Perceptions of Risk, Work, and Lifestyle Changes on Mental Health of Healthcare Workers Amidst the COVID-19 Pandemic.

The COVID-19 outbreak is significantly affecting the mental health of healthcare workers worldwide. This study aims to investigate the mental health outcomes of healthcare workers in a health system located in southeastern US during the first peak of the pandemic and examine the association of specific factors on the mental well-being of healthcare workers. A cross-sectional survey of 388 healthcare workers was conducted. Data were collected using a 79-item questionnaire, which included the Patient Health Questionnaire (PHQ-9) instrument, the 7-item Generalized Anxiety Disorder (GAD-7) instrument, and the 22-item Impact of Event Scale-Revised (IES-R), to assess symptoms of depression, anxiety, and general distress, respectively. Data were analyzed using descriptive, bivariate, and multivariate statistics. Accordingly, 30.1%, 28.7%, and 39.4% of respondents reported depression, anxiety, and distress symptoms, respectively. Younger workers and females reported higher mental symptomologies. We identified significant, nontraditional factors associated with depression and anxiety symptoms among healthcare workers: healthcare procedure change, concern of exposing family to COVID-19, number of missed shifts, and access to psychological resources/services. These findings emphasize the importance of providing the proper training to reduce concerns of exposing family members and psychological interventions to promote mental health well-being for healthcare workers during the stressful COVID-19 pandemic.

Rapid design and implementation of a UVC decontamination room.

With the recent COVID-19 pandemic that has swept the world and the nation, hospitals around the country have experienced shortages in Personal Protective Equipment, specifically N95 filter face-mask respirators (FFRs). This has created the need for facilities to develop sterilization processes to enable reuse of face masks by the health care personnel. Among the various methods of sterilization, UVC light exposure is the easiest to implement given the factors of time, safety, and availability. Face masks and/or other PPE are exposed to UVC light for a specified time to kill any viruses or bacteria that may reside on the surfaces of the masks. A collaborative effort was formed in April of 2020 between Wellstar Health System and Kennesaw State University to (1) setup an appropriate sterilization room at a Wellstar hospital (2) develop the procedural guidelines necessary to ensure quality control and (3) assess employees' perceptions of the N95 FFR decontamination process and efficacy. This paper will first describe the methodology used to validate the layout of the room, which consists of a rudimentary analytical analysis of the UVC photon intensity from bulb-to-mask, computer simulations to determine the lighting power density throughout the room, and experimental measurements to confirm the appropriate energy deposition. This paper will then document the procedures for handling and processing the pre- and post-sterilized masks followed by employee survey findings. It is the hope of the authors that this paper will serve to provide a generic blueprint for hospitals and other organizations to follow if a future need arises for rapid UVC decontamination.

Validating Fall Prevention Icons to Support Patient-Centered Education.

INTRODUCTION: Falls with injury are the most prevalent hospital adverse event. The objective of this project was to refine fall risk and prevention icons for a patient-centric bedside toolkit to promote patient and nurse engagement in accurately assessing fall risks and developing a tailored fall prevention plan. METHODS: Eighty-eight patients and 60 nurses from 2 academic medical centers participated in 4 iterations of testing to refine 6 fall risk and 10 fall prevention icons. During individual interviews, participants rated their satisfaction with the degree to which that icon represented the concept on a 4-point Likert scale, enabling computation of a Content Validity Index (CVI), and provided comments and suggestions for improvement. After reviewing CVI scores and feedback, the research team consulted with the illustrator to revise the icons. RESULTS: Content Validity Index scores improved after icon modifications. Icons that depicted multiple concepts required further iterations to be acceptable. DISCUSSION: Using icons to depict an accurate and easy-to-interpret fall risk assessment and intervention plan for all care team members including patients and family to follow should lead to improved adherence with that plan and decreased falls. CONCLUSIONS: All 16 icons were refined and used to form the basis for a bedside fall prevention toolkit.

Evaluation of a Patient-Centered Fall-Prevention Tool Kit to Reduce Falls and Injuries: A Nonrandomized Controlled Trial.

Importance: Falls represent a leading cause of preventable injury in hospitals and a frequently reported serious adverse event. Hospitalization is associated with an increased risk for falls and serious injuries including hip fractures, subdural hematomas, or even death. Multifactorial strategies have been shown to reduce falls in acute care hospitals, but evidence for fall-related injury prevention in hospitals is lacking. Objective: To assess whether a fall-prevention tool kit that engages patients and families in the fall-prevention process throughout hospitalization is associated with reduced falls and injurious falls. Design, Setting, and Participants: This nonrandomized controlled trial using stepped wedge design was conducted between November 1, 2015, and October 31, 2018, in 14 medical units within 3 academic medical centers in Boston and New York City. All adult inpatients hospitalized in participating units were included in the analysis. Interventions: A nurse-led fall-prevention tool kit linking evidence-based preventive interventions to patient-specific fall risk factors and designed to integrate continuous patient and family engagement in the fall-prevention process. Main Outcomes and Measures: The primary outcome was the rate of patient falls per 1000 patient-days in targeted units during the study period. The secondary outcome was the rate of falls with injury per 1000 patient-days. Results: During the interrupted time series, 37 231 patients were evaluated, including 17 948 before the intervention (mean [SD] age, 60.56 [18.30] years; 9723 [54.17%] women) and 19 283 after the intervention (mean [SD] age, 60.92 [18.10] years; 10 325 [53.54%] women). There was an overall adjusted 15% reduction in falls after implementation of the fall-prevention tool kit compared with before implementation (2.92 vs 2.49 falls per 1000 patient-days [95% CI, 2.06-3.00 falls per 1000 patient-days]; adjusted rate ratio 0.85; 95% CI, 0.75-0.96; P = .01) and an adjusted 34% reduction in injurious falls (0.73 vs 0.48 injurious falls per 1000 patient-days [95% CI, 0.34-0.70 injurious falls per 1000 patient-days]; adjusted rate ratio, 0.66; 95% CI, 0.53-0.88; P = .003). Conclusions and Relevance: In this nonrandomized controlled trial, implementation of a fall-prevention tool kit was associated with a significant reduction in falls and related injuries. A patient-care team partnership appears to be beneficial for prevention of falls and fall-related injuries. Trial Registration: ClinicalTrials.gov Identifier: NCT02969343.

Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.

We established a Patient Safety Learning Laboratory comprising 2 core and 3 individual project teams to introduce a suite of digital health tools integrated with our electronic health record to identify, assess, and mitigate threats to patient safety in real time. One of the core teams employed systems engineering (SE) and human factors (HF) methods to analyze problems, design and develop improvements to intervention components, support implementation, and evaluate the system of systems as an integrated whole. Of the 29 participants, 19 and 16 participated in surveys and focus groups, respectively, about their perception of SE and HF. We identified 7 themes regarding use of the 12 SE and HF methods over the 4-year project. Qualitative methods (interviews, focus, groups, observations, usability testing) were most frequently used, typically by individual project teams, and generated the most insight. Quantitative methods (failure mode and effects analysis, simulation modeling) typically were used by the SE and HF core team but generated variable insight. A decentralized project structure led to challenges using these SE and HF methods at the project and systems level. We offer recommendations and insights for using SE and HF to support digital health patient safety initiatives.

Applying User-Centered Design Methods to the Development of an mHealth Application for Use in the Hospital Setting by Patients and Care Partners.

INTRODUCTION: Developing an optimized and user-friendly mHealth application for patients and family members in the hospital environment presents unique challenges given the diverse patient population and patients' various states of well-being. OBJECTIVE: This article describes user-centered design methods and results for developing the patient and family facing user interface and functionality of MySafeCare, a safety reporting tool for hospitalized patients and their family members. METHODS: Individual and group usability sessions were conducted with specific testing scenarios for participants to follow to test the usability and functionality of the tool. Participants included patients, family members, and Patient and Family Advisory Council (PFAC) members. Engagement rounds were also conducted on study units and lessons learned provided additional information to the usability work. Usability results were aligned with Nielsen's Usability Heuristics. RESULTS: Eleven patients and family members and 25 PFAC members participated in usability testing and over 250 patients and family members were engaged during research team rounding. Specific themes resulting from the usability testing sessions influenced the changes made to the user interface design, workflow functionality, and terminology. CONCLUSION: User-centered design should focus on workflow functionality, terminology, and user interface issues for mHealth applications. These themes illustrated issues aligned with four of Nielsen's Usability Heuristics: match between system and the real world, consistency and standards, flexibility and efficiency of use, and aesthetic and minimalist design. We identified workflow and terminology issues that may be specific to the use of an mHealth application focused on safety and used by hospitalized patients and their families.

Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study.

BACKGROUND: Traditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data. METHODS: We performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations. RESULTS: Conventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data. CONCLUSIONS: Our findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks.

Iterative user centered design for development of a patient-centered fall prevention toolkit.

Due to the large number of falls that occur in hospital settings, inpatient fall prevention is a topic of great interest to patients and health care providers. The use of electronic decision support that tailors fall prevention strategy to patient-specific risk factors, known as Fall T.I.P.S (Tailoring Interventions for Patient Safety), has proven to be an effective approach for decreasing hospital falls. A paper version of the Fall T.I.P.S toolkit was developed primarily for hospitals that do not have the resources to implement the electronic solution; however, more work is needed to optimize the effectiveness of the paper version of this tool. We examined the use of human factors techniques in the redesign of the existing paper fall prevention tool with the goal of increasing ease of use and decreasing inpatient falls. The inclusion of patients and clinical staff in the redesign of the existing tool was done to increase adoption of the tool and fall prevention best practices. The redesigned paper Fall T.I.P.S toolkit showcased a built in clinical decision support system and increased ease of use over the existing version.