ABSTRACT
BACKGROUND: Nonventilator hospital-acquired pneumonia (NV-HAP) is a common hospital-acquired condition that is amenable to basic nursing care interventions. PURPOSE: The purpose of this study was to determine the incidence of NV-HAP in a California community hospital and to identify the patient and nursing care factors including missed nursing care associated with its development. METHODS: A retrospective study identified possible NV-HAP cases with ICD-10 (International Classification of Diseases, Tenth Revision) codes and then validated cases using Centers for Disease Control and Prevention confirmatory criteria. RESULTS: The incidence of NV-HAP in our hospital was 0.64 cases per 1000 patient-days. Patient factors most strongly associated with NV-HAP were age (each year of increased age was associated with a 4% increased likelihood of developing NV-HAP) (OR = 1.04-1.07) and the presence of underlying disease, which reduced odds of developing NV-HAP by 36% (OR = 0.36; 95% CI, 0.12-0.98). Head-of-bed elevation reduced by 26% the odds of developing NV-HAP (OR = 0.26; 95% CI, 0.07-0.08). CONCLUSIONS: NV-HAP can be predicted and potentially prevented. Paradoxically, the presence of underlying disease was not positively associated with the development of NV-HAP in this study.
Subject(s)
Cross Infection , Healthcare-Associated Pneumonia , Pneumonia , Hospitals, Community , Humans , Incidence , Retrospective Studies , Risk FactorsABSTRACT
OBJECTIVE: Hyperglycemia is common in the inpatient setting and providers frequently rely on sliding scale insulin. This case study reviews the experience of one hospital moving from high utilization of sliding scale to basal bolus insulin therapy. METHOD: This Retrospective Quality Improvement Study describes the journey of clinicians at a 580-bed hospital to convert from high usage of SSI to BBI. Hyperglycemic adult patients prescribed insulin, with/without a diagnosis of diabetes, were included. RESULTS: Data over the first year showed that patients treated with Glucommander (GM) spent more time in the target range of 70-180 mg/dL than patients treated with non-Glucommander (non-GM), with 2,434 fewer hypoglycemic events and 40,589 fewer hyperglycemic events. Prior to implementation of GM, SSI was close to 95%, BBI at 5%. Within the first month of use, 96% usage of BBI was achieved. Reduction of hypoglycemic events (% of BG < 70 mg/dL) by 21% with 2.16% non-GM compared to GM at 1.74% and severe Hypoglycemia (% of BG < 50 mg/dL) by 50% in the ICU 3% non-GM compared to GM at 1.5%. In addition, patients treated with GM had a shorter LOS than patients treated with non-GM by 3.18 days and used 47.4% less point of care tests per patient. CONCLUSION: Glycemic management improved with use of eGMS. The conversion from SSI to BBI enhanced overall patient safety, eliminated the time and effort otherwise required when manually titrating insulin and reduced overall cost of care for patients on insulin therapy.
Subject(s)
Hyperglycemia/drug therapy , Hypoglycemic Agents/administration & dosage , Insulin/administration & dosage , Aged , Algorithms , Blood Glucose , Disease Management , Female , Humans , Hyperglycemia/blood , Hypoglycemic Agents/therapeutic use , Insulin/therapeutic use , Male , Middle Aged , Patient Safety , Practice Patterns, Physicians' , Quality Improvement , Quality of Health Care , Retrospective StudiesABSTRACT
OBJECTIVE: The aim of this article is to describe the use of Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) data to measure missed nursing care and construct a missed nursing care metric. BACKGROUND: Missed nursing care varies widely within and between US hospitals. Missed nursing care can be measured utilizing the HCAHPS data. METHODS: This cross-sectional study used HCAHPS data to measure missed care. RESULTS: This analysis includes HCAHPS data from 1125 acute care patients discharged between January 2014 and December 2014. A missed care index was computed by dividing the total number of missed care occurrences as reported by the patient into the total number of survey responses that did not indicate missed care. The computed missed care index for the organization was 0.6 with individual unit indices ranging from 0.2 to 1.4. CONCLUSIONS: Our methods utilize existing data to quantify missed nursing care. Based on the assessment, nursing leaders can develop interventions to decrease the incidence of missed care. Further data should be gathered to validate the incidence of missed care from HCAHPS reports.
