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DOI: 10.1055/a-2379-7206
Multitasking during Medication Management in a Nursing Home: A Time Motion Study
Authors
Funding This study was supported by the National Institute of Nursing Research of the National Institutes of Health under award number 2T32NR012715, Jonas Philanthropies, and the University of Minnesota School of Nursing Foundation.
Abstract
Background Multitasking, defined as performing two or more interventions simultaneously, increases the cognitive burden of clinicians. This may, in turn, lead to higher risk of medication and procedural errors. Time motion study (TMS) data for nurses in nursing homes revealed an extensive amount of multitasking while managing medications. Further investigation of multitasked nursing interventions will provide a foundation for optimizing medication management workflows.
Objectives Using a continuous observational TMS method, this study aimed to describe pairs of multitasked nursing interventions associated with medication management interventions, including preparing and administering medications, assessing medication effects, instructing on medications, and documenting medication administration.
Methods An external nurse observer used 57 predefined Omaha System nursing interventions embedded within TimeCaT (version 3.9), TMS data recording software to collect observation data in a single nursing home. A total of 120 hours of time-stamped observation data from nine nurses were downloaded from TimeCaT and analyzed using descriptive and inferential statistics.
Results The majority (74%) of medication management interventions were multitasked, resulting in 2,003 pairs of multitasked interventions. Of the 57 Omaha System nursing interventions, 35 were involved in these multitasking pairs. When nurses multitasked, the average duration of medication preparation was longer (non-multitasked: 81 seconds; multitasked: 162 seconds, p < 0.05), while the average duration of medication administration record documentation was shorter (non-multitasked: 93 seconds; multitasked: 66 seconds, p < 0.05).
Conclusion The findings reveal the complexity of medication management in nursing homes with numerous and diverse multitasking pairs. Findings provide a platform for in-depth study of medication management multitasking in the clinical context, and inform future efforts to create clinical and informatics solutions to optimize medication management workflow. This method may be also applied to examine medication management and multitasking in other clinical settings.
Background and Significance
Clinicians often face multiple demands and frequently multitask.[1] [2] Multitasking, defined as performing two or more interventions at the same time, delays cognitive response time and causes task switching or skipping.[1] [2] [3] This creates a cognitive bottleneck, as new information enters much faster into working memory than old information is removed.[4] Persistent distractions increase the risk of errors. Indeed, studies show that multitasking leads to more medication and procedural errors, which in turn negatively impacts workflow and outcomes.[1] [2] [5] [6] [7]
Multitasking and its associated sequelae and efforts to mitigate multitasking in nursing home settings have rarely been studied, even though up to 70% of residents have experienced medication errors.[8] [9] [10] [11] By regulation, staffing patterns in nursing homes allow high patient-to-nurse ratios (e.g., 12 residents per nurse) for both registered nurses (RNs) and licensed practical nurses (LPNs).[12] This high staffing ratio causes extreme time pressure, and therefore higher levels of multitasking.[13] [14] [15] Given that financial constraints driving these high patient-to-nurse ratios are likely to persist,[16] [17] it is essential to understand multitasking in order to develop innovative future solutions to reduce time pressure, and alleviate cognitive burden and resulting medication errors. Furthermore, the use of clinical informatics tools and techniques in nursing homes is in its early stages,[18] [19] [20] [21] and there is potential to apply informatics methods to both study and address this multitasking issue.[22]
Time Motion Study
Time motion study (TMS) methods have been widely used in health care settings to observe clinical workflow.[23] Continuous observation by external observers is considered as the gold standard of TMS research, allowing comprehensive data collection with minimal interruptions.[23] [24] Informatics solutions, such as standardized nursing terminologies (e.g., the Omaha System) and observation recording technologies (e.g., TimeCaT [version 3.9]), have proven fruitful in these studies.[3] [25] [26] [27] [28] [29] [30]
The Omaha System
The Omaha System is a multidisciplinary standardized terminology for care practice, documentation, and information management.[31] Researchers have used its inter-related components to develop and evaluate standardized and hierarchical nursing interventions ([Fig. 1]).[31] The Omaha System organizes health and health care-related information in a list of 42 problems terms.[31] It describes actions in a hierarchical classification, with four categories (action terms), 75 targets (objects of action), and customizable client-specific care descriptions.[31] Omaha System nursing interventions, consisting of linked problem-category-target-care description terms, have been employed in TMS studies in various settings.[25] [26] [27] [29] [30]


Omaha System Interventions for Nursing Home Observations
In a previous multi-method, multi-phase study, 57 Omaha System nursing interventions were refined and validated for use in nursing homes from those originally designed for acute care settings ([Table 1]).[32] These Omaha System nursing interventions address 19 problems using all four action categories and 34 targets. Of these 57 interventions, 22 were categorized as communication interventions involving verbal, written, and electronic interactions, while 35 were categorized as task interventions, involving physical actions of a nurse ([Table 1]).
|
Intervention |
Definition |
|||
|---|---|---|---|---|
|
Problem |
Category |
Target |
||
|
Medication management interventions |
CM_mar* |
Medication regimen |
CM[a] |
Medication coordination/ordering |
|
Care description: nurse documents medication administration record |
||||
|
TGC_p/f meds* |
Medication regimen |
TGC[b] |
Medication action/side effects |
|
|
Care description: nurse explains p/f about medication action and side effects |
||||
|
CM_meds |
Medication regimen |
CM |
Medication set up |
|
|
Care description: nurse prepares medications |
||||
|
TP_meds |
Medication regimen |
TP[c] |
Medication administration |
|
|
Care description: nurse administers medications |
||||
|
S_med effects (not observed) |
Medication regimen |
S[d] |
Medication action/side effects |
|
|
Care description: nurse assesses and observes patient for effects of medication |
||||
|
Interventions multitasked with medication management interventions |
CM_report* |
Health care supervision |
CM |
Continuity of care |
|
CM_team* |
Health care supervision |
CM |
Continuity of care |
|
|
CM_notes* |
Health care supervision |
CM |
Communication |
|
|
CM_non p/f workflow* |
Health care supervision |
CM |
Environment |
|
|
TGC_p/f support* |
Health care supervision |
TGC |
Stimulation/nurturance |
|
|
TGC_p/f plan of care* |
Health care supervision |
TGC |
Sickness/injury care |
|
|
TGC_p/f labs* |
Health care supervision |
TGC |
Laboratory findings |
|
|
TGC_training* |
Health care supervision |
TGC |
Nursing care |
|
|
TGC_p/f coping* |
Health care supervision |
TGC |
Coping skills |
|
|
TGC_p/f condition* |
Health care supervision |
TGC |
Anatomy/physiology |
|
|
TGC_p/f procedure* |
Health care supervision |
TGC |
Nursing care |
|
|
CM_coordination* |
Health care supervision |
CM |
Sickness/injury care |
|
|
CM_orders* |
Health care supervision |
CM |
Medical/dental care |
|
|
CM_provider* |
Health care supervision |
CM |
Medical/dental care |
|
|
CM_p/f communication* |
Mental health |
CM |
Behavior modification |
|
|
CM_diet* |
Nutrition |
CM |
Dietary management |
|
|
CM_supplies |
Health care supervision |
CM |
Supplies |
|
|
CM_equipment |
Health care supervision |
CM |
Durable medical equipment |
|
|
CM_safety |
Neighborhood/workplace safety |
CM |
Safety |
|
|
CM_isolation |
Communicable/infectious condition |
CM |
Infection precautions |
|
|
TP_hand hygiene |
Communicable/infectious condition |
TP |
Infection precautions |
|
|
TP_breathing |
Respiration |
TP |
Respiratory care |
|
|
TP_straighten room |
Neighborhood/workplace safety |
TP |
Environment |
|
|
TP_feeding |
Nutrition |
TP |
Feeding procedures |
|
|
TP_transfer |
Physical activity |
TP |
Mobility/transfer |
|
|
TP_reposition |
Neuro-musculo-skeletal function |
TP |
Positioning |
|
|
TP_hygiene |
Personal care |
TP |
Personal hygiene |
|
|
S_chart review |
Health care supervision |
S |
Communication |
|
|
S_labs |
Health care supervision |
S |
Laboratory findings |
|
|
S_bowel function |
Bowel function |
S |
Signs/symptoms of physical |
|
|
S_consciousness |
Consciousness |
S |
Signs/symptoms of physical |
|
|
S_pain |
Pain |
S |
Signs/symptoms of physical |
|
|
S_skin |
Skin |
S |
Signs/symptoms of physical |
|
|
S_iv |
Circulation |
S |
Signs/symptoms of physical |
|
|
S_vitals |
Circulation |
S |
Signs/symptoms of physical |
|
|
Interventions never multitasked with medication management interventions |
CM_pager* |
Health care supervision |
CM |
Communication |
|
TGC_p/f end of life* |
Health care supervision |
TGC |
End-of-life care |
|
|
TGC_p/f diet* |
Nutrition |
TGC |
Dietary management |
|
|
TGC_spiritual care* |
Spirituality |
TGC |
Spiritual care |
|
|
TP_procedure |
Health care supervision |
TP |
Nursing care |
|
|
TP_specimen |
Health care supervision |
TP |
Specimen collection |
|
|
S_assessment |
Health care supervision |
S |
Signs/symptoms of physical |
|
|
S_room |
Neighborhood/workplace safety |
S |
Environment |
|
|
S_ movement |
Neuro-musculo-skeletal function |
S |
Signs/symptoms of physical |
|
|
TP_catheter |
Personal care |
TP |
Bladder care |
|
|
TP_ostomy |
Personal care |
TP |
Ostomy care |
|
|
S_wound |
Skin |
S |
Dressing change/wound care |
|
|
CM_chaplain |
Spirituality |
CM |
Spiritual care |
|
|
CM_guideline |
Health care supervision |
CM |
Nursing care |
|
|
TP_touch |
Mental health |
TP |
Bonding/attachment |
|
|
TP_settle |
Sleep and rest patterns |
TP |
Rest/sleep |
|
|
S_urinary function |
Urinary function |
S |
Signs/symptoms of physical |
|
Note: The interventions with asterisk are communication interventions.
a Case management (CM).
b Teaching, guidance, and counseling (TGC).
c Treatments and procedures (TP).
d Surveillance (S).
Of particular interest in this study, the Medication regimen problem is defined as the use of medications and infusions to meet guidelines for therapeutic action, safety, and schedule.[31] Five nursing interventions that addressed this problem were defined as medication management interventions: preparing medications, administering medications, assessing medication effects, documenting medication administration record (MAR), and instructing residents and family about medications ([Table 1]). Documentation in the MAR and medication instructions are communication interventions, while preparation and administration of medications and assessment of medication effects are task interventions. This granular definition of medication management interventions enabled an in-depth examination of multitasking relationships with other nonmedication-related interventions, which were also defined with similar granularity ([Table 1]).
TimeCaT (Version 3.9)
TimeCaT is web-based digital TMS data recording software, featuring three customizable dimensions: communication, task, and location.[33] This digital software enables users to assess inter-observer reliability by providing Kappa coefficient and percentage of inter-observer agreement, along with visual comparison.[33] Additionally, the software simultaneously captures and visualizes time stamps for each dimension, allowing users to record and analyze multitasking.[33] TimeCaT has been successfully used to capture time motion data for diverse clinicians in various acute and community care settings.[3] [7] [25] [26] [27] [28] [34] [35]
Multitasking in TimeCaT
Multitasking was defined as co-occurring communication and task interventions, as observed using TimeCaT software ([Figs. 2] and [3]).[3] In TimeCaT, verbal, written, and electronic interactions are recorded in the communication field, while physical actions/activities are recorded in the task field.[28] The communication and task fields can be selected simultaneously; therefore, overlap in time between communication and task interventions can be observed and quantified. Time-stamped data downloaded from TimeCaT were used to identify pairs of communication and task interventions with overlapping timestamps, which were operationalized as multitasking ([Fig. 2]). For this study, the 22 communication interventions and 35 task interventions for nursing homes were embedded in the interface of TimeCaT ([Fig. 3]).[32] From the time-stamped multitasking data, pairs including at least one of the five medication management interventions were extracted for further analysis.




Previous Multitasking Findings
Previous studies using TimeCaT software for observations in medical-surgical units found that acute care nurses spent over 20% of their working time multitasking.[3] [28] In addition, studies using TimeCaT software and the Omaha System interventions found 13% multitasking time among acute care nurses overall, with the highest percentage observed in intensive care units (16%), and the lowest percentage observed in telemetry units (11%).[25] [26] [36] A prior analysis in a nursing home using TimeCaT software and Omaha System nursing interventions revealed a higher percentage of time multitasking (29%) and prompted further investigation into their multitasking practices.[13]
Objectives
The purpose of this study was to describe and examine multitasking practice within the nursing workflow related to medication management in a nursing home. Using Omaha System intervention data recorded in TimeCaT, the study aimed to identify nursing interventions multitasked with medication management interventions, and to assess the impact of multitasking on the medication management workflow.
Methods
Study Design
This continuous observational TMS was approved by the University of Minnesota institutional review board (IRB) and used the suggested time and motion procedure (STAMP) checklist to design the study.[37] An external nurse observer used TimeCaT software with 57 nursing interventions, to capture and record interventions performed by nurses in a nursing home.[32]
Study Site
The study was conducted at a 250-bed nursing home located in the Southeastern United States. The study site had three long-term care (LTC) units and three short-term care (STC) units for post-acute care and orthopedic rehabilitation services. Both RNs and LPNs provided direct nursing care, with an average licensed nurse (RNs and LPNs) to resident ratio of 1:12.
Sample Recruitment
The administrator and nursing director approved and supported nurse recruitment and data collection on site. Flyers introducing the study were posted throughout the nursing home. The external nurse observer, who had 4 years of nursing home experience and had completed observation training, conducted the observations. Observer training and reliability assessment is described elsewhere.[13] [32] The nursing director identified licensed nurses from the daily schedule as candidates for observation. The external nurse observer explained the study, including a $20 gift card incentive per session, and obtained verbal consent from the nurses. A total of 11 licensed nurses (7 LPNs and 4 RNs) were recruited for the study. Over 160 hours of observations were collected, exceeding the amount of data collected in previous studies.[3] [25] [26] [28] [30] Of the 160 hours, 40 hours were excluded as they involved observations from two wound care nurses who were not responsible for medication management.
Data Collection
Between September 2019 and March 2020, 41 observation sessions were conducted on weekdays from 7 a.m. to 7 p.m. Each observation session lasted an average of 4 hours, except for one observation session that lasted less than 2 hours due to a personal reason. The external nurse observer used TimeCaT on a hand-held tablet device to collect data. The external nurse observer aimed to remain unobtrusive, only asking nurses about their computer use. The nurse introduced the external nurse observer to residents when they met for the first time. The external nurse observer left the resident room upon request for privacy and resumed observations when invited back by the nurses.
Using the 22 communication interventions and 35 task interventions embedded in TimeCaT software interface ([Fig. 3]), the external nurse observer continuously recorded all interventions performed by nurses during the observation sessions. Shadowing a nurse, the external nurse observer selected interventions as they were performed and deselected them upon completion. For example, when a nurse instructed a resident about medications while administering them, the external nurse observer selected both medication instruction in the communication field and medication administration in the task field ([Fig. 2]). Each intervention was deselected once completed ([Fig. 2]). The selection of co-occurring communication and task interventions resulted in identifiable multitasking pairs within the time motion data. A limitation of TimeCaT is that its interface only allows recording pairs of communication and task interventions as multitasking, even if more than two interventions co-occur (e.g., communication/communication/task or communication/task/task; [Fig. 2]).
Data Analyses
The time motion data were visualized using network graphs and analyzed with descriptive statistics and two-sample t-tests at a significance level of 0.05. All analyses and visualizations were conducted using R (version 4.3.1.).[38] [39]
Results
A total of 120 hours of time motion data from nine licensed nurses were analyzed, excluding data from wound care nurses who did not manage resident medications. Most licensed nurses were LPNs (67%; [Table 2]). The majority were female (89%), over 40 years old (78%), held an associate degree and higher (67%), and had less than 6 years of tenure at the facility (67%; [Table 2]). Nurses spent 11 hours on break, 12 hours transitioning between nursing interventions and locations, and 97 hours delivering nursing interventions. During the 97 hours, nurses communicated for 59 hours (N = 3,619 interventions), performed tasks for 64 hours (N = 3,425 interventions), and multitasked for 26 hours (N = 3,569 pairs of communication and task interventions).
|
Characteristics |
N |
|
|---|---|---|
|
Sex |
Female |
8 |
|
Male |
1 |
|
|
Age |
20–39 |
2 |
|
40–59 |
5 |
|
|
60+ |
2 |
|
|
Title |
LPN |
6 |
|
RN |
3 |
|
|
Education |
Technical |
3 |
|
Associate/Bachelor |
6 |
|
|
Tenure[a] |
1–3 |
5 |
|
4–6 |
1 |
|
|
7+ |
3 |
|
Abbreviations: LPN, licensed practical nurse; RN, registered nurse.
a A working-year at the study site.
Nursing Interventions Multitasked with Medication Management Interventions
Of the 3,569 pairs of multitasked interventions, the majority involved medication management interventions (N = 2,003). One of the medication management interventions, assessing medication effects [S_med effects], was not observed during the observation sessions. Medication management interventions were multitasked with 35 other nursing interventions, as well as other medication management interventions. Approximately 60% of these multitasking pairs involved interventions addressing Health care supervision problems (e.g., provide emotional support [TGC_p/f support]), 5% involved interventions addressing Communicable/infectious condition problems (e.g., perform hand hygiene [TP_hand hygiene]), and 30% involved other medication management interventions (e.g., preparation of medications [CM_meds]; [Table 1] and [Fig. 4a]).


Multitasked Interventions with Medication Administration
[Fig. 4 (A] and [B)] illustrates the network of nursing interventions multitasked with medication management interventions. When nurses administered medications [TP_meds], they simultaneously performed 15 different nursing interventions (N = 748) ([Fig. 4A]). The majority of multitasking pairs involved communication with residents and family, such as providing emotional support [TGC_p/f support, N = 420, mean (standard deviation, SD) = 28 (33) seconds], explaining about medications [TGC_p/f meds, N = 177, mean (SD) = 29 (31) seconds], discussing plan of care [TGC_p/f plan of care, N = 20, mean (SD) = 17 (16) seconds], and redirecting resident behaviors [CM_p/f communication, N = 32, mean (SD) = 48 (54) seconds] ([Fig. 4A, B]). Other multitasking pairs involved communication with staff, including other nurses [CM_report, N = 24, mean (SD) = 15 (13) seconds] and team members [CM_team, N = 9, mean (SD) = 34 (42) seconds] ([Fig. 4A, B]). Additional common interventions included managing resident dietary needs [CM_diet, N = 11, mean (SD) = 9 (4) seconds] and charting nursing notes [CM_notes, N = 3, mean (SD) = 3 (2) seconds] ([Fig. 4A]).
Multitasked Interventions with Medication Preparation
When nurses prepared medications [CM_meds], they multitasked with 16 different nursing interventions (N = 980; [Fig. 4A]). The majority of multitasking pairs involved brief communication with residents and family, such as providing emotional support [TGC_p/f support, N = 286, mean (SD) = 15 (22) seconds], explaining medications [TGC_p/f meds, N = 35, mean (SD) = 12 (14) seconds], and redirecting resident behaviors [CM_p/f communication, N = 8, mean (SD) = 14 (10) seconds] ([Fig. 4A, B]). Communication with other staff was also common, including other nurses [CM_report, N = 214, mean (SD) = 35 (50) seconds], team members [CM_team, N = 80, mean (SD) = 38 (57) seconds], and providers [CM_provider, N = 6, mean (SD) = 20 (23) seconds] ([Fig. 4A, B]). Additional frequent interventions included managing nonresident-related work [CM_non p/f workflow, N = 12, mean (SD) = 12 (13) seconds] and charting nursing notes [CM_notes, N = 51, mean (SD) = 22 (28) seconds] ([Fig. 4A, B]).
Multitasked Interventions with Documentation of Medication Administration
When nurses documented in the MAR [CM_mar], they multitasked with 14 different nursing interventions (N = 464; [Fig. 4A]). The majority of multitasking pairs involved other medication management interventions, such as preparing medications [CM_meds, N = 275, mean (SD) = 46 (81) seconds] and administering medications [TP_meds, N = 26, mean (SD) = 6 (8) seconds]) ([Fig. 4A, B]). Other multitasked interventions included managing care supplies [CM_supplies, N = 16, mean (SD) = 4 (3) seconds] and equipment [CM_equipment, N = 7, mean (SD) = 20 (20) seconds], assessing pain [S_pain, N = 4, mean (SD) = 16 (22) seconds], reviewing the chart [S_chart review, N = 38, mean (SD) = 20 (48) seconds], straightening resident room [TP_straighten room, N = 8, mean (SD) = 9 (14) seconds], feeding residents [TP_feed, N = 2, mean (SD) = 4 (1) seconds], and transferring residents [TP_transfer, N = 2, mean (SD) = 9 (9) seconds] ([Fig. 4A, B]).
Multitasked Interventions with Medication Instruction
When nurses instructed residents and family members about medications [TGC_p/f meds], they multitasked with 19 different nursing interventions (N = 324; [Fig. 4a]). The majority of multitasking pairs were related to medication management, such as preparing medications [CM_meds] and administering medications [TP_meds] ([Fig. 4a, b]). Other multitasked interventions included assessing skin [S_skin, N = 4, mean (SD) = 14 (8) seconds] and intravenous site/function [S_iv, N = 2, mean (SD) = 25 (6) seconds], reviewing the chart [S_chart review, N = 7, mean (SD) = 10 (9) seconds], performing personal hygiene care [TP_hygiene, N = 3, mean (SD) = 25 (20) seconds], and providing breathing care [TP_breathing, N = 3, mean (SD) = 21 (10) seconds] ([Fig. 4A, B]).
Impact of Multitasking on Medication Management Workflow
Of 2,176 observed medication management interventions, 1,612 interventions co-occurred with other nursing interventions, and some of them co-occurred with multiple different nursing interventions yielding a total of 2,003 pairs of multitasked medication management interventions. Of 2,176 medication management interventions, 808 were communication interventions, including medication instruction [TGC_p/f meds, N = 210, 4% of communication time] and MAR documentation [CM_mar, N = 598, 22% of communication time] ([Table 3]). The remaining 1,368 interventions were task interventions, such as medication preparation [CM_meds, N = 791, 48% of task time] and medication administration [TP_meds, N = 577, 1% of task time] ([Table 3]).
|
Dimension |
Interventions |
Overall (N = 2,176) |
Nonmultitasked (N = 564) |
Multitasked (N = 1,612) |
p |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
N |
Total hour |
Mean time (SD)[a] |
N |
Total hour |
Mean time (SD) |
N |
Total hour |
Mean time (SD) |
|||
|
Communication |
TGC_p/f meds |
210 |
2.3 |
39 (39) |
18 |
0.1 |
27 (39) |
192 |
2.2 |
41 (39) |
0.17 |
|
CM_mar |
598 |
12.7 |
77 (135) |
237 |
6.1 |
93 (184) |
361 |
6.6 |
66 (89) |
<0.05 |
|
|
Task |
CM_meds |
791 |
30.3 |
138 (194) |
234 |
5.3 |
81 (116) |
557 |
25.0 |
162 (214) |
<0.05 |
|
TP_meds |
577 |
7.6 |
47 (56) |
75 |
0.8 |
39 (52) |
502 |
6.8 |
48 (57) |
0.14 |
|
a Standard deviation (SD) in seconds.
When multitasking, interventions related to instructing, preparing, and administering medications were of longer duration, while interventions related to documenting in the MAR were of shorter duration ([Table 3]). Specifically, the average time to prepare medications was significantly longer when multitasking (162 seconds), compared to not multitasking (81 seconds, p < 0.05). Conversely, the average time to document in the MAR was significantly shorter when multitasking (66 seconds), compared to not multitasking (93 seconds, p < 0.05) ([Table 3]).
Discussion
This study examined the multitasking practice of nurses during medication management in a nursing home. Findings revealed a highly complex workflow, where the majority of medication management interventions were multitasked with diverse nursing interventions. While multitasking increased the time needed to prepare medications, it reduced the time spent on instances of MAR documentation.
The finding that medication management interventions were multitasked with various interventions is novel and significant. The majority of multitasked interventions such as medication instruction, conversational support for patients or family, and medication administration seem natural within the nursing workflow. However, less common multitasking pairs were also observed, such as managing nonresident-related work while preparing medications or transferring residents while documenting in the MAR. Cognitive experimental research shows that dissimilar stimuli increase response time and errors.[40] Therefore, as a basis for development of clinical solutions, further study is needed to identify which multitasking pairs are interruptive within medication management workflows.
The finding that multitasking increased the duration of medication management interventions aligns with the cognitive burden literature, which explains how multitasking delays response time.[2] This is particularly concerning given that nurses in nursing homes often face interruptions from colleagues and residents, resulting in more medication errors.[14] This highlights the need for interventions to reduce these risks. Additionally, MAR documentation interventions were shorter in duration when multitasking, likely due to frequent interruptions that led to brief and incomplete documentation needing to be finished later. This pattern is consistent with a study in an emergency department where data entry–related tasks were shorter in duration when clinicians multitasked.[7] Optimizing electronic health record system may help nurses document more efficiently and thus reduce the likelihood that documentation would be interrupted.[41] Furthermore, examining MAR documentation by nurse licensure (RNs or LPNs), working units (LTC or STC units), and staffing levels could provide further insights.[41]
Building on previous studies, the use of the Omaha System and TimeCaT in this study strengthens the methodological foundation for future multitasking research.[25] [26] [27] The consistent use of standardized TMS methods across different care settings and roles will enhance understanding of both multitasking practice and methodology itself. For example, the assessment of medication effects [S_med effects] was not recorded in our data, nor in the data of acute care nurses.[25] It is possible that this intervention might be interpreted and recorded as other interventions such as assessment of vitals, laboratory results, or consciousness. Such discrepancies between what nurses do and what observers observe highlight the need for ongoing methodological improvement.[28] [30] [33] Future research using these standardized methods should reassess interventions and their definitions to determine if the interventions need further revision, with a caveat that researchers should make as few changes as possible for data comparability.[30] Additionally, no patient safety concerns have been reported in previous studies using TimeCaT.[3] [7] [25] [26] [28] This may be due to lack of explicit study of potential safety issues related to TMS observations and how to safeguard patients when TMS (specifically TimeCaT) is in progress. Such studies in clinical settings are needed to ensure care safety during TMS observations.
There are three limitations common to observational TMS studies. First, as nurses were aware of being watched by the external nurse observer, the Hawthorne effect may have biased the findings.[42] To minimize the Hawthorne effect, the external nurse observer employed strategies from previous studies, such as building a relationship with nurses beforehand and maintaining distance from nurses during the observations.[43] [44] Second, there were a few brief interruptions due to technical issues, but the recording resumed immediately. One case of refusal to observe skin care accounted for only 0.2% of the data, and this recording was excluded from the data analysis. Finally, the study was conducted on weekdays during the day shift (7 a.m. to 7 p.m.) at one nursing home. More studies using TMS methods in different types of nursing homes and shifts are needed to increase generalizability of study findings.
Conclusion
This study examined multitasking intervention pairs within the medication management workflow of nurses working in a nursing home. Numerous and diverse multitasking pairs were observed, highlighting the complexity of their medication management practice. The findings will inform future efforts to create clinical and informatics solutions to optimize medication management workflow for nurses. The use of the Omaha System as a standardized terminology for intervention classification within TimeCaT enabled discrete observations revealing complex patterns, extending the knowledge base regarding multitasking. Such methods may be used across settings and disciplines to advance clinical informatics science and practice.
Clinical Relevance Statement
Extensive multitasking increases the complexity of medication management for nurses in a nursing home. Nurses and administrators should be aware of multitasking and related sequelae, in order to identify and minimize interruptions that may disrupt medication management interventions.
Multiple-Choice Questions
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According to the study findings, what nursing intervention was most frequently multitasked when nurses prepared medications?
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Documentation of nursing notes
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Documentation of medication administration record (MAR)
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Communication with other nurses
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Communication with residents and family
Correct Answer: The correct answer is option d. Nurses prepared medications while performing various types of communication interventions. When we look into the pairs of multitasked nursing interventions observed in this study ([Fig. 4b]), nurses most frequently communicated with residents and family while preparing medications. A total of 321 pairs of interventions was observed; 286 pairs of resident support (TGC_p/f support)-medication preparation (CM_meds) were observed and 35 pairs of medication instruction (TGC_p/f meds)-medication preparation (CM_meds) were observed.
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In the cognitive psychology field, multitasking is generally known to:
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Delay response time to the next task
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Shorten response time to the next task
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Have no effect on response time to next task
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Reduce task errors
Correct Answer: The correct answer is option a. According to a recent literature review, many cognitive psychology studies reported delayed response and increased time to respond to next task when human executes two tasks in close proximity.
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Conflict of Interest
None declared.
Acknowledgements
The authors acknowledge the University of Minnesota, Center for Nursing Informatics.
Protection of Human and Animal Subjects
The study was exempted by the University of Minnesota IRB as non-human subjects research.
-
References
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- 2 Douglas HE, Raban MZ, Walter SR, Westbrook JI. Improving our understanding of multi-tasking in healthcare: drawing together the cognitive psychology and healthcare literature. Appl Ergon 2017; 59 (Pt A): 45-55
- 3 Yen PY, Kelley M, Lopetegui M. et al. Understanding and visualizing multitasking and task switching activities: a time motion study to capture nursing workflow. AMIA Annu Symp Proc 2017; 2016: 1264-1273
- 4 Strayer DL, Castro SC, Turrill J, Cooper JM. The persistence of distraction: the hidden costs of intermittent multitasking. J Exp Psychol Appl 2022; 28 (02) 262-282
- 5 Westbrook JI, Woods A, Rob MI, Dunsmuir WTM, Day RO. Association of interruptions with an increased risk and severity of medication administration errors. Arch Intern Med 2010; 170 (08) 683-690
- 6 Westbrook JI, Raban MZ, Walter SR, Douglas H. Task errors by emergency physicians are associated with interruptions, multitasking, fatigue and working memory capacity: a prospective, direct observation study. BMJ Qual Saf 2018; 27 (08) 655-663
- 7 Moy AJ, Aaron L, Cato KD. et al. Characterizing multitasking and workflow fragmentation in electronic health records among emergency department clinicians: using time-motion data to understand documentation burden. Appl Clin Inform 2021; 12 (05) 1002-1013
- 8 Ferrah N, Lovell JJ, Ibrahim JE. Systematic review of the prevalence of medication errors resulting in hospitalization and death of nursing home residents. J Am Geriatr Soc 2017; 65 (02) 433-442
- 9 Barber ND, Alldred DP, Raynor DK. et al. Care homes' use of medicines study: prevalence, causes and potential harm of medication errors in care homes for older people. Qual Saf Health Care 2009; 18 (05) 341-346
- 10 Gurwitz JH, Field TS, Judge J. et al. The incidence of adverse drug events in two large academic long-term care facilities. Am J Med 2005; 118 (03) 251-258
- 11 Pierson S, Hansen R, Greene S. et al. Preventing medication errors in long-term care: results and evaluation of a large scale web-based error reporting system. Qual Saf Health Care 2007; 16 (04) 297-302
- 12 Kolanowski A, Cortes TA, Mueller C. et al. A call to the CMS: mandate adequate professional nurse staffing in nursing homes. Am J Nurs 2021; 121 (03) 24-27
- 13 Kang YJ, Mueller CA, Gaugler JE, Mathiason Moore MA, Monsen KA. Toward ensuring care quality and safety across settings: examining time pressure in a nursing home with observational time motion study metrics based on the Omaha system. J Am Med Inform Assoc 2023; 30 (11) 1837-1845
- 14 Holmqvist M, Ekstedt M, Walter SR, Lehnbom EC. Medication management in municipality-based healthcare: a time and motion study of nurses. Home Healthc Now 2018; 36 (04) 238-246
- 15 Kim Y, Lee MJ, Choi M, Cho E, Ryu GW. Exploring nurses' multitasking in clinical settings using a multimethod study. Sci Rep 2023; 13 (01) 5704
- 16 American Health Care Association. AHCA files lawsuit against federal staffing mandate. Published May 24, 2024 . Accessed June 9, 2024 at: https://www.ahcancal.org/News-and-Communications/Press-Releases/Pages/AHCA-Files-Lawsuit-Against-Federal-Staffing-Mandate.aspx
- 17 American Health Care Association. Staffing mandate analysis. Accessed June 9, 2024 at: https://www.ahcancal.org/Data-and-Research/Pages/Staffing-Mandate-Analysis.aspx
- 18 Jones W, Drake C, Mack D, Reeder B, Trautner B, Wald H. Developing mobile clinical decision support for nursing home staff assessment of urinary tract infection using goal-directed design. Appl Clin Inform 2017; 8 (02) 632-650
- 19 Fossum M, Ehnfors M, Fruhling A, Ehrenberg A. An evaluation of the usability of a computerized decision support system for nursing homes. Appl Clin Inform 2011; 2 (04) 420-436
- 20 Boyce RD, Perera S, Nace DA, Culley CM, Handler SM. A survey of nursing home physicians to determine laboratory monitoring adverse drug event alert preferences. Appl Clin Inform 2014; 5 (04) 895-906
- 21 Alexander GL, Rantz M, Galambos C. et al. Preparing nursing homes for the future of health information exchange. Appl Clin Inform 2015; 6 (02) 248-266
- 22 Zheng K, Ratwani RM, Adler-Milstein J. Studying workflow and workarounds in electronic health record-supported work to improve health system performance. Ann Intern Med 2020; 172 (11, Suppl): S116-S122
- 23 Lopetegui M, Yen PY, Lai A, Jeffries J, Embi P, Payne P. Time motion studies in healthcare: what are we talking about?. J Biomed Inform 2014; 49: 292-299
- 24 Blay N, Duffield CM, Gallagher R, Roche M. A systematic review of time studies to assess the impact of patient transfers on nurse workload. Int J Nurs Pract 2014; 20 (06) 662-673
- 25 Schenk E, Schleyer R, Jones CR, Fincham S, Daratha KB, Monsen KA. Impact of adoption of a comprehensive electronic health record on nursing work and caring efficacy. Comput Inform Nurs 2018; 36 (07) 331-339
- 26 Schenk E, Schleyer R, Jones CR, Fincham S, Daratha KB, Monsen KA. Time motion analysis of nursing work in ICU, telemetry and medical-surgical units. J Nurs Manag 2017; 25 (08) 640-646
- 27 Altiner M, Secginli S, Kang YJ. Refinement, reliability and validity of the Time Capture Tool (TimeCaT) using the Omaha System to support data capture for time motion studies. Jpn J Nurs Sci 2020; 17 (02) e12296
- 28 Yen PY, Kellye M, Lopetegui M. et al. Nurses' time allocation and multitasking of nursing activities: a time motion study. AMIA Annu Symp Proc 2018; 2018: 1137-1146
- 29 Fratzke J, Melton GB, Monsen KA. Time and cost of acute care interventions. international conference on research methods for standardized terminologies. Published 2013 . Accessed August 25, 2021 at: https://omahasystempartnership.org/international-conference-on-research-methods-for-standardized-terminologies/
- 30 Zhang Y, Monsen KA, Adam TJ, Pieczkiewicz DS, Daman M, Melton GB. Systematic refinement of a health information technology time and motion workflow instrument for inpatient nursing care using a standardized interface terminology. AMIA Annu Symp Proc 2011; 2011: 1621-1629
- 31 Martin K. The Omaha System: A Key to Practice, Documentation, and Information Management. 2nd ed. Omaha, NE:: Health Connections Press;; 2005
- 32 Kang YJ, Duan Y, Mueller CA, McMorris BJ, Gaugler JE, Monsen KA. Interventions employed by licensed nurses in nursing homes: refinement and validation of an existing Omaha System nursing intervention set. Res Theory Nurs Pract 2022; 36 (04) 395-421
- 33 Lopetegui M, Yen PY, Lai AM, Embi PJ, Payne PRO. Time Capture Tool (TimeCaT): development of a comprehensive application to support data capture for Time Motion Studies. AMIA Annu Symp Proc 2012; 2012: 596-605
- 34 Baker KM, Magee MF, Smith KM. Understanding nursing workflow for inpatient education delivery: time and motion study. JMIR Nurs 2019; 2 (01) e15658
- 35 Schwartz J, Elias J, Slater C, Cato K, Rossetti SC. An interprofessional approach to clinical workflow evaluation focused on the electronic health record using time motion study methods. AMIA Annu Symp Proc 2020; 2019: 1187-1196
- 36 Schenk B, Schleyer R, Daratha K, Lopetegui M. Capturing complexity: use of TimeCaT & the Omaha System to study multi-tasking activities of acute care nurses. International Conference on Research Methods for Standardized Terminologies. Published 2015 . Accessed February 25, 2021 at: https://omahasystempartnership.org/international-conference-on-research-methods-for-standardized-terminologies/
- 37 Zheng K, Guo MH, Hanauer DA. Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research. J Am Med Inform Assoc 2011; 18 (05) 704-710
- 38 Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal, Complex Systems 2006; 1695 (05) 1-9
- 39 R Core Team. R: A language and environment for statistical computing. Published online 2021. Accessed December 12, 2023 at: https://www.R-project.org/
- 40 Radović T, Manzey D. Effects of complexity and similarity of an interruption task on resilience toward interruptions in a procedural task with sequential constraints. J Exp Psychol Hum Percept Perform 2022; 48 (02) 159-173
- 41 Hultman GM, Marquard JL, Kandaswamy S, Lindemann EA, Pakhomov S, Melton GB. Electronic progress note reading patterns: an eye tracking analysis. Stud Health Technol Inform 2019; 264: 1684-1685
- 42 Wickström G, Bendix T. The “Hawthorne effect”–what did the original Hawthorne studies actually show?. Scand J Work Environ Health 2000; 26 (04) 363-367
- 43 Munyisia E, Yu P, Hailey D. The effect of an electronic health record system on nursing staff time in a nursing home: a longitudinal cohort study. Australas Med J 2014; 7 (07) 285-293
- 44 Yen K, Shane EL, Pawar SS, Schwendel ND, Zimmanck RJ, Gorelick MH. Time motion study in a pediatric emergency department before and after computer physician order entry. Ann Emerg Med 2009; 53 (04) 462-468.e1
Address for correspondence
Publication History
Received: 29 January 2024
Accepted: 04 August 2024
Accepted Manuscript online:
05 August 2024
Article published online:
23 October 2024
© 2024. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
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References
- 1 Madore KP, Wagner AD. Multicosts of multitasking. Cerebrum 2019; 2019: 2019
- 2 Douglas HE, Raban MZ, Walter SR, Westbrook JI. Improving our understanding of multi-tasking in healthcare: drawing together the cognitive psychology and healthcare literature. Appl Ergon 2017; 59 (Pt A): 45-55
- 3 Yen PY, Kelley M, Lopetegui M. et al. Understanding and visualizing multitasking and task switching activities: a time motion study to capture nursing workflow. AMIA Annu Symp Proc 2017; 2016: 1264-1273
- 4 Strayer DL, Castro SC, Turrill J, Cooper JM. The persistence of distraction: the hidden costs of intermittent multitasking. J Exp Psychol Appl 2022; 28 (02) 262-282
- 5 Westbrook JI, Woods A, Rob MI, Dunsmuir WTM, Day RO. Association of interruptions with an increased risk and severity of medication administration errors. Arch Intern Med 2010; 170 (08) 683-690
- 6 Westbrook JI, Raban MZ, Walter SR, Douglas H. Task errors by emergency physicians are associated with interruptions, multitasking, fatigue and working memory capacity: a prospective, direct observation study. BMJ Qual Saf 2018; 27 (08) 655-663
- 7 Moy AJ, Aaron L, Cato KD. et al. Characterizing multitasking and workflow fragmentation in electronic health records among emergency department clinicians: using time-motion data to understand documentation burden. Appl Clin Inform 2021; 12 (05) 1002-1013
- 8 Ferrah N, Lovell JJ, Ibrahim JE. Systematic review of the prevalence of medication errors resulting in hospitalization and death of nursing home residents. J Am Geriatr Soc 2017; 65 (02) 433-442
- 9 Barber ND, Alldred DP, Raynor DK. et al. Care homes' use of medicines study: prevalence, causes and potential harm of medication errors in care homes for older people. Qual Saf Health Care 2009; 18 (05) 341-346
- 10 Gurwitz JH, Field TS, Judge J. et al. The incidence of adverse drug events in two large academic long-term care facilities. Am J Med 2005; 118 (03) 251-258
- 11 Pierson S, Hansen R, Greene S. et al. Preventing medication errors in long-term care: results and evaluation of a large scale web-based error reporting system. Qual Saf Health Care 2007; 16 (04) 297-302
- 12 Kolanowski A, Cortes TA, Mueller C. et al. A call to the CMS: mandate adequate professional nurse staffing in nursing homes. Am J Nurs 2021; 121 (03) 24-27
- 13 Kang YJ, Mueller CA, Gaugler JE, Mathiason Moore MA, Monsen KA. Toward ensuring care quality and safety across settings: examining time pressure in a nursing home with observational time motion study metrics based on the Omaha system. J Am Med Inform Assoc 2023; 30 (11) 1837-1845
- 14 Holmqvist M, Ekstedt M, Walter SR, Lehnbom EC. Medication management in municipality-based healthcare: a time and motion study of nurses. Home Healthc Now 2018; 36 (04) 238-246
- 15 Kim Y, Lee MJ, Choi M, Cho E, Ryu GW. Exploring nurses' multitasking in clinical settings using a multimethod study. Sci Rep 2023; 13 (01) 5704
- 16 American Health Care Association. AHCA files lawsuit against federal staffing mandate. Published May 24, 2024 . Accessed June 9, 2024 at: https://www.ahcancal.org/News-and-Communications/Press-Releases/Pages/AHCA-Files-Lawsuit-Against-Federal-Staffing-Mandate.aspx
- 17 American Health Care Association. Staffing mandate analysis. Accessed June 9, 2024 at: https://www.ahcancal.org/Data-and-Research/Pages/Staffing-Mandate-Analysis.aspx
- 18 Jones W, Drake C, Mack D, Reeder B, Trautner B, Wald H. Developing mobile clinical decision support for nursing home staff assessment of urinary tract infection using goal-directed design. Appl Clin Inform 2017; 8 (02) 632-650
- 19 Fossum M, Ehnfors M, Fruhling A, Ehrenberg A. An evaluation of the usability of a computerized decision support system for nursing homes. Appl Clin Inform 2011; 2 (04) 420-436
- 20 Boyce RD, Perera S, Nace DA, Culley CM, Handler SM. A survey of nursing home physicians to determine laboratory monitoring adverse drug event alert preferences. Appl Clin Inform 2014; 5 (04) 895-906
- 21 Alexander GL, Rantz M, Galambos C. et al. Preparing nursing homes for the future of health information exchange. Appl Clin Inform 2015; 6 (02) 248-266
- 22 Zheng K, Ratwani RM, Adler-Milstein J. Studying workflow and workarounds in electronic health record-supported work to improve health system performance. Ann Intern Med 2020; 172 (11, Suppl): S116-S122
- 23 Lopetegui M, Yen PY, Lai A, Jeffries J, Embi P, Payne P. Time motion studies in healthcare: what are we talking about?. J Biomed Inform 2014; 49: 292-299
- 24 Blay N, Duffield CM, Gallagher R, Roche M. A systematic review of time studies to assess the impact of patient transfers on nurse workload. Int J Nurs Pract 2014; 20 (06) 662-673
- 25 Schenk E, Schleyer R, Jones CR, Fincham S, Daratha KB, Monsen KA. Impact of adoption of a comprehensive electronic health record on nursing work and caring efficacy. Comput Inform Nurs 2018; 36 (07) 331-339
- 26 Schenk E, Schleyer R, Jones CR, Fincham S, Daratha KB, Monsen KA. Time motion analysis of nursing work in ICU, telemetry and medical-surgical units. J Nurs Manag 2017; 25 (08) 640-646
- 27 Altiner M, Secginli S, Kang YJ. Refinement, reliability and validity of the Time Capture Tool (TimeCaT) using the Omaha System to support data capture for time motion studies. Jpn J Nurs Sci 2020; 17 (02) e12296
- 28 Yen PY, Kellye M, Lopetegui M. et al. Nurses' time allocation and multitasking of nursing activities: a time motion study. AMIA Annu Symp Proc 2018; 2018: 1137-1146
- 29 Fratzke J, Melton GB, Monsen KA. Time and cost of acute care interventions. international conference on research methods for standardized terminologies. Published 2013 . Accessed August 25, 2021 at: https://omahasystempartnership.org/international-conference-on-research-methods-for-standardized-terminologies/
- 30 Zhang Y, Monsen KA, Adam TJ, Pieczkiewicz DS, Daman M, Melton GB. Systematic refinement of a health information technology time and motion workflow instrument for inpatient nursing care using a standardized interface terminology. AMIA Annu Symp Proc 2011; 2011: 1621-1629
- 31 Martin K. The Omaha System: A Key to Practice, Documentation, and Information Management. 2nd ed. Omaha, NE:: Health Connections Press;; 2005
- 32 Kang YJ, Duan Y, Mueller CA, McMorris BJ, Gaugler JE, Monsen KA. Interventions employed by licensed nurses in nursing homes: refinement and validation of an existing Omaha System nursing intervention set. Res Theory Nurs Pract 2022; 36 (04) 395-421
- 33 Lopetegui M, Yen PY, Lai AM, Embi PJ, Payne PRO. Time Capture Tool (TimeCaT): development of a comprehensive application to support data capture for Time Motion Studies. AMIA Annu Symp Proc 2012; 2012: 596-605
- 34 Baker KM, Magee MF, Smith KM. Understanding nursing workflow for inpatient education delivery: time and motion study. JMIR Nurs 2019; 2 (01) e15658
- 35 Schwartz J, Elias J, Slater C, Cato K, Rossetti SC. An interprofessional approach to clinical workflow evaluation focused on the electronic health record using time motion study methods. AMIA Annu Symp Proc 2020; 2019: 1187-1196
- 36 Schenk B, Schleyer R, Daratha K, Lopetegui M. Capturing complexity: use of TimeCaT & the Omaha System to study multi-tasking activities of acute care nurses. International Conference on Research Methods for Standardized Terminologies. Published 2015 . Accessed February 25, 2021 at: https://omahasystempartnership.org/international-conference-on-research-methods-for-standardized-terminologies/
- 37 Zheng K, Guo MH, Hanauer DA. Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research. J Am Med Inform Assoc 2011; 18 (05) 704-710
- 38 Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal, Complex Systems 2006; 1695 (05) 1-9
- 39 R Core Team. R: A language and environment for statistical computing. Published online 2021. Accessed December 12, 2023 at: https://www.R-project.org/
- 40 Radović T, Manzey D. Effects of complexity and similarity of an interruption task on resilience toward interruptions in a procedural task with sequential constraints. J Exp Psychol Hum Percept Perform 2022; 48 (02) 159-173
- 41 Hultman GM, Marquard JL, Kandaswamy S, Lindemann EA, Pakhomov S, Melton GB. Electronic progress note reading patterns: an eye tracking analysis. Stud Health Technol Inform 2019; 264: 1684-1685
- 42 Wickström G, Bendix T. The “Hawthorne effect”–what did the original Hawthorne studies actually show?. Scand J Work Environ Health 2000; 26 (04) 363-367
- 43 Munyisia E, Yu P, Hailey D. The effect of an electronic health record system on nursing staff time in a nursing home: a longitudinal cohort study. Australas Med J 2014; 7 (07) 285-293
- 44 Yen K, Shane EL, Pawar SS, Schwendel ND, Zimmanck RJ, Gorelick MH. Time motion study in a pediatric emergency department before and after computer physician order entry. Ann Emerg Med 2009; 53 (04) 462-468.e1








