Effect of a Hospital-Acquired Pressure Injury (HAPI) Risk Score on HAPI Rates in Patients With Vascular Diseases.

PURPOSE: The purpose of this study was to assess whether a validated hospital-acquired pressure injury (HAPI) risk scale and best practice interventions were associated with lower HAPI rates compared with previous care. We also sought to identify a cut score of HAPI risk when using the instrument. DESIGN: Nonequivalent 2-group pre- and postintervention comparative study. SUBJECTS AND SETTING: The sample comprised 2871 patients treated for vascular diseases; data were collected on 2674 patients before the intervention and 197 patients postintervention. Their mean (SD) age was 69.3 (12.4) years; 29.3% (n = 842) had a history of diabetes mellitus. Based on discharge status, more patients received home health care after discharge in the postintervention group, 34% (n = 67/197) versus 16.2% (n = 430/2662), P = .001. The study setting was a quaternary care hospital in the Midwestern United States. METHODS: Patients who were at high risk for HAPI, based on a nomogram score, received a mobility and ambulation program intervention. Pre- and postintervention cohorts were compared using analysis of variance, χ 2 test, and Fisher exact test. A receiver operating characteristic curve plot was generated to determine the ability of the risk score tool to identify HAPI risk at all possible cut points. RESULTS: Despite differences in patient characteristics, primary medical diagnosis, and postdischarge health care needs, the HAPI rate decreased postintervention from 13.8% (n = 370/2674) to 1.5% (n = 3/197), P = .001. A HAPI risk-predicted value cut score of 18 had strong sensitivity (0.81) and specificity (0.81), and positive and negative predictive values of 0.42 and 0.96, respectively. CONCLUSION: Despite higher patient acuity during the intervention period, HAPI rate decreased after HAPI nomogram and nurse-led mobility intervention implementation.

From the Patient's Perspective: Orthopedic Virtual Rounds.

Interdisciplinary rounding on hospital inpatients is an integral part of providing high-quality, safe patient care. As orthopedic groups have grown and geographic coverage increased, surgeons are challenged to make in-person rounds on their patients every day given time constraints and physical distances. Virtual technology is being used in multiple healthcare settings to provide patients with the opportunity to connect with health care professionals when in-person options are not available. The purpose of this study was to explore the patient experience of virtual inpatient rounding. Using digital communication technology, virtual rounds were conducted by having the surgeon connect via their mobile device or laptop to the nursing unit's communication tablet. Twenty-seven patient interviews were digitally recorded and qualitatively analyzed. Results demonstrated that virtual rounds provided a positive patient experience for many. Most patients felt that virtual rounds were a good alternative when in-person rounds are not possible. Dissatisfaction was related to feeling "rushed" by the surgeon. This feedback can be used to better prepare patients and providers for virtual rounds and to enhance virtual technologies.

Validation of a Model for Predicting Pressure Injury Risk in Patients With Vascular Diseases.

PURPOSE: The purpose of this study was to validate a 10-factor model of risk factors for hospital-acquired pressure injury (HAPI) risk in patients with vascular disease. SUBJECTS AND SETTING: Medical reviews identified 800 patients from a 1063 admissions to a 1400 bed quarternary care hospital in the midwestern United States. DESIGN: Retrospective review of medical records. METHODS: Medical records of consecutive patients treated during an 18-month period on a medical-surgical vascular progressive care unit were reviewed. Ten previously identified risk factors for HAPI-(1) lower right ankle-brachial index, (2) low Braden Scale for Pressure Sore Risk score, (3) cared for in intensive care unit, (4) low serum hematocrit values, (4) elevated serum hematocrit levels (5) female gender, (6) nonwhite individual, (7) atherosclerosis, (8) diabetes mellitus, (9) elevated blood urea nitrogen levels, and (10) high body mass index-were compared to determine their ability to predict development of HAPI. Logistic regression model was used to validate the model. RESULTS: One hundred forty-six (16.1%) out of 800 patients developed an HAPI. The 10-factor risk model produced a concordance index of predicted to actual risk of 0.851, and the likelihood of developing an HAPI based on the model was significant (P < .001). CONCLUSIONS: A 10-factor model of HAPI risk was developed for patients with vascular disease. Routine assessment of risk factors is crucial in planning individualized interventions to diminish the risk of HAPI occurrences.

Predictors of pressure ulcer development in patients with vascular disease.

BACKGROUND: Although pressure ulcer (PU) risk factors are well known in the general population, little research is available in hospitalized surgical patients admitted with vascular diseases. METHODS: Using a retrospective medical records review, characteristics of hospitalized surgical patients with vascular diseases were assessed. Variables were based on literature review of PUs and availability of medical records and administrative data. Trained registered nurses collected data. Analyses included descriptive and comparative statistics, and multivariable modeling was used to determine predictors of PU. RESULTS: In 849 adult admissions, 18.9% had a PU; 11.8% were hospital-acquired PU (HAPU). Patients were more likely to be elderly, male (n = 575; 67.7%), and Caucasian (n = 704; 83.3%). Common diagnoses were aneurysms/embolisms (43.2%) and atherosclerosis (31.2%). Patients with HAPU were more likely to be discharged to a skilled nursing or other facility compared with home (P < .001). In univariate analyses, 12 patient characteristics were associated with HAPU presence: Female gender, non-married status, current smoker, non-Caucasian race, non-intensive care unit (ICU) stay, primary diagnosis of atherosclerosis, higher analgesic use, higher right ankle brachial index (ABI), lower Braden score, higher blood urea nitrogen (BUN) higher serum creatinine and higher total protein levels. In multivariate analyses, nine factors predicted HAPU: Lower right ABI and Braden score, an ICU stay, low and high hematocrit values, female gender, non-White race, atherosclerosis history, and higher BUN and body mass index (BMI). The concordance index for the nine-item model was 0.854. CONCLUSION: The rate of HAPU in hospitalized surgical patients with vascular diseases was greater than expected. Assessment of important HAPU factors and implementation of interventions are needed to decrease risk and improve clinical outcomes.