Extended Roles in Primary Care When Physiotherapist-Initiated Referral to X-Ray Can Save Time and Reduce Costs

ABSTRACT Background We evaluated an extended role for the physiotherapist in primary care in referring patients to plain X-ray. Methods This prospective cohort study was set in a single region in Sweden. It included 20 physiotherapists who were educated in a one-day training in performing referral to X-ray, along with 107 patients with musculoskeletal disorders who were referred to X-ray. We evaluated that referral quality, patient and physiotherapist satisfaction, and calculated health care and patient costs. Results All referrals fulfilled the basic requirements of quality, and 78% were classified as good, fulfilling all criteria. Both patients and physiotherapists were satisfied with the extended role for the physiotherapist that decreased waiting time to diagnosis and to adequate treatment. Costs were reduced for patients (by €53/patient) and health care (by €6286.2/107 patients). The cost to visit a physician was twice that of a physiotherapist visit. Conclusions An extended role for physiotherapists in primary care in referring patients to X-ray was effective and safe for patients and reduced costs for patients and for health care. Physiotherapists in primary care were able to refer patients to X-ray after one day of training, and the extended role freed up 45 minutes of physician time for each patient with a musculoskeletal disorder in need of an X-ray.

Resident Physician Experience and Duration of Electronic Health Record Use

Background Electronic health records (EHRs) demand a significant amount of physician time for documentation, orders, and communication during care delivery. Resident physicians already work long hours as they gain experience and develop both clinical and socio-technical skills. Objectives Measure how much time resident physicians spend in the EHR during clinic hours and after-hours, and how EHR usage changes as they gain experience over a 12-month period. Methods Longitudinal descriptive study where participants were 622 resident physicians across postgraduate year cohorts (of 948 resident physicians at the institution, 65.6%) working in an ambulatory setting from July 2017 to June 2018. Time spent in the EHR per patient, patients records documented per day, and proportion of EHR time spent after-hours were the outcome, while the number of months of ambulatory care experience was the predictor. Results Resident physicians spent an average of 45.6 minutes in the EHR per patient, with 13.5% of that time spent after-hours. Over 12 months of ambulatory experience, resident physicians reduced their EHR time per patient and saw more patients per day, but the proportion of EHR time after-hours did not change. Conclusion Resident physicians spend a significant amount of time working in the EHR, both during and after clinic hours. While residents improve efficiency in reducing EHR time per patient, they do not reduce the proportion of EHR time spent after-hours. Concerns over the impact of EHRs on physician well-being should include recognition of the burden of EHR usage on early-career physicians.

Acute Diseases Prognosis using Chatbot

The role of chatbots in healthcare is to help free-up valuable physician-time by reducing or eliminating unnecessary doctor’s appointments. As the increase in cost, various healthcare organizations are looking for different ways to manage cost while improving the user’s experience. As we know there is shortage of healthcare professionals that makes it increasingly necessary for us to augment technology with health facilities in order to allow doctors to focus on more critical patient needs. Keeping this in Mind we are aiming to develop a Project that will basically ask for Symptoms from the Patient and perform the Prognosis on the basis of already developed dataset. The Machine Learning Algorithm will work on that dataset of symptoms and their prognosis to tell exactly what has happened to the Patient and will help to Reach the Desired Consultant/Doctor with respect to the Prognosis. It will also help the Patients to get Useful Information regarding different diseases that may help to deal with some Chronic Diseases at an early Stage!’

Telemedicine visits result in a significantly lower rate of cancellations compared to in-person visits for interventional oncology clinic patients.

e13624 Background: Telemedicine allows increased access to specialists, less time in a waiting room and on-demand options with little to no transportation costs. These changes have been accelerated by the COIVD-19 pandemic. The purpose of the study was to test the hypothesis that a virtual telemedicine clinic would significantly decrease no-show rates and cancellations compared to in-person visits for interventional oncology (IO) clinic patients. Methods: Telemedicine visits were performed by a physician or advanced practice provider (PA or NP) at a single institution, academic medical center including 5 regional sites to patients at home in multiple states. Total patients encounters and data from January 2020 to December 2020 were analyzed. Visit types included new visits and follow up visits. Phone only visits were excluded. Primary outcome measures were an analysis of total cancelled visits (both same day and rescheduled visits), completed visits, and total scheduled visits with calculation of the telemedicine and in-person cancellation rates. Results: There was a total of 9,044 IR clinic visits in 2020 from 6,348 unique patients across the MSK Main Campus and Regional Network. Of these clinic visits, 5586 were telemedicine visits and 3458 were in-person visits. There was a significant decrease in no show and cancellation rates for telemedicine patients (6.3%) compared to in-person visits (8.1%) (p-value <0.00001). Conclusions: Telemedicine visits resulted in a significantly lower rate of visit cancellation compared to in-person visits. This reduction in no-show and cancellation rates may yield significant cost savings by eliminating gaps in the interventional oncology clinic schedule to allow for more efficient use of physician time and resources.

Defining Data Migration Across Multidisciplinary Ambulatory Clinics Using Participatory Design

Objective This study aimed to develop an institutional approach for defining data migration based on participatory design principles. Methods We outline a collaborative approach to define data migration as part of an electronic health record (EHR) transition at an urban hospital with 20 ambulatory clinics, based on participatory design. We developed an institution-specific list of data for migration based on physician end-user feedback. In this paper, we review the project planning phases, multidisciplinary governance, and methods used. Results Detailed data migration feedback was obtained from 90% of participants. Depending on the specialty, requests for historical laboratory values ranged from 2 to as many as 145 unique laboratory types. Lookback periods requested by physicians varied and were ultimately assigned to provide the most clinical data. This clinical information was then combined to synthesize an overall proposed data migration request on behalf of the institution. Conclusion Institutions undergoing an EHR transition should actively involve physician end-users and key stakeholders. Physician feedback is vital for developing a clinically relevant EHR environment but is often difficult to obtain. Challenges include physician time constraints and overall knowledge about health information technology. This study demonstrates how a participatory design can serve to improve the clinical end-user's understanding of the technical aspects of an EHR implementation, as well as enhance the outcomes of such projects.

Advancing pediatric antimicrobial stewardship: Has pharmacodynamic dosing for gram-negative infections taken effect?

Objective: To characterize pharmacodynamic dosing strategies used at children’s hospitals using a national survey. Design: Survey. Setting: Children’s hospitals. Participants: Volunteer sample of antimicrobial stewardship program (ASP) respondents. Methods: A nationwide survey was conducted to gain greater insight into the current adoption of nontraditional dosing methods and monitoring of select β-lactam and fluoroquinolone antibiotics used to treat serious gram-negative infections in pediatric populations. The survey was performed through the Sharing Antimicrobial Reports for Pediatric Stewardship (SHARPS) Collaborative. Results: Of the 75 children’s hospitals that responded, 68% of programs reported adoption of pharmacodynamically optimized dosing using prolonged β-lactam infusions and 35% using continuous β-lactam infusions, although use was infrequent. Factors including routine MIC monitoring and formal postgraduate training and board certification of ASP pharmacists were associated with increased utilization of pharmacodynamic dosing. In addition, 60% of programs reported using pharmacodynamically optimized ciprofloxacin and 14% reported using pharmacodynamically optimized levofloxacin. Only 20% of programs monitored β-lactam levels; they commonly cited lack of published guidance, practitioner experience, and laboratomory support as reasons for lack of utilization. Less physician time dedicated to ASP programs was associated with lower adoption of optimized dosing. Conclusions: Use of pharmacodynamic dosing through prolonged and continuous infusions of β-lactams have not yet been routinely adopted at children’s hospitals. Further guidance from trials and literature are needed to continue to guide pediatric pharmacodynamic dosing efforts. Children’s hospitals should utilize these data to compare practices and to prioritize further research and education efforts.

Emergency Department Mean Physician Time per Patient and Workload Predictors ED-MPTPP

One key element for emergency department (ED) staff calculation is the mean physician time per patient (MPTPP) and its influencing factors. The aims of this study were measuring the MPTPP, identifying factors with significant influence on the MPTPP, and developing a model to predict the MPTPP. This study was a prospective trial conducted at the ED of a university hospital in Germany. The MPTPP was measured with a specifically developed app. The influence of different factors on MPTPP were first tested in univariate analysis. Then, all significant factors were used in a multivariant regression model to minimize collinearities and to develop a prediction model. In total, 202 patients treated by 32 different physicians were observed within one year. The MPTPP was 47 min (standard deviation: 34 min). Relevant factors influencing the MPTPP were treatment area, Emergency Severity Index (ESI) triage level, guiding symptom category, and physician level (all p < 0.001). This model predicted 45% of the variance in the MPTPP (p < 0.001), which corresponds to a large effect size. We developed an effective prediction model for ED MPTPP, resulting in an MPTPP of 47 min. Future studies are needed to validate our model, which could serve as a benchmark for other EDs where the MPTPP is not available.