CognitiveTask_032513comp Methods to Improve Patient-Centered Medical Home Models by Understanding...

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cAgency for Healthcare Research and Quality

Advancing Excellence in Health Care www.ahrq.gov

Prevention & Chronic Care ProgramI M P R O V I N G P R I M A R Y C A R E

Cognitive TaskAnalysis:

Methods to Improve Patient-CenteredMedical Home Models by

Understanding and Leveraging its

Knowledge Work

PCMH Research Methods Series


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Cognitive Task Analysis: Methods to Improve Patient-CenteredMedical Home Models by Understanding and Leveraging itsKnowledge Work

Tis brie ocuses on using cognitive task analysis (CA) to evaluate patient-centered medical home

(PCMH) models. It is part o a series commissioned by the Agency or Healthcare Research and

Quality (AHRQ) and developed by Mathematica Policy Research under contract, with input rom

other nationally recognized thought leaders in research methods and PCMH models. Te series is

designed to expand the toolbox o methods used to evaluate and rene PCMH models. Te PCMH

is a primary care approach that aims to improve quality, cost, and patient and provider experience.

PCMH models emphasize patient-centered, comprehensive, coordinated, accessible care, and a

systematic ocus on quality and saety.

I. Cognitive Task AnalysisCognitive task analysis is a amily o methods designed to reveal the thinking involved in perorming

tasks in real-world contexts and is especially well suited to understanding and helping improve several

aspects o PCMH models. CA methods can be used to uncover and describe the key patterns,

variations, opportunities or improvement, and leverage points in the knowledge worknot just the

physical worko primary care sta and clinicians. Its results can then be used to help individuals and

teams maximize the eectiveness o their implementation process by showing them where and how to

ocus their eorts. Moreover, many CA methods were designed to understand how high perormers

(that is, experts) unction, and thus identiy contextually grounded best practices. Tese best practices

can be used to inorm and improve the training o individuals and teams in new roles such as care

management, new clinical routines, and the meaningul use o technology.

CA methods help us understand and improve peoples perormance on both clinical and

organizational tasks because they identiy the critical cognitive aspects o those tasks that would

otherwise remain hidden. Identiying these cognitive aspects allows or more comprehensive, accurate,

and eective ormative evaluations, implementation planning and troubleshooting, and knowledge

transer (such as training and scaling up best practices). Te cognitive aspects o tasks that are oten

not directly observable are the macrocognitive processes o clinical or organizational tasks that

occur where individual knowledge and cognition interacts with group knowledge and cognition

(Crandall, Klein, and Homan, 2006; Homan and Woods, 2000). Macrocognition is the collection

o cognitive processes that characterize how people think in natural settings (Crandall, Klein, and

Homan, 2006). Tese macrocognitive processes include how individuals, teams, and organizationsmake decisions, make sense o events and experiences (called sensemaking), use and share knowledge,

plan and replan, coordinate, learn, monitor their work, detect problems, manage the unknown, and

adapt to changing conditions. Although these processes are conceptually distinct rom one another,

they interact in all clinical routines and organizational change eorts that require thinking. CA is

useul in studying PCMH models because macrocognitive processes are central to the way the sta in a

PCMH organizes the practice to deliver patient care.


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Although CA is an applied method designed to study macrocognition (that is, cognition in real-

world contexts), it is inormed by laboratory-based research on cognition. It is designed primarily

to study thinking processes and structures, not to evaluate outcomes. Tat said, CA can easily be

combined with outcome-ocused quantitative techniques using mixed methods. CA methods have

been used successully or several decades in a wide range o settings requiring high reliability, suchas military and civil aviation, air trac control, naval ship command, nuclear power plant operation,

and reghting, but have only recently been used in health care (Crandall and Calderwood, 1989;

Dominguez, Hutton, Flach, et al., 1995; Crandall and Grome, 2010). CA comprises a wide

range o qualitative techniques rom disparate disciplines that have been adapted to the study o

macrocognition. In act, many researchers and practitioners do orms o CA without calling it that.

Te advantage o drawing on CA explicitly, however, is that the literature on what has been done in

the past can help researchers more systematically and eectively choose and adapt methods to address

their own research questions.

Regardless o the technique used, CA consists o three main steps: (1) knowledge elicitation, (2)

data analysis, and (3) knowledge representation (Crandall, Klein, and Homan, 2006). Te choice owhich method(s) to use to elicit the knowledge, conduct the analysis, and represent results depends

upon the questions being asked, the context in which they are being asked, and the objectives o the

project. Broadly speaking, CA can be used to better understand the macrocognition in any clinical

or organizational task, how and when it occurs, where it occurs, who is involved, and how technology

and artiacts such as orms, emails, logs, and patient charts are (or can be) involved. Although we will

ocus on describing CA methods that are suited to understanding and improving the typical types

o organizational and clinical routines in a PCMH, additional CA methods do exist should the

reader wish to investigate the macrocognition o uncommon, critical events related to PCMH models

(Crandall, Klein, and Homan, 2006).

II. Uses of Cognitive Task Analysis

In this section, we describe three commonly used CA techniques, give examples, and discuss how

they might benet implementation studies o PCMH transormation projects and dissemination o

successul approaches. All three techniques can be used when conducting on-site research.

Task Diagram

Te goal o constructing a ask Diagram is to capture one or more aspects o macrocognition involved

in a routine task. Building a ask Diagram involves getting a rich, multi-perspective description o

the task by interviewing the range o people involved in it. In the rst pass, the interviewer asks theinterviewee (such as a physician, patient, or other practice sta) to break the task into our to seven

large steps. In subsequent passes, the interviewer uses predened (but open-ended) probes, guided by

psychological and organizational theory, to elicit the macrocognitive processes within and between

those steps. For example, CA analysts might try to uncover: (1) the step(s) in which the most

challenging decisions were made, (2) what made those decisions dicult, (3) what inormation was

needed to make the critical decisions, (4) who needed the inormation, (5) how that inormation was


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obtained and transmitted, (6) what went wrong or ell through the cracks and why, and (7) how the

team detected ailures and problems in the task.

An important eature o these interviews is that respondents are asked to rst identiy a single, recent

instance o the task in which they were involved (such as a specic patients visit this week). Tey are

then asked to keep that instance in mind when answering questions. Once that instance is described,

the interviewer shits the ocus and tries to identiy naturally occurring variations in the task. o do

so, the interviewer asks respondents to identiy other specic cases in which the task deviated rom the

norm, and tries to probe with plausible, hypothetical what i scenarios to reveal how the interviewees

think they would perorm their part o the task and why. Great care is taken to guide the interviewees

away rom general or decontextualized task descriptions. As the interviewer collects dierent

interviewee perspectives on the task, the interviewer begins to develop a more complete and richer

sense o the task and the characteristics o its macrocognitive dynamics. In the end, the ask Diagram

method produces a depiction o the physical work fow with some o its critical macrocognitive

processes uncovered and described. Te result can be shown to members o the organization, who

are oten surprised at how accurate and inormative it is. It can also be used as the basis or processredesign, or to identiy areas warranting deeper investigation using other CA methods.

Examples

Christensen, Fetters, and Green (2005) conducted ask Diagram interviews with experienced

amily physicians to understand the range o ways in which they structured visits, ocusing on when

computerized reminders or preventive and chronic disease management services could be inserted

into the work fow. Te purpose was to understand the cognitivenot physicaldimension o

their work fow well enough that they could introduce computerized reminders while minimizing

the risk o negative consequences, such as distracting rom patients primary concerns or increasing

provider burden and stress. Tey discovered clear patterns in how physicians structured patient visits,

which helped pinpoint stages at which reminders would be helpul, rather than disruptive. Te

ndings allowed the team to design and implement an eective clinical reminder system that avoided

producing reminder atigue (Green, Nease, and Klinkman, 2009), the commonly observed decrease

o response rates to reminders over time as a result o excessive reminders.

As another example, Shachak, Hadas-Dayagi, Ziv, et al. (2009) used ask Diagram interviews and

observations to understand the cognitive aspects o physician electronic medical record (EMR) use.

Tey ocused on the benets, errors, and patient communication problems associated with EMR

use, and the role o physician EMR expertise in overcoming those communication problems. On the

one hand, they ound that physicians elt the EMR helped their decisionmaking, and thus improved

patient care and saety, by making patient inormation more comprehensive, organized, and readable,

and including decision aids and warnings o adverse drug interactions. On the other hand, they

discovered that physicians were susceptible to EMR-specic errors, including making typos, choosing

an option next to the correct one on pull-down menus, and entering data on the wrong patients

chart. Tey also ound that physicians were aware that these errors were occurring, and, in some cases,

routines had been put in place to better catch them (known as problem detection). Finally, they

ound that certain computer skills and spatial organization o oces helped physicians overcome some

EMR-related patient communication barriers.


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PCMH Application

Implementing PCMH unctions in a practice requires improving clinical and organizational routines,

and key aspects o those routines are macrocognitive in nature. Te ask Diagram method ocuses

on revealing the macrocognitive aspects o practices routine work fows, to oer important new

insights into clinical and organizational process redesign. For example, it can be used or the ormative

evaluation o practices change routines. We are currently conducting a study using ask Diagrams

supplemented by eam Knowledge Audits (see below) or, among other things, studying and oering

consultation on improving practices change routines so that the practices can more eectively

implement a health inormation technology (I) system. We ound great variation in how practices

were approaching change implementation, but none had any change or implementation routines

per se. Tey varied widely in their ability to engage in sensemaking, planning, communication,

problem detection, and replanning. Identiying how practices address these macrocognitive unctions

during implementation gave us a more detailed understanding o their change capacity. Tis, in

turn, allowed us to make evidence-based and contextually tailored predictions about the uture

implementation diculties they were likely to ace, and make targeted recommendations, customizedor each practice.

Concept Mapping

Te objective o Concept Mapping is to understand and graphically depict how ideas (that is,

concepts) on a given topic are related. In CA, these ideas reer primarily to belies and values, which

are connected in a network or mental model. Te belies and values in ones mental model o a

topic and the connections between them dene ones understanding o that topic. In CA, Concept

Mapping has traditionally been used to map the mental models o experts on critical tasks. Experts

mental models shape what they are aware o, what they pay attention to, what options and possibilities

they consider, how they make sense o events and experiences, solve problems, make judgments, andultimately make decisions and act. aken together, these account or how well and consistently they

perorm both routine and exceptionally challenging tasks.

Concept Mapping a mental model involves choosing a topic, eliciting an individuals belies and values

about that topic, identiying how those belies and values are related, and then graphically depicting

the parts o the model and their relationships. For practical purposes, topics typically address: (1)

how some category o things is organized, (2) how a system works, or (3) how to perorm some task

properly. Te rst type o mental model tends to be typological, whereas the latter two tend to have

sequential and causal links. Models can vary in a number o ways, including their completeness, their

internal consistency, their sophistication, and their ability to account or phenomena. For example,

consider how dierently the mechanisms o diabetes are understood by a molecular biologist, a amilyphysician, a diabetic educator, and a patient.

Concept Mapping has evolved over time so that, in addition to being used to capture experts mental

models, it is now used to measure group consensus (rochim and Kane, 2005), team mental models

(Burtscher and Manser, 2012; Mohammed, Ferzandi, and Hamilton, 2010), and cultural mental

models (Sieck, 2010).


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Example

An example o one o the newest orms o Concept Mapping is Rasmussen, Sieck, and Smarts (2009)

cultural network analysis (CNA), which they used to reveal and explain key cultural dierences

between American and British military conceptions o eective planning. In mapping out the network

o ocers concepts, values, and causal belies about eective planning, they discovered that, in British

military culture, eective planning consists o communicating the plans intent so that it can be

fexibly implemented in the eld as circumstances change. In contrast, eective planning in American

military culture aims to reduce the need to make decisions in the eld by working through various

contingencies ahead o time. Tese ndings were used to improve joint British-American military

planning operations.

PCMH Application

One o the cornerstones o a PCMH is to improve patient care by developing more eective

coordination among providers, sta, and organizations involved in a given patients care. Providers and

sta inevitably identiy with dierent personal, proessional, and organizational cultures. Tis meansthat, or a PCMH model to succeed, it is important to identiy and address important tacit dierences

in their mental models o such organizational and clinical unctions as planning, coordination,

cooperation, remuneration, disease management, sel-management, and even what it means to be

a PCMH (see Ho, 2010). As demonstrated in the example o military planning, (cultural) mental

models need not be identical or coordination to succeed. However, understanding dierences in

mental models, as well as the eect o these dierences on social interactions, helps one calibrate and

reorganize complex interactions so that they are more eective.

Team Knowledge Audit

Te eam Knowledge Audit (KA) is derived rom the well-studied Knowledge Audit (KA) CAtool (Klein and Militello, 2005; Militello and Hutton, 1998). Te KA was developed using insights

rom the literature on expert-novice dierences in decisionmaking (Ericsson and Smith, 1991), and

is designed to probe or macrocognition unctions in routine knowledge work. Te KA is the KA

extended to ocus on macrocognitive unctions between, as well as within, individuals on a team

(Klein, Pliske, and Tordsen, 1999; Militello, Kyne, Klein, et al., 1999). Much o a teams expertise is

contained in tacit understandings o how it perorms macrocognitive unctions, and key knowledge

may be distributed (held across team members) or dispersed (portions held by dierent members)

(Becker, 2004). Like the highly automatized knowledge o individual experts, the teams expertise is

oten employed with little conscious awareness.

Te KA ocuses on identiying the specics o how members o a team carry out macrocognitiveunctions, rather than on how they understand them (that is, team mental models), as would

be revealed by the Concept Mapping method. KA uses mainly semi-structured interviews, but

commonly includes observations o team interactions and analyses o orms, logs, patient charts, and

other artiacts. Each interview begins with a set o probe questions that are structured to elicit the

tacit knowledge o the team. Multiple team members are interviewed independently to elicit both


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distributed and dispersed knowledge and distinguish the two. Te probes ocus on how the team

executes macrocognitive unctions related to the task and context. Similarly, observations and artiact

analyses ocus on uncovering macrocognitive unctions.

Te KA typically builds on a ask Diagram, and develops additional detail about the execution o

each step and the coordination between steps. Not all categories o macrocognition are necessarily

inormative or any given task, so the interviewers will oten increase or decrease their use o various

planned probes as the interviews progress. As in the ask Diagram method, interviewees are guided

to relate how tasks are carried out with specic examples in mind, and are careully dissuaded rom

answering in the abstract. Finally, the KA usually ocuses on how teams currently carry out their

tasks, though it can be used or studying past routine tasks.

Examples

Te KA has been applied successully to develop a training program or surgical teams to make

optimal use o newly introduced, very complex patient status and management plan displays in

cardiothoracic surgery suites (Crandall and Grome, 2010). Detailed mapping o the teams planning,problem detection, coordination, and replanning revealed patterns that resulted in marked changes

rom the initial design o the displays themselves and the training program or introducing them. As

a result o this process, improvements were introduced beore the training began, avoiding potentially

costly and disruptive revision.

In another project, we are combining a ask Diagram and KA to understand how practices

implement care management or chronic diseases, and relating the ndings to quantitative changes

in quality indicators. In yet another, we are using the KA to examine macrocognition process

dierences in whether and how primary care practices accomplish the changes necessary to implement

a PCMH unctionality o their choosing (such as, test tracking and ollowup, patient registries, or care

management) in a setting where they have nancial and organizational incentives to do so.

PCMH Application

Te KA has been used extensively in other elds or knowledge transer, that is, to understand what

high-perorming teams are doing accurately enough to instruct new or lower-perorming teams and

improve their perormance (see, or example, Klein and Militello, 2005). In a PCMH context, the

KA oers a structured, rigorous approach to yield more comprehensive and contextually detailed

best practices. Tese best practices can distill the skills developed and used by practices doing well

with PCMH activities to help those doing less well. KAs also can be conducted within organizations

with teams within practices that dier in levels o success, enabling them to share knowledge to

increase overall eectiveness. Finally, KAs and other CA techniques can also be used to understand

and improve the ways best practices are disseminated.

III. Advantages

Macrocognition is rarely studied in health services research or addressed in practical primary care

applications, and yet is at the heart o complex, interdependent knowledge work such as the team-


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based care that PCMH models require. Below we list three advantages o using CA to understand

and improve PCMH implementation.

Helps uncover the thinking and decisionmaking involved in PCMH models. A key advantage o

CA is that its structured approach to elicitation and its ocus on macrocognition reveal important

phenomena that are oten missed by traditional methodologies (Ryder and Redding, 1993;

Schneider, 1985). CA arose in part because attempts to implement ndings rom behavioral task

analysis resulted in errors and poor perormance (Schraagen, Chipman, and Shute, 2000), leading

to a realization that observation and more traditional interview approaches produced incomplete

inormation. Macrocognitive processes oten are not observable, and introspection in un- or semi-

structured interviewing does not oten bring them out spontaneously. Skilled teams usually carry out

macrocognitive unctions and processes so automatically that the methods and reasons behind them go

unnoticed or are misperceived unless specically and skillully elicited. CAs specic ocus on eliciting

macrocognitive unctions and processes helps ensure that they will not be overlooked.

Provides results that can be used to improve training and transition processes. Te power and

fexibility o CA methods to help understand a variety o relevant eatures in a given cognitive

landscape has yielded benets in individual and team training, quality improvement and saety, and

change eorts more generally. Each o these, in turn, serves to decrease the risk o being blindsided

by unanticipated consequences when implementing a PCMH, which keeps costs down, and quality,

productivity, and collective sel-ecacy high.

Supports eforts to obtain organizational buy-in. Te existence o a large, practical, applied body

o CA literature and respected consultants with portolios o successul work or prominent clients

provides reassurance and credibility to teams anxious about change and looking or guidance.

IV. LimitationsRequires a airly high level o skill to execute properly. Investigators who possess a clear

understanding o how the dierent macrocognitive and organizational theories bear on their objective

(in this case, PCMH models) yield better results. Both interviewers and analysts (i they are not the

same) benet greatly rom understanding how the techniques are grounded in the cognitive sciences,

as this aords the necessary fexibility to adapt and blend CA methods to ones purposes, including

on the fy during interviews. For this reason, CA is not amenable to scripted interviews conducted

by student research assistants.

Involves time-consuming processes. Tough it need not be excessively so, using CA methods

can be time-consuming. With training, practice, and a suciently ocused objective, a CA can be

designed, conducted, and analyzed in a weeks time. An example o a smaller CA project might be

mapping an exceptionally good care managers mental model o eective communication with and

engagement o providers.

Better suited to process than outcomes studies. Like other qualitative methods, CA is not

especially good at testing hypotheses (although, Crandall, Klein, and Homan [2006] do describe how


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to use CA in an experimental design). Ultimately, CA is best suited or uncovering, describing, and

explaining how thinking happens in a specic and complex context.

V. Conclusion

CAs benets are showcased by its decades-long track record o success in delivering tangible benets

where stakes are high and ailure is very visible, including or high-prole organizations such as the

U.S. Armed Forces, the national air trac control system, nuclear power plants, and intensive care

unit and operating room teams in major health care systems (Crandall and Grome, 2010; Crandall,

Klein, and Homan, 2006). CA is a powerul addition to methods or studying the implementation

o PCMH models and identiying and disseminating contextually grounded best practices. It is used

to understand how cognitive tasks are carried outhow the knowledge work o a PCMH is doneby

primary care clinicians and sta. Ultimately, this richer understanding acilitates the transer o what is

essential in best practice skills to other sta and organizations implementing PCMH models.

VI. References

Becker MC. Organizational routines: a review o the literature. Industrial and Corporate Change

2004;13:64377.

Burtscher MJ, Manser . eam mental models and their potential to improve teamwork and saety: a

review and implications or uture research in healthcare. Sa Sci 2012;50:134454.

Christensen RE, Fetters MD, Green LA. Opening the black box: cognitive strategies in amily

practice. Ann Fam Med 2005; 3:144150.

Crandall B, Calderwood R. Clinical Assessment Skills o Experienced Neonatal Intensive Care Nurses.(Prepared or the National Center or Nursing, NIH, under Contract No. 1 R43 NR0191101.)

Fairborn, OH: Klein Associates Inc., 1989.

Crandall B, Grome A. CA workshop. Presented at the University o Michigan; 2010 Jan.

Crandall B, Klein GA, Homan RR. Working Minds: A Practitioners Guide o Cognitive ask

Analysis. Cambridge, MA: MI Press; 2006. http://www.books24x7.com/marc.asp?bookid=12926.

Dominguez C, Hutton R, Flach J, et al. Perception-action coupling in endoscopic surgery: a cognitive

task analysis approach. In: Barry B, Boutsma RJ, and Guiard Y, eds. Studies In Perception And Action

III. Mahwah, NJ: Lawrence Erlbaum Associates; 1995.

Ericsson KA, Smith J. oward A General Teory O Expertise: Prospects And Limits. Cambridge, UK:Cambridge University Press; 1991.

Green LA, Nease DE, Klinkman MS. Clinical reminders designed and implemented using cognitive

and organizational science principles do not produce reminder atigue. Presented at the 31st Annual

Meeting o the Society or Medical Decision Making; 2009 Oct; Hollywood, CA.Ho . Te patient-

centered medical home: what we need to know more about. Med Care Res Rev 2010;67(4):38392.

Homan R, Woods DD. Studying cognitive systems in context. Hum Factors 2000;42(1):17.


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Klein GA, Militello L. Te Knowledge Audit as a method or cognitive task analysis. In Lipshitz R

and Brehmer B, eds. How Proessionals Make Decisions. Mahwah, NJ: Lawrence Erlbaum Associates;

2005.

Klein GA, Pliske R, Tordsen M, et al. A Model O Distributed eam Perormance. Fairborn, OH:

Klein Associates; 1999.

Militello LG, Hutton RJ. Applied cognitive task analysis (ACA): a practitioners toolkit or

understanding cognitive task demands. Ergonomics 1998 Nov;41(11):161841.

Militello LG, Kyne M, Klein GA, et al. A synthesized model o team perormance. Int J Cogn Ergon

1999;3(2):13158.

Mohammed S, Ferzandi L, Hamilton K. Metaphor no more: a 15-year review o the team mental

model construct. J Manage 2010 Jul;36:876910.

Rasmussen LJ, Sieck WR, Smart, P. What is a good plan? Cultural variations in expert planners

concepts o plan quality. Journal o Cognitive Engineering & Decision Making 2009;3, 22849.

Ryder JM, Redding RE. Integrating cognitive task analysis into instructional systems development.

Educ echnol Res Dev 1993;41:7596.

Schneider W. raining high-perormance skills: allacies and guidelines. Hum Factors 1985; 27:285

300.

Schraagen JM, Chipman SF, Shute VJ. State-o-the-art review o cognitive task analysis techniques.

In Schraagen JM, Chipman SF, and Shute VJ, eds. Cognitive ask Analysis. Mahwah, NJ: Lawrence

Erlbaum Associates; 2000. p. 46787.

Shachak A, Hadas-Dayagi M, Ziv A, et al. Primary care physicians use o an electronic medical record

system: a cognitive task analysis. J Gen Intern Med. 2009;24(3):3418.Sieck,WR. Cultural network analysis: method and application. In Schmorrow D and Nicholson D,

eds. Advances In Cross-Cultural Decision Making. Boca Raton: CRC Press/aylor & Francis, Ltd;

2010. p. 2609.

rochim W, Kane M. Concept mapping: an introduction to structured conceptualization in health

care. International Journal o Quality Health Care 2005 Jun;17(3):18791.

VII. Resources

Guides to Conducting CTABuchanan, D. A., & Bryman, A. (Eds.). Te Sage Handbook o Organizational Research Methods.

Tousand Oaks, CA: Sage; 2009.

Crandall B, Klein G, Homan RR. Working Minds: A Practitioners Guide o Cognitive ask

Analysis. Cambridge, MA: MI Press; 2006.


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Klein GA, Militello L. Te Knowledge Audit as a method or cognitive task analysis. In Lipshitz R

and Brehmer B, eds. How Proessionals Make Decisions. Mahwah, NJ: Lawrence Erlbaum Associates;

2005.

MacroCognition. Web site. http://www.macrocognition.com.

Militello LG, Hutton RJ. Applied cognitive task analysis (ACA): a practitioners toolkit or

understanding cognitive task demands. Ergonomics 1998 Nov;41(11):161841.

Sieck WR. Cultural network analysis: method and application. In Schmorrow D and Nicholson D,

eds. Advances In Cross-Cultural Decision Making. Boca Raton: CRC Press/aylor & Francis, Ltd;

2010. p. 2609.

Applications of CTA

Burtscher MJ, Manser . eam mental models and their potential to improve teamwork and saety: a

review and implications or uture research in healthcare. Sa Sci 2012;50:134454.

Christensen RE, Fetters MD, Green LA. Opening the black box: cognitive strategies in amily

practice. Ann Fam Med 2005; 3:14450.

Crandall B, Calderwood R. Clinical Assessment Skills o Experienced Neonatal Intensive Care Nurses.

(Prepared or the National Center or Nursing, NIH, under Contract 1 R43 NR0191101.) Fairborn,

OH: Klein Associates Inc., 1989.

Dominguez C, Hutton R, Flach J, et al. Perception-action coupling in endoscopic surgery: a cognitive

task analysis approach. In: Barry B, Boutsma RJ, and Guiard Y, eds. Studies In Perception And Action

III. Mahwah, NJ: Lawrence Erlbaum Associates; 1995.

Green LA, Nease DE, Klinkman MS. Clinical reminders designed and implemented using cognitive

and organizational science principles do not produce reminder atigue. Presented at the 31st Annual

Meeting o the Society or Medical Decision Making; 2009 Oct; Hollywood, CA.

Minkman A, Fabbricotti N, Huijsman. A quality management model or integrated care: results o a

Delphi and Concept Mapping study. Int J Qual Health Care 2009;21(1):6675.

Rasmussen LJ, Sieck WR, Smart P. What is a good plan? Cultural variations in expert planners

concepts o plan quality. Journal o Cognitive Engineering & Decision Making 2009;3:22849.

Ryder JM, Redding RE. Integrating cognitive task analysis into instructional systems development.

Educ echnol Res Dev 1993;41:7596.

Schraagen JM, Chipman SF, Shute VJ. State-o-the-art review o cognitive task analysis techniques.

In Schraagen JM, Chipman SF and Shute VJ, eds. Cognitive ask Analysis. Mahwah, NJ: Lawrence

Erlbaum Associates; 2000. p. 46787.

Shachak A, Hadas-Dayagi M, Ziv A, et al. Primary care physicians use o an electronic medical record

system: a cognitive task analysis. J Gen Intern Med 2009;24(3):3418.


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Weir CR, Nebeker JJ, Hicken BL, et al. A cognitive task analysis o inormation management strategies

in a computerized provider order entry environment. J Am Med Inorm Assoc 2007;14:6575.

Tis brie was prepared by Georges Potworowski, Ph.D. ([email protected], University at Albany,

State University o New York) and Lee A. Green, M.D., M.P.H. (University o Alberta).

Suggested Citation: Potworowski G. and Green L. A. Cognitive ask Analysis: Methods to Improve

Patient-Centered Medical Home Models by Understanding and Leveraging its Knowledge Work.

Rockville, MD: Agency or Healthcare Research and Quality. February 2013. AHRQ Publication No.

13-0023-EF.

Tis brie and companion bries in this series are available or download rom pcmh.ahrq.gov.


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bAHRQ Publication No. 13-0023-EF

March 2013

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