Measuring clinician experience in value-based healthcare initiatives: a 10-item core clinician experience measure

Reema Harrison; Louise A Ellis; Maryam Sina; Ramya Walsan; Rebecca Mitchell; Ramesh Walpola; Glen Maberly; Catherine Chan; Liz Hay

doi:10.1071/AH24003

RESEARCH ARTICLE (Open Access)

Previous Next Contents Vol 48(2)

Measuring clinician experience in value-based healthcare initiatives: a 10-item core clinician experience measure

Reema Harrison

^A ^* , Louise A Ellis ^B , Maryam Sina ^A , Ramya Walsan

^A , Rebecca Mitchell ^B , Ramesh Walpola ^C , Glen Maberly ^D , Catherine Chan ^E and Liz Hay ^E

+ Author Affiliations

- Author Affiliations

^A Centre for Health Systems and Safety, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2109, Australia.

^B Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2109, Australia.

^C School of Health Sciences, University of New South Wales, NSW 2052, Australia.

^D Western Sydney Diabetes, Blacktown and Western Sydney Local Health District, NSW 2151, Australia.

^E Strategic Reform Branch, NSW Ministry of Health, Sydney, NSW 2065, Australia.

^* Correspondence to: reema.harrison@mq.edu.au

Australian Health Review 48(2) 160-166 https://doi.org/10.1071/AH24003

Submitted: 8 January 2024 Accepted: 22 February 2024 Published: 12 March 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of AHHA. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Objective

Clinician’s experiences of providing care are identified as a key outcome associated with value-based healthcare (VBHC). In contrast to patient-reported experience measures, measurement tools to capture clinician’s experiences in relation to VBHC initiatives have received limited attention to date. Progressing from an initial 18-item clinician experience measure (CEM), we sought to develop and evaluate the reliability of a set of 10 core clinician experience measure items in the CEM-10.

Methods

A multi-method project was conducted using a consensus workshop with clinicians from a range of NSW Health local health districts to reduce the 18-item CEM to a short form 10-item core clinician experience measure (CEM-10). The CEM-10 was deployed with clinicians providing diabetes care, care for older adults and virtual care across all districts and care settings of New South Wales, Australia. Psychometric analysis was used to determine the internal consistency of the tool and its suitability for diverse clinical contexts.

Results

Consensus building sessions led to a rationalised 10-item tool, retaining the four domains of psychological safety (two items), quality of care (three items), clinician engagement (three items) and interprofessional collaboration (two items). Data from four clinician cohorts (n = 1029) demonstrated that the CEM-10 four-factor model produced a good fit to the data and high levels of reliability, with factor loadings ranging from 0.77 to 0.92, with Cronbach’s alpha (range: 0.79–0.90) and composite reliability (range: 0.80–0.92).

Conclusions

The CEM-10 provides a core set of common clinician experience measurement items that can be used to compare clinician’s experiences of providing care between and within cohorts. The CEM-10 may be supported by additional items relevant to particular initiatives when evaluating VBHC outcomes.

Keywords: clinician experience, measurement, survey, value‐based care, workforce.

References

1 Porter ME. What is value in health care. N Engl J Med 2010; 363(26): 2477-81.
| Crossref | Google Scholar | PubMed |

2 Koff E, Lyons N. Implementing value‐based health care at scale: the NSW experience. Med J Aust 2020; 212(3): 104-6.e1.
| Crossref | Google Scholar | PubMed |

3 Iqbal MP, Manias E, Mimmo L, Mears S, Jack B, Hay L, et al. Clinicians’ experience of providing care: a rapid review. BMC Health Serv Res 2020; 20(1): 1-10.
| Crossref | Google Scholar |

4 NSW Government. About value-based health care. 2023. Available at https://www.health.nsw.gov.au/Value/Pages/about.aspx

5 Sikka R, Morath JM, Leape L. The Quadruple Aim: care, health, cost and meaning in work. BMJ Qual Saf 2015; 24(10): 608-10.
| Crossref | Google Scholar | PubMed |

6 Harrison R, Manias E, Ellis L, Mimmo L, Walpola R, Roxas-Harris B, et al. Evaluating clinician experience in value-based health care: the development and validation of the Clinician Experience Measure (CEM). BMC Health Serv Res 2022; 22(1): 1484.
| Crossref | Google Scholar | PubMed |

7 Dawda P, True A, Dickinson H, Janamian T, Johnson T. Value-based primary care in Australia: how far have we travelled? Med J Aust 2022; 216(S10): S24-7.
| Crossref | Google Scholar | PubMed |

8 NSW Government. Local Health Districts. 2024. Available at: https://www.nsw.gov.au/health/local-health-districts#:~:text=In%20NSW%2C%2015%20local%20health%20districts%20%28LHDs%29%20manage,services%20to%20defined%20geographical%20areas%20across%20the%20state

9 IBM Corp. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp; 2017.

10 Tabachnick BG, Fidell LS. Using multivariate statistics, International edn. Pearson; 2013.

11 Kline RB. Principles and practice of structural equation modeling. Guilford Publications; 2015.

12 McDonald RP, Marsh HW. Choosing a multivariate model: Noncentrality and goodness of fit. Psychol Bull 1990; 107(2): 247.
| Crossref | Google Scholar |

13 Joreskog K, Sorbom D. Structural equation modelling: Guidelines for determining model fit. New York: University Press of America; 1993.

14 Ullman J. Structural equation modeling: In Tabachnick BG, Fidell LS, editors. Using multivariate statistics, 6th edn.Harlow: Pearson Education Limited; 2014. pp. 731–836.

15 Griffin MM, Steinbrecher TD. Large-scale datasets in special education research. Int Rev Res Develop Disabilities 2013; 45: 155-83.
| Google Scholar |

16 Brown TA. Confirmatory factor analysis for applied research. Guilford Publications; 2015.

17 van Diepen C, Fors A, Ekman I, Hensing G. Association between person-centred care and healthcare providers’ job satisfaction and work-related health: a scoping review. BMJ Open 2020; 10(12): e042658.
| Crossref | Google Scholar | PubMed |

18 Jarden RJ, Siegert RJ, Koziol-McLain J, Bujalka H, Sandham MH. Wellbeing measures for workers: a systematic review and methodological quality appraisal. Front Public Health 2023; 11: 1053179.
| Crossref | Google Scholar | PubMed |

19 Edú-Valsania S, Laguía A, Moriano JA. Burnout: A review of theory and measurement. Int J Environ Res Public Health 2022; 19(3): 1780.
| Crossref | Google Scholar | PubMed |

20 Karaferis D, Aletras V, Niakas D. Determining dimensions of job satisfaction in healthcare using factor analysis. BMC Psychol 2022; 10(1): 240.
| Crossref | Google Scholar |

21 NHS Staff Coordination Centre. NHS Staff Surveys. 2023. Available at https://www.nhsstaffsurveys.com/

22 NSW Government Public Service Commission. People Matter Employee Survey. 2023. Available at https://www.psc.nsw.gov.au/reports-and-data/people-matter-employee-survey

23 Victorian Public Sector Commission. About the People matter survey. 2023. Available at https://vpsc.vic.gov.au/data-and-research/about-the-people-matter-survey/