WOMBAT

WOMBAT was developed to provide a reliable method for investigating the ways in which health professionals’ work and communication patterns change following the introduction of clinical information systems in hospitals. The aim was to advance existing methods, which failed to enable collection of multiple dimensions of work, interruptions and multitasking. In this way, WOMBAT sought to reflect a greater level of the complexity of clinical work.

Interventions and reforms often result in changes to work practices and many questions arise regarding the nature and value of those changes. For example, while there is great enthusiasm regarding the ways in which clinical information systems might streamline work processes and allow greater time in direct care activities, systems may also have negative consequences on some aspects of work efficiency and safety. Thus, there is a need for rigorous studies which quantify the impact of interventions and reforms and assess the nature of changes and their implications.

In the informatics field, we need quality data about how systems enhance or disrupt existing patterns of work and communication, so that we can move to re-design systems and/or work practices in ways which avoid any possible negative outcomes and which take advantage of the benefits information technology presents.

The history of WOMBAT

WOMBAT 1.0

WOMBAT 1.0, developed in 2006, allowed trained observers to shadow individuals and record four fixed dimensions of work activities: what task, with whom, where, and how. Each task was automatically timestamped. Instances of multitasking and interruptions could also be recorded. The software was developed for Windows PDA (HP iPAQ running Windows Mobile) [1].

WOMBAT 2.0

WOMBAT was redesigned in 2011 with the aim of allowing the tool to be used by research teams across the world. WOMBAT 2.0 provided researchers the flexibility to create custom data collection templates that could include the original four dimensions, or different/additional dimensions and variables. WOMBAT 2.0 also allowed interruptions and multitasking to be recorded and examined in greater detail. The new functionality increased the range of research questions that could be addressed with WOMBAT data, and expanded its application beyond health care. WOMBAT 2.0 was developed for devices running an Android operating system (4.0 and above) [2].

WOMBAT 3.0

In 2019, WOMBAT underwent redevelopment to improve the user interface and usability, and expand its functionality. WOMBAT 3.0 has been designed for use on devices running the Apple operating system (iOS) including iPad, iPad mini and iPhone. The WOMBAT App is freely available on the App Store and includes a Lite Version, which allows users to explore how WOMBAT works, how data are collected using WOMBAT, what collected WOMBAT data looks like, and examples of measures for analysis. WOMBAT 3.0 allows researchers to include a free text field in their data collection templates, further increasing the capacity to examine and answer different research questions. See WOMBAT in action.

Find WOMBAT 3.0 on the App Store.

WOMBAT is comprised of two separate but interlinked components: the WOMBAT App and the WOMBAT Web App.

• The WOMBAT App is the software application that is installed on your iOS device (iPad, iPad mini or iPhone) and enables the collection of data, which is stored on your iOS device until uploaded to the WOMBAT Web App.
• The WOMBAT Web App is a web portal with a unique address that sits on a secure external server. The Web App is where data collection templates are designed, and uploaded study data are securely stored.

The WOMBAT App is freely available on the App Store and includes a Lite Version. In the Lite Version, you can explore WOMBAT data collection using the provided sample study data collection templates. Please note, collected data are not saved to your device in the Lite Version. A licence is required to access the My WOMBAT Studies section of the App where data can be collected and saved. Licenced users are provided with My WOMBAT Sign In credentials, which links the WOMBAT App to a WOMBAT Web App allowing users access to their custom designed data collection templates and uploading of collected data.

See WOMBAT in action.

Find WOMBAT 3.0 on the App Store.

The WOMBAT tool may be of benefit to you if you are seeking to undertake a direct observational study, particularly to quantify aspects of work and workflow. The use of WOMBAT as a reliable method for quantifying work continues to grow. WOMBAT has been used by research teams from several countries, including: Australia, United States, United Kingdom, Canada, New Zealand, South Africa, Italy, Finland, Sweden and Norway.

WOMBAT allows researchers to design their own data collection templates that can be tailored to answer a particular research question, or to focus on the work of a specific professional group. Thus, WOMBAT affords the ability for researchers to undertake observational studies of different health professionals in different settings and to answer a wide range of questions using a rigorous approach. Examples include:

• examining hospital ward nurses’ time in medication related tasks [1] and interruptions during medication related tasks [2, 3]
• assessing hospital doctors’ and nurses’ patterns of work and communication [4, 5] and measuring the impact of health information technologies [6-10]
• quantifying how and with whom doctors on hospital wards spend their time [11]
• examining intensive care unit nurse workflow during shift change [12]
• quantifying the work patterns of doctors in intensive care units [13-16]
• assessing the rate of interruptions and multitasking by intensive care doctors and nurses [17-19]
• investigating work patterns, interruptions and multitasking in surgical wards [20, 21]
• measuring the work patterns of hospital pharmacists’ [22, 23] and the impact of electronic medication management systems [23-25]
• examining pharmacists’ workflow in community pharmacy [26]
• quantifying work and interruptions experienced by nuclear medicine technologists [27]
• quantifying junior doctors’ work practices after hours and on weekends [28, 29]
• evaluating the impact of a drug monitoring system on nurses’ work in ambulatory care [30]
• assessing interruptions and multitasking by doctors in emergency departments [31-35] and their impact on prescribing errors [36]
• examining work patterns and the use of electronic health records in ambulatory care [37]
• quantifying renal dietitians’ time [38]
• examining medication management work processes of nurses in home healthcare [39]
• assessing hand hygiene in birth attendants [40].

Researchers can also elect to use validated data collection templates to facilitate comparison of findings with previously published data, which is a great advantage of using the WOMBAT tool. Thus, we suggest that, where possible, you consider using existing definitions of work tasks which will allow you to compare your findings with those from other WOMBAT studies. WOMBAT also provides the opportunity to undertake multi-site and cross-country studies.

References

Which study data collection template – existing or new?

As with any research project, there are a number of key elements that need to be considered when developing the protocol (research plan) for a WOMBAT study.

Consider whether the research question(s) you wish to answer require the development of a new study template, or whether a study template used in a previous WOMBAT study could be used. Developing a new study template can take time and several iterations to ensure all activities of interest are sufficiently captured by the task classification underpinning the template. The task classification (i.e., the definition/scope of each variable included in a study template) needs to be clearly described in the study protocol.

Whenever possible, we suggest using a previously validated study template and/or task classification. If a previously developed study template does not exactly fit your study needs, it may be easy to make some modifications to the template rather than creating a new one. Using a previously developed template should speed up the design process and enable quicker piloting, observer training, and progression to data collection.

Designing a new study template

You need to consider the number of variables (dimensions, categories and subcategories) that you will include. In WOMBAT, it is possible to add as many dimensions and categories as you wish. Bear in mind, however, that data collection will be difficult if there are too many categories, and this may also require observers to scroll the screen and inhibit accurate data collection. Attempting to collect very detailed information will also prove difficult if observers cannot keep up with the speed at which activities change.

Study template designers also need to think about:

• Which dimensions should be mandatory? The first dimension on any study template is the study focus and is automatically mandatory. Other dimensions which are important to the research question should also be mandatory.
• When should dimensions be optional? Optional dimensions can make data collection easier for observers. If, for example, you are only interested in collecting information on computer use for certain tasks then if these tasks are not being undertaken, “computer” does not need to be selected.
• Which dimensions should allow multiple selections? Multiple options and/or selections should be used for dimensions which aren’t the direct focus of the study.

Selecting and training observers

The quality of your WOMBAT data will depend upon the quality of the data collection processes established. Observers need to undergo training and consistency between observers should be tested prior to commencing formal data collection.

As the primary data collectors, observers are integral to the success of any observational study. Whilst it may be desirable to select observers that already have an intimate knowledge of the work environment being studied, this is not always possible. Thus, training is key and training modules should include:

• Outlining the purpose of the study, background, method and overview of protocol;
• Providing detailed explanations of definitions used for the study template and task classification, with discussion of examples;
• Instructions on WOMBAT App use (see the WOMBAT App training videos in the WOMBAT Resources section) and further explanation of study template definitions, with practice scenarios;
• Short simultaneous observation sessions between the teaching/experienced observer and trainee observer(s), to ensure the trainee has understood the task classification and is applying it correctly when recording activities in the study template;
• Assessment of inter-rater reliability, with both the experienced and trainee observer simultaneously, but independently, carrying out a thirty-minute period of observation on the same participant. The trainee observer is deemed to be able to carry out independent observational work when inter-rater reliability, as measured by kappa scores, is equal to or greater than 0.85.

The above is as a very general guide. The time it takes to train observers will be highly dependent upon the complexity of the study and the data collected using WOMBAT. If interruptions are involved in the project, the assessment of inter-rater reliability may involve checking the type and frequency of interrupting and interrupted tasks. For those projects with multitasking, the length of time on multitasking should also be examined.

Observation schedule

With the WOMBAT study research questions in mind, consideration needs to be given to determining the observation period (e.g. day/evening/night shifts, weekdays, weekends, public holidays). Observation periods should be equally distributed, and observation of participants should be randomised across the selected times/days/observers. In most previous WOMBAT studies, observation periods were equally distributed across between 0700 to 1900 hours, Monday to Friday. Public holidays were not included. Each observation period was a maximum of two hours, and no individual participant was observed for more than a total of ten hours.

The length of each observation session also needs to be considered. Depending on the complexity of the study data collection template and the activities being observed, each observer may only be able to observe for a total of 1 to 2 hours at a time. After this time period, researcher fatigue may impact on the data quality.

Ethics

Ethical approval from an institutional Human Research Ethics Committee may be required prior to commencing data collection. Approval from study sites may also be required.

The principles of ethical research demand that all identifying details obtained by researchers remain confidential. We recommend de-identifying data relating to participants in the following ways:

• Assigning a unique number to each participant at the time of written consent;
• Using only the unique number for data collection purposes;
• Undertaking analysis using only the unique number;
• Keeping any documents linking unique numbers to participant names separate from collected data, and stored in locked cabinets or on password protected computers;
• Limiting access to data to the researchers involved in data collection and analysis;
• Presenting all data in aggregate form.

A primary aim of making the WOMBAT tool more widely available is to build the evidence base regarding health professionals’ work and communication patterns, how these are influenced by interventions such as the introduction of clinical information systems, and how changes in work relate to efficient, safe and effective care.

In the WOMBAT community section of this website, we share case studies of research published by other WOMBAT users as a way of supporting this aim. We would also welcome any feedback on WOMBAT. Please email us with your study details, experiences and ideas at wombat@mq.edu.au.

The world of WOMBATs

WOMBAT case studies

Read about studies that have used WOMBAT

The process for obtaining a WOMBAT licence is outlined below:

• New WOMBAT licences
  • Australian users
  • International users
• WOMBAT licence extensions (existing WOMBAT users)
  • Australian users - extension
  • International users - extension
• Once approved, you will be sent a link to our ePayments page to process payment of the licence fee by credit card
• Once payment has been received, your WOMBAT instance will be established and access details provided. It may take up to two weeks for your WOMBAT instance to be established.
• The detailed WOMBAT user manual will be forwarded to you

WOMBAT Licence Agreement

Please see the following links for the answers to some of our most frequently asked questions about WOMBAT.

I am interested in WOMBAT

I am a current WOMBAT user

Analysing WOMBAT data

Papers published by the WOMBAT team.

1. Brooke-Cowden KJ. Examining the patient experience in a paediatric oncology outpatient clinic: Macquarie University; 2022.
2. Guidi S, Tanzini M, Westbrook J. IORapp: An R tool for Inter-Observer Reliability Assessment of Time and Motion data.  European Conference on Cognitive Ergonomics 2021; Siena, Italy: Association for Computing Machinery; 2021. p. Article 8.
3. Havnes K, Lehnbom EC, Walter SR, Garcia BH, Halvorsen KH. Time distribution for pharmacists conducting a randomized controlled trial-An observational time and motion study. PLoS One. 2021;16(4):e0250898.
4. Lichtner V, Prgomet M, Gates P, Franklin BD. Automatic dispensing cabinets and governance of controlled drugs: an exploratory study in an intensive care unit. European Journal of Hospital Pharmacy. 2021:ejhpharm-2020-002552.
5. Tanzini M, Westbrook JI, Guidi S, Sunderland N, Prgomet M. Measuring Clinical Workflow to Improve Quality and Safety.  Textbook of Patient Safety and Clinical Risk Management: Springer, Cham; 2021. p. 393-402.
6. Chen EYH, Bell JS, Ilomaki J, Corlis M, Hogan ME, Caporale T, Van Emden J, Westbrook JI, Hilmer SN, et al. Medication administration in Australian residential aged care: A time-and-motion study. J Eval Clin Pract. 2020.
7. Prgomet M, Walter S, Jorgensen M, Georgiou A, Westbrook J. Understanding the work of case managers in Australian community aged care: a longitudinal time and motion study. Australian Health Review. 2020;44(6):853-61.
8. Walter SR, Raban MZ, Westbrook JI. Visualising clinical work in the emergency department: understanding interleaved patient management. Applied Ergonomics. 2019;79:45-53.
9. Westbrook JI, Li L, Shah S, Lehnbom EC, Prgomet M, Schofield B, et al. A cross-country time and motion study to measure the impact of electronic medication management systems on the work of hospital pharmacists in Australia and England. Int J Med Inform. 2019.
10. Bellandi T, Cerri A, Carreras G, Walter S, Mengozzi C, Albolino S, Mastrominico E, Renzetti F, Tartaglia R, Westbrook J. Interruptions and multitasking in surgery: a multicentre observational study of the daily work patterns of doctors and nurses. Ergonomics. 2018;61(1):40-7.
11. Westbrook JI, Raban M, 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 Quality & Safety. 2018.
12. Georgiou A, McCaughey EJ, Tariq A, Walter SR, Li J, Callen J, Paoloni R, Runciman WB, Westbrook JI. What is the impact of an electronic test result acknowledgement system on Emergency Department physicians’ work processes? A mixed-method pre-post observational study. Int J Med Inform. 2017;99:29-36.
13. Larcos G, Prgomet M, Georgiou A, Westbrook J. A work observation study of nuclear medicine technologists: interruptions, resilience and implications for patient safety. BMJ Qual Saf. 2017;26(6):466-74.
14. Walter SR, Raban MZ, Dunsmuir WTM, Douglas HE, Westbrook JI. Emergency doctors' strategies to manage competing workload demands in an interruptive environment: an observational workflow time study. Applied Ergonomics. 2017;58:454-60.
15. Westbrook JI, Li L, Hooper TD, Raban MZ, Middleton S, Lehnbom EC. Effectiveness of a ‘do not interrupt’ bundled intervention to reduce interruptions during medication administration: a cluster randomised controlled feasibility study. BMJ Quality & Safety. 2017;26(9):734.
16. Lehnbom EC, Li L, Prgomet M, Lam W, Westbrook JI, editors. Little things matter: a time and motion study of pharmacists’ activities in a paediatric hospital. Digital Health Innovation for Consumers, Clinicians, Connectivity and Community: Selected Papers from the 24th Australian National Health Informatics Conference (HIC 2016); 2016: IOS Press.
17. Richardson LC, Lehnbom EC, Baysari MT, Walter SR, Day RO, Westbrook JI. A time and motion study of junior doctor work patterns on the weekend: a potential contributor to the weekend effect? Intern Med J. 2016;46(7):819-25.
18. Sinsky C, Colligan L, Li L, Prgomet M, Reynolds S, Goeders L, Westbrook J, Tutty M, Blike G. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Annals of Internal Medicine. 2016;165(11):753-60.
19. Westbrook JI, Shah S, Lehnbom EC, Girling A. Collaborative cross-country study to measure the impact of electronic medication management systems. International Journal for Quality in Health Care. 2016;28(suppl_1):10-1.
20. Baysari MT, Lehnbom EC, Westbrook JI, editors. A workshop on how to use the Work Observation By Activity Timing (WOMBAT) tool – an easy and precise way to quantify patterns of work and communication. 19th Triennial Congress of the International Ergonomics Association; 2015 9-14 August 2015; Melbourne.
21. Li L, Hains I, Hordern T, Milliss D, Raper R, Westbrook J. What do ICU doctors do? A multisite time and motion study of the clinical work patterns of registrars. Critical Care and Resuscitation. 2015;17(3):159.
22. Raban MZ, Walter SR, Douglas HE, Strumpman D, Mackenzie J, Westbrook JI. Measuring the relationship between interruptions, multitasking and prescribing errors in an emergency department: a study protocol. BMJ Open. 2015;5(10):e009076.
23. Schofield B, Cresswel K, Westbrook J, Slee A, Girling A, Shah S, et al. The impact of electronic prescribing systems on pharmacists’ time and workflow: protocol for a time-and-motion study in English NHS hospitals. BMJ Open. 2015;5(10).
24. Walter SR, Li L, Dunsmuir WTM, Westbrook JI. Managing competing demands through task-switching and multitasking: a multi-setting observational study of 200 clinicians over 1000 hours. BMJ Quality & Safety. 2014;23(3):231-41.
25. Arabadzhiyska PN, Baysari MT, Walter S, Day RO, Westbrook JI. Shedding light on junior doctors' work practices after hours. Intern Med J. 2013;43(12):1321-6.
26. Callen J, Hordern A, Gibson K, Li L, Hains IM, Westbrook JI. Can technology change the work of nurses? Evaluation of a drug monitoring system for ambulatory chronic disease patients. Int J Med Inform. 2013;82(3):159-67.
27. Lehnbom EC, Baysari MT, Westbrook JI, editors. Quantifying health professionals' patterns of work and communication and the impact of health information technology: a workshop on how to design and use the Work Observation Method by Activity Timing (WOMBAT) tool. MedInfo; 2013; Copenhagen, Denmark.
28. Westbrook JI, Li L, Georgiou A, Paoloni R, Cullen J. Impact of an electronic medication management system on hospital doctors’ and nurses’ work: a controlled pre–post, time and motion study. Journal of the American Medical Informatics Association : JAMIA. 2013;20(6):1150-8.
29. Westbrook JI, Creswick NJ, Duffield C, Li L, Dunsmuir WTM. Changes in nurses’ work associated with computerised information systems: opportunities for international comparative studies using the revised Work Observation Method By Activity Timing (WOMBAT). Proceedings of the 11th International Congress on Nursing Informatics. 2012;2012:448.
30. Ballermann M, Shaw N, Mayes D, Gibney RN, Westbrook J. Validation of the Work Observation Method By Activity Timing (WOMBAT) method of conducting time-motion observations in critical care settings: an observational study. BMC Medical Informatics and Decision Making. 2011;11(1):32.
31. Westbrook J, Duffield C, Li L, Creswick N. How much time do nurses have for patients? a longitudinal study quantifying hospital nurses' patterns of task time distribution and interactions with health professionals. BMC Health Services Research. 2011;11(1):319.
32. Lo C, Burke R, Westbrook JI. Electronic medication management systems' influence on hospital pharmacists' work patterns. Journal of Pharmacy Practice and Research. 2010;40(2):106-10.
33. Westbrook JI, Coiera E, Dunsmuir WTM, Brown BM, Kelk N, Paoloni R, et al. The impact of interruptions on clinical task completion. Quality and Safety in Health Care. 2010;19(4):284-9.
34. Westbrook JI, Ampt A. Design, application and testing of the Work Observation Method by Activity Timing (WOMBAT) to measure clinicians' patterns of work and communication. Int J Med Inform. 2009;78 Suppl 1:S25-33.
35. Westbrook JI, Braithwaite J, Gibson K, Paoloni R, Callen J, Georgiou A, et al. Use of information and communication technologies to support effective work practice innovation in the health sector: a multi-site study. BMC Health Services Research. 2009;9(1):201.
36. Westbrook JI, Ampt A, Kearney L, Rob MI. All in a day's work: an observational study to quantify how and with whom doctors on hospital wards spend their time. Med J Aust. 2008;188(9):506-9.
37. Ampt A, Westbrook J, Creswick N, Mallock N. A comparison of self-reported and observational work sampling techniques for measuring time in nursing tasks. Journal of Health Services Research & Policy. 2007;12(1):18-24.
38. Ampt A, Westbrook JI. Measuring nurses' time in medication related tasks prior to the implementation of an electronic medication management system. Stud Health Technol Inform. 2007;130:157-67.
39. Westbrook JI, Ampt A, Williamson M, Nguyen K, Kearney L, editors. Methods for measuring the impact of health information technologies on clinicians' patterns of work and communication. Medinfo 2007: Proceedings of the 12th World Congress on Health (Medical) Informatics; Building Sustainable Health Systems; 2007: IOS Press.

Papers published by the WOMBAT community:

1. Magee K, Fromont M, Ihle E, Cheung M, Percival M, Poole SG, Bell C, Theobald B, Dooley MJ, et al. Direct observational time and motion study of the daily activities of hospital dispensary pharmacists and technicians. Journal of Pharmacy Practice and Research. 2023.
2. Aylin A, Kaya BY, ÇAKIT E, Dağdeviren M. Üretim sistemlerindeki dijital dönüşümün iş etüdü teknikleri üzerindeki etkisi. Verimlilik Dergisi. 2022:110-22.
3. Gaitan Gómez OL, Bueno-Robles LS, Pape T. Medication Administration Distraction Observation Sheet Checklist: Cultural Adaptation and Validation Into Spanish. CuidArte Journal. 2022;11(22).
4. Havnes K. Optimising drug therapy in older patients. Exploring different approaches across the patient pathway. UiT The Arctic University of Norway: UiT The Arctic University of Norway; 2022.
5. Huynh S, Rush L, Dadalias D, Githinji D, Ta M, Poole SG, et al. Time and motion study quantifying the activities of the cardiology, respiratory, and geriatric clinical pharmacist. Journal of Pharmacy Practice and Research. 2022;52(5):383-90.
6. Karia A, Norman R, Robinson S, Lehnbom E, Laba T-L, Durakovic I, et al. Pharmacist’s time spent: Space for Pharmacy-based Interventions and Consultation TimE (SPICE)—an observational time and motion study. BMJ open. 2022;12(3):e055597.
7. Mietchen MS, Short CT, Samore M, Lofgren ET, Program CDCMIDiH. Examining the impact of ICU population interaction structure on modeled colonization dynamics of Staphylococcus aureus. PLoS Comput Biol. 2022;18(7):e1010352.
8. Nymoen LD, Tran T, Walter SR, Lehnbom EC, Tunestveit IK, Øie E, et al. Emergency department physicians’ distribution of time in the fast paced-workflow-a novel time-motion study of drug-related activities. International Journal of Clinical Pharmacy. 2022:1-11.
9. Olin K, Göras C, Nilsson U, Unbeck M, Ehrenberg A, Pukk-Härenstam K, et al. Mapping registered nurse anaesthetists' intraoperative work: tasks, multitasking, interruptions and their causes, and interactions: a prospective observational study. BMJ Open. 2022;12(1):e052283.
10. Sinnott C, Moxey JM, Marjanovic S, Leach B, Hocking L, Ball S, et al. Identifying how GPs spend their time and the obstacles they face: a mixed-methods study. British Journal of General Practice. 2022;72:e148-e60.
11. Stellman R, Redfern A, Lahri Sa, Esterhuizen T, Cheema B. How much time do doctors spend providing care to each child in the ED? A time and motion study. Emergency Medicine Journal. 2022;39:23-9.
12. Leslie HH, Laos D, Cárcamo C, Pérez-Cuevas R, García PJ. Health care provider time in public primary care facilities in Lima, Peru: a cross-sectional time motion study. BMC Health Services Research. 2021;21(1):123.
13. Lichtner V, Prgomet M, Gates P, Franklin BD. Automatic dispensing cabinets and governance of controlled drugs: an exploratory study in an intensive care unit. European Journal of Hospital Pharmacy. 2021:ejhpharm-2020-002552.
14. Cooper AL, Brown JA, Eccles SP, Cooper N, Albrecht MA. Is nursing and midwifery clinical documentation a burden? An empirical study of perception versus reality. Journal of Clinical Nursing. 2021;30(11-12):1645-52.
15. Elenjord R, Ostbo A, Svendsen K, Lehnbom E. How do pharmacy staff distribute the time in a Hospital outpatient Pharmacy? The first WOMBAT time and motion study in a Norwegian Hospital Pharmacy (Abstracts of 48th ESCP symposium on clinical pharmacy 23–25 October 2019, Ljubljana (Slovenia)). International Journal of Clinical Pharmacy. 2020;42(1):224.
16. Gon G, Ali SM, Aunger R, Campbell OM, de Barra M, de Bruin M, et al. A Practical Guide to Using Time-and-Motion Methods to Monitor Compliance With Hand Hygiene Guidelines: Experience From Tanzanian Labor Wards. Global Health: Science and Practice. 2020.
17. Gon G, Virgo S, de Barra M, Ali SM, Campbell OM, Graham WJ, et al. Behavioural determinants of hand washing and glove recontamination before aseptic procedures at birth: a time-and-motion study and survey in Zanzibar labour wards. International Journal of Environmental Research and Public Health. 2020;17(4):1438.
18. Karia AM, Balane C, Norman R, Robinson S, Lehnbom E, Durakovic I, et al. Community pharmacist workflow: Space for Pharmacy-based Interventions and Consultation TimE study protocol. International Journal of Pharmacy Practice. 2020;28(5):441-8.
19. Wise S, Duffield C, Fry M, Roche M. Clarifying workforce flexibility from a division of labor perspective: a mixed methods study of an emergency department team. Human Resources for Health. 2020;18(1):17.
20. Göras C, Olin K, Unbeck M, Pukk-Härenstam K, Ehrenberg A, Tessma MK, et al. Tasks, multitasking and interruptions among the surgical team in an operating room: a prospective observational study. BMJ Open. 2019;9(5):e026410.
21. Hand RK, Albert JM, Sehgal AR. Quantifying the time used for renal dietitian's responsibilities: a pilot study. Journal of Renal Nutrition. 2019;29(5):416-27.
22. Cavaye D, Lehnbom EC, Laba T-L, El-Boustani E, Joshi R, Webster R. Considering pharmacy workflow in the context of Australian community pharmacy: a pilot time and motion study. Research in Social and Administrative Pharmacy. 2018.
23. Gon G, de Bruin M, de Barra M, Ali SM, Campbell OM, Graham WJ, et al. Hands washing glove use, and avoiding recontamination before aseptic procedures at birth: A multicenter time-and-motion study conducted in Zanzibar. American journal of infection control. 2018.
24. Graham TA, Ballermann M, Lang E, Bullard MJ, Parsons D, Mercuur G, et al. Emergency physician use of the Alberta Netcare Portal, a province-wide interoperable electronic health record: multi-method observational study. JMIR. 2018;6(3):e10184.
25. Holmqvist M, Ekstedt M, Walter SR, Lehnbom EC. Medication management in municipality-based healthcare: a time and motion study of nurses. Home Healthcare Now. 2018;36(4):238-46.
26. Reed CC, Minnick AF, Dietrich MS. Nurses’ responses to interruptions during medication tasks: a time and motion study. International Journal of Nursing Studies. 2018;82:113-20.
27. Hefter Y, Madahar P, Eisen LA, Gong MN. A time-motion study of ICU workflow and the impact of strain*. Critical Care Medicine. 2016;44(8):1482-9.
28. Stellman R. How much time do doctors spend looking after children in South African Emergency Departments? 2016.
29. Hefter Y, Madahar P, Eisen L, Gong M. A time motion study to describe workflow of attendings and residents in medical and surgical ICUs.  C94 High Imapct Clinical Trials in Critical Care. American Thoracic Society International Conference Abstracts: American Thoracic Society; 2015. p. A5126-A.
30. Hefter Y, Madahar P, Eisen LA, Gong MN. Relationship of ICU strain factors and allocation of physician time in the ICU.  C103 Optimizing Limited ICU Resources: Am Thoracic Soc; 2015. p. A5233-A.
31. Reed CC. Nursing work and responses to interruptions. Nashville, Tennessee: Vanderbilt University; 2015.
32. Ballermann M, Shaw NT, Mayes DC, Gibney RN. Impact of a clinical information system on multitasking in two intensive care units. Electronic Journal of Health Informatics. 2012;7(1):2.
33. Ballermann M, Shaw NT, Mayes DC, Gibney RTN. Critical care providers refer to information tools less during communication tasks after a critical care clinical information system introduction. Stud Health Technol Inform. 2011;164:37-41.
34. Shaw NT, Ballermann MA, Hagtvedt R, Ho S, Mayes DC, Gibney N. Intensive care unit nurse workflow during shift change prior to the introduction of a critical care clinical information system. electronic Journal of Health Informatics. 2011;6(1):5.
35. Ballermann M, Shaw N, Mayes D, Gibney R, editors. Intensive care unit health care providers spend less time multitasking after the introduction of a critical care clinical information system. HIC 2010: 18th Annual Health Informatics Conference: Informing the Business of Healthcare; 2010 24-26 August 2010; Melbourne Convention and Exhibition Centre: Health Informatics Society of Australia.
36. Ballermann MA, Shaw NT, Arbeau KJ, Mayes DC, Noel Gibney R. Impact of a critical care clinical information system on interruption rates during intensive care nurse and physician documentation tasks. Stud Health Technol Inform. 2010;160(Pt 1):274-8.