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DOI: 10.1055/s-0042-1756368
Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience
Funding This study was supported by the U.S. Agency for Healthcare Research and Quality (K12HS026370). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The sponsors had no role in the study design, data collection, analysis, writing of the report, or decision to submit the article for publication.![](https://www.thieme-connect.de/media/10.1055-s-00035026/202204/lookinside/thumbnails/10-1055-s-0042-1756368_220049ra-1.jpg)
Abstract
Objectives The purpose of this study is to identify combinations of workplace conditions that uniquely differentiate high, medium, and low registered nurse (RN) ratings of appropriateness of patient assignment during daytime intensive care unit (ICU) work shifts.
Methods A collective case study design and coincidence analysis were employed to identify combinations of workplace conditions that link directly to high, medium, and low RN perception of appropriateness of patient assignment at a mid-shift time point. RN members of the study team hypothesized a set of 55 workplace conditions as potential difference makers through the application of theoretical and empirical knowledge. Conditions were derived from data exported from electronic systems commonly used in nursing care.
Results Analysis of 64 cases (25 high, 24 medium, and 15 low) produced three models, one for each level of the outcome. Each model contained multiple pathways to the same outcome. The model for “high” appropriateness was the simplest model with two paths to the outcome and a shared condition across pathways. The first path comprised of the absence of overtime and a before-noon patient discharge or transfer, and the second path comprised of the absence of overtime and RN assignment to a single ICU patient.
Conclusion Specific combinations of workplace conditions uniquely distinguish RN perception of appropriateness of patient assignment at a mid-shift time point, and these difference-making conditions provide a foundation for enhanced observability of nurses' work experience during hospital work shifts. This study illuminates the complexity of assessing nursing work system status by revealing that multiple paths, comprised of multiple conditions, can lead to the same outcome. Operational decision support tools may best reflect the complex adaptive nature of the work systems they intend to support by utilizing methods that accommodate both causal complexity and equifinality.
Protection of Human and Animal Subjects
This study was approved by the Oregon Health and Science University Institutional Review Board.
Publikationsverlauf
Eingereicht: 05. März 2022
Angenommen: 13. Juli 2022
Artikel online veröffentlicht:
31. August 2022
© 2022. Thieme. All rights reserved.
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References
- 1 Woods D, Branlat M. Basic patterns in how adaptive systems fail. In: Hollnagel E, Paries J, Woods D, Wreathall J. eds. Resilience Engineering in Practice: A Guidebook. U.K.: Taylor & Francis Group; 2011: 127-144
- 2 Oliveira AC, Garcia PC, Nogueira LS. Nursing workload and occurrence of adverse events in intensive care: a systematic review. Rev Esc Enferm USP 2016; 50 (04) 683-694
- 3 Needleman J, Buerhaus P, Pankratz VS, Leibson CL, Stevens SR, Harris M. Nurse staffing and inpatient hospital mortality. N Engl J Med 2011; 364 (11) 1037-1045
- 4 Tubbs-Cooley HL, Mara CA, Carle AC, Mark BA, Pickler RH. Association of nurse workload with missed nursing care in the neonatal intensive care unit. JAMA Pediatr 2019; 173 (01) 44-51
- 5 Bragadóttir H, Kalisch BJ, Tryggvadóttir GB. Correlates and predictors of missed nursing care in hospitals. J Clin Nurs 2017; 26 (11-12): 1524-1534
- 6 Ball JE, Murrells T, Rafferty AM, Morrow E, Griffiths P. ‘Care left undone’ during nursing shifts: associations with workload and perceived quality of care. BMJ Qual Saf 2014; 23 (02) 116-125
- 7 Kalisch BJ, Tschannen D, Lee H, Friese CR. Hospital variation in missed nursing care. Am J Med Qual 2011; 26 (04) 291-299
- 8 Cho E, Lee NJ, Kim EY. et al. Nurse staffing level and overtime associated with patient safety, quality of care, and care left undone in hospitals: a cross-sectional study. Int J Nurs Stud 2016; 60: 263-271
- 9 Sturm H, Rieger MA, Martus P. et al; WorkSafeMed Consortium. Do perceived working conditions and patient safety culture correlate with objective workload and patient outcomes: a cross-sectional explorative study from a German university hospital. PLoS One 2019; 14 (01) e0209487
- 10 Choi J, Miller P. Registered nurse perception of patient assignment linking to working conditions and outcomes. J Nurs Scholarsh 2018; 50 (05) 530-539
- 11 Sir MY, Dundar B, Barker Steege LM, Pasupathy KS. Nurse-patient assignment models considering patient acuity metrics and nurses' perceived workload. J Biomed Inform 2015; 55: 237-248
- 12 Steege LM, Pinekenstein BJ, Rainbow JG, Arsenault Knudsen É. Addressing occupational fatigue in nurses: current state of fatigue risk management in hospitals, part 1. J Nurs Adm 2017; 47 (09) 426-433
- 13 Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA 2002; 288 (16) 1987-1993
- 14 Rushton CH, Batcheller J, Schroeder K, Donohue P. Burnout and resilience among nurses practicing in high-intensity settings. Am J Crit Care 2015; 24 (05) 412-420
- 15 Jones SK, Griep Y. “I can only work so hard before I burn out.” A time sensitive conceptual integration of ideological psychological contract breach, work effort, and burnout. Working Conditions & Industrial Safety 3670. Front Psychol 2018; 9: 131
- 16 See KC, Zhao MY, Nakataki E. et al; SABA Study Investigators and the Asian Critical Care Clinical Trials Group. Professional burnout among physicians and nurses in Asian intensive care units: a multinational survey. Intensive Care Med 2018; 44 (12) 2079-2090
- 17 Holland PJ, Tham TL, Gill FJ. What nurses and midwives want: findings from the national survey on workplace climate and well-being. Int J Nurs Pract 2018; 24 (03) e12630
- 18 Notarnicola I, Petrucci C, De Jesus Barbosa MR. et al. Complex adaptive systems and their relevance for nursing: an evolutionary concept analysis. Int J Nurs Pract 2017;23(03):
- 19 Boustani MA, Munger S, Gulati R, Vogel M, Beck RA, Callahan CM. Selecting a change and evaluating its impact on the performance of a complex adaptive health care delivery system. Clin Interv Aging 2010; 5: 141-148
- 20 Garcia AL. Variability in acuity in acute care. J Nurs Adm 2017; 47 (10) 476-483
- 21 Woods DD. Four concepts for resilience and the implications for the future of resilience engineering. Reliab Eng Syst Saf 2015; 141: 5-9
- 22 Armistead C, Clark G. The “coping” capacity management strategy in services and the influence on quality performance. Int J Serv Ind Manage 1994; 5 (02) 5-22
- 23 Miller A, Buerhaus PI. The changing nature of ICU charge nurses' decision making: from supervision of care delivery to unit resource management. Jt Comm J Qual Patient Saf 2013; 39 (01) 38-47
- 24 Baumgartner M. Uncovering deterministic causal structures: a Boolean approach. Synthese (Dordrecht) 2009; 170 (01) 71-96
- 25 Baumgartner M, Epple R. A coincidence analysis of a causal chain: the Swiss minaret vote. Sociol Methods Res 2014; 43 (02) 280-312
- 26 Yin RK. Case Study Research and Applications: Design and Methods. Sixth ed.. CA: SAGE Publications, Inc.; 2018
- 27 Petrik AF, Green B, Schneider J. et al. Factors influencing implementation of a colorectal cancer screening improvement program in community health centers: an applied use of configurational comparative methods. J Gen Intern Med 2020; 35 (Suppl 2): 815-822
- 28 Yakovchenko V, Miech EJ, Chinman MJ. et al. Strategy configurations directly linked to higher hepatitis C virus treatment starts: an applied use of configurational comparative methods. Med Care 2020; 58 (05) e31-e38
- 29 Thiem A. Conducting configurational comparative research with qualitative comparative analysis: a hands-on tutorial for applied evaluation scholars and practitioners. Am J Eval 2016; 38 (03) 420-433
- 30 Womack D, Warren C, Hayes M, Stoyles S, Eldredge D. Evaluation of electronic health record-generated work intensity scores and nurse perceptions of workload appropriateness. Comput Inform Nurs 2021; 39 (06) 306-311
- 31 Lake ET. Development of the practice environment scale of the Nursing Work Index. Res Nurs Health 2002; 25 (03) 176-188
- 31 Ambuhl M, Barmgartner M. cna: causal modeling with coincidence analysis. R package v 3.0.1. 2020. Accessed August 31, 2022 at: https://CRAN.R-project.org/package=cna
- 33 Hickman SE, Miech EJ, Stump TE, Fowler NR, Unroe KT. Identifying the implementation conditions associated with positive outcomes in a successful nursing facility demonstration project. Gerontologist 2020; 60 (08) 1566-1574
- 34 Rattray NA, Miech EJ, True G. et al. Modeling contingency in veteran community reintegration: a mixed methods approach. J Mixed Methods Res 2022; DOI: 10.1177/15586898211059616.
- 35 Baumgartner M, Thiem A. Model ambiguities in configurational comparative research. Sociol Methods Res 2017; 46 (04) 954-987
- 36 Greckhamer T, Furnari S, Fiss PC, Aguilera RV. Studying configurations with qualitative comparative analysis: best practices in strategy and organization research. Strateg Organ 2018; 16 (04) 482-495
- 37 Hollnagel E. The ETTO Principle Efficiency-Thoroughness Trade-Off—Why Things That Go Right Sometimes Go Wrong. Farnham: Ashgate Publishing Ltd; 2009
- 38 Myny D, Van Hecke A, De Bacquer D. et al. Determining a set of measurable and relevant factors affecting nursing workload in the acute care hospital setting: a cross-sectional study. Int J Nurs Stud 2012; 49 (04) 427-436
- 39 Jennings BM, Sandelowski M, Higgins MK. Turning over patient turnover: an ethnographic study of admissions, discharges, and transfers. Res Nurs Health 2013; 36 (06) 554-566
- 40 Womack DM, Vuckovic NN, Steege LM, Eldredge DH, Hribar MR, Gorman PN. Subtle cues: qualitative elicitation of signs of capacity strain in the hospital workplace. Appl Ergon 2019; 81: 102893
- 41 Monaghan T, Dinour L, Liou D, Shefchik M. Factors influencing the eating practices of hospital nurses during their shifts. Workplace Health Saf 2018; 66 (07) 331-342
- 42 Hollnagel E, Woods DD. Joint Cognitive Systems: Patterns in Cognitive Systems Engineering. Boca Raton: CRC/Taylor & Francis; 2006
- 43 Welton JM, Kleiner C, Valdez C, Richardson S, Boyle K, Lucas E. Using time-referenced data to assess medication administration performance and quality. J Nurs Adm 2018; 48 (02) 100-106
- 44 Chen YF, Armoiry X, Higenbottam C. et al. Magnitude and modifiers of the weekend effect in hospital admissions: a systematic review and meta-analysis. BMJ Open 2019; 9 (06) e025764
- 45 Mosaly PR, Mazur LM, Jones EL. et al. Quantifying the impact of cross coverage on physician's workload and performance in radiation oncology. Pract Radiat Oncol 2013; 3 (04) e179-e186
- 46 Patterson ES, Ebright PR, Saleem JJ. Investigating stacking: how do registered nurses prioritize their activities in real-time?. Int J Ind Ergon 2011; 41 (04) 389-393
- 47 Padgett SM. Professional collegiality and peer monitoring among nursing staff: an ethnographic study. Int J Nurs Stud 2013; 50 (10) 1407-1415
- 48 Steege LM, Rainbow JG. Fatigue in hospital nurses—‘Supernurse’ culture is a barrier to addressing problems: a qualitative interview study. Int J Nurs Stud 2017; 67: 20-28
- 49 Li X, Zhang L, Gong F, Ai Y. Incidence and risk factors for delirium in older patients following intensive care unit admission: a prospective observational study. J Nurs Res 2020; 28 (04) e101
- 50 Nilsson A, Rasmussen BH, Edvardsson D. A threat to our integrity—meanings of providing nursing care for older patients with cognitive impairment in acute care settings. Scand J Caring Sci 2016; 30 (01) 48-56
- 51 Brzozowski SL, Cho H, Arsenault Knudsen EN, Steege LM. Predicting nurse fatigue from measures of work demands. Appl Ergon 2021; 92: 103337
- 52 Womack DM, Hribar MR, Steege LM, Vuckovic NH, Eldredge DH, Gorman PN. Registered nurse strain detection using ambient data: an exploratory study of underutilized operational data streams in the hospital workplace. Appl Clin Inform 2020; 11 (04) 598-605
- 53 Wu DTY, Xu C, Kim A, Bindhu S, Mah KE, Eckman MH. A scoping review of health information technology in clinician burnout. Appl Clin Inform 2021; 12 (03) 597-620