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JONAVolume 38, Number 1, pp 19-26Copyright B 2008 Wolters Kluwer Health | Lippincott Williams & Wilkins

T H E J O U R N A L O F N U R S I N G A D M I N I S T R A T I O N

Quantifying Nursing Workflowin Medication Administration

Carol A. Keohane, BSN, RN

Anne D. Bane, MSN, RN

Erica Featherstone, BS

Judy Hayes, MSN, RN

Seth Woolf, BS

Ann Hurley, DNSc, RN

David W. Bates, MD, MSc

Tejal K. Gandhi, MD, MPH

Eric G. Poon, MD, MPH

New medication administration systems are showingpromise in improving patient safety at the point ofcare, but adoption of these systems requires signifi-cant changes in nursing workflow. To prepare forthese changes, the authors report on a time-motionstudy that measured the proportion of time thatnurses spend on various patient care activities,focusing on medication administrationYrelatedactivities. Implications of their findings are discussed.

Technology is increasingly being used at the patientbedside to improve patient safety and streamlineclinicians’ work. A thorough understanding of thescope of nurses’ workflow in the inpatient environ-ment is critical to the successful integration of anybedside technology. Although bedside technology

such as bar coding has the potential to improvemedication safety,1 it may also have a major effecton nursing workflow. For example, if bar codetechnology causes nurses to take longer to administermedications, this could divert nurses from otherimportant patient care activities, which may have asimilar effect to decreasing nursing staffing ratios andlead to poorer patient outcomes.2 In addition, thelack of sufficient time to administer medicationsmight encourage nurses to bypass the bar codescanning step and greatly diminish the intendedimpact of this technology on patient safety. In fact,during the planning stages of developing our hospi-tal’s bar code/electronic medication administrationrecord (bar code/eMAR) system, nurses voiced theirconcern about increasing the time spent on adminis-tering medications and decreasing time with patients.Objective data were needed about the relativeamounts of time spent on the many tasks that nursesare required to complete. Therefore, we decided toperform a baseline assessment of nursing workflowto inform the development of our eMAR system.

The distribution of time over various nurse ac-tivities can be studied through work sampling, con-tinuous self-reporting, or continuous time-motionobservation. Work sampling involves the intermit-tent recording of nursing activities by an independentobserver. Work sampling records each activity butdoes not capture the time spent performing theactivity. Work sampling methodology is based onthe laws of probability, meaning that observationstaken at repeated, random times will have the samedistribution. Urden and Roode3 used work samplingmethodology to determine the amount of time that

JONA � Vol. 38, No. 1 � January 2008 19

Authors’ Affiliations: Program Director (Ms Keohane), Divi-sion of General Internal Medicine, Brigham and Women’sHospital, Boston; Manager of Clinical Systems Innovations(Ms Bane), Center for Nursing Excellence, Brigham and Women’sHospital, Boston; Research Assistant (Ms Featherstone), Divisionof General Internal Medicine, Brigham and Women’s Hospital,Boston; Chief Nursing Officer (Ms Hayes), Nursing, FaulknerHospital, West Roxbury; Research Assistant (Mr Woolf), Divisionof General Internal Medicine, Brigham and Women’s Hospital,Boston; Center for Nursing Excellence Senior Nurse Scientist,Emerita (Ms Hurley), Brigham and Women’s Hospital, Boston;Chief (Dr Bates), Division of General Internal Medicine, Brighamand Women’s Hospital, Boston; Director of Patient Safety (DrGandhi), Division of General Internal Medicine, Brigham andWomen’s Hospital, Boston; Assistant Professor of Medicine/Physician Scientist (Dr Poon), Division of General Internal Medi-cine, Brigham and Women’s Hospital, Boston, Massachusetts.

Corresponding author: Ms Keohane, Division of GeneralMedicine and Primary Care, Brigham and Women’s Hospital, 3/F,1620 Tremont St, Boston, MA 02120 ([email protected]).

This work was supported by a grant from the Agency forHealthcare Research and Quality (no. HS14053-02).


nurses and nurse extenders spent on documentationand direct and indirect patient care activities beforethe implementation of computerized documentation.Capuano et al4 also used work sampling method-ology to evaluate the impact of work environmentchanges on nursing and support staff roles, and simi-lar to the work of Urden and Roode, activities weregrouped into 5 major categories: direct care, indirectcare, unit related, personal, and documentation.

Both time-motion and continuous self-reportingmethods have been used to measure nursing work.5

Self-reporting involves recording one’s activitiesbased on predefined categories during a specifictime frame. Although continuous self-reporting canbe a low-cost method for measuring work activities,perceptual differences among the self-reporters canlead to discrepancies in how activities are catego-rized. Self-report also proved burdensome to nursesas they attempted to record their activities whilemanaging patient care assignments. Subsequently,nurses often recorded their activities at infrequentintervals as opposed to real time, giving an incon-sistent reflection of actual time spent on eachindividual activity.

In continuous time-motion observation, a trainedobserver passively shadows the subject while notingthe amount of time spent on activities, allowingaccurate recording of the start and end time of eachactivity.5 The burden of recording is placed on anindependent observer. Continuous time-motion ob-servation methodology within 4-hour observationsessions was used to study the changes in intensivecare unit (ICU) task activities after the installationof a third-generation ICU information system. Thestudy revealed that installation of the computerizeddocumentation system decreased time spent ondocumentation by 30%.6

Although continuous time-motion observationis a more costly method of measuring nursingworkflow, this method eliminates the potential biasof self-reporting and captures very detailed andtime-specific information related to nursing activi-ties. Our goal was to collect objective data via con-tinuous time-motion observation to qualitativelyand quantitatively characterize the activities onwhich nurses spend their time to learn the impactof bedside technologies on nursing workflow andnursing practice.

Methods

Instrument

The time-motion observation instrument wasdeveloped to record all tasks performed by indi-vidual bedside nurses during a 2-hour period of a

designated shift and to capture the amount of timerequired for completion of these observed activi-ties. Three master’s-prepared clinical experts func-tioning as educators and 1 doctoral-prepared nurseeducator who were experienced in orienting newlylicensed nurses contributed to the development ofthe time-motion observation instrument. Eacheducator independently prepared a comprehensivetask list in preparation for a consensus meeting.After discussing and resolving initial differences inlabeling and definitions, agreement was reached ona prototype paper master list of 112 tasks. Taskswere organized under 12 major categories, similarto the Urden and Roode3 and Capuano et al4

classification methods.The prototype list with category structure was

made computer compatible using Microsoft Accessdatabase software and installed onto a laptop com-puter. Because the observers would follow the nurse,observations could take place in several geographicareas in a short period of time. Loading the instru-ment onto a tablet personal computer providedportability for the observer. The format of the in-strument on the computer screen allowed the observ-ers to quickly and easily click on a touch screen asthey observed the multiple tasks the nurse performed.Speed and accuracy were critical in order to capturetasks, many of which are performed in very shortperiods of time.

Pilot testing consisted of conducting 10 obser-vations on 4 types of units for examining observeragreement, instrument usability/comprehensiveness,and ease of using the software/hardware. Datafrom direct examination of nurse observers andusers’ field notes/critiques were used to developthe final task list for the instrument and confirmassignment to categories. The final time-motionobservation instrument consists of 112 discreteobservable patient care tasks grouped into 12 majorcategories (Figure 1).

Observer Training

Two nonclinician research assistant observersworked with nurses and experienced time-motionobservers to learn the proper observation tech-niques during the training period. They learned thetask categories, definitions, and placement on theobservation instrument before conducting anyobservations and asked questions of the experi-enced observers, the designers of the task list, andthe senior investigator. Each observer conductedthree 2-hour practice sessions. These data werecritically reviewed with observers in training anddiscussed to resolve discrepancies and ensureproper data collection.

20 JONA � Vol. 38, No. 1 � January 2008


Study Setting

The time-motion observations were performedon the inpatient units of a 735-bed tertiary aca-demic medical center over a 6-month period. Inthe study hospital, approximately 45,000 inpa-tients are treated annually and 2,800 nurses areemployed on a full-time, part-time, or per diembasis. Institutional review board approval wasreceived.

The hospital is organized according to patientpopulation. The observations for this study wereconducted on 23 units, each containing approxi-mately 15 beds with medical, surgical, or a combi-nation of medical and surgical patients. The studywas also performed in 6 ICUs that each housedapproximately 10 beds. These observations were notconducted on the hematology/oncology unitsbecause this specific clinical area was not going tobe part of the initial phase of bar code/eMARimplementation. Medical and surgical nurses rou-

tinely care for 2 to 5 patients, and intensive carenurses routinely care for 1 to 2 patients during theirshifts.

Study Design

The study design was based on time-motion studiesperformed on physicians at the Regenstrief Insti-tute for Health Care7 and at Partners Healthcare.8

Our study personnel met with staff nurses and theirmanagers to educate them about the study andexplained the study’s aims to nurses directly beforeeach observation session. Nurses were offered theopportunity to voluntarily participate in the study.No patient information was collected. Nurses’general demographic information was collectedand de-identified. Observation data were identifiedby randomly assigned nurse identification num-bers. Information obtained during these observa-tion periods remained confidential. Members ofthe research team were the only personnel to have

Figure 1. Time-motion instrument.



access to this confidential information, which wasanalyzed in aggregate only. Hospital administra-tion did not have access to any individual data,thus preventing any data from being used as part ofany employee’s performance evaluation.

At the beginning of each observation period, allpermanent, per diem, and float nurses were invitedto participate. One nurse was randomly selectedfor this 2-hour observation and provided writteninformed consent. Because the observation instru-ment included observing nurses performing directpatient care, staff nurses explained the study topatients. If either patient or nurse requested thatthe observer not be present during direct patientcare activities, the observer would not enter theroom. Observers did record workflow activities ofpatients who were on contact precautions. Oncein the room and introduced to the patient, theobserver did not interact with either the patient ornurse and remained in the role of passive observer.The observer did not enter the rooms of patientson respiratory precautions. This session time wasnot recorded, and the observer waited outside thepatient’s room.

Participating nurses were observed for approxi-mately 2 hours during a total of 116 two-hourobservation sessions. A total of 108 nurses wereobserved, with 7 nurses participating more thanonce. Observations began at various times of day,evening, and night. Session periods were staggeredand divided into 5 start times (0730, 0930, 1130,1400, and 1800). A large proportion, 50 of 116, wereperformed during times when medications werefrequently administered to assure capturing medi-cation administration activities and, ultimately, toassess the impact that the bar code/eMAR wouldhave on these tasks.

Data Collection

At the beginning of each session, after obtainingconsent from the nurse, the observer entered generalsession data, including his or her identification, thenurse’s study identification number, the session date,the unit code, and the start time. During observationsessions, when the nurse initiated an activity, theobserver clicked on the ‘‘Start Observation’’ buttonto record the activity start time in the database. Next,the observer visually identified the task being per-formed by the nurse. If unable to visually classify theactivity and the nurse was available, the observerwould ask him or her for clarification. Once visuallyidentified, the observer selected the task on theAccess data entry form. Because of the large numberof minor categories in the task set, 2 screens were

required for visualization. One screen containedmedication administrationYrelated activities, andthe other screen, nonYmedication administrationactivities. The observer was able to add free textcomments to that activity’s data. Once the activitywas complete, the observer would tap the ‘‘EndObservation’’ button and the end time of the activitywould be entered into the database. At this time, thestart time, end time, and the identity of the taskobserved became a permanent entry in the database.This design enabled observers to correctly identify orreclassify the task if necessary.

The observer was limited to categorizing 1 taskat a time and thus had to identify the primaryactivity of the nurse at that specific instant. Con-sequently, if the nurse was watching a patient takean oral medication while concurrently talkingwith patient’s family members, the ‘‘observepatients taking oral medications’’ would berecorded until the patient finished taking themedications. Then, a new activity would be startedand assigned ‘‘communicating with patients andfamilies.’’ During the pilot sessions and againduring the actual study sessions, veryYshort-termactivities where nurses switched back and forthbetween 2 discrete tasks were more likely to occurthan actual multitasking. Observers were ableto use the data entry instrument to accuratelyrecord such rapidly occurring short-term activi-ties. Multiple activities were not recorded simul-taneously but rather separately, by the order inwhich each activity was performed. When ob-servers were asked not to enter the room or wereunable to enter because of the patient’s respira-tory precautions, the observer would click on‘‘observer not in room.’’ Observers judged whethera medication was being administered in his orher absence based on a visual evaluation or con-versation with the nurse before entry into thepatient’s room.

After 2 hours of data collection, the observerwould tap the ‘‘End Session’’ button. He or she wouldalso count the number of patients treated by thenurse during the session. Lastly, the observer wouldcount the number of activities that involved the nurseassisting another nurse with his or her work. Nopatient-related information was collected.

Statistical Analysis

The main goal of the study was to describe thedistribution of nurses’ time over the major catego-ries of activities that are listed in Figure 1. Data inthe access database were converted to SAS for thepurpose of statistical analysis. These data were



then converted to percentages for the purpose ofpresenting the results.

Results

Findings from 116 two-hour observation periodsrevealed that nurses spent 26.9% of their time onmedication-related activities and 73.1% of their timeon nonYmedication-related activities. We furtherexamined the distribution of time by various clinicalsettings. Figure 2 reflects the overall distribution of

nursing workflow throughout the general medical/surgical and intensive care units. Times remainedrelatively consistent across clinical areas, with theaverage time spent on medication-related activitiesranging from 22.8% in the ICU setting to 29.1% incombined medical/surgery units. The proportionof time spent on medication-related versus non-medication-related activities was consistent through-out the day (Figure 3).

Figure 4 identifies the tasks associated withmedication administrationYrelated activities and

Figure 2. Average time spent on medication administration (Med Admin) versus nonYmedication administration (NonMed Admin) by type of clinical unit.

Figure 3. Average medication administration (Med Admin) versus nonYmedication administration (Non Med Admin)tasks by time of day.



the percentage of time spent on each. The task thatoccupied most of the nurses’ time was obtaining andverifying the medications. Obtaining the medicationsrequired a search in one of several designated storageareas on the units, automated dispensing cabinets,medication carts, or the refrigerators. Once the drugwas located or received from the pharmacy, the nurseconfirmed that it matched the provider’s orders.Medication delivery involved all steps in the requiredprocess for administering the prescribed drug tothe patient, including reviewing medications withthe patients, preparing oral and intravenous medi-cations, obtaining liquids for the patient to takewith the medications, flushing intravenous lines, andobserving the patient take the medications. Manage-ment of orders included discussions with care pro-viders and resolving questions surrounding the order.Information retrieval consisted of time spent onlooking up drug information or consulting with apharmacist on how to administer the medication.Documentation of medication administration in-cluded time spent to record the date, time, dose,

and signature of the individual administering thedrug along with any critical laboratory values orparameters specific to that administration.

Time designated as uncharacterized by theobserver was a reflection of times that the nurseasked the observer to wait outside the patient’s roombecause of a patient situation. Inefficient waitingincluded such things as delays in time associated withwaiting for the medication to be approved and sentby the pharmacist, waiting for the physician to callback to answer questions regarding an order, orlooking for equipment to administer the medications.

Figure 5 reflects the average proportion of timethat nurses spent on other nonYmedication-relatedcommon activities (73.1% of total observed time).The largest category in this area was communication,including any time spent on communicating withpatients, families, or anyone of the many direct careproviders and other persons who support patientcare. Physical care of patients involved a multitude ofactivities that provide direct contact with a patient,such as bathing, dressings, performing patient care

Figure 4. Average percentage of time spent on medication-related activities by type.

Figure 5. Average percentage of time spent on nonYmedication administration activities by type.



assessments, and others. Miscellaneous activitiesincluded any other tasks that could not be capturedin 1 of the 12 major categories. Of particular note,within the miscellaneous category, nurses spent 83%of that 14% traveling within the unit. Paper-baseddocumentation included any recording of patientcare on flow sheets, medical records, or any otherforms. Computer usage was time spent on anydesktop device to access any available informationsuch as doctor’s orders from the existing computer-ized order entry system. The last category, lookingfor, was the time spent searching for supplies, charts,and other items needed in delivering patient care.

Discussion

As nurse executives consider adopting bar code/eMAR systems, it is very important for organiza-tions to know how nurses spend their time so thatnew systems support nurses’ workflow and maxi-mize the time spent at the bedside with patients.These findings indicate that nurses spend about25% of their time on medication administrationand roughly 25% on communication, emphasizingthe importance of these 2 processes. It was alsoimportant to note that the activity of medicationadministration occurs throughout the day and inequal proportions on different types of units.

Our research expands upon previous workscited in this article3-8 that examined nursing work-flow by including specific details on the processesand tasks associated with medication administra-tion. Because such a large portion of nursing timeis spent on medication administration, and becausemedication administration is such a high-risk ac-tivity, advances in technology should be aimed atexamining opportunities to streamline this processand increase work efficiency.

Our study identified several potential ineffi-ciencies, such as time spent traveling within theunit and time spent on transcription to a paper-based medication administration record (MAR).Careful assessment of workflow design can serve asa guide in the development of software function-ality aimed at eliminating practice inefficiencies.Items for consideration to improve these inefficien-cies should include adequate hardware for clini-cians to access the eMAR along with the ability tosign on quickly to ensure that time spent lookingfor the paper MAR is not substituted by lookingfor an electronic device to access and log on. Func-tionality that saves information so that a clinician’swork will not be lost if he or she is interrupted totend to patient care is also another opportunity toimprove efficiency.

Direct access to drug information, hospitalpolicies, and procedures concerning medication ad-ministration and access to patient clinical results areadditional features that would help with the effi-ciency of an eMAR. Finally, an eMAR eliminates theneed for transcription altogether, reducing time spentmaking sense of illegible handwriting and having togo back to the original order.

Time spent obtaining medications from the ap-propriate storage areas also presents another oppor-tunity for improvement when designing a new system.Because multiple sites are used for drug storage, anelectronic display on the MAR identifying where thedrug is located should reduce inefficiencies associatedwith searching and minimize unnecessary telephonecalls to the pharmacists. Two other features of aneMAR that would help efficiency are (1) a bidirec-tional link to the pharmacy system so that communi-cation between the nurse and pharmacists occurs inreal time, such as electronic requests for medicationsthat are out of stock on the unit; and (2) the ability forthe pharmacy to automatically prioritize the approvaland delivery of medications based on the medicationadministration schedule set by the nurse.

This study has a number of limitations. It wasperformed in only 1 institution, so the results may notbe representative of other tertiary care or communityhospitals. There may have been potential observererrors during the recording of the observations,particularly in instances of multitasking, such as theexample of the nurse observing the patient take anoral drug while talking with the family. Even withcareful observer training and piloting of the instru-ment, there remained the possibility for variationin how activities were categorized. Medications areoften given in a continuous fashion in the ICU setting,and the time-motion instrument may not adequatelyaccount for nurse time when medications are con-tinuously infused.

The importance of nursing critical thinking skillsand an emphasis on the 5Rs (right patient, right drug,right dose, right route, right time) cannot be over-emphasized with the introduction of technologiesdesigned to improve systems and promote patientsafety. Hospital systems need to support nursingpractice. Technology that promotes the 5 rights ofsafe medication administration not only supportspatient safety but also allows the nurse to focus onthe professional component of medication adminis-tration, such as ongoing assessment and monitoring.In conclusion, our study expanded upon the scarcityof data quantifying the amount of time that nursesspend on medication-related activities and commu-nication. Because we found that activities aroundmedication administration accounted for the single



largest amount of nursing time, it is critical tostreamline this process. In addition, communicationand direct physical care of patients were the 2 othermajor primary activities where nurses spend their

time. It is imperative that as new technologiesemerge, their adoption into practice must supportthe workflow of nurses and enhance and not limittheir ability to provide direct patient care.

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