Development and evaluation of best practice advisory alert for patient eligibility in a hospital-at-home program: A multicenter retrospective study

BACKGROUND

Hospital-at-home (HaH) is a growing model of care that has been shown to improve patient outcomes, satisfaction, and cost-effectiveness. However, selecting appropriate patients for HaH is challenging, often requiring burdensome manual screening by clinicians. To facilitate HaH enrollment, electronic health record (EHR) tools such as best practice advisories (BPAs) can be used to alert providers of potential HaH candidates.

OBJECTIVE

To describe the development and implementation of a BPA for identifying HaH eligible patients in Mayo Clinic's Advanced Care at Home (ACH) program, and to evaluate the provider response and the patient characteristics that triggered the BPA.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a retrospective multicenter study of hospitalized patients who triggered the BPA notification for ACH eligibility between March and December 2021 at Mayo Clinic in Jacksonville, FL and Mayo Clinic Health System in Eau Claire, WI. We extracted demographic and diagnosis data from the patients as well as characteristics of the providers who received the BPA notification.

INTERVENTION

The BPA was developed based on the ACH inclusion and exclusion criteria, which were derived from clinical guidelines, literature review, and expert consensus. The BPA was integrated into the EHR and displayed a pop-up message to the provider when a patient met the criteria for ACH eligibility. The provider could choose to refer the patient to ACH, dismiss the notification, or defer the decision.

MAIN OUTCOMES AND MEASURES

The main outcomes were the number and proportion of BPA notifications that resulted in a referral to ACH, and the number and proportion of referrals that were accepted by the ACH clinical team and transferred to ACH. We also analyzed the factors associated with the provider's decision to refer or not refer the patient to ACH, such as the provider's role, location, and specialty.

RESULTS

During the study period, 8962 notifications were triggered for 2847 patients. Providers opted to refer 711 (11.4%) of the total notifications linked to 324 unique patients. After review by the ACH clinical team, 31 of the 324 referrals (9.6%) met clinical and social criteria and were transferred to ACH. In multivariable analysis, Wisconsin nurses, physician assistants, and in-training personnel had lower odds of referring the patients to ACH when compared to attending physicians.

Benefits and Challenges of Remote Patient Monitoring as Perceived by Health Care Practitioners: A Systematic Review

BACKGROUND

Remote patient monitoring (RPM), or telemonitoring, offers ways for health care practitioners to gather real-time information on the physiological conditions of patients. As telemedicine, and thus telemonitoring, is becoming increasingly relevant in today's society, understanding the practitioners' opinions is crucial. This systematic review evaluates the perspectives and experiences of health care practitioners with telemonitoring technologies.

METHODS

A database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the selection of articles measuring health care practitioners' perspectives and experiences with RPM technologies published between 2017 and 2021. Only articles written in English were included. No statistical analysis was performed and thus this is a qualitative review.

RESULTS

A total of 1605 studies were identified after the initial search. After applying the inclusion and exclusion criteria of this review's authors, 13 articles were included in this review. In all, 2351 practitioners' perspectives and experience utilizing RPM technology in a variety of medical specialties were evaluated through close- and open-ended surveys. Recurring themes emerged for both the benefits and challenges. Common benefits included continuous monitoring of patients to provide prompt care, improvement of patient self-care, efficient communication, increased patient confidence, visualization of health trends, and greater patient education. Challenges comprised increased workload, higher patient anxiety, data inaccuracy, disorienting technology, financial issues, and privacy concerns.

CONCLUSION

Health care practitioners generally believe that RPM is feasible for application. Additionally, there is a consensus that telemonitoring strategies will become increasingly relevant. However, there are still drawbacks to the technology that need to be considered.

The ASA Classification System as a Predictive Factor to Stay at the Virtual Hybrid Care Hotel

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.

Renal Manifestations of Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) Syndrome: A Systematic Review of 71 Cases

Unlike other adverse drug reactions, visceral organ involvement is a prominent feature of drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome and correlates with mortality. The aim of this study was to systematically review cases published in PubMed-indexed, peer-reviewed journals in which patients had renal injury during the episode of DRESS syndrome (DS). We found 71 cases, of which 67 were adults and 56% were males. Female sex was associated with higher mortality. Chronic kidney disease (CKD) was present in 14% of patients who developed acute kidney injury (AKI) during DS. In 21% of cases, the kidneys were the only visceral organ involved, while 54% of patients had both liver and kidney involvement. Eosinophilia was absent in 24% of patients. The most common classes of medication associated with renal injury in DS were antibiotics in 34%, xanthine oxidase inhibitors in 15%, and anticonvulsants in 11%. Among antibiotics, vancomycin was the most common culprit in 68% of patients. AKI was the most common renal manifestation reported in 96% of cases, while isolated proteinuria or hematuria was present in only 4% of cases. In cases with AKI, 88% had isolated increase in creatinine and decrease in glomerular filtration (GFR), 27% had AKI concomitantly with proteinuria, 18% had oliguria, and 13% had concomitant AKI with hematuria. Anuria was the rarest manifestation, occurring in only 4% of patients with DS. Temporary renal replacement therapy was needed in 30% of cases, and all but one patient fully recovered renal function. Mortality of DS in this cohort was 13%, which is higher than previously reported. Medication class, latency period, or pre-existing CKD were not found to be associated with higher mortality. More research, particularly prospective studies, is needed to better recognize the risks associated with renal injury in patients with DS. The development of disease-specific biomarkers would also be useful so DS with renal involvement can be easier distinguished from other eosinophilic diseases that might affect the kidney.

Surgical service and distance traveled drive patient preference for Care Hotel: a retrospective cohort study

Mayo Clinic's Care Hotel is a virtual hybrid care model which allows postoperative patients to recover in a comfortable environment after a low-risk procedure. Hospitals need to understand the key patient factors that promote acceptance of the Care Hotel if they are to benefit from this innovative care model. This study aims to identify factors that can predict whether a patient will stay at Care Hotel.

Materials and methods

This retrospective chart review of 1065 patients was conducted between 23 July 2020, and 31 December 2021. Variables examined included patient age, sex, race, ethnicity, Charlson comorbidity index, distance patient travelled to hospital, length of surgery, day of the week of surgery, and surgical service. Associations of patient and surgery characteristics with the primary outcome of staying at the Care Hotel were assessed using unadjusted and multivariable logistic regression models.

Results

Of the 1065 patients who met criteria for admission to the Care Hotel during the study period, 717 (67.3%) chose to stay at the Care Hotel while 328 (32.7%) choose to be admitted to the hospital. In multivariable analysis, there was a significant association between surgical service and staying at the Care Hotel (P<0.001). Specifically, there was a higher likelihood of staying at the Care Hotel for patients from Neurosurgery [odds rato (OR)=1.86, P=0.004], Otorhinolaryngology (OR=2.70, P<0.001), and General Surgery (OR=2.75, P=0.002). Additionally, there was a higher likelihood of staying at the Care Hotel with distance travelled over 110 miles [OR (per each doubling)=1.10, P=0.007].

Conclusion

When developing a post-surgical care model for patients following outpatient procedures, the referring surgical service is a primary factor to consider in order to ensure patient acceptance, along with patient distance. This study can assist other healthcare organizations considering this model, as it provides guidance on which factors are most indicative of acceptance.

Staff Successes and Challenges with Telecommunications-Facilitated Patient Care in Hybrid Hospital-at-Home during the COVID-19 Pandemic

Technology-enhanced hospital-at-home (H@H), commonly referred to as hybrid H@H, became more widely adopted during the COVID-19 pandemic. We conducted focus group interviews with Mayo Clinic staff members (n = 14) delivering hybrid H@H in three separate locations-a rural community health system (Northwest Wisconsin), the nation's largest city by area (Jacksonville, FL), and a desert metropolitan area (Scottsdale, AZ)-to understand staff experiences with implementing a new care delivery model and using new technology to monitor patients at home during the pandemic. Using a grounded theory lens, transcripts were analyzed to identify themes. Staff reported that hybrid H@H is a complex care coordination and communication initiative, that hybrid H@H faces site-specific challenges modulated by population density and state policies, and that many patients are receiving uniquely high-quality care through hybrid H@H, partly enabled by advances in technology. Participant responses amplify the need for additional qualitative research with hybrid H@H staff to identify areas for improvement in the deployment of new models of care enabled by modern technology.

Avoiding Escalation to the Emergency Department by Activating an In-Home Rapid Response Team in the 30 Days After Hospital-at-Home Discharge

BACKGROUND

Mayo Clinic's virtual hybrid hospital-at-home program, Advanced Care at Home (ACH) monitors acute and post-acute patients for signs of deterioration and institutes a rapid response (RR) system if detected.

OBJECTIVE

This study aimed to describe Mayo Clinic's ACH RR team and its effect on emergency department (ED) use and readmission rates.

METHODS

This was a retrospective review of all post-inpatient (restorative phase) ACH patients admitted from July 6, 2020 through June 30, 2021. If the restorative patient had a clinical decompensation, an RR was activated. All RR activations were analyzed for patient demographic characteristics, admitting and escalation diagnosis, time spent by virtual team on the RR, and whether the RR resulted in transport to the ED or hospital readmission.

RESULTS

Three hundred and twenty patients were admitted to ACH during the study interval; 230 received restorative care. Seventy-two patients (31.3%) had events that triggered an RR. Fifty (69.4%) of the RR events were related to the admission diagnosis (p < 0.001; 95% CI 0.59-0.80). Twelve patients (16.7%) required transport to an ED for further treatment and were readmitted and 60 patients (83.3%) were able to be treated successfully in the home by the RR team (p < 0.001; 95% CI 0.08-0.25).

CONCLUSIONS

The use of an ACH RR team was effective at limiting both escalations back to an ED and hospital readmissions, as 83% of deteriorating patients were successfully stabilized and managed in their homes. Implementing a hospital-at-home RR team can reduce the need for ED use by providing critical resources and carrying out required interventions to stabilize the patient's condition.

Severity of illness and risk of mortality in Mayo Clinic's virtual hybrid advanced care at home program: a retrospective cohort study

BACKGROUND

In July 2020, Mayo Clinic launched Advanced Care at Home (ACH), a high-acuity virtual hybrid hospital-at-home model (HaH) of care at Mayo Clinic Florida and Northwest Wisconsin, an urban destination medical center and a rural community practice respectively. This study aims to describe demographic characteristics of ACH patients as well as their acuity of illness using severity of illness (SOI) and risk of mortality (ROM), to illustrate the complexity of patients in the program, taking into account the different diagnostic related groups.

METHODS

Mayo Clinic uses All Patient Refined-Diagnosis Related Groups (APR-DRG) to calculate SOI and ROM on hospitalized patients. APR-DRG data, including SOI and ROM, were gathered from individual chart reviews from July 6, 2020, to March 31, 2022.

RESULTS

 Out of 923 patients discharged from ACH, the average APR-DRG SOI was 2.89 (SD 0.81) and ROM was 2.73. (SD 0.92). Mean age was 70.88 (SD 14.46) years, 54.6% were male patients and the average length of stay was 4.10 days. The most frequent diagnosis was COVID-19 infection with 162 patients (17.6%), followed by heart failure exacerbation (12.7%) and septicemia (10.9%). The 30-day readmission rate after discharge from ACH was 11.2% (n = 103) and the 30-day mortality rate was 1.8% (n = 17). There were no in-program patient deaths.

CONCLUSIONS

SOI and ROM from patients at the ACH program have been shown to be in the range of "moderate/major" according to the APR-DRG classification. The ACH program is capable of accepting and managing highly complex patients that require advanced therapeutic means. Furthermore, the ACH program has an in-program mortality rate of 0 to date. Therefore, ACH is rising as a capable alternative to the brick-and-mortar hospital.

Implementation of a virtual and in-person hybrid hospital-at-home model in two geographically separate regions utilizing a single command center: a descriptive cohort study

BACKGROUND

As providers look to scale high-acuity care in the patient home setting, hospital-at-home is becoming more prevalent. The traditional model of hospital-at-home usually relies on care delivery by in-home providers, caring for patients in urban communities through academic medical centers. Our objective is to describe the process and outcomes of Mayo Clinic's Advanced Care at Home (ACH) program, a hybrid virtual and in-person hospital-at-home model combining a single, virtual provider-staffed command center with a vendor-mediated in-person medical supply chain to simultaneously deliver care to patients living near an urban hospital-at-home command center and patients living in a rural region in a different US state and time zone.

METHODS

A descriptive, retrospective medical records review of all patients admitted to ACH between July 6, 2020, and December 31, 2021. Patients were admitted to ACH from an urban academic medical center in Florida and a rural community hospital in Wisconsin. We collected patient volumes, age, sex, race, ethnicity, insurance type, primary hospital diagnosis, 30-day mortality rate, in-program mortality, 30-day readmission rate, rate of return to hospital during acute phase, All Patient Refined-Diagnosis Related Groups (APR-DRG) Severity of Illness (SOI), and length of stay (LOS) in both the inpatient-equivalent acute phase and post-acute equivalent restorative phase.

RESULTS

Six hundred and eighty-six patients were admitted to the ACH program, 408 in Florida and 278 in Wisconsin. The most common diagnosis seen were infectious pneumonia (27.0%), septicemia / bacteremia (11.5%), congestive heart failure exacerbation (11.5%), and skin and soft tissue infections (6.3%). Median LOS in the acute phase was 3 days (IQR 2-5) and median stay in the restorative phase was 22 days (IQR 11-26). In-program mortality rate was 0% and 30-day mortality was 0.6%. The mean APR-DRG SOI was 2.9 (SD 0.79) and the 30-day readmission rate was 9.7%.

CONCLUSIONS

The ACH hospital-at-home model was able to provide both high-acuity inpatient-level care and post-acute care to patients in their homes through a single command center to patients in urban and rural settings in two different geographical locations with favorable outcomes of low mortality and hospital readmissions.

Smartphones and Threshold-Based Monitoring Methods Effectively Detect Falls Remotely: A Systematic Review

In the US, at least one fall occurs in at least 28.7% of community-dwelling seniors 65 and older each year. Falls had medical costs of USD 51 billion in 2015 and are projected to reach USD 100 billion by 2030. This review aims to discuss the extent of smartphone (SP) usage in fall detection and prevention across a range of care settings. A computerized search was conducted on six electronic databases to investigate the use of remote sensing technology, wireless technology, and other related MeSH terms for detecting and preventing falls. After applying inclusion and exclusion criteria, 44 studies were included. Most of the studies targeted detecting falls, two focused on detecting and preventing falls, and one only looked at preventing falls. Accelerometers were employed in all the experiments for the detection and/or prevention of falls. The most frequent course of action following a fall event was an alarm to the guardian. Numerous studies investigated in this research used accelerometer data analysis, machine learning, and data from previous falls to devise a boundary and increase detection accuracy. SP was found to have potential as a fall detection system but is not widely implemented. Technology-based applications are being developed to protect at-risk individuals from falls, with the objective of providing more effective and efficient interventions than traditional means. Successful healthcare technology implementation requires cooperation between engineers, clinicians, and administrators.

Impact of an Acquisition Advanced Practice Provider on Home Hospital Patient Volumes and Length of Stay

In July 2020, Mayo Clinic introduced a hospital-at-home program, known as Advanced Care at Home (ACH) as an alternate option for clinically stable medical patients requiring hospital-level care. This retrospective cohort study evaluates the impact of the addition of a dedicated ACH patient acquisition Advanced Practice Provider (APP) on average length of stay (ALOS) and the number of patients admitted into the program between in Florida and Wisconsin between 6 July 2020 and 31 January 2022. Patient volumes and ALOS of 755 patients were analyzed between the two sites both before and after a dedicated acquisition APP was added to the Florida site on 1 June 2021. The addition of a dedicated acquisition APP did not affect the length of time a patient was in the emergency department or hospital ward prior to ACH transition (2.91 days [Florida] vs. 2.59 days [Wisconsin], p = 0.22), the transition time between initiation of the ACH consult to patient transfer home (0.85 days [Florida] vs. 1.16 days [Wisconsin], p = 0.28), or the total ALOS (6.63 days [Florida] vs. 6.34 days [Wisconsin], p = 0.47). The average number of patients acquired monthly was significantly increased in Florida (38.3 patients per month) compared with Wisconsin (21.6 patients per month) (p < 0.01). The addition of a dedicated patient acquisition APP resulted in significantly higher patient volumes but did not affect transition time or ALOS. Other hospital-at-home programs may consider the addition of an acquisition APP to maximize patient volumes.

Treatment of a high healthcare utilizer with sepsis in a virtual hybrid hospital-at-home program

High healthcare utilizers are often chronically ill patients who require aggressive hospital and outpatient care. We describe a patient with septic shock who was stabilized in the intensive care unit, then transitioned to a virtual hybrid hospital-at-home to complete both inpatient care as well as outpatient wound and rehabilitation therapy.

Diagnosis Related Groups of Patients Admitted from an Urban Academic Medical Center to a Virtual Hybrid Hospital-at-Home Program

Background

The diagnosis related group (DRG) is used as an economic patient classification system based on clinical characteristics, hospital stay, and treatment costs. Mayo Clinic's virtual hybrid hospital-at-home program, advanced care at home (ACH), offers high-acuity home inpatient care for a variety of diagnosis. This study aimed to determine the DRGs admitted to the ACH program at an urban academic center.

Methods

A retrospective study was performed on all patients discharged from the ACH program at Mayo Clinic Florida from July 6, 2020, to February 1, 2022. DRG data were extracted from the Electronic Health Record (EHR). Categorization of DRG was done by systems.

Results

The ACH program discharged 451 patients with DRGs. Categorization of the DRG demonstrated that the most frequent code assigned corresponded to respiratory infections (20.2%), followed by septicemia (12.9%), heart failure (8.9%), renal failure (4.9%), and cellulitis (4.0%).

Conclusion

The ACH program covers a wide range of high-acuity diagnosis across multiple medical specialties at its urban academic medical campus, including respiratory infections, severe sepsis, congestive heart failure, and renal failure, all with major complications or comorbidities. The ACH model of care may be useful in taking care of patients with similar diagnosis at other urban academic medical institutions.

Patient satisfaction with telemedicine in acute care setting: A systematic review

BACKGROUND

Telemedicine has revolutionized health-care services with its unprecedented abilities to connect patients with health-care professional across the distances. Patient satisfaction is an important measure of the quality and effectiveness of health-care services.

AIM

The goal of this systematic review is to investigate patient satisfaction with telemedicine in acute care setting.

METHODS AND RESULTS

Four sources of data were searched PubMed, Cumulative Index of Nursing and Allied Health Literature, Scopus, and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. Our analysis has showed that acute telemedicine was effective in managing a broad spectrum of acute medical conditions while achieving high levels of patient satisfaction.

CONCLUSION

Patient satisfaction is a complex product of expectations and experiences. Furthermore, it is an important indicator of the quality of the service. Despite the challenging nature of acute medicine, telemedicine services were successful in improving the quality of the service and achieving high levels of patient satisfaction.

RELEVANCE FOR PATIENTS

Telemedicine is rapidly evolving as an essential component of our healthcare system. Implementing telemedicine in acute care is a relatively new concept and patient satisfaction in these settings needs to be evaluated.

Small Bowel Obstruction Conservatively Managed in Hospital-At-Home

In 2020, Mayo Clinic established an Advanced Care at Home (ACH) program. ACH is a virtual hybrid hospital-at-home (HaH) program that combines telemedicine with in-home care services by utilizing a state that is software-driven, vendor-mediate medical supply chain. The program initially focused on acute medical diagnosis but has expanded to oversee surgical and postsurgical patients with continued inpatient needs. Here, we report the first case of a small bowel obstruction (SBO) managed under a HaH program. A 52-year-old lady presented to the emergency department with symptoms suggestive of mechanical SBO. The diagnosis was confirmed with an abdominopelvic computed tomography (CT) scan, and the patient was admitted to the hospital. Based on the patient's presentation and laboratory results, the care team proceeded with conservative treatment including nasogastric tube (NG) placement and suctioning, intravenous (IV) fluid replacement, and daily laboratory studies. She spent the first hospital day in the physical hospital ward so that the surgical team could ensure stability clinically and no urgent need for surgical intervention. On hospital day two, she was transferred home with ACH where the NG suctioning and IV replacement therapy could continue, while the medical team conducted daily virtual visits to ensure continued improvement. Additionally, a paramedic and a nurse performed an in-person, head-to-toe assessment and administered medications to the patient twice daily. She spent 5 days in ACH getting acute care and then was discharged into a postacute phase equivalent to outpatient monitoring called the restorative phase. She was monitored remotely for the duration of the restorative phase for 10 more days, and then she recovered fully. This case highlights that high-acuity patients with SBO can receive invasive treatments like NG tube suction as well as be appropriately monitored for clinical decompensation by a virtual hybrid home hospital program which combines virtual care providers with an in-home vendor-mediated supply chain.

Telemedicine allows for effective communication between a medically complex cancer patient and his virtual hospital medical team

Good physician-patient communication is key for effective hospital care. We describe a patient diagnosed with an acute pulmonary embolism and bacteremia who was treated in a virtual hybrid hospital-at-home program. Constant communication with the virtual and in-home healthcare teams enabled a unified knowledge of the patient's wishes.

Overall patient experience with a virtual hybrid hospital at home program

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.

A Virtual Hybrid Care Hotel Model Supports the Recovery of Post-procedural Patients with Mild to Severe Systemic Diseases

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.

Provider Evaluation of a Novel Virtual Hybrid Hospital at Home Model

Background

Healthcare provider’s experience with new models of care is crucial for long-term success. In July 2020, Mayo Clinic implemented a novel virtual hybrid hospital at home program called Advanced Care at Home (ACH). This model allows virtual providers in a command center to care for high-acuity patients in the home setting through collaboration with a vendor-mediated supply chain. This study aims to describe the outcomes obtained from a survey applied to the ACH providers to determine their acceptance of the quality and safety of the virtual hybrid care model, their perception towards the decision-making and teamwork between the command center and supplier network, and determine if the overall experience with ACH was rewarding.

Methods

A 15-question anonymous survey was distributed via email quarterly to all the physicians and nurse practitioners registered in ACH program at Mayo Clinic. The survey encompassed questions related to the overall experience in ACH concerning work environment, quality of care, service reliability, teamwork, decision-making, and satisfaction. All the questions were Likert-like scale choice, and a descriptive analysis using frequency distribution and percentages of the data was performed.

Results

Between September 1, 2020 and April 30, 2021, three quarterly surveys were sent to a total of 21 physicians and nurse practitioners caring for patients virtually in ACH. The response rate reported was 72%, 33%, and 66%, respectively, at the first, second, and third quarters. Eighty percent or more of providers consistently gave positive scores to all three areas analyzed throughout the 8-month study.

Conclusion

Providers found the ACH virtual hybrid model of home hospital care very rewarding. They were able to deliver high-quality and safe care to their patients through positive teamwork with a vendor-mediated supply chain. This novel model of hospital at home has the potential to be a great provider satisfier moving forward.

Eliminating disparities in pain management

Not all patients are treated equally for their pain with some therefore being undertreated. Discrepancies still exist in the way physicians treat special populations of patients such as racial minorities, women, and substance abusers. All healthcare providers need to be aware of the not so readily apparent disparities resulting from stereotyping, bias, ageism, and socioeconomic considerations. Physicians can best provide appropriate and equal care by following pain management guidelines; however, they may receive contradictory information and be apprehensive about prescribing opioids, especially to substance abusers. In this "refreshed" article, the authors describe patient encounters with patients of color and offer some goals for removing inequality and inequity from clinical settings.

Double-ended lidar technique for aerosol studies

The technique of inverting a single-ended lidar return to obtain range-dependent atmospheric extinction coefficients requires an assumption concerning the relationship between the volumetric backscatter and extinction coefficients. By comparing the powers returned from a volume common to each of two lidars located at opposite ends of a propagation path the need for this relationship can be eliminated, and the extinction coefficient is determined as a function of position between the two lidars. If the lidars are calibrated, the backscatter coefficients and their relationship to extinction can then be determined as a function of position. We present measurements obtained with two lidars which were operated reciprocally over a slant path of ~1 km during reduced visibility conditions. The measured extinction and backscatter coefficients determined by this method provide the boundary value inputs to both the forward and reverse integration algorithms for inverting the single-ended lidar returns. The accuracies by which both singleended integration schemes can reproduce the double-ended measurements are examined by allowing the ratio of backscatter to extinction coefficients to be either constant or varying with position between the two lidars as measured.