Development of a New Tool to Combine the Promotion of Patient Mobility With Safe Patient Handling Equipment: The Johns Hopkins Safe Patient Handling Mobility (JH-SPHM) Guide.

BACKGROUND: Promoting safe patient mobility for providers and patients is a safety priority in the hospital setting. Safe patient handling equipment aids safe mobility but can also deter active movement by the patient if used inappropriately. Nurses need guidance to choose equipment that ensures their safety and that of the patients while promoting active mobility and preventing workplace-related injury. METHODS: Using a modified Delphi approach with a diverse group of experts, we created the Johns Hopkins Safe Patient Handling Mobility (JH-SPHM) Guide. This diverse group of 10 experts consisted of nurses, nurse leaders, physical and occupational therapists, safe patient handling committee representatives, and a fall prevention committee leader. The application of the tool was then tested in the hospital environment by two physical therapists. FINDINGS: Consensus was reached for safe patient handling (SPH) equipment recommendations at each level of the Johns Hopkins Mobility Goal Calculator (JH-Mobility Goal Calculator). Expert SPH equipment recommendations were then added to JH-Mobility Goal Calculator levels to create the JH-Safe Patient Handling Mobility Guide. JH-Safe Patient Handling Mobility Guide equipment suggestions were compared with equipment recommendations from physical therapists revealing strong agreement (n = 125, 88%). CONCLUSION: The newly created JH-Safe Patient Handling Mobility Guide provides appropriate safe patient-handling equipment recommendations to help accomplish patients' daily mobility goals. APPLICATIONS TO PRACTICE: The Johns Hopkins Safe Patient Handling Mobility Guide simultaneously facilitates patient mobility and optimizes safety for nursing staff through recommendations for safe patient-handling equipment for use with hospitalized patients.

Does nurse use of a standardized flowsheet to document communication with advanced providers provide a mechanism to detect pulse oximetry failures? A retrospective study of electronic health record data.

BACKGROUND: Pulse oximetry guides clinical decisions, yet does not uniformly identify hypoxemia. We hypothesized that nursing documentation of notifying providers, facilitated by a standardized flowsheet for documenting communication to providers (physicians, nurse practitioners, and physician assistants), may increase when hypoxemia is present, but undetected by the pulse oximeter, in events termed "occult hypoxemia." OBJECTIVE: To compare nurse documentation of provider notification in the 4 h preceding cases of occult hypoxemia, normal oxygenation, and evident hypoxemia confirmed by an arterial blood gas reading. METHODS: We conducted a retrospective study using electronic health record data from patients with COVID-19 at five hospitals in a healthcare system with paired SpO2 and SaO2 readings (measurements within 10 min of oxygen saturation levels in arterial blood, SaO2, and by pulse oximetry, SpO2). We applied multivariate logistic regression to assess if having any nursing documentation of provider notification in the 4 h prior to a paired reading confirming occult hypoxemia was more likely compared to a paired reading confirming normal oxygen status, adjusting for characteristics significantly associated with nursing documentation. We applied conditional logistic regression to assess if having any nursing documentation of provider notification was more likely in the 4-hour window preceding a paired reading compared to the 4-hour window 24 h earlier separately for occult hypoxemia, visible hypoxemia, and normal oxygenation. RESULTS: There were data from 1910 patients hospitalized with COVID-19 who had 44,972 paired readings and an average of 26.5 (34.5) nursing documentation of provider notification events. The mean age was 63.4 (16.2). Almost half (866/1910, 45.3 %) were White, 701 (36.7 %) were Black, and 239 (12.5 %) were Hispanic. Having any nursing documentation of provider notification was 46 % more common in the 4 h before an occult hypoxemia paired reading compared to a normal oxygen status paired reading (OR 1.46, 95 % CI: 1.28-1.67). Comparing the 4 h immediately before the reading to the 4 h one day preceding the paired reading, there was a higher likelihood of having any nursing documentation of provider notification for both evident (OR 1.45, 95 % CI 1.24-1.68) and occult paired readings (OR 1.26, 95 % CI 1.04-1.53). CONCLUSION: This study finds that nursing documentation of provider notification significantly increases prior to confirmed occult hypoxemia, which has potential in proactively identifying occult hypoxemia and other clinical issues. There is potential value to encouraging standardized documentation of nurse concern, including communication to providers, to facilitate its inclusion in clinical decision-making.

Association of Longitudinal Mobility Levels in the Hospital and Injurious Inpatient Falls.

ABSTRACT: Falls are one of the most common adverse events in hospitals, and patient mobility is a key risk factor. In hospitals, risk assessment tools are used to identify patient-centered fall risk factors and guide care plans, but these tools have limitations. To address these issues, we examined daily patient mobility levels before injurious falls using the Johns Hopkins Highest Level of Mobility, which quantifies key patient mobility milestones from low-level to community distances of walking. We aimed to identify longitudinal characteristics of patient mobility before a fall to help identify fallers before the event. Conducting a retrospective matched case-control analysis, we compared mobility levels in the days leading up to an injurious fall between fallers and nonfallers. We observed that patients who experienced an injurious fall, on average, spent 28% of their time prefall at a low mobility level (Johns Hopkins Highest Level of Mobility levels 1-4), compared with nonfallers who spent 19% of their time at a low mobility level (mean absolute difference, 9%; 95% confidence interval, 1%-16%; P = 0.026; relative difference, 44%). This suggests that assessing a patient's mobility levels over time can help identify those at an increased risk for falls and enable hospitals to manage mobility problems more effectively.

Revealing the tension: The relationship between high fall risk categorization and low patient mobility.

BACKGROUND: Using an inpatient fall risk assessment tool helps categorize patients into risk groups which can then be targeted with fall prevention strategies. While potentially important in preventing patient injury, fall risk assessment may unintentionally lead to reduced mobility among hospitalized patients. Here we examined the relationship between fall risk assessment and ambulatory status among hospitalized patients. METHODS: We conducted a retrospective cohort study of consecutively admitted adult patients (n = 48,271) to a quaternary urban hospital that provides care for patients of broad socioeconomic and demographic backgrounds. Non-ambulatory status, the primary outcome, was defined as a median Johns Hopkins Highest Level of Mobility <6 (i.e., patient walks less than 10 steps) throughout hospitalization. The primary exposure variable was the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) category (Low, Moderate, High). The capacity to ambulate was assessed using the Activity Measure for Post-Acute Care (AM-PAC). Multivariable regression analysis controlled for clinical demographics, JHFRAT items, AM-PAC, comorbidity count, and length of stay. RESULTS: 8% of patients at low risk for falls were non-ambulatory, compared to 25% and 54% of patients at moderate and high risk for falls, respectively. Patients categorized as high risk and moderate risk for falls were 4.6 (95% CI: 3.9-5.5) and 2.6 (95% CI: 2.4-2.9) times more likely to be non-ambulatory compared to patients categorized as low risk, respectively. For patients with high ambulatory potential (AM-PAC 18-24), those categorized as high risk for falls were 4.3 (95% CI: 3.5-5.3) times more likely to be non-ambulatory compared to patients categorized as low risk. CONCLUSIONS: Patients categorized into higher fall risk groups had decreased mobility throughout their hospitalization, even when they had the functional capacity to ambulate.

Creating a Standardized Post-Fall Debrief Tool: A Quality Improvement Project.

BACKGROUND: Performing post-fall debriefing improves patient outcomes through learning from defects and addresses adherence to fall prevention programs. LOCAL PROBLEM: While addressing an increase in fall rates, a quality improvement team discovered there was no standardized tool or process for completing post-fall debriefing. METHODS: The team used the Plan-Do-Study-Act (PDSA) process to improve the post-fall debrief tool, with an analysis of pilot using the implementation science RE-AIM framework. INTERVENTIONS: Three units with a high focus on falls and an established debriefing culture participated in pilot to generate and standardize a post-fall debrief tool. RESULTS: Through 2 revisions with end user and champion feedback, the tool was refined to assess any contributing factors to the fall. CONCLUSION: Through use of the PDSA cycle, the team established content validity of the post-fall debrief tool. This tool is appropriate for inpatient adult and pediatric scale-up and complementary to current fall risk assessment tools.

Patient isolation for infection control and patient experience.

OBJECTIVE: Hospitalized patients placed in isolation due to a carrier state or infection with resistant or highly communicable organisms report higher rates of anxiety and loneliness and have fewer physician encounters, room entries, and vital sign records. We hypothesized that isolation status might adversely impact patient experience as reported through Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys, particularly regarding communication. DESIGN: Retrospective analysis of HCAHPS survey results over 5 years. SETTING: A 1,165-bed, tertiary-care, academic medical center. PATIENTS: Patients on any type of isolation for at least 50% of their stay were the exposure group. Those never in isolation served as controls. METHODS: Multivariable logistic regression, adjusting for age, race, gender, payer, severity of illness, length of stay and clinical service were used to examine associations between isolation status and "top-box" experience scores. Dose response to increasing percentage of days in isolation was also analyzed. RESULTS: Patients in isolation reported worse experience, primarily with staff responsiveness (help toileting 63% vs 51%; adjusted odds ratio [aOR], 0.77; P = .0009) and overall care (rate hospital 80% vs 73%; aOR, 0.78; P < .0001), but they reported similar experience in other domains. No dose-response effect was observed. CONCLUSION: Isolated patients do not report adverse experience for most aspects of provider communication regarded to be among the most important elements for safety and quality of care. However, patients in isolation had worse experiences with staff responsiveness for time-sensitive needs. The absence of a dose-response effect suggests that isolation status may be a marker for other factors, such as illness severity. Regardless, hospitals should emphasize timely staff response for this population.