IMPORTANCE Learning curves are unavoidable for practicing surgeons when adopting new technologies. However, patient outcomes are worse in the early stages of a learning curve vs after mastery. Therefore, it is critical to find a way to decrease these learning curves without compromising patient safety.OBJECTIVE To evaluate the association of mentorship and a formal proficiency-based skills curriculum with the learning curves of 3 generations of surgeons and to determine the association with increased patient safety. DESIGN, SETTING, AND PARTICIPANTS All consecutive robotic pancreaticoduodenectomies (RPDs) performed at the University of Pittsburgh Medical Center between 2008 and 2017 were included in this study. Surgeons were split into generations based on their access to mentorship and a proficiency-based skills curriculum. The generations are (1) no mentorship or curriculum, (2) mentorship but no curriculum, and (3) mentorship and curriculum. Univariable and multivariable analyses were used to create risk-adjusted learning curves by surgical generation and to analyze factors associated with operating room time, complications, and fellows completing the full resection. The participants include surgical oncology attending surgeons and fellows who participated in an RPD at University of Pittsburgh Medical Center between 2008 and 2017. MAIN OUTCOMES AND MEASURESThe primary outcome was operating room time (ORT). Secondary outcomes were postoperative pancreatic fistula and Clavien-Dindo classification higher than grade 2. RESULTSWe identified 514 RPDs completed between 2008 and 2017, of which 258 (50.2%) were completed by first-generation surgeons, 151 (29.3%) were completed by the second generation, and 82 (15.9%) were completed by the third generation. There was no statistically significant difference between groups with respect to age (66.3-67.3 years; P = .52) or female sex (n = 34 [41.5%] vs n = 121 [46.9%]; P = .60). There was a significant decrease in ORT (P < .001), from 450.8 minutes for the first-generation surgeons to 348.6 minutes for the third generation. Additionally, across generations, Clavien-Dindo classification higher than grade 2 (n = 74 [28.7%] vs n = 30 [9.9%] vs n = 12 [14.6%]; P = .01), conversion rates (n = 18 [7.0%] vs n = 7 [4.6%] vs n = 0; P = .006), and estimated blood loss (426 mL vs 288.6 mL vs 254.7 mL; P < .001) decreased significantly with subsequent generations. There were no significant differences in postoperative pancreatic fistula. CONCLUSIONS AND RELEVANCEIn this study, ORT, conversion rates, and estimated blood loss decreased across generations without a concomitant rise in adverse patient outcomes. These findings suggest that a proficiency-based curriculum coupled with mentorship allows for the safe introduction of less experienced surgeons to RPD without compromising patient safety.
Objectives To compare rates of 30‐day readmission between hospital units with a Hospital Elder Life Program (HELP) and control units without HELP. Design Retrospective cohort study. Setting The study took place from July 1, 2013, to June 30, 2014, at the University of Pittsburgh Medical Center Shadyside, a 520‐bed community teaching hospital that has used HELP since 2002. Eight medical and surgical units with HELP were compared with 10 medical and surgical units without HELP. Participants During the study period, HELP units, had 4,794 patients aged 70 and older, and usual care units had 2,834. Intervention HELP is a multifactorial, multidisciplinary program that provides targeted interventions for delirium risk factors in at‐risk individuals in collaboration with bedside staff. Measurements Mixed‐effects Poisson regression models were used to estimate the adjusted incident risk ratio for 30‐day readmission between HELP and usual care units for the overall cohort and for the subgroup of individuals discharged home, with or without services. Results Patients on HELP units were more likely than those in usual care units to be older, female, and black and had an unadjusted readmission rate of 16.9%, versus 18.9% for patients on control units. The adjusted risk of readmission was 0.83 (95% confidence interval (CI) = 0.73–0.94, P = .003) for HELP unit patients overall and 0.74 (95% CI = 0.63–0.87, P < .001) for HELP unit patients discharged to home with or without services. Conclusion The HELP program is associated with lower risk of 30‐day hospital readmission overall and for the subgroup of individuals discharged to home. Prospective studies are needed to confirm these observations.
Some demographic variation exists between users of APP versus physician e-visits. Provider response time seems more driven by service policy than provider type. Finally, variation exists between provider types in quantities of prescriptions written. As health systems and policymakers develop protocols and reimbursement strategies for e-visits, these model considerations will be important.
Background and Objectives The Commonwealth of Pennsylvania passed the Caregiver Advise, Record, Enable (CARE) Act on April 20, 2016. We designed a study to explore early implementation at a large, integrated delivery financing system. Our goal was to assess the effects of system-level decisions on unit implementation and the incorporation of the CARE Act’s three components into routine care delivery. Research Design and Methods We conducted a multisite, ethnographic case study at three different hospitals’ medical–surgical units. We conducted observations and semi-structured interview to understand the implementation process and the approach to caregiver identification, notification, and education. We used thematic analysis to code interviews and observations and linked findings to the Promoting Action on Research Implementation in Health Services framework. Results Organizational context and electronic health record capability were instrumental to the CARE Act implementation and integration into workflow. The implementation team used a decentralized strategy and a variety of communication modes, relying on local hospital units to train staff and make the changes. We found that the system facilitated the CARE Act implementation by placing emphasis on the documentation and charting to demonstrate compliance with the legal requirements. Discussion and Implications General acute hospitals will be making or have made similar decisions on how to operationalize the regulatory components and demonstrate compliance with the CARE Act. This study can help to inform others as they design and improve their compliance and implementation strategies.
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