Development of a primary care physician task list to evaluate clinic visit workflow

Determinants of Patient Aligned Care Team (PACT) members' burnout and its relationship with patient-centered care

Burnout is a prevalent issue among healthcare providers affecting up to 54% of physicians and 35% of nurses. Patient Aligned Care Teams (PACT) is a team-based primary care delivery model designed to assure the delivery of high-quality care while improving clinicians' well-being. Limited studies evaluated the relationship between work environment variables and PACT members' burnout and the relationship between PACT members' burnout and patient-centered care. This cross-sectional study is based on the 2018 Veterans Health Administration (VHA) national web-based PACT survey. Burnout was measured using a single-item question that was validated in previous studies. Descriptive statistics and logistic regression were used to analyze the data. Fifty-one percent of primary care providers and 40.12% of nurses reported high burnout. PACT members with a work environment characterized by high-quality team interaction, leadership support, and psychological safety experienced lower levels of burnout. PACT members' burnout explained 6% of the variance in PACT members' ability to deliver patient-centered care. Burnout among PACT members is attributed to multiple personal and occupational variables. This study identified modifiable work environment variables that can be used to inform burnout interventions.

WORKING AT THE TOP OF THEIR CAPABILITIES: HOW TEAMWORK SUPPORT ATTENUATES LEADER ROLE CONFLICT

Objective

To understand whether team member support reduces team leader stress.

Method

In Phase 1, we used hierarchical linear modeling with survey data and administrative records from 45 Veterans Health Administration teams (73 providers and 228 associated members) to investigate how teamwork support mitigates leader stress. In Phase 2, we adopted a parallel/simultaneous mixed methods design, utilizing open- and closed-ended responses from 267 additional Veterans Health Administration providers. With the mixed methods design we first analyzed open-ended responses using directed content analysis and hypothesis coding. Next, we transformed our codes into counts and compared them with closed-ended responses to understand whether teamwork support allows leaders to engage in work aligned with their qualifications.

Results

As predicted, providers' role conflict corresponded with decreased performance under low teamwork support, but this negative relationship was attenuated with high teamwork support as such support allows leaders to focus on tasks they are uniquely qualified to perform.

Conclusions

These findings emphasize the facilitative nature of teams in supporting leaders: followers provide teamwork support that helps leaders navigate role conflict by allowing leaders to work on tasks consistent with their qualifications.

"Mm-hm," "Uh-uh": are non-lexical conversational sounds deal breakers for the ambient clinical documentation technology?

OBJECTIVES

Ambient clinical documentation technology uses automatic speech recognition (ASR) and natural language processing (NLP) to turn patient-clinician conversations into clinical documentation. It is a promising approach to reducing clinician burden and improving documentation quality. However, the performance of current-generation ASR remains inadequately validated. In this study, we investigated the impact of non-lexical conversational sounds (NLCS) on ASR performance. NLCS, such as Mm-hm and Uh-uh, are commonly used to convey important information in clinical conversations, for example, Mm-hm as a "yes" response from the patient to the clinician question "are you allergic to antibiotics?"

MATERIALS AND METHODS

In this study, we evaluated 2 contemporary ASR engines, Google Speech-to-Text Clinical Conversation ("Google ASR"), and Amazon Transcribe Medical ("Amazon ASR"), both of which have their language models specifically tailored to clinical conversations. The empirical data used were from 36 primary care encounters. We conducted a series of quantitative and qualitative analyses to examine the word error rate (WER) and the potential impact of misrecognized NLCS on the quality of clinical documentation.

RESULTS

Out of a total of 135 647 spoken words contained in the evaluation data, 3284 (2.4%) were NLCS. Among these NLCS, 76 (0.06% of total words, 2.3% of all NLCS) were used to convey clinically relevant information. The overall WER, of all spoken words, was 11.8% for Google ASR and 12.8% for Amazon ASR. However, both ASR engines demonstrated poor performance in recognizing NLCS: the WERs across frequently used NLCS were 40.8% (Google) and 57.2% (Amazon), respectively; and among the NLCS that conveyed clinically relevant information, 94.7% and 98.7%, respectively.

DISCUSSION AND CONCLUSION

Current ASR solutions are not capable of properly recognizing NLCS, particularly those that convey clinically relevant information. Although the volume of NLCS in our evaluation data was very small (2.4% of the total corpus; and for NLCS that conveyed clinically relevant information: 0.06%), incorrect recognition of them could result in inaccuracies in clinical documentation and introduce new patient safety risks.

Expanding the role of non-physician medical staff in primary care in Germany: protocol for a mixed-methods study exploring the perspectives of physicians in rural practices

INTRODUCTION

Primary care faces substantial challenges worldwide through an increasing mismatch in supply and demand, particularly in rural areas. One option to address this mismatch might be increasing efficiency by delegation of tasks to non-physician medical staff. Possible influencing factors, motives and beliefs regarding delegation to non-physician medical staff and the potential of an expanded role, as perceived by primary care physicians, however, remain unclear. The aim of this study is to assess these factors to guide development of potential interventions for expanding the role of non-physician medical staff in delivering primary care services in rural Germany.

METHODS AND ANALYSIS

This mixed-methods study based on the theoretical domains framework (TDF) consists of survey and interviews conducted sequentially. The survey, to be sent to all primary care physicians active in rural Baden-Wuerttemberg (estimated n=1250), includes 37 items: 15 assessing personal and practice characteristics, 15 matching TDF domains and 7 assessing opportunities for delegation. The interview, to be performed in a subsample (estimated n=12-20), will be informed by results of the survey. The initial interview guide consists of 11 questions covering additional TDF domains. Perspectives towards delegation will be maximised by comparing data emerging in either part of the study, seeking confirmation, disagreement or further details.

ETHICS AND DISSEMINATION

The Ethics Committee of Heidelberg University approved this study (approval number: 2021-530). Written informed consent will be obtained before each interview; consent for participation in the survey will be assumed when the survey has been returned. Results will be disseminated via publications in peer-reviewed journals and talks at conferences. By combining quantitative and qualitative methods, our results will support future research for crafting potential interventions to expand the role of non-physician medical staff in rural primary care.

Automatic Classification of Screen Gaze and Dialogue in Doctor-Patient-Computer Interactions: Computational Ethnography Algorithm Development and Validation

Background

The study of doctor-patient-computer interactions is a key research area for examining doctor-patient relationships; however, studying these interactions is costly and obtrusive as researchers usually set up complex mechanisms or intrude on consultations to collect, then manually analyze the data.

Objective

We aimed to facilitate human-computer and human-human interaction research in clinics by providing a computational ethnography tool: an unobtrusive automatic classifier of screen gaze and dialogue combinations in doctor-patient-computer interactions.

Methods

The classifier’s input is video taken by doctors using their computers' internal camera and microphone. By estimating the key points of the doctor's face and the presence of voice activity, we estimate the type of interaction that is taking place. The classification output of each video segment is 1 of 4 interaction classes: (1) screen gaze and dialogue, wherein the doctor is gazing at the computer screen while conversing with the patient; (2) dialogue, wherein the doctor is gazing away from the computer screen while conversing with the patient; (3) screen gaze, wherein the doctor is gazing at the computer screen without conversing with the patient; and (4) other, wherein no screen gaze or dialogue are detected. We evaluated the classifier using 30 minutes of video provided by 5 doctors simulating consultations in their clinics both in semi- and fully inclusive layouts.

Results

The classifier achieved an overall accuracy of 0.83, a performance similar to that of a human coder. Similar to the human coder, the classifier was more accurate in fully inclusive layouts than in semi-inclusive layouts.

Conclusions

The proposed classifier can be used by researchers, care providers, designers, medical educators, and others who are interested in exploring and answering questions related to screen gaze and dialogue in doctor-patient-computer interactions.

Remembering Ben-Tzion Karsh's scholarship, impact, and legacy

Dr. Ben-Tzion (Bentzi) Karsh was a mentor, collaborator, colleague, and friend who profoundly impacted the fields of human factors and ergonomics (HFE), medical informatics, patient safety, and primary care, among others. In this paper we honor his contributions by reflecting on his scholarship, impact, and legacy in three ways: first, through an updated simplified bibliometric analysis in 2020, highlighting the breadth of his scholarly impact from the perspective of the number and types of communities and collaborators with which and whom he engaged; second, through targeted reflections on the history and impact of Dr. Karsh's most cited works, commenting on the particular ways they impacted our academic community; and lastly, through quotes from collaborators and mentees, illustrating Dr. Karsh's long-lasting impact on his contemporaries and students.

A Markov chain model for analysis of physician workflow in primary care clinics

This paper studies physician workflow management in primary care clinics using terminating Markov chain models. The physician workload is characterized by face-to-face encounters with patients and documentation of electronic health record (EHR) data. Three workflow management policies are considered: preemptive priority (stop ongoing documentation tasks if a new patient arrives); non-preemptive priority (finish ongoing documentation even if a new patient arrives); and batch documentation (start and finish documentation when the desired number of tasks is reached). Analytical formulas are derived to quantify the performance measures of three management policies, such as physician's daily working time, patient's waiting time, and documentation waiting time. A comparison of the results under three policies is carried out. Finally, a case study in a primary care clinic is carried out to illustrate model applicability. Such a work provides a quantitative tool for primary care physicians to design and manage their workflow to improve care quality.

It's time to bring human factors to primary care policy and practice

Primary health care is a complex, highly personal, and non-linear process. Care is often sub-optimal and professional burnout is high. Interventions intended to improve the situation have largely failed. This is due to a lack of a deep understanding of primary health care. Human Factors approaches and methods will aid in understanding the cognitive, social and technical needs of these specialties, and in designing and testing proposed innovations. In 2012, Ben-Tzion Karsh, Ph.D., conceived a transdisciplinary conference to frame the opportunities for research human factors and industrial engineering in primary care. In 2013, this conference brought together experts in primary care and human factors to outline areas where human factors methods can be applied. The results of this expert consensus panel highlighted four major research areas: Cognitive and social needs, patient engagement, care of community, and integration of care. Work in these areas can inform the design, implementation, and evaluation of innovations in Primary Care. We provide descriptions of these research areas, highlight examples and give suggestions for future research.

Using the PARAFAC2 tensor factorization on EHR audit data to understand PCP desktop work

BACKGROUND

Activity or audit log data are required for EHR privacy and security management but may also be useful for understanding desktop workflow.

OBJECTIVE

We determined if the EHR audit log file, a rich source of complex time-stamped data on desktop activities, could be processed to derive primary care provider (PCP) level workflow measures.

METHODS

We analyzed audit log data on 876 PCPs across 17,455 ambulatory care encounters that generated 578,394 time-stamped records. Each individual record represents a user interaction (e.g., point and click) that reflects all or part of a specific activity (e.g., order entry access). No dictionary exists to define how to combine clusters of sequential audit log records to represent identifiable PCP tasks. We determined if PARAFAC2 tensor factorization could: (1) learn to identify audit log record clusters that specifically represent defined PCP tasks; and (2) identify variation in how tasks are completed without the need for ground-truth labels. To interpret the result, we used the following PARAFAC2 factors: a matrix representing the task definitions and a matrix containing the frequency measure of each task for each encounter.

RESULTS

PARAFAC2 automatically identified 4 clusters of audit log records that represent 4 common clinical encounter tasks: (1) medications' access, (2) notes' access, (3) order entry access, and (4) diagnosis modification. PARAFAC2 also identified the most common variants in how PCPs accomplish these tasks. It discovered variation in how the notes' access task was done, including identification of 9 distinct variants of notes access that explained 77% of the input data variation for notes. The discovered variants mapped to two known workflows for notes' access and to two distinct PCP user groups who accessed notes by either using the Visit Navigator or the Wrap-Up option.

CONCLUSIONS

Our results demonstrate that EHR audit log data can be rapidly processed to create higher-level constructed features that represent time-stamped PCP tasks.

Computerization and the future of primary care: A survey of general practitioners in the UK

OBJECTIVE

To describe the opinions of British general practitioners regarding the potential of future technology to replace key tasks carried out in primary care.

DESIGN

Cross sectional online survey.

PARTICIPANTS

1,474 registered GPs in the United Kingdom.

MAIN OUTCOME MEASURES

Investigators measured GPs' opinions about the likelihood that future technology will be able to fully replace-not merely aid-the average GP in performing six primary care tasks; in addition, if GPs considered replacement for a particular task likely, the survey measured opinions about how many years from now this technological capacity might emerge.

RESULTS

A total of 720 (49%) responded to the survey. Most GPs believed it unlikely that technology will ever be able to fully replace physicians when it comes to diagnosing patients (489, 68%), referring patients to other specialists (444, 61%), formulating personalized treatment plans (441, 61%), and delivering empathic care (680, 94%). GPs were not in agreement about prognostics: one in two participants (380, 53%) considered it likely that technology will be fully capable of replacing physicians in performing this task, nearly half (187, 49%) of whom believed that the technological capacity will arise in the next ten years. Against these findings, the majority of GPs (578, 80%) believed it likely that future technology will be able to fully replace humans to undertake documentation; among them 261 (79%) estimated that the technological wherewithal would emerge during the next ten years. In general, age and gender were not correlated with opinions; nor was reported burnout and job satisfaction or whether GPs worked full time or part time.

CONCLUSIONS

The majority of UK GPs in this survey were skeptical about the potential for future technology to perform most primary care tasks as well as or better than humans. However, respondents were optimistic that in the near future technology would have the capacity to fully replace GPs' in undertaking administrative duties related to patient documentation.

Assessing Unwanted Variations in Rheumatology Clinic Previsit Rooming

BACKGROUND

Rheumatologists face time pressures similar to primary care but have not generally benefitted from optimized team-based rooming during the time from the waiting room until the rheumatologist enters the room.

OBJECTIVE

The aim of this study was to assess current capacity for population management in rheumatology clinics; we aimed to measure the tasks performed by rheumatology clinic staff (medical assistants or nurses) during rooming.

METHODS

We performed a cross-sectional time-study and work-system analysis to measure rooming workflows at 3 rheumatology clinics in an academic multispecialty practice during 2014-2015. We calculated descriptive statistics and compared frequencies and durations using Fisher exact test and analysis of variance.

RESULTS

Observing 190 rheumatology clinic previsit rooming sequences (1419 minutes), we found many significant variations. Total rooming duration varied by clinic (median, 6.75-8.25 minutes; p < 0.001). Vital sign measurement and medication reconciliation accounted for more than half of rooming duration. Among 3 clinics, two of 15 tasks varied significantly in duration, and 9 varied in frequency. Findings led clinic leaders to modify policies and procedures regarding 6 high-variation tasks streamlining assessment of weight, height, pain scores, tobacco use, disease activity, and refill needs.

CONCLUSIONS

Assessing rheumatology rooming tasks identified key opportunities to improve quality and efficiency without burdening providers. This project demonstrated user-friendly methods to identify opportunities to standardize rooming and support data-driven decisions regarding rheumatology clinic practice changes to improve population management in rheumatology.

Improving over-the-counter medication safety for older adults: A study protocol for a demonstration and dissemination study

BACKGROUND

Adverse drug events (ADEs) associated with over-the-counter (OTC) medications cause 178,000 hospitalizations each year. Older adults, aged 65 and older, are particularly vulnerable to ADEs. Of the 2.2 million older adults considered at risk for a major ADE, more than 50% are at risk due to concurrent use of an OTC and prescription medication.

OBJECTIVES

To refine the intervention and implementation strategy through diagnostic and formative evaluation; to evaluate the effectiveness of the intervention for preventing misuse of high-risk OTC medications by older adults; and to evaluate the implementation of the intervention in community pharmacies.

METHODS

A system redesign intervention to decrease high-risk OTC medication misuse will be tested to reduce misuse by improving communication between older adults and community pharmacists via the following features: a redesign of the physical environment to sensitize older adults to high-risk OTC medications, and the implementation of a clinical decision tool to support the pharmacist when critically evaluating the older adult's health status. The study will be conducted in three phases: a participatory design phase, a beta phase, and a test phase. The test phase will be conducted in three mass-merchandise stores. A total of 144 older adults will be recruited. A pre (control)/post (intervention) test will determine the effectiveness of the intervention. The primary outcome will be a comparison of proportion of older adults who misuse OTC medication from baseline to post-intervention. The process of implementation in the community pharmacy setting will be evaluated using the taxonomy proposed by Proctor et al. The participatory design phase has been approved by the institution's IRB (2016-0743).

PROJECTED IMPACT

It is anticipated that this project, which focuses on achieving systems-based improvement in an underemphasized area of the medication use process, will reduce ADEs associated with inappropriate OTC medication use in older adults.

Recommendations for health information technology implementation in rural hospitals

Purpose

– The purpose of this paper is to investigate violations against work standards associated with using a new health information technology (HIT) system. Relevant recommendations for implementing HIT in rural hospitals are provided and discussed to achieve meaningful use.

Design/methodology/approach

– An observational study is conducted to map medication administration process while using a HIT system in a rural hospital. Follow-up focus groups are held to determine and verify potential adverse factors related to using the HIT system while passing drugs to patients.

Findings

– A detailed task analysis demonstrated several violations, such as only relying on the barcode scanning system to match up with patient and drugs could potentially result in the medical staff forgetting to provide drug information verbally before administering drugs. There was also a lack of regulated and clear work procedure in using the new HIT system. In addition, the computer system controls and displays could not be adjusted so as to satisfy the users’ expectations. Nurses prepared medications and documentation in an environment that was prone to interruptions.

Originality/value

– Recommendations for implementing a HIT system in rural healthcare facilities can be categorized into five areas: people, tasks, tools, environment, and organization. Detailed remedial measures are provided for achieving continuous process improvements at resource-limited healthcare facilities in rural areas.

Team Science Approach to Developing Consensus on Research Good Practices for Practice-Based Research Networks: A Case Study

Using peer learning strategies, seven experienced PBRNs working in collaborative teams articulated procedures for PBRN Research Good Practices (PRGPs). The PRGPs is a PBRN-specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. This paper describes the team science processes which culminated in the PRGPs. Skilled facilitators used team science strategies and methods from the Technology of Participation (ToP®), and the Consensus Workshop Method to support teams to codify diverse research expertise in practice-based research. The participatory nature of "sense-making" moved through identifiable stages. Lessons learned include (1) team input into the scope of the final outcome proved vital to project relevance; (2) PBRNs with diverse domains of research expertise contributed broad knowledge on each topic; and (3) ToP® structured facilitation techniques were critical for establishing trust and clarifying the "sense-making" process.

The myth of standardized workflow in primary care

OBJECTIVE

Primary care efficiency and quality are essential for the nation's health. The demands on primary care physicians (PCPs) are increasing as healthcare becomes more complex. A more complete understanding of PCP workflow variation is needed to guide future healthcare redesigns.

METHODS

This analysis evaluates workflow variation in terms of the sequence of tasks performed during patient visits. Two patient visits from 10 PCPs from 10 different United States Midwestern primary care clinics were analyzed to determine physician workflow. Tasks and the progressive sequence of those tasks were observed, documented, and coded by task category using a PCP task list. Variations in the sequence and prevalence of tasks at each stage of the primary care visit were assessed considering the physician, the patient, the visit's progression, and the presence of an electronic health record (EHR) at the clinic.

RESULTS

PCP workflow during patient visits varies significantly, even for an individual physician, with no single or even common workflow pattern being present. The prevalence of specific tasks shifts significantly as primary care visits progress to their conclusion but, notably, PCPs collect patient information throughout the visit.

DISCUSSION

PCP workflows were unpredictable during face-to-face patient visits. Workflow emerges as the result of a "dance" between physician and patient as their separate agendas are addressed, a side effect of patient-centered practice.

CONCLUSIONS

Future healthcare redesigns should support a wide variety of task sequences to deliver high-quality primary care. The development of tools such as electronic health records must be based on the realities of primary care visits if they are to successfully support a PCP's mental and physical work, resulting in effective, safe, and efficient primary care.

Quantitative ethnographic study of physician workflow and interactions with electronic health record systems

This study explores the relationship between primary care physicians' interactions with health information technology and primary care workflow. Clinical encounters were recorded with high-resolution video cameras to capture physicians' workflow and interaction with two objects of interest, the electronic health record (EHR) system, and their patient. To analyze the data, a coding scheme was developed based on a validated list of primary care tasks to define the presence or absence of a task, the time spent on each task, and the sequence of tasks. Results revealed divergent workflows and significant differences between physicians' EHR use surrounding common workflow tasks: gathering information, documenting information, and recommend/discuss treatment options. These differences suggest impacts of EHR use on primary care workflow, and capture types of workflows that can be used to inform future studies with larger sample sizes for more effective designs of EHR systems in primary care clinics. Future research on this topic and design strategies for effective health information technology in primary care are discussed.

Rethinking primary care visits: how much can be eliminated, delegated or performed outside of the face-to-face visit?

RATIONALE, AIMS AND OBJECTIVES

Office visits represent the core component of primary care practice, but little is known about what percentage of primary care provider (PCP) visit time could be suitable for reassignment to another medical home team member or to a non-face-to-face modality (e.g. secure messaging) in order to optimize face-to-face PCP visit time.

METHOD

We videotaped 121 PCP office visits at four Veterans Health Administration Medical Centers and divided visits into discrete activity segments. Two physicians reviewed each visit recording and provided independent clinical judgments regarding which segments might be suitable for reassignment. We examined the activity category distribution of visit time rated as needing face-to-face time with a PCP.

RESULTS

Reviewers judged 53% of the 5398 minutes of rated visit time as suitable for reassignment to another team member or modality. The percentage of time rated as needing face-to-face PCP care varied greatly by activity category, from a high of 73.9% (for examining patients) to a low of 16.2% (for medication review). Rater agreement regarding tasks' suitability for reassignment varied across activity categories.

CONCLUSIONS

These data offer an example of how face-to-face PCP visit time might be optimized as practices seek to shift components of patient care to other team members and other modalities. Given variations in provider preferences and judgments, successful redesign efforts will need to involve stakeholders in decisions about how to best utilize medical home resources.

Approaches and challenges to optimising primary care teams' electronic health record usage

BACKGROUND

Although the presence of an electronic health record (EHR) alone does not ensure high quality, efficient care, few studies have focused on the work of those charged with optimising use of existing EHR functionality.

OBJECTIVE

To examine the approaches used and challenges perceived by analysts supporting the optimisation of primary care teams' EHR use at a large U.S. academic health care system.

METHODS

A qualitative study was conducted. Optimisation analysts and their supervisor were interviewed and data were analysed for themes.

RESULTS

Analysts needed to reconcile the tension created by organisational mandates focused on the standardisation of EHR processes with the primary care teams' demand for EHR customisation. They gained an understanding of health information technology (HIT) leadership's and primary care team's goals through attending meetings, reading meeting minutes and visiting with clinical teams. Within what was organisationally possible, EHR education could then be tailored to fit team needs. Major challenges were related to organisational attempts to standardise EHR use despite varied clinic contexts, personnel readiness and technical issues with the EHR platform. Forcing standardisation upon clinical needs that current EHR functionality could not satisfy was difficult.

CONCLUSIONS

Dedicated optimisation analysts can add value to health systems through playing a mediating role between HIT leadership and care teams. Our findings imply that EHR optimisation should be performed with an in-depth understanding of the workflow, cognitive and interactional activities in primary care.

Are Spanish primary care professionals aware of patient safety?

BACKGROUND

Knowledge about safety culture improves patient safety (PS) in health-care organizations. The first contact a patient has with health care occurs at the primary level. We conducted a survey to measure patient safety culture (PSC) among primary care professionals (PCPs) of health centres (HCs) in Spain and analyzed PS dimensions that influence PSC.

METHODS

We used Agency for Healthcare Research and Quality (AHRQ) Medical Office Survey on Patient Safety Culture translated and validated into Spanish to conduct a cross-sectional anonymous postal survey. We randomly selected a sample of 8378 PCPs at 289 HCs operated by 17 Regional Health Services. Statistical analysis was performed on sociodemographic variables, survey items, PS dimensions and a patient safety synthetic index (PSSI), calculated as average score of the items per dimension, to identify potential predictors of PSC. We used AHRQ data to conduct international comparison.

RESULTS

A total of 4344 PCPs completed the questionnaire. The response rate was 55.69%. Forty-two percent were general practitioners, 34.9% nurses, 18% administrative staff and 4.9% other professionals. The highest scoring dimension was 'PS and quality issues' 4.18 (4.1-4.20) 'Work pressure and pace' was the lowest scored dimension with 2.76 (2.74-2.79). Professionals over 55 years, with managerial responsibilities, women, nurses and administrative staff, had better PSSI scores. Professionals with more than 1500 patients and working for more than 11 years at primary care had lower PSSI scores.

CONCLUSIONS

This is the first national study to measure PSC in primary care in Spain. Results may reflect on-going efforts to build a strong PSC. Further research into its association with safety outcomes and patients' perceptions is required.

The work of adult and pediatric intensive care unit nurses

BACKGROUND

Researchers have used various methods to describe and quantify the work of nurses. Many of these studies were focused on nursing in general care settings; therefore, less is known about the unique work nurses perform in intensive care units (ICUs).

OBJECTIVES

The aim of this study was to observe adult and pediatric ICU nurses in order to quantify and compare the duration and frequency of nursing tasks across four ICUs as well as within two discrete workflows: nurse handoffs at shift change and patient interdisciplinary rounds.

METHODS

A behavioral task analysis of adult and pediatric nurses was used to allow unobtrusive, real-time observation. A total of 147 hours of observation were conducted in an adult medical-surgical, a cardiac, a pediatric, and a neonatal ICU at one rural, tertiary care community teaching hospital.

RESULTS

Over 75% of ICU nurses' time was spent on patient care activities. Approximately 50% of this time was spent on direct patient care, over 20% on care coordination, 28% on nonpatient care, and approximately 2% on indirect patient care activities. Variations were observed between units; for example, nurses in the two adult units spent more time using monitors and devices. A high rate and variety of tasks were also observed: Nurses performed about 125 activities per hour, averaging a switch between tasks every 29 seconds.

DISCUSSION

This study provides useful information about how nurses spend their time in various ICUs. The methodology can be used in future research to examine changes in work related to, for example, implementation of health information technology.