignment of the components and limbs were not different between the IE and E surgeon (p ≥ 0.6994). A surgeon that switches to unrestricted KA with manual instruments can determine their learning curve by computing the deviation of the distal and posterior femoral resections from the planned resection. Based on the present study, an IE surgeon could have resection accuracy, post-operative patient outcomes, and component alignment comparable to an E surgeon.}, language = {en} }