Advertisement
Research| Volume 44, ISSUE 6, P624-631.e2, November 2018

Download started.

Ok

Emergency Department Crowding and Time at the Bedside: A Wearable Technology Feasibility Study

Published:April 25, 2018DOI:https://doi.org/10.1016/j.jen.2018.03.005

      Abstract

      Introduction

      ED crowding is a public health crisis, limiting quality and access to lifesaving care. The purpose of this study was to (1) evaluate the feasibility of radio-frequency identification tags to measure clinician-patient contact and (2) to test the relationship between ED occupancy and clinician-patient contact time.

      Methods

      In this 4-week observational study, radio-frequency identification tags were worn by emergency clinicians in a 21-bay urban teaching hospital emergency department. The time-motion data were merged with electronic medical repository patient information (N = 3,237) to adjust for occupancy, age, gender, and acuity. Qualitative themes were generated from focus group (N = 39) debriefings of the quantitative results.

      Results

      Data were collected on 56,342 total clinician events. Adjusting for patient age, increasing ED occupancy increased the number of times the attending physician entered and left the patient room (b = 0 .008, 95% confidence interval [CI] = [0.001-0.016], P = 0.03). There was no relationship for patient gender, triage acuity, shift at arrival, disposition to home, or discharge diagnosis category with either total minutes or number of encounters per patient visit. No time-motion and occupancy associations were observed for nurses, residents, or nurse practitioners/physician assistants. Debriefings indicated occupancy influenced the quality of care, despite maintaining the same quantity of contact time.

      Discussion

      The physical environment and clinician privacy concerns limit the feasibility of wearable tracking technology in the emergency setting. Attending physician care becomes more fragmented with increasing ED occupancy. Other clinicians report changes in the quality of care, whereas the quantity of time and encounters were unchanged with occupancy rates.
      Contribution to Emergency Nursing Practice
      • The current state of scientific knowledge on clinical-patient contact time indicates ED crowding may be detrimental to the quality, quantity, and consistency of care.
      • The main findings of this research include the following: As occupancy increases, we did not observe differences in time and motion for nurses and nurse practitioners/physician assistants, and we found that attending-physician care becomes more fragmented. There are several physical, architectural barriers to deploying radio-frequency identification tags in the emergency setting. Participating clinicians relayed several qualitative benefits and drawbacks to wearable tracking technology.
      • Key implications for emergency nursing practice indicate that additional revisions and considerations are needed to enhance wearable tracker feasibility for emergency clinicians.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of Emergency Nursing
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Bernstein SL
        • Aronsky D
        • Duseja R
        • et al.
        The effect of emergency department crowding on clinically oriented outcomes.
        Acad Emerg Med. 2009; 16: 1-10
        • Gaieski DF
        • Agarwal AK
        • Mikkelsen ME
        • et al.
        The impact of ED crowding on early interventions and mortality in patients with severe sepsis.
        Am J Emerg Med. 2017; 35: 953-960
        • Pines JM
        • Decker SL
        • Hu T
        Exogenous predictors of national performance measures for emergency department crowding.
        Ann Emerg Med. 2012; 60: 293-298
        • Sun BC
        • Hsia RY
        • Weiss RE
        • et al.
        Effect of emergency department crowding on outcomes of admitted patients.
        Ann Emerg Med. 2013; 61 (e606): 605-611
        • Rui P
        • Kang K
        National Hospital Ambulatory Medical Care Survey.
        in: Emergency Department Summary Tables. 2014 (http://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency/2014_ed_web_tables.pdf)
        • Aiken LH
        • Sloane DM
        • Cimiotti JP
        • et al.
        Implications of the California nurse staffing mandate for other states.
        Health Serv Res. 2010; 45: 904-921
        • Berry DL
        • Blumenstein BA
        • Halpenny B
        • et al.
        Enhancing patient-provider communication with the electronic self-report assessment for cancer: a randomized trial.
        J Clin Oncol. 2011; 29: 1029-1035
        • Asplin BR
        • Magid DJ
        • Rhodes KV
        • Solberg LI
        • Lurie N
        • Camargo Jr., CA
        A conceptual model of emergency department crowding.
        Ann Emerg Med. 2003; 42: 173-180
        • Chisholm CD
        • Weaver CS
        • Whenmouth L
        • Giles B
        A task analysis of emergency physician activities in academic and community settings.
        Ann Emerg Med. 2011; 58: 117-122
        • Institute of Medicine Committee on the Future of Emergency Care in the United States Health System
        Hospital-Based Emergency Care: At the Breaking Point.
        National Academies Press, Washington, DC2007
        • Li SY
        • Magrabi F
        • Coiera E
        A systematic review of the psychological literature on interruption and its patient safety implications.
        J Am Med Inform Assoc. 2012; 19: 6-12
        • Westbrook JI
        • Coiera E
        • Dunsmuir WT
        • et al.
        The impact of interruptions on clinical task completion.
        Qual Saf Health Care. 2010; 19: 284-289
        • Ward DR
        • Ghali WA
        • Graham A
        • Lemaire JB
        A real-time locating system observes physician time-motion patterns during walk-rounds: a pilot study.
        BMC Med Educ. 2014; 14: 37
        • Stahl JE
        • Drew MA
        • Kimball AB
        Patient-clinician concordance, face-time and access.
        Int J Health Care Qual Assur. 2014; 27: 664-671
        • Dufour JC
        • Reynier P
        • Boudjema S
        • Soto Aladro A
        • Giorgi R
        • Brouqui P
        Evaluation of hand hygiene compliance and associated factors with a radio-frequency identification-based real-time continuous automated monitoring system.
        J Hosp Infect. 2017; 95: 344-351
        • Shinmoto Torres RL
        • Visvanathan R
        • Abbott D
        • Hill KD
        • Ranasinghe DC
        A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people.
        PLoS One. 2017; 12e0185670
        • Dorrell RD
        • Vermillion SA
        • Clark CJ
        Feasibility of real-time location systems in monitoring recovery after major abdominal surgery.
        Surg Endosc. 2017; 31: 5457-5462
        • Perez MM
        • Gonzalez GV
        • Dafonte C
        The development of an RFID solution to facilitate the traceability of patient and pharmaceutical data.
        Sensors. 2017; 17: 2247
        • Stoller JK
        • Roberts V
        • Matt D
        • Chom L
        • Sasidhar M
        • Chatburn RL
        Radio-frequency tracking of respiratory equipment: rationale and early experience at the Cleveland Clinic.
        Respir Care. 2013; 58: 2069-2075
        • Hsiao RS
        • Kao CH
        • Chen TX
        • Chen JL
        A passive RFID-based location system for personnel and asset monitoring.
        Technol Health Care. 2018; 26: 11-16
        • Cole SL
        • Siddiqui J
        • Harry DJ
        • Sandrock CE
        WiFi RFID demonstration for resource tracking in a statewide disaster drill.
        Am J Disaster Med. 2011; 6: 155-162
        • Lai YL
        • Chou YH
        • Chang LC
        An intelligent IoT emergency vehicle warning system using RFID and WiFi technologies for emergency medical services.
        Technol Health Care. 2017; https://doi.org/10.3233/thc-171405
        • Madanian S
        • Parry D
        • Norris T
        Healthcare in Disasters and the Role of RFID.
        Stud Health Technol Inform. 2015; 216: 1008
        • Steer S
        • Bhalla MC
        • Zalewski J
        • Frey J
        • Nguyen V
        • Mencl F
        Use of radio frequency identification to establish emergency medical service offload times.
        Prehosp Emerg Care. 2016; 20: 254-259
        • Schnock KO
        • Biggs B
        • Fladger A
        • Bates DW
        • Rozenblum R
        Evaluating the impact of radio frequency identification retained surgical instruments tracking on patient safety: literature review.
        J Patient Saf. 2017; (Epub ahead of print. http://dx.doi.org/10.1097/PTS.0000000000000365)
        • Choi WJ
        • Moon JH
        • Min JS
        • et al.
        Real-time detection system for tumor localization during minimally invasive surgery for gastric and colon cancer removal:in vivo feasibility study in a swine model.
        J Surg Oncol. 2017; https://doi.org/10.1002/jso.24922
        • Hendrich A
        • Chow MP
        • Bafna S
        • Choudhary R
        • Heo Y
        • Skierczynski BA
        Unit-related factors that affect nursing time with patients: spatial analysis of the time and motion study.
        HERD. 2009; 2: 5-20
        • Castner J
        • Sullivan SS
        • Titus AH
        • Klingman KJ
        Strengthening the role of nurses in medical device development.
        J Prof Nurs. 2016; 32: 300-305
        • Holden RJ
        • Carayon P
        • Gurses AP
        • et al.
        SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients.
        Ergonomics. 2013; 56: 1669-1686
        • Carayon P
        • Schoofs Hundt A
        • Karsh BT
        • et al.
        Work system design for patient safety: the SEIPS model.
        Qual Saf Health Care. 2006; 15: i50-i58
        • Norten A
        Predicting nurses' acceptance of radiofrequency identification technology.
        Comput Inform Nurs. 2012; 30: 531-537
        • Okoniewska B
        • Graham A
        • Gavrilova M
        • et al.
        Multidimensional evaluation of a radio frequency identification wi-fi location tracking system in an acute-care hospital setting.
        J Am Med Inform Assoc. 2012; 19: 674-679
        • Pineles LL
        • Morgan DJ
        • Limper HM
        • et al.
        Accuracy of a radiofrequency identification (RFID) badge system to monitor hand hygiene behavior during routine clinical activities.
        Am J Infect Control. 2014; 42: 144-147
        • Dao TK
        • Nguyen HL
        • Pham TT
        • Castelli E
        • Nguyen VT
        • Nguyen DV
        User localization in complex environments by multimodal combination of GPS, WiFi, RFID, and pedometer technologies.
        Sci World J. 2014; 2014: 814538
        • Castner J
        • Grinslade S
        • Guay J
        • Hettinger AZ
        • Seo JY
        • Boris L
        Registered nurse scope of practice and ED complaint-specific protocols.
        J Emerg Nurs. 2013; 39 (e3): 467-473
        • Castner J
        • Yin Y
        • Loomis D
        • Hewner S
        Medical Mondays: ED utilization for Medicaid recipients depends on the day of the week, season, and holidays.
        J Emerg Nurs. 2016; 42: 317-324
        • Chang AM
        • Cohen DJ
        • Lin A
        • et al.
        Hospital strategies for reducing emergency department crowding: a mixed-methods study.
        Ann Emerg Med. 2018; 71 (e4): 497-505
        • Brennan PF
        • Bakken S
        Nursing needs big data and big data needs nursing.
        J Nurs Scholarsh. 2015; 47: 477-484
        • Mumma BE
        • McCue JY
        • Li CS
        • Holmes JF
        Effects of emergency department expansion on emergency department patient flow.
        Acad Emerg Med. 2014; 21: 504-509
        • Castner J
        • Suffoletto H
        Radio-frequency time and motion study: the relationship of emergency department crowding, physical workspace, and patient-provider contact.
        Ann Emerg Med. 2012; 60: S52

      Biography

      Jessica Castner, Member, Western New York ENA Chapter, is President, Castner Incorporated; President Healthcare Research Consulting, Inc.; Faculty, D'Youville College School of Nursing; University at Buffalo School of Nursing; School of Public Health and Health Professions, Epidemiology and Environmental Health; Jacobs School of Medicine and Biomedical Sciences, Biomedical Informatics; and School of Engineering and Applied Sciences, Biomedical Engineering, Buffalo, NY.

      Biography

      Heidi Suffoletto is Clinical Assistant Professor at University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Department of Emergency Medicine, Buffalo, NY.