scholarly journals The Impact of e-Prescribing on Prescriber and Staff Time in Ambulatory Care Clinics: A Time-Motion Study

2007 ◽  
Vol 14 (6) ◽  
pp. 722-730 ◽  
Author(s):  
W. Hollingworth ◽  
E. B. Devine ◽  
R. N. Hansen ◽  
N. M. Lawless ◽  
B. A. Comstock ◽  
...  
Keyword(s):  
Ambulatory Care ◽  
Staff Time ◽  
Time Motion ◽  
Motion Study ◽  
Ambulatory Care Clinics ◽  
The Impact

scholarly journals P105: Observational study of distribution of time and activities over the course of an emergency physician's shift

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S102-S103
Author(s):  
E. Feng ◽  
Z. Zia ◽  
C. Tong ◽  
N. Cornell
Keyword(s):  
Medical Information ◽  
Patient Flow ◽  
Second Phase ◽  
Time Motion ◽  
Patient Interaction ◽  
Physician Productivity ◽  
Motion Study ◽  
One Year ◽  
The Impact ◽  
Insight Into

Introduction: The growing scrutiny to improve Emergency Department (ED) wait times and patient flow have resulted in many efforts to increase efficiency and maximize patient throughput via systems improvements. This study investigates areas of efficiency improvement from the Emergency Physician (EP) perspective by examining EP workflow in a two phased observational time-motion study. In the initial phase, the distribution of time and activities of EPs were dissected to identify potential sources for streamlining to maximize physician productivity. The first phase was of the study was completed during the period immediately preceding the implementation of an Electronic Health Records (EHR). The second phase of the study will repeat the analysis one year post EHR implementation. This data will be dissected to again identify sources for streamlining in an EHR environment and to identify shifts in work flow from a paper-based system. Methods: An observational time motion study was conducted at St. Mary's Hospital ED, in Kitchener Ontario. An observer was paired with an EP for the duration of an 8 hour shift, to a total of 14 shifts in the first phase of the study. Nine task categories were measured concurrently with a stopwatch application on a tablet, along with the number of interruptions experienced by the EP. Means of each category were calculated and converted to percentages, representing the amount of time per 8 hour shift dedicated to each activity. The second phase will be repeated in Fall 2020, 1 year after EHR implementation. Results: A total of 14 shifts were observed, accounting for 112 hours of observation. EP's time was allocated amongst the following categories: direct patient interaction (40.8%), documentation (27.1%), reviewing patient results (18.4%), communicating with ED staff (7.63%), personal activities (5.7%), writing orders (5.1%), communicating with consultants (3.3%), teaching (1.7%) and medical information searches (1.3%). On average, EPs experienced 15.8 interruptions over the course of an 8 hour shift. Conclusion: In a paper charting system, the direct patient interaction accounts for the largest timeshare over the course of a given shift. However, the next two largest categories, documentation and reviewing patient data, both represent areas of potential streamlining via clerical improvements. Additionally, detailed measurements of EPs’ activities have proven feasible and provides the potential for future insight into the impact of EHR's on EP workflow.

scholarly journals A Time Motion Study Evaluating the Impact of Geographic Cohorting of Hospitalists

2019 ◽  
Vol 15 (6) ◽  
Keyword(s):  
Multilevel Modeling ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Direct Care ◽  
Time Motion ◽  
Motion Study ◽  
Indirect Care ◽  
The Impact ◽  
Computer Interactions

BACKGROUND: Geographic cohorting (GCh) localizes hospitalists to a unit. Our objective was to compare the GCh and non-GCh workday. METHODS: In an academic, Midwestern hospital we observed hospitalists in GCh and non-GCh teams. Time in patient rooms was considered direct care; other locations were considered ‘indirect’ care. Geotracking identified time spent in each location and was obtained for 17 hospitalists. It was supplemented by in-person observation of four GCh and four non-GCh hospitalists for a workday each. Multilevel modeling was used to analyze associations between direct and indirect care time and team and workday characteristics. RESULTS: Geotracking yielded 10,522 direct care episodes. GCh was associated with longer durations of patient visits while increasing patient loads were associated with shorter visits. GCh, increasing patient loads, and increasing numbers of units visited were associated with increased indirect care time. In-person observations yielded 3,032 minutes of data. GCh hospitalists were observed spending 56% of the day in computer interactions vs non-GCh hospitalists (39%; P < .005). The percentage of time spent multitasking was 18% for GCh and 14% for non-GCh hospitalists (P > .05). Interruptions were pervasive, but the highest interruption rate of once every eight minutes in the afternoon was noted in the GCh group. CONCLUSION: GCh may have the potential to increase patient–hospitalist interactions but these gains may be attenuated if patient loads and the structure of cohorting are suboptimal. The hospitalist workday is cognitively intense. The interruptions noted may increase the time taken for time-intensive tasks like electronic medical record interactions.

Evaluating the Impact of Computer-Generated Rounding Reports on Physician Workflow in the Nursing Home: A Feasibility Time-Motion Study

2013 ◽  
Vol 14 (5) ◽  
pp. 358-362 ◽  
Author(s):  
Patrice T. Thorpe-Jamison ◽  
Colleen M. Culley ◽  
Subashan Perera ◽  
Steven M. Handler
Keyword(s):  
Nursing Home ◽  
Time Motion ◽  
Motion Study ◽  
The Impact

scholarly journals MP02: The impact of adoption of an electronic health record on emergency physician work: a time motion study

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S42-S43
Author(s):  
S. Calder-Sprackman ◽  
G. Clapham ◽  
T. Kandiah ◽  
J. Choo-Foo ◽  
S. Aggarwal ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Patient Care ◽  
Emergency Physician ◽  
Chart Review ◽  
Direct Patient Care ◽  
Health Record ◽  
Physical Movement ◽  
Time Motion ◽  
Motion Study ◽  
The Impact

Introduction: Adoption of a new Electronic Health Record (EHR) can introduce radical changes in task allocation, work processes, and efficiency for providers. In June 2019, The Ottawa Hospital transitioned from a primarily paper based EHR to a comprehensive EHR (Epic) using a “big bang” approach. The objective of this study was to assess the impact of the transition to Epic on Emergency Physician (EP) work activities in a tertiary care academic Emergency Department (ED). Methods: We conducted a time motion study of EPs on shift in low acuity areas of our ED (CTAS 3-5). Fifteen EPs representing a spectrum of pre-Epic baseline workflow efficiencies were directly observed in real-time during two 4-hour sessions prior to EHR implementation (May 2019) and again in go live (August 2019). Trained observers performed continuous observation and measured times for the following EP tasks: chart review, direct patient care, documentation, physical movement, communication, teaching, handover, and other (including breaks). We compared time spent on tasks pre Epic and during go live and report mean times for the EP tasks per patient and per shift using two tailed t-test for comparison. Results: All physicians had a 17% decrease in patients seen after Epic implementation (2.72/hr vs 2.24/hr, p < 0.01). EPs spent the same amount of time per patient on direct patient care and chart review (direct patient care: 9min06sec/pt pre vs 8min56sec/pt go live, p = 0.77; chart review: 2min47sec/pt pre vs 2min50sec/pt go live, p = 0.88), however, documentation time increased (5min28sec/pt pre vs 7min12sec/pt go live, p < 0.01). Time spent on shift teaching learners increased but did not reach statistical significance (31min26sec/shift pre vs 36min21sec/shift go live, p = 0.39), and time spent on non-patient-specific activities – physical movement, handover, team communication, and other – did not change (50min49sec/shift pre vs 50min53sec/shift go live, p = 0.99). Conclusion: Implementation of Epic did not affect EP time with individual patients - there was no change in direct patient care or chart review. Documentation time increased and EP efficiency (patients seen per hr on shift) decreased after go live. Patient volumes cannot be adjusted in the ED therefore anticipating the EHR impact on EP workflow is critical for successful implementation. EDs may consider up staffing 20% during go live. Findings from this study can inform how to best support EDs nationally through transition to EHR.

A Time-Motion Study of ICU Workflow and the Impact of Strain*

2016 ◽  
Vol 44 (8) ◽  
pp. 1482-1489 ◽  
Author(s):  
Yosefa Hefter ◽  
Purnema Madahar ◽  
Lewis A. Eisen ◽  
Michelle N. Gong
Keyword(s):  
Time Motion ◽  
Motion Study ◽  
The Impact

scholarly journals The impact of adoption of an electronic health record on emergency physician work: A time motion study

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Samantha Calder‐Sprackman ◽  
Glenda Clapham ◽  
Trisha Kandiah ◽  
Jade Choo‐Foo ◽  
Simran Aggarwal ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Emergency Physician ◽  
Health Record ◽  
Time Motion ◽  
Motion Study ◽  
Electronic Health ◽  
The Impact ◽  
Physician Work

scholarly journals A mobile application to support bedside nurse documentation and care: a time and motion study

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Frederic Ehrler ◽  
Danny T Y Wu ◽  
Pascal Ducloux ◽  
Katherine Blondon
Keyword(s):  
Smartphone Application ◽  
Mobile App ◽  
Clinical Workflow ◽  
Time Motion ◽  
Time And Motion ◽  
Motion Study ◽  
Patient Provider Communication ◽  
Bedside Documentation ◽  
Real Time Information ◽  
The Impact

Abstract   Documentation at the bedside is still often initiated on paper before being entered in electronic charts, even after implementing electronic health records (EHRs). This 2-step process is time-consuming, a potential source of error, and hinders the use of real-time information. We developed the “Bedside mobility” smartphone application to facilitate bedside documentation in the EHR. Objective This study aims to evaluate the impact of our app in 2 wards of a teaching hospital with a pre-post design. Materials and methods The duration and location of all documentation activities were recorded using a time motion study. Results Using the app significantly decreased the duration of EHR documentation per hour of observation by 4.10 min (P = 0.003), while the time spent interacting with patient increased by 1.45 min although not significantly. Also, in the intervention period, the average duration of uninterrupted documentation episodes increased by 0.27 min (P = 0.16) and the uninterrupted interaction with patient increased by 8.50 min (P = 0.027). Discussion By reducing the fragmentation of documentation workflow, decreasing the overall EHR documentation time and allowing nurses to spend more time with their patients, app use led to potential higher quality of care and higher patient satisfaction and may help maintain a smoother workflow. Conclusion Our mobile app has the potential to positively impact bedside nurses’ clinical workflow and documentation, as well as patient–provider communication and relationship.

Comparison of Time spent between an electronic and a paper-based laboratory information system by laboratorians at a polyclinic in Greater Accra, Ghana: A time-motion study

2020 ◽  
Author(s):  
Philip Boakye
Keyword(s):  
Information System ◽  
Negative Impact ◽  
Laboratory Information System ◽  
Time Motion ◽  
Accessible Information ◽  
Motion Study ◽  
Significant Difference ◽  
Significant Negative Impact ◽  
Key Issues ◽  
Motion Studies

The acceptance of electronic laboratory information system (LIS) is gradually increasing in developing countries. However, the issue of time effectiveness due to computerization is less clear as there is fewer accessible information. One of the key issues for laboratorians is their indecision with LISs’ would-be effect of time on their work. A polyclinic in Ghana was in the process of implementing electronic LIS. Several of the laboratorians did not have knowledge and skill in computing and there were disagreeing views on the time effectiveness of the LIS after implementation. The management of the polyclinic laboratory was concerned to assess time advantageousness of recording data when using the electronic LIS compared with paper-based LIS. <div><br></div><div>Five randomly selected laboratorians were provided two sheets of paper with tables to document the time they spent for both paper-based and electronic LIS. Data were collected for a total of 230 records,115 electronic LIS and 115 paper-based LIS. The t-test (mean-comparison test) was computed to compare the means of both electronic and paperbased LIS times. </div><div><br></div><div>There was a statistical significant difference in the time spent between electronic and paper-based LIS. The time spent between paper-based and electronic LIS was 0.41 minutes (95% CI 0.15 to 0.66) longer than in electronic LIS. </div><div><br></div><div>LIS can be adopted in polyclinics without having significant negative impact on time spent between electronic and paper-based LIS. More time–motion studies that include laboratorians are however necessary in order to get a more complete picture of time spent between electronic and paper-based LIS. </div>

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