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1.
Hum Factors ; 64(1): 159-172, 2022 02.
Article in English | MEDLINE | ID: mdl-34478340

ABSTRACT

OBJECTIVE: To identify physiological correlates to stress in intensive care unit nurses. BACKGROUND: Most research on stress correlates are done in laboratory environments; naturalistic investigation of stress remains a general gap. METHOD: Electrodermal activity, heart rate, and skin temperatures were recorded continuously for 12-hr nursing shifts (23 participants) using a wrist-worn wearable technology (Empatica E4). RESULTS: Positive correlations included stress and heart rate (ρ = .35, p < .001), stress and skin temperature (ρ = .49, p < .05), and heart rate and skin temperatures (ρ = .54, p = .0008). DISCUSSION: The presence and direction of some correlations found in this study differ from those anticipated from prior literature, illustrating the importance of complementing laboratory research with naturalistic studies. Further work is warranted to recognize nursing activities associated with a high level of stress and the underlying reasons associated with changes in physiological responses. APPLICATION: Heart rate and skin temperature may be used for real-time detection of stress, but more work is needed to validate such surrogate measures.


Subject(s)
Occupational Stress , Skin Temperature , Galvanic Skin Response , Heart Rate/physiology , Humans , Intensive Care Units
2.
BMC Med Inform Decis Mak ; 19(1): 223, 2019 11 14.
Article in English | MEDLINE | ID: mdl-31727058

ABSTRACT

BACKGROUND: The use of post-acute care (PAC) for cardiovascular conditions is highly variable across geographical regions. Although PAC benefits include lower readmission rates, better clinical outcomes, and lower mortality, referral patterns vary widely, raising concerns about substandard care and inflated costs. The objective of this study is to identify factors associated with PAC referral decisions at acute care discharge. METHODS: This study is a retrospective Electronic Health Records (EHR) based review of a cohort of patients with coronary artery bypass graft (CABG) and valve replacement (VR). EHR records were extracted from the Cerner Health-Facts Data warehouse and covered 49 hospitals in the United States of America (U.S.) from January 2010 to December 2015. Multinomial logistic regression was used to identify associations of 29 variables comprising patient characteristics, hospital profiles, and patient conditions at discharge. RESULTS: The cohort had 14,224 patients with mean age 63.5 years, with 10,234 (71.9%) male and 11,946 (84%) Caucasian, with 5827 (40.96%) being discharged to home without additional care (Home), 5226 (36.74%) to home health care (HHC), 1721 (12.10%) to skilled nursing facilities (SNF), 1168 (8.22%) to inpatient rehabilitation facilities (IRF), 164 (1.15%) to long term care hospitals (LTCH), and 118 (0.83%) to other locations. Census division, hospital size, teaching hospital status, gender, age, marital status, length of stay, and Charlson comorbidity index were identified as highly significant variables (p- values < 0.001) that influence the PAC referral decision. Overall model accuracy was 62.6%, and multiclass Area Under the Curve (AUC) values were for Home: 0.72; HHC: 0.72; SNF: 0.58; IRF: 0.53; LTCH: 0.52, and others: 0.46. CONCLUSIONS: Census location of the acute care hospital was highly associated with PAC referral practices, as was hospital capacity, with larger hospitals referring patients to PAC at a greater rate than smaller hospitals. Race and gender were also statistically significant, with Asians, Hispanics, and Native Americans being less likely to be referred to PAC compared to Caucasians, and female patients being more likely to be referred than males. Additional analysis indicated that PAC referral practices are also influenced by the mix of PAC services offered in each region.


Subject(s)
Coronary Artery Bypass , Heart Diseases/surgery , Heart Valve Prosthesis Implantation , Patient Discharge , Referral and Consultation , Subacute Care , Aged , Cohort Studies , Female , Home Care Services , Hospitals , Humans , Logistic Models , Male , Middle Aged , Skilled Nursing Facilities , United States
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