Christine Yang
Biographic Data
| ID | 5535523 |
|---|---|
| NAME | Christine Yang |
| GIVEN NAMES | Christine |
| FAMILY NAME | Yang |
| SIGNATURE | YANG C |
| AFFILIATIONS | Michael E. DeBakey VA Medical Center, Houston, TX |
| ORCID | 0000-0003-2945-4586 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Relationship Between Number of Assigned Patients and RN Time to Administer Medications During the Peak-Time Medication Pass
BACKGROUND: Inpatient nurse staffing affects patient outcomes. Less is known about the mechanism of this relationship and how lower overall staffing in a unit affects individual RN activities at the bedside. OBJECTIVES: Estimate the relationship between the number of patients assigned to an RN and time spent on medication administration at the peak-time medication pass (PTM), a common nursing task. RESEARCH DESIGN: Estimate the association using …
Using Medication Pass Analysis to Examine Longitudinal Changes in VA Inpatient Nurse Staffing and Workload Before and Through the Covid-19 Pandemic
BACKGROUND: The COVID-19 pandemic resulted in extended disruption to the health care system. National-level data-driven comparisons of inpatient nurse staffing and workload before and during the pandemic have been limited. OBJECTIVES: Assess the extent to which registered nurse (RN) staffing and workload changed from prepandemic levels in a national integrated health care system. RESEARCH DESIGN: Longitudinal descriptive analysis. Medication pass…
Beyond Hospital-Level Aggregated Data
BACKGROUND: Studies of nurse staffing frequently use data aggregated at the hospital level that do not provide the appropriate context to inform unit-level decisions, such as nurse staffing. OBJECTIVES: Describe a method to link patient data collected during the provision of routine care and recorded in the electronic health record (EHR) to the nursing units where care occurred in a national dataset. RESEARCH DESIGN: We identified all Veterans He…
Investigating college EFL learners’ perceptions toward the use of Google Assistant for foreign language learning
Recent studies on the use of Intelligent Personal Assistant (IPA) for second language (L2) learnring have found that IPAs such as Amazon’s Alexa is useful and motivating for L2 learners and that learners’ language proficiency might influence their perceptions toward IPAs. However, most existing studies focused on the potentials of Alexa and paid little attention to Google Assistant (GA). This study was thus conducted to investigate how L2 learner…
An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives
BACKGROUND: Hospital performance comparisons for transparency initiatives may be inadequate if peer comparison groups are poorly defined. OBJECTIVE: The objective of this study was to evaluate a new approach identifying hospital peers for comparison. DESIGN/SETTING: We used Mahalanobis distance as a new method of developing peer-specific groupings for hospitals to incorporate both external and internal complexity. We compared the overlap in group…
No prominent works on this page.
An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives
BACKGROUND: Hospital performance comparisons for transparency initiatives may be inadequate if peer comparison groups are poorly defined. OBJECTIVE: The objective of this study was to evaluate a new approach identifying hospital peers for comparison. DESIGN/SETTING: We used Mahalanobis distance as a new method of developing peer-specific groupings for hospitals to incorporate both external and internal complexity. We compared the overlap in group…
Investigating college EFL learners’ perceptions toward the use of Google Assistant for foreign language learning
Recent studies on the use of Intelligent Personal Assistant (IPA) for second language (L2) learnring have found that IPAs such as Amazon’s Alexa is useful and motivating for L2 learners and that learners’ language proficiency might influence their perceptions toward IPAs. However, most existing studies focused on the potentials of Alexa and paid little attention to Google Assistant (GA). This study was thus conducted to investigate how L2 learner…
Beyond Hospital-Level Aggregated Data
BACKGROUND: Studies of nurse staffing frequently use data aggregated at the hospital level that do not provide the appropriate context to inform unit-level decisions, such as nurse staffing. OBJECTIVES: Describe a method to link patient data collected during the provision of routine care and recorded in the electronic health record (EHR) to the nursing units where care occurred in a national dataset. RESEARCH DESIGN: We identified all Veterans He…
Relationship Between Number of Assigned Patients and RN Time to Administer Medications During the Peak-Time Medication Pass
BACKGROUND: Inpatient nurse staffing affects patient outcomes. Less is known about the mechanism of this relationship and how lower overall staffing in a unit affects individual RN activities at the bedside. OBJECTIVES: Estimate the relationship between the number of patients assigned to an RN and time spent on medication administration at the peak-time medication pass (PTM), a common nursing task. RESEARCH DESIGN: Estimate the association using …
Using Medication Pass Analysis to Examine Longitudinal Changes in VA Inpatient Nurse Staffing and Workload Before and Through the Covid-19 Pandemic
BACKGROUND: The COVID-19 pandemic resulted in extended disruption to the health care system. National-level data-driven comparisons of inpatient nurse staffing and workload before and during the pandemic have been limited. OBJECTIVES: Assess the extent to which registered nurse (RN) staffing and workload changed from prepandemic levels in a national integrated health care system. RESEARCH DESIGN: Longitudinal descriptive analysis. Medication pass…
Staffing (3 works) · Computer Science (2 works) · Medicine (2 works) · MEDLINE (2 works) · Nursing (2 works) · Psychology (2 works) · Active listening (1 work) · Acute care (1 work) · AI in Service Interactions (1 work) · Communication (1 work)