Torres‐Guzman, Ricardo A.

Chronically ill patients with superimposed acute illness requiring hospitalization are more likely to develop an extended length of stay, hospital-acquired infections, and adverse events throughout their hospitalization. An excellent alternative to managing this population of patients in the traditional bricks-and-mortal (BAM) hospital is the hospital-at-home (HaH) model. The Advanced Care at Home (ACH) program is Mayo Clinic’s HaH model that provides acute and postacute care to high-acuity patients in their homes rather than in the traditional hospital and skilled nursing facility. We report a case of postoperative care through the ACH program of a patient suffering from short gut syndrome, high-output ileostomy, and severe protein-calorie malnutrition in the setting of previously diagnosed triple-negative invasive ductal carcinoma (IDC) of the right breast complicated by lung and brain metastasis. The patient had multiple complications that required repeated scare escalations directed by a multidisciplinary virtual care. Despite these complications, the ACH model of care was able to keep the patient in the home setting the majority of the time, limiting BAM hospital days, and eliminating the need to use the emergency department for acute escalation for 3 months. The patient was able to recover during this time period and proceed to successful take-down of the ileostomy. This case highlights the benefits of the ACH program by offering high-acuity hospital-level care to severely ill patients in the comfort of their homes. Highly qualified providers paired with curated technology in the home allowed for prompt identification of patient decompensation and timely initiation of treatment while avoiding institutionalization.

Introduction The Care Hotel is a virtual hybrid care model for postoperative patients after low-risk procedures which allow recovery in an outpatient environment. This study aimed to analyze if the American Society of Anesthesiologists Physical Status (ASA PS) Classification System can be used as a predictive factor for staying at Mayo Clinic’s Care Hotel. Methods This retrospective cohort study was conducted between July 23, 2020, and June 4, 2021, at Mayo Clinic in Florida, a 306-bed community academic hospital. ASA PS Class and post-procedure care setting (Care Hotel vs inpatient ward) were collected. Patients were classified into two ASA PS groups (ASA PS Classes 1-2 and 3-4). Pearson’s Chi-square test was used to determine if the ASA PS Class and having stayed or not at the Care Hotel were independent and an Odds Ratio (OR) calculated. Results Out of 392 surgical and procedural patients, 272 (69.39%) chose the Care Hotel and 120 (30.61%) chose the inpatient ward. There was a statistically significant association between ASA PS Class and staying at the Care Hotel, P < .01. The OR of preferring to stay at the Care Hotel in patients with ASA PS Class 1-2 vs ASA PC Class 3-4 was 1.91 ( P = .0041, 95% CI: 1.229-2.982) Conclusion Patients with ASA PS Classes 1-2 are almost twice as likely to elect to stay at the Care Hotel compared to those with ASA PS Classes 3-4. This finding may help care teams focus their Care hotel recruitment efforts.

Background: Breast cancer is the most common malignancy and the second most common cause of death in women worldwide. Axillary lymph node metastasis (ALNM) is the most significant prognostic factor in breast cancer. Under the current guidelines, sentinel lymph node biopsy (SLNB) is the standard of axillary staging in patients with clinically-node negative breast cancer. Despite the minimally invasive nature of SLNB, it can cause short and long-term morbidities including pain, sensory impairment, and upper limb motor dysfunction. However, lymphedema remains the most feared adverse event, and it affects 7% of patients within 36 months of follow-up. Recently, we have witnessed the implication of radiomics and artificial intelligence domains in the diagnosis and follow-up of many malignancies with promising results. Therefore, we have conducted a systematic search to investigate the potentials of radiomics and artificial intelligence in predicting ALNM. Methods: Four electronic databases were searched: PubMed, Scopus, CINAHL, and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. Results: For radiomics, area under the curve (AUC) for the included studies ranged from 0.715 to 0.93. Accuracy ranged from 67.7% to 98%. Sensitivity and specificity ranged from 70.3% to 97.8% and 58.4% to 98.2%, respectively. For other artificial intelligence methods, AUC ranged from 0.68 to 0.98, while accuracy ranged from 55% to 89%. Conclusion: The results of radiomics and artificial intelligence in predicting ALNM are promising. However, validation as a substitute to SLNB requires more substantial evidence from large randomized trials.

Objectives: Traditional hospital at home models often have high patient experience scores. The purpose of this study is to look at the patient experience of a new virtual hybrid model of hospital at home called Advanced Care at Home. Methods: Patients in Mayo Clinic’s Advanced Care at Home program received a survey via email from 1 January–31 May 2021. Each survey consisted of 20 questions divided into 18 multiple-choice and two open-ended questions. Results: Ninety-nine surveys were sent and 41 partially or completely finished surveys were returned for a response rate of 41.4%. Patients responded positively, denoted by answering “strongly agree or somewhat agree,” with regard to the ability to reach the team right away 100% of the time, being kept informed 92% of the time, the command center responding promptly to their needs 95% of the time, the team providing comfort and support 98% of the time, feeling comfortable with interacting with their provider by phone or tablet 95% of the time, the ease of use from the equipment 97% of the time, the virtual and in-person staff working well together 98% of the time, the staff treating patients with courtesy and respect 100% of the time, and the ease of understanding the discharge process and feeling ready to leave the program 100% of the time. All providers received positive responses on listening ⩾88% of the time. Patients gave a top rating in likelihood to recommend the program 100% of the time. Conclusion: Overall, the Advanced Care at Home model of hospital at home was highly recommended by patients. Patients scored the program high on responsiveness, staff engagement and communication, ease of equipment use, and readiness for discharge, strengthening the overall confidence in this novel program.

Background Patients with mild to severe chronic systemic disease undergoing low-risk procedures are often hospitalized for observation. The Care Hotel is a novel virtual medicine hybrid model of care that offers patients a comfortable, out of hospital environment where they can receive both in-person and virtual care after a surgery or procedure. This study aimed to analyze if virtual hybrid post-procedure care in a hotel could be both conducted on and accepted by patients, even those with moderate to severe chronic diseases. Methods This retrospective cohort study was conducted between July 23, 2020 and June 4, 2021 at Mayo Clinic in Florida, a 306-bed community academic hospital. We collected the sex, age, race, ethnicity, acceptance rate, ASA score, and primary procedure of patients using the Care Hotel. Results Out of 392 patients, 272 (69.4%) opted for care in the program. Median patient age was 61.5 years, 59.56% were males, and 86.40% were white. We found that 50.37% had an ASA score of 2 and 43.4% had an ASA score of 3. Ten different surgical specialties were able to utilize the Care Hotel for care in 47 different procedure types. Urology had the most patients (n=70, 25.7%). Post-electrophysiologic procedures were the most common procedures (n=39, 14.3%). Conclusion Our virtual hybrid Care Hotel program was widely accepted by patients and could care for a multitude of post-operative procedures. Additionally, this novel program can care for patients with both mild and severe systemic diseases.

An 85-year-old male presented to the podiatry clinic following a 1st to 5th left toe amputation as a complication of severe peripheral arterial disease and nonhealing wound despite endovascular intervention with an angiogram. At the visit, cellulitis with gangrene of the surgical site was noted. The patient was admitted to the brick and mortar (BAM) hospital and taken to surgery for a transmetatarsal amputation of the left limb. In the immediate postoperative period, the incisional margins appeared dusky creating concern for flap viability. The medical team recommended a vascular bypass versus a below-knee amputation. However, given the age, comorbidities, and nutritional status, the family refused further surgical intervention. As such, Mayo Clinic’s home hospital program, Advanced Care at Home (ACH), was consulted for continued nonsurgical acute management at home. The patient was transferred to ACH and transported home three days after BAM admission to continue IV antibiotic therapy and wound care. Discharge from ACH occurred 11 days after admission to the BAM hospital. This case highlights the importance of developing health care alternatives to traditional hospitalization and demonstrates that ACH can manage highly complex, elder postoperative patients from the comfort of their homes.

AbstractBackgroundDue to duty hour regulations, patient safety and inadequate operative time simulation have become a necessary part of surgical education and training in residency. Currently, there is no formal adoption of simulators for the use of surgical education or assessment in hand surgery. This literature review analyzes that the simulation techniques established thus far in hand surgery.MethodsA comprehensive literature search was performed on PubMed. Search results were filtered by title and abstract to isolate articles that were relevant to simulation in hand surgery. Articles that were nonspecific to the hand, non‐English and cadaveric were excluded. Additional articles were identified through references from the initial search.ResultsA total of 1192 articles were yielded from the initial query. After the application of the inclusion criteria, this was narrowed down to 28 articles. Another 8 additional articles were excluded as they did not pertain to the hand although the simulators could be adapted for hand surgery. A total of 20 articles were included in this study.ConclusionsSurgical simulation is a growing and essential field of surgical education. Simulators in hand surgery are limited and require further research and validation. Like other surgical subspecialties, hand surgery may benefit from the adoption of an official simulation curriculum for the assessment of residents and enhancement of technical skills.