Workflow modeling in critical care: Piecing together your own puzzle

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Journal of Biomedical Informatics 40 (2007) 81–92

Workflow modeling in critical care: Piecing together your own puzzle

Sameer Malhotra a,*, Desmond Jordan a,b, Edward Shortliffe a, Vimla L. Patel a

a Laboratory of Decision Making and Cognition, Department of Biomedical Informatics, Columbia University, 622 West 168th Street,

VC-5, New York, NY 10032-372, USAb Department of Anesthesiology, Columbia University Medical Center, USA

Received 20 July 2005Available online 9 June 2006

Abstract

The intensive care unit (ICU) is an instance of a very dynamic health care setting where critically ill patients are being managed. Toprovide good care, an extensive and coordinated communication amongst the role players, use of numerous information systems andoperation of devices for monitoring and treatment purposes are required. The purpose of this research is to study error evolutionand management within this environment. The focus is on representing the workflow of critical care environment, which emphasizesthe importance such a representation may play in strategizing the management of medical errors. We used ethnographic observationand interview data to build individual pieces of the workflow, dependent on the individual and the activity concerned. Key personnelwere intensively followed during their respective patient care activities and the related actions. All interactions were recorded for analysis.These clinicians and nurses were interviewed to complement the observation data and to delineate their individual workflows. These piec-es of the ICU workflow were used to develop a generalize-able cognitive model to represent the intricate workflow applicable to otherhealth care settings. The proposed model can be used to identify and characterize medical errors and for error prediction in practice.� 2006 Elsevier Inc. All rights reserved.

Keywords: Medical errors; Critical care workflow; Error prediction; Decision making models

1. Introduction

The paper describes an approach for representing theworkflow of critical care environments and emphasizesthe importance such a representation may play in strategiz-ing the management of medical errors. The Institute ofMedicine’s Nov 1999 report on medical errors was notthe first study on this topic but it had an especially vividinfluence on the problem’s public visibility and suggestedthat medical errors were the eighth leading cause of deathin the US [1]. One study has estimated that—for just 18specific categories of injury—medical errors extend hospi-tal stays by a combined 2.4 millions days per year, addingup to $9.3 billion in hospital charges, and are responsiblefor 32,500 patient deaths per year [2,3]. In addition to thechorus of evidence in the literature illustrating problems

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doi:10.1016/j.jbi.2006.06.002

* Corresponding author. Fax: +1 212 305 3302.E-mail address: [email protected] (S. Malhotra).

with quality in health care, work is being undertaken totackle those problems and authorities have issued recom-mendations aimed at curbing errors. Recommendationsinclude use of information technology and improve under-standing of the complex workflow and practice of healthcare [4]. Pursuing the workflow part of the recommenda-tion, we believe that a visual representation of clinicalworkflow can aid in its better understanding. Although,an attempt to represent visually the workflow of a complexwork environment such as that of a critical care setting islike working on a jigsaw puzzle with no picture to guideyou. The same pieces (clinicians/tasks/devices/policies/ITsystems) may be used to build more than one final picture,the resulting composite serving as a piece for the still biggerpicture.

The question we are trying to answer is how to modelworkflows in complex environments? Workflow analysisand representation is a complex task, as the number ofinter-acting entities to deal with at any given time is huge.Deciding the level of granularity needed for analyzing work

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82 S. Malhotra et al. / Journal of Biomedical Informatics 40 (2007) 81–92

flow and participant behavior is what makes the task ofrepresentation even more difficult. Using cognitive scienceprinciples and methodologies such as cognitive Task Anal-

ysis and cognitive Walkthroughs we can assess humanbehavior, including their interactions with one anotherand with devices, in the utmost detail [5,6]. A detailed levelof analysis is not always required, however, and may in factmake it tedious to understand the workflow of a setting inwhich there are numerous and varied individuals as well asobjects.

Clinical workflow representation requires multiple levelsof depiction. These levels of representation need to beinterrelated and intuitive in design for optimum utilizationby people of different profiles related to the clinical setting.For example medical error analysis of a single event willrequire a detailed analysis of local factors surroundingthe error by an investigator; on the other hand such kindof detailed representation would prove to be detrimentaland unnecessarily complicated for use by an administratorwho needs to see a more global picture for system wideintervention planning. An analogy to the situation wouldbe planning a road trip. Using familiar online mappingresources, one can select a range of magnification levelsstarting from street level up to country level. If a personwere to travel in a large city from one end to the other, astate level map would be useless to him as it fails to givethe level of detail he needs. On the other hand, a detailedstreet level map may make the reading tedious since hemight feel that a city map showing only the major intersec-tions and streets would have sufficed. The key for goodanalysis is to be able to calibrate the view so that we areable to see, what we need to see.

In this paper we develop a generic model, derived usinga cognitive perspective, for representing the workflow in acritical care setting. The objective is to delineate the work-flow, role players, devices, protocols, and communicationsso that we can identify and focus on areas where cognitiveaids, technology or interventions may be of assistance.Understanding the workflow will allow smooth incorpora-tion of interventions that promote patient safety andcounter medical errors.

2. Theoretical background

In organizational settings there are two main approach-es to fixing a problem; the first one is the patch and moveoption where an error on discovery is prevented in thefuture by instituting a policy change or taking related mea-sures. The advantage of this approach is that it can possi-bly be quickly achieved and generally, it does not requireextensive effort or input for implementation. It is best usedfor dealing with errors on a one to one basis, i.e. an errorprops up; a solution is designed to prevent it from occur-ring again. The down side is that it works only in selectivesituations, it may not necessarily be based on evidentialresearch and may not be generalizable to other situations.An example would be a policy change mandating two co-

signers instead of one for blood transfusion orders where,in the past, transfusion errors (the right blood to the wrongpatient) were made when a single person signed for bloodproducts.

The second approach is more of a ‘System’ approachwhere the system encompasses all the policies, activitiesand entities belonging to the setting. This approach relieson understanding how the setting in question operatesand how the users, devices and IT systems interrelate toeach other while operating under the organizations poli-cies [7]. It also may involve researching the nature oferrors, starting from the cognitive mechanisms operatingin the user’s minds prior to, during the evolution of andthe completion of the error. The outcome of this researchis usually not a single solution but a conglomeration offacts which highlights system latencies and flaws, andgives insight on projected problems as well as providessolutions to current problems. An example of this kindof pro-active approach would be the installation and cus-tomization of a clinical information system after research-ing the study site for need and estimation of possiblebenefits from such interventions.

Cognitive science methods and theories illuminate dif-ferent facets of human behavior that govern actions anduse of information and thus it plays an important role inconducting research in complex settings like the ICU. Itprovides insight into the nature of cognitive processesinvolved in human–human, human–computer interactionand thereby improve the application of medical informa-tion systems by addressing the knowledge, memory, andstrategies used in a variety of cognitive activities [8].The power of cognition is reflected in the ability to formabstractions—to represent perceptions, experiences, andthoughts in some medium other than that in which theyhave occurred without extraneous or irrelevant informa-tion (Norman, 1993) [9]. The study discussed in thispaper is aimed at modeling the workflow of a clinical set-ting so as to allow strategic error analysis followed byintervention involving policy changes, decision supporttools or IT systems. Increasing the number of informa-tion systems or decision support systems is not theapproach we are looking for. The two most often repeat-ed reasons for dissatisfaction with computer ordering—longer completion time and considerable workflow dis-ruptions—require careful user–system interaction analysisand complex design changes to meet user needs (Meyeret al., 1998) [10]. Another important concept is that ofDistributive Cognition [11]. From the perspective of dis-tributive cognition, clinical workplaces can be viewed ascognitive systems. The cognitive processes do not takeplace in the individual minds of clinicians alone, but ascollaborative team processes in interaction with theirtools: the tools are patient records, documentations, lab-oratory reports, drug lists, medical devices etc., and theirphysical arrangement in space. Thus, ethnography, asocial science research method is particularly useful insuch settings:

S. Malhotra et al. / Journal of Biomedical Informatics 40 (2007) 81–92 83

‘‘When used as a method, ethnography typically refers to

fieldwork (alternatively, participant-observation) con-

ducted by a single investigator who ‘lives with and lives

like’ those who are studied, usually for a year or

more.’’—John Van Maanen, 1996 [12].

It relies heavily on up-close, personal experience andpossible participation, not just observation, by research-ers trained in the art of ethnography. These ethnogra-phers often work in multidisciplinary teams. Theethnographic focal point may include intensive languageand culture learning, intensive study of a single field ordomain, and a blend of historical, observational, andinterview methods [13,14]. Typical ethnographic researchemploys three kinds of data collection: interviews, obser-vation, and documents. This in turn produces three kindsof data: quotations, descriptions, and excerpts of docu-ments, resulting in one product: a narrative description.This narrative description is used to create the proposedworkflow model.

Before going into clinical workflow modeling it seemsprudent to have a look at a model of cognitive engineering.Norman’s (1986) seven stage model of action (Fig. 1) is onesuch model that illustrates a cyclical pattern of interactionwith a system [15]. The action cycle begins with a goal andfollows intention, action specification, execution, percep-tion, interpretation and evaluation phases which partlyexist in the mind of the user (cognitive) and partly as phys-ical activities. The beauty of the model lies in the fact that itis of a very abstract nature, independent of any system andcan be applied in different domains of human function.

Workflow modeling is basically the process of simplify-ing reality. The modeling is based on facts gathered dur-ing observations and we need to accept that this

Fig. 1. Norman’s seven stage model.

representation can never be perfect. Expectations from amodel should be limited to the intentions with which itis designed for, be it problem solving or understandingof system intricacies. There exists a myriad of literatureon such models which describe workflows in both busi-ness as well as clinical settings [16–20]. Each of themhas been developed such that they contain features uniqueto the native environment/clinical setting to which theauthor/researcher belongs and has his/her own uniquemodeling approach and technique. Some studies focusmore on specific operational aspects without the need ofdescribing the overall workflow in detail; e.g. Renardet al. [21] discussed how task allocation in the ICU settingcan have an impact on overall efficiency and impact onhealthcare delivery. All these techniques and generatedmodels are designed to meet the goals of the concernedstudy and are inspirational but rarely directly usable orapplicable to future studies planned in similar domainsbut with different objectives. This may not be construedas a disadvantage but a universal/generic workflow modelwould provide an element of standardization and allowreuse in future research in varied healthcare settings. Inthe real world this may not seem possible consideringthe intricacies and uniqueness of different health caresettings.

This being said, it is somewhat ironic to state thatthe workflow model we present in this paper is aimedat being generic to critical care settings. This is wherewe take inspiration from Norman’s 7 stage model. Nor-man’s model allows a very detailed analysis of a simpletasks/procedures but fails to model higher level work-flows (analogy of the map showing main intersectionsand not the detailed street level). This fact will be moreevident in the study design section where on obtaininga clinical workflow model we proceed to a consolida-tion stage where key features (of generic nature) areconsolidated and extracted to derive a cognitive work-flow model which similar to Norman’s model will havewide range applicability (although specific for health-care) at the workflow level rather than individual tasklevel.

3. Methods

Ethnographic observation and semi-structured inter-views were used for the study.

3.1. Ethnographic observations

Study site: Cardiothoracic ICU of a tertiary care hos-pital: Columbia University Medical Center. In the ICUthe patient cubicles are arranged around the central nurs-ing station which is equipped with telecommunicationresources, information systems, telemetry monitors etc.The available IT systems serve different dedicated func-tions but also provide some redundancy in terms ofavailable content. IT systems are also available in each


patient cubicle for nursing documentation purposes.Apart from electronic records each patient has a paperchart as well.

Participants: ICU Staff. The ICU is a 16 bed unit with66 staff nurses, 1 attending physician, one clinical fellow,four residents and one physicians assistant.

Ethnographic observations were carried out in twophases: during the first phase a researcher (SM) who isalso a physician followed and unobtrusively observedthe activities going on at different times and locationswithin the ICU and took notes of the same. During thisphase different clinical team members were followed forperiods ranging from two to six hours at various timesduring the day: starting at morning sign-outs, morningrounds, afternoon patient care activities, evening rounds,post operative procedures and transfers etc. The purposewas to identify and delineate these activities in order toguide and improve efficiency of data collection in the nextphase (discussed in more detail in the next section of thepaper). The second phase which is similar to the previousone except that the times and locations are guided fromthe data from the previous and the notes are supplement-ed by audio recordings of the role players while they carryout their work. Consent from the role players and IRBapproval was obtained together with certificate of confi-dentiality. At the end of each observation key conceptsand observations were extracted from the notes and tran-scribed audio recordings. In this way, analysis and obser-vation were interwoven in keeping with the principles ofgrounded theory as defined by Corbin and Strauss so asto ensure that theory development was grounded in thedata; i.e. emergent in nature [20].

3.2. Semi-structured interviews

Participants: ICU attending physicians, residents, nurses(three each), a total of nine subjects.

The concepts found during the first ethnographic phasewere used to design a semi-structured interview. Three ICUattending physicians, three nurses and three residents wereconsidered representative of the ICU task force and wereselected for the semi structured interview. These were con-sidered to be representative of the professional groupsactively involved during the patient care process. The inter-view questions are given in Appendix A. The responseswere recorded and transcribed at a later time. The tran-scripts were then coded and the key concepts for each ofthe interviews were extracted and combined to obtain aworkflow model.

4. Study design

Conforming to the study environment, the study designis somewhat complex. As mentioned before the methodol-ogy is of an emergent nature and the data collection andanalysis is primarily distributed in to the following threestages.

4.1. Stage 1

Preliminary observation and identification of criticalzones (CZ). During the initial ethnographic observationperiod we attempted to delineate situations/events and timeperiods of the ICU workflow. Observations made duringthese periods were also used to model the questionnairemeant for interviewing the key personal. These were calledcritical zones (CZs). The purpose was to improve the effi-ciency of ethnographic data collection by focusing downon these periods and to segregate key activities of thepatient care process. Second, we were able to provide labelsto identify or qualify an error or significant event.

Fig. 2 gives the schematic layout of the CTICU whichhas the nursing station along with the information systemsin the center and is surrounded by the patient cubicles. Thedifferent activities of the clinical team are also depicted.These activities are clubbed into seven critical zones. TheseCZs are of a generic nature which allows them to be appli-cable across different healthcare settings to define health-care activities. Table 1 contains the seven CZs, theirdescriptions and examples of activities (most of which aregiven in Fig. 2, the CTICU setting). Broadly summarizingthe contents of the critical zones, each day starts with re-orientation (handoff by outgoing team) of the patient andbed situation and carrying out of the orders determinedon the previous day. This is followed by re-assessmentand formulation of the patient management plan. Theactivities determined by the management plan are subse-quently carried out for the remainder of the day along withwork pertaining to the transfer or admission of patients tothe ICU. Reassessment of new admissions and a prelimin-ary determination of the next days admission/transfer planis made sometime in the evening. Finally, informationrelated to the management and care of patients is handedover to the incoming night team which continues the man-agement overnight. Information regarding overnightchanges or events gets exchanged once again in the morn-ing the next day when the rest of the medical team returns,and the cycle repeats itself.

4.2. Stage 2

Semi-structured interviews and preliminary coding: Thisis the stage where we attempt to paint a picture of the sub-sections of a still larger workflow. Now to define the stateof an activity in the ICU including aspects of cognitive loadwe need the following:

(a) A framework to temporally relate and identify activ-ities: Observations during the first stage and criticalzones contribute to this purpose.

(b) Individual workflows with appropriate qualifiers todescribe actions, interactions, and communication:transcripts from the interview sessions provide mostof this information which is then coded using themat-ic coding. The categories used for coding were not

Table 1Critical zones (CZs) with their descriptions and examples of activities from the CTICU ethnographic study

Critical zone (CZ) Examples of activities Description

Re-orientation andpreliminary planning

Resident change (handoff) Morning sign-out by (night) nurses and residents to their in-comingcounterparts

Nurse change (handoff) Re-orientation to patients condition, assessment of criticality‘‘ICU assessment’’ by attending Preliminary determination of rounding sequence and future

admission/discharge plans

Goal formulation Morning clinical rounds Morning rounds (patient management goals determined)Procedures and patient care activities conducted during rounds.Finalization of admission/discharge plan

Goal execution Post clinical round resident activity Documentation of management plan, orders for patients,charting carried out

Post clinical round nurse activity Patient care activities based on management plan discussed inclinical round are carried outConsults from health personal external to the clinical team are obtained

Transfers Patient transfer from OR to ICU Patients ready for step down care are prepared and transferredTransfer of existing patient inICU to floors (wards)

Transfer summary, continued management plan documented, initiatedand communicated to the clinical unit receiving the patient

Admissions OR to Nurse information transfer Information of patients due to be admitted from the operating room(OR) or emergency department (ED) is received

Receipt of patient by resident Based on the information preparations to received the patient are madePatient handover and determination of preliminary management(or continuation of the management as communicated by the personalhanding over the patient)

Re-assessment Evening clinical round New admissions are assessed and initial management determinedNext days step down/transfer/discharge plan for existing patients discussed

Evening sign-out Resident change (handoff) Information of patients handed off to the incoming night team(residents and nurses)

Nurse change (handoff) Overnight patient care activities carried out based on the information providedDocumentation of overnight activities and preparation for morningsign-out (handoff to incoming team) are made

Fig. 2. Schematic layout of the CTICU and key activities during which observations were conducted. Patient cubicles surround the Nursing station wheremost of the clinical information systems lie. The letters on the human representations signify the following: A, attending physician; R, resident; F, clinicalfellow; PA, physicians assistant; N, nurse.



predefined, but emerged during the course of analy-sis. This was in keeping with the theoretical frame-work of the grounded theory approach of dataanalysis [22].

(c) Situational and environmental qualifiers on whichperformance of an individual will depend (dependen-cies): Once we know the time, the activity and theactions an individual, the third item we need to defineis the situations surrounding these activities sincethese environmental variables can determine howeffectively or efficiently the individual in question willbe able to perform a task. This performance will alsodepend on the inherent qualities and skill of the per-son in question. Information for these factors will beobtained from both the interviews as well as from thecontinued observation phase.

Combining the three aspects mentioned above, weobtain an individual’s workflow during the course of a typ-ical day. Environmental variables, points of interactionwith devices, shared activities and communication withother personal in the ICU form the sticky locations ofthe individual workflow model. Using these sticky pointswe combine each team member’s workflow in order to gen-erate an overall workflow model of the ICU setting.

Fig. 3. Schematic representation of stages 2 and 3 of the analysis. Rectangles inthe individual’s (R, resident; A, attending; N, nurse) day. Activity sharing pairscircles indicate the sticky points where an activity is linked to another part of thcan be linked to and integrated into the main workflow model of the ICU. Theof ‘admitting a patient’, the nurse and resident will be doing certain activities o(rhomboids).

4.3. Stage 3

Integration of individual workflows and consolidationto form the cognitive workflow model: As mentioned inthe last step we use the sticky points of each individual’sworkflow as well as the temporal framework obtained byidentifying the CZs to obtain an overall model of the ICU’sworkflow. Fig. 3 gives a schematic version of these twosteps where individual workflows are being combined toform a much more complicated main workflow model. Thisversion will obviously contain surplus content and infor-mation regarding the ICU operation but its complexityfails the purpose of providing a consolidated and under-standable view of the same.

Therefore, the final stage of the analysis is to consolidateand extract key features to form a cognitive model which ismore generic in nature and allows planned interventionsfor workflow improvement and medical error preventionpurposes.

4.3.1. Knowledge-matter-knowledge cycles

Information exists in two forms; mental and document-ed (matter: electronic medical record or paper notes) form.In the workflow cycles discussed above the key underlyingprocess is transfer of this information, which maybe

the individual workflows represent different activities during the course ofdepict activities that are performed along with another team member. The

e main workflow and thus serves as a point where the individual workflowsRhomboids are shared activities. For example for the main workflow taskf their own (rectangles), while some tasks will be shared or done together

Table 2Coding scheme used to define individual workflows

Codes Purpose of code

Activity defining codesTIME Time of the day of the activity concernedCIZ The critical zone to which the activity

belongsPrimary subject

and activityThe key person whose workflow is beingfollowed (the interviewee)

Shared activity/communication person

Communication with other person

Knowledge transfer codesKnowledge transfer To define whether the process involved

knowledge acquisition/transfer/or documentation

Paper documentationa Documentation of informationInformation system usea IT system used and purpose of use

Problem/error codesTask problema To define any problems involved with

the concerned activityError typea Type of errorOther error qualifiersa Further specifications to define the error

a These codes were not used in the development of this paper.


complete, lossy,1 skewed, misinterpreted or even non-exis-tent. The knowledge (related to patient conditions) thatexists in the healthcare personnel’s mind undergoes degra-dation with passage of time. This happens with increasedwork and cognitive load on the person, with increasingnumber of people it is passed down in the communicationchain and is directly proportional to the interim periodbetween knowledge acquisition and its documentation.Documentation solidifies the knowledge in time and pro-vides a new starting point for acquiring further new knowl-edge, combining the two and then documenting it all overagain. While coding the interview and observational datato delineate activities and interactions, we introduced theelement of knowledge acquisition/transfer/documentation.Once made part of the workflow model, it will help to visu-alize CZs where knowledge degradation and consequentmedical errors are imminent.

5. Summary of methods

Just to summarize the three stages of our study design:we collected data from two sources, through ethnographicobservation and by interviewing individuals of the clinicalteam being observed. We delineated the workflow in to dif-ferent activities during the day and then clubbed thembased on their criticality or temporal relevance into sevencritical zones. Coding of the interview data and combiningit with the observational data allowed us to build individ-ual daily workflows of the each key person of the clinicalteam. Private (individual) or shared tasks and related com-

1 Scheme of organizing information in a more compact form where someinformation is lost to gain higher levels of compaction.

munication to other team members were all part of this.Using the critical zones as a template, the different work-flows were combined to generate a combined workflowmodel. As a final stage this model was consolidated to forma more generic version and the element of Norman’s modeldefining the cyclical mental and physical activities involvedin task execution was also added.

6. Data analysis

The transcripts of the interviews were broken down intopropositions, each illustrating a specific theme. Each prop-osition was coded using the codes given in Table 2. Propo-sitional analysis and thematic coding was based onmethods used in our past research [23]. These codes areintended to define the activity state of the concerned personin complete totality. Our criterion for completeness includethe activity of the person, the people with whom he is inter-acting, the critical zone during which this activity is takingplace, knowledge acquisition or documentation nature ofthe process, problems or errors related to the activity etc.

Fig. 4 represents the combination of the daily typicalworkflows of three key personnel in the ICU, an attendingdoctor, a nurse and a resident. This was built using codesused for defining the workflow (Table 2) and the CZs (crit-ical zones) defined in stage 1 of the study. Basing the com-bined workflow on the CZs allows us to visualize whichactivities go hand in hand and which set of individualsare interdependent for the concerned work. The threeworkflows described in this diagram progress from criticalzone one through seven as shown in the left most columnwith an arrow along side. Individual workflows progressas the day goes on in the direction of the arrow (fromCZ 1 through CZ 7). Please note that individual workflowsthat were constructed for the clinical fellows, nurse manag-ers and other members of the clinical taskforce are notshown here for the purpose of simplicity. Significant over-lap exists in terms of training, skill and responsibilities ofthe different people involved in clinical care which is whyan attending, nurse and resident were chosen to be repre-sentative from a task and hierarchical perspective. Thesethree have therefore been used for discussion and workflowmodeling purpose in the rest of the paper.

Enclosure 1 shows one such workflow (of the attendingphysician). Each individual’s workflow has activities whichare either carried out by the individual alone (shown inwhite boxes) or are carried out as a collaborative effortwith another team member (indicated by shaded boxes).The symbols KA, KT, KD, and A are qualifiers for theseactivity boxes to indicate whether the task was a knowledgeacquisition, transfer, documentation or pure action task,respectively. Enclosure 2 encircles those activities underthe residents column which may span across multipleCZs and can potentially overload the resident both cogni-tively and physically, depending on the prevailing circum-stances. The following are some points that can be drawnfrom the analysis of this combined workflow model:

Fig. 4. Stage 2: Integrating individual pieces of the workflow (see text for description).


• Activities overlap critical zones. The CZ with the maxi-mum overlapping activities is generally the one with themaximum number of people interacting and communi-cation flowing. Medical errors are more likely to occurin these zones.

• Following the lines of Norman’s seven stage model, eachactivity has an action, evaluation and interpretationsequence. In medicine, each action requires a baseknowledge for execution. This knowledge comes fromthe documented notes or is communicated by the personwho has previously enacted an action–evaluation–inter-pretation sequence. If such information gets incorrectlydocumented in the previous step, the following actioncycles may be disrupted and a medical error may ensue.

• Highlighting the first point regarding activities overlap-ping multiple critical zones, we observe that the activi-ties expected from a resident particularly crowd in thezones two through five. Zone 2 (Goal formulation) is acritical step in the whole patient care process. Duringthis step, a management plan is developed by the attend-ing physician, which is based on the patient assessmentand the information provided by resident and documen-tations from Lab and imaging systems. Depending onhow skillfully the attending physician orchestrates theclinical round and coordinates the inflow (new admis-sions) and outflow (transfers/step down care) of thepatients, the concentration and stress level on the resi-dents may accordingly vary. In the worse case scenarioa resident may be performing knowledge acquisition

and documentation related to the management goalsas well as conducting procedures and transfers or com-municating orders for the same to the nurses, all in closeintervals to each other. Increased patient load is an enti-ty which directly may affect performance on all tasks byany of the role players. Enclosure 2 indicates this CZoverlap and multitasking. The resultant cognitive over-load may translate into medical errors in any of thetasks which may not be evident at the moment butmay cause a chain of events or be of consequence at alater stage. The multitasking we are referring to here isbasically the execution of multiple tasks in an interrupt-ed fashion such that a task gets initiated before the pre-vious one was concluded. For example a residentmoving on to a procedure on another patient beforehe has finished documenting his assessments on the cur-rent one, may miss out or wrongly enter importantassessments when he returns to the patient because ofan interruption in the flow of thoughts or due to theinherent limitation of short term memory [24,25]. Thewrongly documented fact may propagate to an erroras discussed in the previous point.

• The crowding of activities and their overlap in to neigh-boring critical zones is not entirely dependent on thecoordination skills and performance of the staff. Factorsthat are not under the control of the clinical team suchas scheduling of patients in the OR, availability of bedson the floors (step down care in clinical wards), critical-ity of ICU patients and non-routine events (NREs) [16]


may all contribute to cognitive overload and is part ofthe ‘distributed’ workflow of the clinical team members.NRE is defined as any event that is perceived by careproviders or skilled observers to be unusual, out-of-the-ordinary, or atypical and contribute to inefficiencyor possibility of errors. Difficulties finding anesthesiaor medical supplies, providers bumping into or trippingover IV poles are considered good examples of theseevents.

7. Building the cognitive workflow model

The building blocks for the workflow model are: the keypersonnel, their activities and the critical zones of opera-tion. The representation of an individual draws inspirationfrom data processing systems and Norman’s model defin-ing mental and system activities required for task comple-tion. The clinical team members are similar to dataprocessing systems where given a set of inputs they processthe information to perform actions (the output). The inputis basically the knowledge acquisition (KA) process, thesource being: documents and information systems (paperor electronic), communication from other clinical teammembers and active assessments of patient condition. InFig. 5 we see the depiction of the knowledge acquisition(KA), knowledge transfer (KT), the mental workings,and related dependencies of a clinical personnel. Theattending has been used as an example in this Fig. 5; a sim-

Fig. 5. The internal workings of the attending that take place in order to accepThe dependant factors (dependencies) for perception of the arriving informatdepiction would apply for any other member (resident/nurse) in the clinical woKA: Knowledge acquisition marks the information input for the individual an

ilar representation would apply for fellows, nurses or resi-dents. The dependencies affecting each of their workingswould however be different. This representation of the indi-vidual (Clinical personnel) is used in the cognitive work-flow model, developed and illustrated in Fig. 6.

Fig. 5 details the processes in the minds of the clinicalpersonnel from a mechanistic point of view. For this repre-sentation, we draw on three basic elements from Norman’smodel: the first containing the elements of perception,interpretation, and evaluation; the second specifying theintention, action specification, and execution modalities;the third is the connecting segment where the processingis represented along with the dependencies which will deter-mine the outcomes of the first two parts. Knowing thedependencies of both the perception (KA) and the informa-tion processing segments, this can be important in deter-mining what kind of errors may occur in the presence ofa faltering dependency. By plugging-in the representationsof the key individual into the workflow model, we areattempting to predict medical errors with relation to thecritical zones. These are based on the knowledge of thesedependencies.

The consolidated version of the cognitive workflowmodel is illustrated in Fig. 6. The green boxes are the crit-ical zones that we developed in stage 1 of the study and theblue boxes adjacent to them are the activities occurringduring those CZs. The CZs are clubbed into three groupsdenoted by differing background colors (yellow, blue, andgrey) to show that significant overlap in the zone activities

t, interpret, process, and act upon the information arriving from a source.ion as well as the processing of the information is also depicted. Similarrkflow; although the dependencies for the concerned individual may differ.d KT: knowledge transfer and ACT: actions show the processed outputs.

Fig. 6. The cognitive workflow model for inpatient care. The workflow flows in an anti-clockwise fashion. Although this being a continuous cycle with nostart or finish, the symbol of the sun (morning) can be used as the starting point. Please note the three levels of abstraction (see text for details): (a) thecomplete workflow model as top level, (b) the grouped CZs shown with different background colors—1 through 3, (c) the individual critical zones—1through 7. The 4th level is the individual level which was shown in Fig. 5 with the attending as an example. (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of this paper.)


may occur, i.e. certain activities of different CZs in thegroup can occur at the same time. Knowledge exchangeis denoted by connecting lines.

8. Interpretation of the model

Instead of attempting to absorb the model as a whole,we need to narrow down to the level of abstraction werequire. There are four levels of abstraction: (1) the com-plete model as the top level. (2) The three different back-ground colors (yellow, blue, and grey, i.e. grouping ofCZs) form the next level where we can observe activitiesand parts of the workflow that may be carried out or/and take place at the same time. This view can provideleads to where and when medical errors are likely to occurif an individual is multitasking between different CZs and iscognitively overloaded. (3) The third level of abstractionnarrows down to the individual critical zones. Here, wecan observe the interplay of the different members of thehealthcare team and follow the information flow chain.(4) The final level is that of an individual member of theclinical team. It allows us to focus on his/her incumbentdependencies (from Fig. 5) and outcomes related to knowl-edge acquisition–processing–execution–communication.Depending upon his position in the model, we may predict

which part of the workflow may breakdown because of afaltering dependency. As mentioned previously this modelutilizes the attending, nurse and resident for representingthe clinical task force. Other members such as clinical fel-lows have not been included (although were part of datacollection) because of significant overlap in their role; theymay operate partly as an attending or for some tasks sim-ilar to a resident. Other personnel such as nurse manager’sfollow suit. The purpose of the model is to simplify work-flow depiction which is why by using the attending, resi-dent, nurse hierarchical setup we steered away from using‘new’ qualifying titles apt for their roles or by includingall actual members involved in clinical care. The model’scognitive foundation allows the discussion and incorpora-tion of cognitive science facets to any planned workflowresearch if used as a standard template with appropriatemodifications.

9. Discussion

Two main features of picture puzzles are that (1) theycan be broken down into individual pieces with each jigsawpiece having almost unique edges which link it to otherpieces, thus defining its place in the picture, and (2) somepieces can be combined to form a sub-section of the picture


that is sensible and informative. To summarize ourapproach in this paper our research involved working onsomething quite similar to the picture puzzle, where wedivided the whole workflow into individual activities, thentried segregating these activities into temporal events(times) and locations based on their critical importance,and then combined and built individual workflows in thesecritical zones. Finally, we viewed the relationships of thecritical zones to one another based on the elements thatcomposed it and all this contributed to forming the com-plete workflow picture of the critical care setting.

The proposed consolidated cognitive workflow model isgeneric in nature but its application in different clinicaldomains may require some adjustments or reconfigurations.For most settings the only modification required may be theremoval of a critical zone or two, while other workflowsmight even contain additional zones of importance. Similar-ly additional members or activities can be made part of themodel when deemed appropriate for the clinical workflowproblem that is being studied or monitored. The environ-mental and situational factors (external dependencies) uponwhich an individual’s performance depends may also differ.For a given situation, knowledge of these dependencies caninform us about the nature of the individual’s performance.Following the chain of events we could possibly predictwhich of his/her activities are likely to suffer (communica-tion, documentation or action, etc) in those circumstances.The model aids in pattern recognition; if a certain situationor medical error is recognized in one segment of the model,similar circumstances can be identified at other locationswithin the workflow allowing early intervention and height-ened caution. For example if an error was documented on aprevious occasion where an intern was admitting three newpatients after midnight, an onsite pharmacist is unavailableand he/she is cross covering on two critical patients; thenusing the model we can map his activities such that if a similarsituation arises again we can consequently predict which partof the workflow may breakdown and spawn a medical error.An error in those weak links can be prevented by providingadditional support (e.g. policy/staff changes; alerts to super-vising residents/fellows).

Our continued research lies in the area of developing ataxonomy and identifying root causes of medical errors.Combining it with this cognitive workflow model we hopeto contribute to error prediction and prevention (or man-agement) in medicine. Future course of the study aims atcarrying out a detailed qualitative analysis in the ICUdomain followed by its evaluation and application in otherclinical settings. Decision support tools, alerts or caution-ary advice can then be developed and dispensed in specificareas which are prone to medical errors.

Acknowledgments

Support for this research was provided by Grant R01LM07894 from NLM to Vimla Patel. We express our grat-itude to the subjects from the ICU for taking time to be

available for our research. We also thank Jiajie Zhangfor his advice on the cognitive model.

Appendix A. Interview questions

General:

1. Describe a typical day in the ICU? Your activities, inter-actions with other people, information systems anddevices?

2. Are there any problems in the current workflow of theICU?

3. Is there any thing that can be done to improve the prob-lems you mentioned?

4. Is any aspect of the workflow impeded by ‘less number’of individuals or ‘less time’?

5. Which information is most frequently used by you andfor what purpose?

6. Which Clinical Information do you prefer to use andwhy?

IT system, documentation and communication specificquestions:

1. Do you think that certain events or times during thepatient care process are associated with medical errorsor potential errors as against other times?

2. Is there any problem with multiple information systems?If yes, any suggestions for improvement? Integration?Removal?

3. In paper documentation of patients file do you considerany information sheets unnecessary that simply add tothe bulk?

4. What aspects of the patient file (lab values, dischargesummary. . . etc?) need to be frequently accessed? Whichones are hardly ever seen?

5. How would you like to receive/give orders regardingpatient management keeping in mind efficiency and cer-tainty of communication:a. Written orders, always except in emergenciesb. Written orders, always
c. Written orders, with post-activity mandatory double
checkingd. Verbal Orders with post-activity co-signing
e. Verbal Orders with mandatory double checking f. Verbal Orders (with instant Digital voice record doc-
umentation)g. Other

References

[1] Institute of medicine. To Err is human: building a safer health system.Washington, DC: National Academy Press; 1999. Publication.

[2] Zhan C, Miller MR. Excess length of stay, charges, and mortalityattributable to medical injuries during hospitalization. JAMA2003;290:1868–74.


[3] Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug eventsin hospitalized patients. JAMA 1997;277(4):307–11.

[4] Bates DW, Cohen M, Leape LL, Overhage JM, Shabot MM,Sheridan T. Reducing the frequency of errors in medicine usinginformation technology. J Am Med Inform Assoc 2001;8(4):299–308.

[5] Kushniruk AW, Patel VL. Cognitive and usability engineeringapproaches to the evaluation of clinical information systems. JBiomed Inform 2004;37(1):56–76.

[6] Patel VL, Arocha JF, Kaufman DR. A primer on aspects ofcognition for medical informatics. J Am Med Inform Assoc2001;8:324–43.

[7] Zhang J, Patel VL, Johnson TR, Shortliffe EH. A cognitive taxonomyof medical errors. J Biomed Inform 2004;37(3):193–204.

[8] Patel VL, Kaufman DR. Cognitive science and biomedical infor-matics. In: Shortliffe EH, Cimino JJ, editors. Biomedical informatics:computer applications in health care and biomedicine. NewYork: Springer; 2004.

[9] Norman DA. Things that make us smart: defending human attributesin the age of the machine. Reading, MA: Addison-Wesley; 1993.

[10] Meyer KE, Altamore R, Chapko M, Miner M, McGann M, Hill E,et al. The need for a thoughtful deployment strategy: evaluatingclinicians’ perceptions of critical deployment issues. Medinfo1998;9(Pt. 2):854–8.

[11] Patel VL, Arocha JF. The nature of constraints on collaborativedecision making in health care settings. In: Salas E, Klein G, editors.Linking expertise and naturalistic decision making. Mahawah,NJ: Erlbaum; 2000. p. 83–485.

[12] Van Maanen J. Ethnography. In: Kuper A, Kuper J, editors. Thesocial science encyclopedia. 2nd ed. London: Routledge; 1996. p.263–5.

[13] Ethnography and health care. (Education and Debate) BritishMedical Journal, Dec 2, 2000, by Jan Savage.

[14] Hammersley M. Reading ethnographic research: a criticalguide. London: Longman; 1990.

[15] Norman DA. Cognitive engineering. In: Norman DA, DraperSW, editors. User centered system design: new perspectives onhuman-computer interaction. Hillsdale, NJ: Lawrence Erlbaum;1986. p. 31–61.

[16] Weinger MB, Slagle J. Human factors research in anesthesia patientsafety: techniques to elucidate factors affecting clinical task perfor-mance and decision making. J Am Med Inform Assoc 2002;9(Nov–Dec Suppl):S58–63. doi:10.1197/jamia.M1229.

[17] Graeber S. The impact of workflow management systems on thedesign of hospital information systems. AMIA 2001 symposiumproceedings.

[18] Hersh WR. Medical informatics: improving health care throughinformation. JAMA 2002;288:1955–8.

[19] Muehlen MZ. Organizational management in workflow applica-tions—issues and perspectives. ITM Journal Kluwer AcademicPublishers 2004;5(3):271–91.

[20] Dazzi1 L, Fassino C, Saracco1 R, Quaglini S, Stefanelli M. A patientworkflow management system built on guidelines. AMIA 1997symposium.

[21] Renard JM, Bricon-Souf N, Guigue L, Beuscart R. A modelization ofthe task allocation problem for prescribing activity in an ICU. ProcAMIA Symp, 2000.

[22] Corbin, Juliet, Anselm Strauss. Grounded theory research: proce-dures, canons, and evaluative criteria. Qual Sociol 1990;13(1):3–21.

[23] Malhotra S, Laxmisan A, Keselman A, Zhang J, Patel VL. Designingthe design phase of critical care devices: a cognitive approach. JBiomed Inform 2005;38(1):34–50.

[24] Chisholm CD, Collison EK, Nelson DR, Cordell WH. Emergencydepartment workplace interruptions: are emergency physicians ‘‘in-terrupt-driven’’ and ‘‘multitasking’’? Acad Emerg Med2000;7(11):1239–43.

[25] Coiera EW, Jayasuriya RA, Hardy J, Bannan A, Thorpe ME.Communication loads on clinical staff in the emergency department.Med J Aust 2002;176(9):415–8.

http://dx.doi.org/10.1197/jamia.M1229

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Workflow modeling in critical care: Piecing together your own puzzle