Appl Clin Inform 2015; 06(04): 650-668
DOI: 10.4338/ACI-2015-05-RA-0054
Research Article
Schattauer GmbH

A Method to Evaluate Critical Factors for Successful Implementation of Clinical Pathways

W. Dong
1   Cardiology Department, Chinese PLA General Hospital, Beijing, China
,
Z. Huang
2   College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
› Author Affiliations
Further Information

Correspondence to:

Dr. Zhengxing Huang
College of Biomedical Engineering and Instrument
Science, Zhejiang University
Zhou Yiqin building 512
Zheda road 38
Hangzhou 310008, Zhejiang, China

Publication History

received: 11 May 2015

accepted in revised form: 13 September 2015

Publication Date:
19 December 2017 (online)

 

Summary

Objective: Clinical pathways (CPs) have been viewed as a multidisciplinary tool to improve the quality and efficiency of evidence-based care. Despite widespread enthusiasm for CPs, research has shown that many CP initiatives are unsuccessful. To this end, this study provides a methodology to evaluate critical success factors (CSFs) that can aid healthcare organizations to achieve successful CP implementation.

Design: This study presents a new approach to evaluate CP implementation CSFs, with the aims being: (1) to identify CSFs for implementation of CPs through a comprehensive literature review and interviews with collaborative experts; (2) to use a filed study data with a robust fuzzy DEMATEL (the decision making trial and evaluation laboratory) approach to visualize the structure of complicated causal relationships between CSFs and obtain the influence level of these factors.

Participants: The filed study data is provided by ten clinical experts of a Chinese hospital.

Results: 23 identified CSF factors which are initially identified through a review of the literature and interviews with collaborative experts. Then, a number of direct and indirect relationships are derived from the data such that different perceptions can be integrated into a compromised cause and effect model of CP implementation.

Conclusions: The results indicate that the proposed approach can systematically evaluate CSFs and realize the importance of each factor such that the most common causes of failure of CP implementation could be eliminated or avoided. Therefore, the tool proposed would help healthcare organizations to manage CP implementation in a more effective and proactive way.


#

 


#

Conflicts of interest

The authors declare that they have no competing interests.

  • References

  • 1 Campbell H, Hotchkiss R, Bradshaw N, Porteous M. Integrated care pathways. BMJ 1998; 316 7125 133-137.
  • 2 Hunter B, Segrott J. Re-mapping client journeys and professional identities: a review of the literature on clinical pathways. Int J Nurs Stud 2008; 45 (04) 608-625.
  • 3 Schuld J, Schäfer T, Nickel S, Jacob P, Schilling MK, Richter S. Impact of IT supported clinical pathways on medical staff satisfaction. A prospective longitudinal cohort study. Int J Med Inform 2011; 80 (03) 151-156.
  • 4 Huang Z, Lu X, Duan H. On mining clinical pathway patterns from medical behaviors. Artificial Intelligence in Medicine 2012; 56 (01) 35-50.
  • 5 Huang Z, Lu X, Duan H, Fan W. Summarizing clinical pathways from event logs. Journal of Biomedical Informatics 2013; 46 (Suppl. 01) 111-127.
  • 6 Panella M, Marchisio S, Di Stanislao F. Reducing clinical variations with clinical pathways: do pathways work?. Int J Qual Health Care 2003; 15 (06) 509-521.
  • 7 Huang Z, Lu X, Duan H. Anomaly detection in clinical processes. AMIA Annu Symp Proc 2012; 370-379.
  • 8 Li H. Informationazation is the foundation to achieve the standard management of clinical pathway. China Digit Med 2010; 5 (10) 1.
  • 9 Renholm M, Leino-Kilpi H, Suominen T. Critical pathways: a systematic review. Journal of Nursing Administration 2002; 32 (04) 196-202.
  • 10 Verhelst D, Nachtergaele M, Hindryckx C, Vandevyvere V, Seghers S, Smessaert K, Vanderschueren S. Can a care pathway help streamline the care process for patients with chronic fatigue syndrome?. International Journal of Care Pathways 2011; 15 (04) 115-118.
  • 11 Vanhaecht K, Panella M, Van Zelm R, Sermeus W. Is there a future for pathways? Five pieces of the puzzle. International Journal of Care Pathways 2009; 13 (02) 82-86.
  • 12 Choo J. Critical success factors in implementing clinical pathways/case management. Ann Acad Med Singapore 2001; 30 (04) 17-21.
  • 13 Rotter T, Kinsman L, James EL, Machotta A, Gothe H, Willis J, Snow P, Kugler J. Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs. Eval Health Prof 2012; 35 (01) 3-27.
  • 14 Emmerson B, Frost A, Fawcett L, Ballantyne E, Ward W, Catts S. Do clinical pathways really improve clinical performance in mental health settings?. ” Australasian Psychiatry 2006; 14 (Suppl. 04) 295-398.
  • 15 Shi J, Su Q, Zhao Z. Critical factors for the effectiveness of clinical pathway in improving care outcomes. Service Systems and Service Management 2008; 1-6.
  • 16 Evans-Lacko S, Jarrett M, McCrone P, Thornicroft G. Facilitators and barriers to implementing clinical care pathways. BMC Health Services Research 2010; 10: 182.
  • 17 Pace KB, Sakulkoo S, Hoffart N, Cobb AK. Barriers to successful implementation of a clinical pathway for CHF. Journal for Healthcare Quality 2002; 24 (05) 32-38.
  • 18 Wu WW. Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method. Applied Soft Computing 2012; 12 (01) 527-535.
  • 19 Vanhaecht K, Bollmann M, Bower K, Gallagher C, Gardini A, Guezo J, Jansen U, Massoud R, Moody K, Sermeus W, van Zelm R, Whittle C, Yazbeck AM, Zander K, Panella M. International survey on the use and dissemination of clinical pathways in 23 countries. Journal of Integrated Care Pathways 2006; 10 (01) 28-34.
  • 20 Guo S, Tao H, Qu H, Ke X, Liu P, Liang J. Analysis of key links of the medical service process under the management mode of clinical pathway. Chinese Journal of Hospital Administration 2009; 25 (12) 808-811.
  • 21 Haddock CC, McLean RD. Careers in Healthcare Management: How to Find your Path and Follow It. Chicago: Health Administration Press; 2002
  • 22 Huang Z, Lu X, Duan H, Zhao C. Collaboration-based medical knowledge recommendation. Artificial Intelligence in Medicine 2012; 55 (01) 13-24.
  • 23 Hu P, Wang Y, Lu J, Li D, Zhang W. Impacting factors and suggestions on implementing clinical pathway. Chinese Journal of Hospital Administration 2012; 28 (01) 15-18.
  • 24 Rigby M. Citation Analysis in Health Care Sciences. Methods Inf Med 2014; 53 (06) 459-463.
  • 25 Reeder B, Chung J, Le T, Thompson H, Demiris G. Analytic Hierarchy Process (AHP) for Examining Healthcare Professionals’ Assessments of Risk Factors. Methods Inf Med 2011; 50 (05) 435-444.
  • 26 Abdullah L, Zulkifli N. Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management. Expert Systems with Applications 2015; 42 (09) 4397-4409.
  • 27 Wu WW, Lee YT. Developing global manager’s competencies using the fuzzy EDEMATEL method. Expert Systems with Applications 2007; 32 (02) 499-507.
  • 28 Tseng ML. Using the extension of DEMATEL to integrate hotel service quality perceptions into a cause-effect model in uncertainty. Expert Systems with Applications 2009; 36 (05) 9015-9023.
  • 29 Opricovic S, Tzeng GH. Defuzzification within a multicriteria decision model. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 2003; 11 (05) 635-652.
  • 30 Dai J, Tao HB, Yu Y. The significance and prospects of medical institution surveillance by applying clinical pathways to control medical quality. Chinese Hospital Management 2008; 28 (07) 14-15.
  • 31 Gooch P, Roubsari A. Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems. J Am Med Inform Assoc 2011; 18 (06) 738-748.
  • 32 Defossez G, Rollet A, Dameron O, Ingrand P. Temporal representation of care trajectories of cancer patients using data from a regional information system: An application in breast cancer. BMC Medical Informatics and Decision Making 2014; 14: 24.
  • 33 Huang Z, Dong W, Duan H, Li H. Similarity measure between patient traces for clinical pathway analysis: problem, method, and applications. IEEE J Biomed Health Inform 2014; 18 (01) 4-14.
  • 34 Huang Z, Dong W, Ji L, Gan C, Lu X, Duan H. Discovery of clinical pathway patterns from event logs using probabilistic topic models. J Biomed Inform 2014; 47: 39-57.
  • 35 Sung K, Chung C, Lee K, Lee S, Ahn S, Park S, Choi I, Cho TJ, Yoo W, Lee J, Park M. Application of clinical pathway using electronic medical record system in pediatric patients with supracondylar fracture of the humerus: a before and after comparative study. BMC Medical Informatics and Decision Making 2013; 13: 87.
  • 36 Huang Z, Dong W, Bath P, Ji L, Duan H. On mining latent treatment patterns from electronic medical records. Data Mining and Knowledge Discovery 2015; 29 (04) 914-949.
  • 37 Patil SK, Kant R. A hybrid approach based on fuzzy DEMATEL and FMCDM to predict success of knowledge management adoption in supply chain. Applied Soft Computing 2014; 18: 126-135.
  • 38 Abdekhoda M, Ahmadi M, Dehnad A, Hosseini AF. Information Technology Acceptance in Health Information Management. Methods Inf Med 2014; 53 (01) 14-20.
  • 39 Govindan K, Khodaverdi R, Vafadarnikjoo A. Intuitionistic fuzzy based DEMATEL method for developing green practices and performance in a green supply chain. Expert Systems with Applications 2015; 42 (20) 7207-7220.
  • 40 Li Y, Hu Y, Zhang X, Deng Y, Mahadevan S. An evidential DEMATEL method to identify critical success factors in emergency management. Applied Soft Computing 2014; 22: 504-510.

Correspondence to:

Dr. Zhengxing Huang
College of Biomedical Engineering and Instrument
Science, Zhejiang University
Zhou Yiqin building 512
Zheda road 38
Hangzhou 310008, Zhejiang, China

  • References

  • 1 Campbell H, Hotchkiss R, Bradshaw N, Porteous M. Integrated care pathways. BMJ 1998; 316 7125 133-137.
  • 2 Hunter B, Segrott J. Re-mapping client journeys and professional identities: a review of the literature on clinical pathways. Int J Nurs Stud 2008; 45 (04) 608-625.
  • 3 Schuld J, Schäfer T, Nickel S, Jacob P, Schilling MK, Richter S. Impact of IT supported clinical pathways on medical staff satisfaction. A prospective longitudinal cohort study. Int J Med Inform 2011; 80 (03) 151-156.
  • 4 Huang Z, Lu X, Duan H. On mining clinical pathway patterns from medical behaviors. Artificial Intelligence in Medicine 2012; 56 (01) 35-50.
  • 5 Huang Z, Lu X, Duan H, Fan W. Summarizing clinical pathways from event logs. Journal of Biomedical Informatics 2013; 46 (Suppl. 01) 111-127.
  • 6 Panella M, Marchisio S, Di Stanislao F. Reducing clinical variations with clinical pathways: do pathways work?. Int J Qual Health Care 2003; 15 (06) 509-521.
  • 7 Huang Z, Lu X, Duan H. Anomaly detection in clinical processes. AMIA Annu Symp Proc 2012; 370-379.
  • 8 Li H. Informationazation is the foundation to achieve the standard management of clinical pathway. China Digit Med 2010; 5 (10) 1.
  • 9 Renholm M, Leino-Kilpi H, Suominen T. Critical pathways: a systematic review. Journal of Nursing Administration 2002; 32 (04) 196-202.
  • 10 Verhelst D, Nachtergaele M, Hindryckx C, Vandevyvere V, Seghers S, Smessaert K, Vanderschueren S. Can a care pathway help streamline the care process for patients with chronic fatigue syndrome?. International Journal of Care Pathways 2011; 15 (04) 115-118.
  • 11 Vanhaecht K, Panella M, Van Zelm R, Sermeus W. Is there a future for pathways? Five pieces of the puzzle. International Journal of Care Pathways 2009; 13 (02) 82-86.
  • 12 Choo J. Critical success factors in implementing clinical pathways/case management. Ann Acad Med Singapore 2001; 30 (04) 17-21.
  • 13 Rotter T, Kinsman L, James EL, Machotta A, Gothe H, Willis J, Snow P, Kugler J. Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs. Eval Health Prof 2012; 35 (01) 3-27.
  • 14 Emmerson B, Frost A, Fawcett L, Ballantyne E, Ward W, Catts S. Do clinical pathways really improve clinical performance in mental health settings?. ” Australasian Psychiatry 2006; 14 (Suppl. 04) 295-398.
  • 15 Shi J, Su Q, Zhao Z. Critical factors for the effectiveness of clinical pathway in improving care outcomes. Service Systems and Service Management 2008; 1-6.
  • 16 Evans-Lacko S, Jarrett M, McCrone P, Thornicroft G. Facilitators and barriers to implementing clinical care pathways. BMC Health Services Research 2010; 10: 182.
  • 17 Pace KB, Sakulkoo S, Hoffart N, Cobb AK. Barriers to successful implementation of a clinical pathway for CHF. Journal for Healthcare Quality 2002; 24 (05) 32-38.
  • 18 Wu WW. Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method. Applied Soft Computing 2012; 12 (01) 527-535.
  • 19 Vanhaecht K, Bollmann M, Bower K, Gallagher C, Gardini A, Guezo J, Jansen U, Massoud R, Moody K, Sermeus W, van Zelm R, Whittle C, Yazbeck AM, Zander K, Panella M. International survey on the use and dissemination of clinical pathways in 23 countries. Journal of Integrated Care Pathways 2006; 10 (01) 28-34.
  • 20 Guo S, Tao H, Qu H, Ke X, Liu P, Liang J. Analysis of key links of the medical service process under the management mode of clinical pathway. Chinese Journal of Hospital Administration 2009; 25 (12) 808-811.
  • 21 Haddock CC, McLean RD. Careers in Healthcare Management: How to Find your Path and Follow It. Chicago: Health Administration Press; 2002
  • 22 Huang Z, Lu X, Duan H, Zhao C. Collaboration-based medical knowledge recommendation. Artificial Intelligence in Medicine 2012; 55 (01) 13-24.
  • 23 Hu P, Wang Y, Lu J, Li D, Zhang W. Impacting factors and suggestions on implementing clinical pathway. Chinese Journal of Hospital Administration 2012; 28 (01) 15-18.
  • 24 Rigby M. Citation Analysis in Health Care Sciences. Methods Inf Med 2014; 53 (06) 459-463.
  • 25 Reeder B, Chung J, Le T, Thompson H, Demiris G. Analytic Hierarchy Process (AHP) for Examining Healthcare Professionals’ Assessments of Risk Factors. Methods Inf Med 2011; 50 (05) 435-444.
  • 26 Abdullah L, Zulkifli N. Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management. Expert Systems with Applications 2015; 42 (09) 4397-4409.
  • 27 Wu WW, Lee YT. Developing global manager’s competencies using the fuzzy EDEMATEL method. Expert Systems with Applications 2007; 32 (02) 499-507.
  • 28 Tseng ML. Using the extension of DEMATEL to integrate hotel service quality perceptions into a cause-effect model in uncertainty. Expert Systems with Applications 2009; 36 (05) 9015-9023.
  • 29 Opricovic S, Tzeng GH. Defuzzification within a multicriteria decision model. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 2003; 11 (05) 635-652.
  • 30 Dai J, Tao HB, Yu Y. The significance and prospects of medical institution surveillance by applying clinical pathways to control medical quality. Chinese Hospital Management 2008; 28 (07) 14-15.
  • 31 Gooch P, Roubsari A. Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems. J Am Med Inform Assoc 2011; 18 (06) 738-748.
  • 32 Defossez G, Rollet A, Dameron O, Ingrand P. Temporal representation of care trajectories of cancer patients using data from a regional information system: An application in breast cancer. BMC Medical Informatics and Decision Making 2014; 14: 24.
  • 33 Huang Z, Dong W, Duan H, Li H. Similarity measure between patient traces for clinical pathway analysis: problem, method, and applications. IEEE J Biomed Health Inform 2014; 18 (01) 4-14.
  • 34 Huang Z, Dong W, Ji L, Gan C, Lu X, Duan H. Discovery of clinical pathway patterns from event logs using probabilistic topic models. J Biomed Inform 2014; 47: 39-57.
  • 35 Sung K, Chung C, Lee K, Lee S, Ahn S, Park S, Choi I, Cho TJ, Yoo W, Lee J, Park M. Application of clinical pathway using electronic medical record system in pediatric patients with supracondylar fracture of the humerus: a before and after comparative study. BMC Medical Informatics and Decision Making 2013; 13: 87.
  • 36 Huang Z, Dong W, Bath P, Ji L, Duan H. On mining latent treatment patterns from electronic medical records. Data Mining and Knowledge Discovery 2015; 29 (04) 914-949.
  • 37 Patil SK, Kant R. A hybrid approach based on fuzzy DEMATEL and FMCDM to predict success of knowledge management adoption in supply chain. Applied Soft Computing 2014; 18: 126-135.
  • 38 Abdekhoda M, Ahmadi M, Dehnad A, Hosseini AF. Information Technology Acceptance in Health Information Management. Methods Inf Med 2014; 53 (01) 14-20.
  • 39 Govindan K, Khodaverdi R, Vafadarnikjoo A. Intuitionistic fuzzy based DEMATEL method for developing green practices and performance in a green supply chain. Expert Systems with Applications 2015; 42 (20) 7207-7220.
  • 40 Li Y, Hu Y, Zhang X, Deng Y, Mahadevan S. An evidential DEMATEL method to identify critical success factors in emergency management. Applied Soft Computing 2014; 22: 504-510.