Skip to main content
Top
Published in: BMC Primary Care 1/2016

Open Access 01-12-2016 | Research article

It could be a ‘Golden Goose’: a qualitative study of views in primary care on an emergency admission risk prediction tool prior to implementation

Authors: Alison Porter, Mark Rhys Kingston, Bridie Angela Evans, Hayley Hutchings, Shirley Whitman, Helen Snooks

Published in: BMC Primary Care | Issue 1/2016

Login to get access

Abstract

Background

Rising demand for health care has prompted interest in new technologies to support a shift of care from hospital to community and primary care, which may require clinicians to undertake new working practices. A predictive risk stratification tool (Prism) was developed for use in primary care to estimate patients’ risk of an emergency hospital admission. As part of an evaluation of Prism, we aimed to understand what might be needed to bring Prism into effective use by exploring clinicians and practice managers’ attitudes and expectations about using it. We were informed by Normalisation Process Theory (NPT) which examines the work needed to bring an innovation into use.

Methods

We conducted 4 focus groups and 10 interviews with a total of 43 primary care doctors and colleagues from 32 general practices. All were recorded and transcribed. Analysis focussed in particular on the construct of ‘coherence’ within NPT, which examines how people understand an innovation and its purpose.

Results

Respondents were in agreement that Prism was a technological formalisation of existing practice, and that it would function as a support to clinical judgment, rather than replacing it. There was broad consensus about the role it might have in delivering new models of care based on active management, but there were doubts about the scope for making a difference to some patients and about whether Prism could identify at-risk patients not already known to the clinical team. Respondents did not expect using the tool to be onerous, but were concerned about the work which might follow in delivering care. Any potential value would not be of the tool in isolation, but would depend on the availability of support services.

Conclusions

Policy imperatives and the pressure of rising demand meant respondents were open to trying out Prism, despite underlying uncertainty about what difference it could make.

Trial registration

Controlled Clinical Trials no. ISRCTN55538212.
Footnotes
1
Grimm’s Fairy Tales contain two stories about geese and gold: the goose who lays the golden eggs is the source of undreamt of bounty; but another story has a golden goose to which the unwary stick when they grab it, with unfortunate consequences. We assume that our respondent was thinking of the former.
 
Literature
1.
go back to reference Castro V, McCoy T, Cagan H, Rosenfield H, Murphy S, Churchill S, et al. Stratification of risk for hospital admissions for injury related to fall: cohort study. BMJ. 2014;349:g5863.PubMedCentralCrossRefPubMed Castro V, McCoy T, Cagan H, Rosenfield H, Murphy S, Churchill S, et al. Stratification of risk for hospital admissions for injury related to fall: cohort study. BMJ. 2014;349:g5863.PubMedCentralCrossRefPubMed
2.
go back to reference Janssen K, Vergouwe Y, Kalkman J, Diederick C, Grobbee D, Karel K, et al. A simple method to adjust clinical prediction models to local circumstances. Can J Anesth/J Can Anesth. 2009;56:194–201.CrossRef Janssen K, Vergouwe Y, Kalkman J, Diederick C, Grobbee D, Karel K, et al. A simple method to adjust clinical prediction models to local circumstances. Can J Anesth/J Can Anesth. 2009;56:194–201.CrossRef
3.
go back to reference Lewis G, Curry N, Bardsley M. Choosing a predictive risk model: a guide for commissioners in England. London: The Nuffield Trust; 2011. Lewis G, Curry N, Bardsley M. Choosing a predictive risk model: a guide for commissioners in England. London: The Nuffield Trust; 2011.
4.
go back to reference Georghiou T, Blunt I, Steventon A, Lewis G, Billings J, Bardsley M. Predictive risk and healthcare: an overview. London: The Nuffield Trust; 2011. Georghiou T, Blunt I, Steventon A, Lewis G, Billings J, Bardsley M. Predictive risk and healthcare: an overview. London: The Nuffield Trust; 2011.
5.
go back to reference Curry N, Billings J, Darin B, Dixon J, Williams M, Wennberg D. Predictive Risk Project Literature Review. London: The King’s Fund; 2005. Curry N, Billings J, Darin B, Dixon J, Williams M, Wennberg D. Predictive Risk Project Literature Review. London: The King’s Fund; 2005.
12.
go back to reference Health Dialog, NHS Wales, Informing Healthcare: Wales Predictive Model. Final Report and Technical Documentation. 2008. Health Dialog, NHS Wales, Informing Healthcare: Wales Predictive Model. Final Report and Technical Documentation. 2008.
13.
go back to reference Hutchings H, Evans BA, Fitzsimmons D, Harrison J, Heaven H, Huxley P, et al. Predictive risk stratification model: a progressive cluster-randomised trial in chronic conditions management (PRISMATIC) research protocol. Trials. 2013;14:301.PubMedCentralCrossRefPubMed Hutchings H, Evans BA, Fitzsimmons D, Harrison J, Heaven H, Huxley P, et al. Predictive risk stratification model: a progressive cluster-randomised trial in chronic conditions management (PRISMATIC) research protocol. Trials. 2013;14:301.PubMedCentralCrossRefPubMed
14.
go back to reference Berwick DM. Disseminating innovations in health care. JAMA. 2003;289:1969e75.CrossRef Berwick DM. Disseminating innovations in health care. JAMA. 2003;289:1969e75.CrossRef
15.
go back to reference Ferlie E, Fitzgerald L, Wood M. The nonspread of innovations: the mediating role of professionals. Acad Manag J. 2005;48:117e34.CrossRef Ferlie E, Fitzgerald L, Wood M. The nonspread of innovations: the mediating role of professionals. Acad Manag J. 2005;48:117e34.CrossRef
17.
go back to reference Greenhalgh T, Robert G, Bate P, Kyriakidou O, Macfarlane F, Peacock R. How to spread good ideas: a systematic review of the literature on diffusion, dissemination and sustainability of innovations in health service delivery and organisation. London: National Co-ordinating Centre for NHS Service Delivery and Organisation R & D; 2004. Greenhalgh T, Robert G, Bate P, Kyriakidou O, Macfarlane F, Peacock R. How to spread good ideas: a systematic review of the literature on diffusion, dissemination and sustainability of innovations in health service delivery and organisation. London: National Co-ordinating Centre for NHS Service Delivery and Organisation R & D; 2004.
19.
go back to reference Arce R, De Ormijana A, Orueta J, Gagnon M-P, Nuno-Solinis R. A qualitative study on clinicians’ perceptions about the implementation of a population risk stratification tool in primary care practice of the Basque Health Service. BMC Fam Pract. 2014;15:150.PubMedCentralCrossRef Arce R, De Ormijana A, Orueta J, Gagnon M-P, Nuno-Solinis R. A qualitative study on clinicians’ perceptions about the implementation of a population risk stratification tool in primary care practice of the Basque Health Service. BMC Fam Pract. 2014;15:150.PubMedCentralCrossRef
20.
go back to reference Pope C, Halford S, Turnbull J, Prichard J, Calestani M, May C. Using computer decision support systems in NHS emergency and urgent care: ethnographic study using normalisation process theory. BMC HSR. 2013;13:111. Pope C, Halford S, Turnbull J, Prichard J, Calestani M, May C. Using computer decision support systems in NHS emergency and urgent care: ethnographic study using normalisation process theory. BMC HSR. 2013;13:111.
21.
go back to reference May C, Finch T. Implementation, embedding, and integration: an outline of Normalization Process Theory. Sociology. 2009;43:535–54.CrossRef May C, Finch T. Implementation, embedding, and integration: an outline of Normalization Process Theory. Sociology. 2009;43:535–54.CrossRef
22.
go back to reference McEvoy R, Ballini L, Maltoni S, O’Donnell C, Mair F, MacFarlane A. A qualitative systematic review of studies using the normalization process theory to research implementation processes. Implement Sci. 2014;9:2.PubMedCentralCrossRefPubMed McEvoy R, Ballini L, Maltoni S, O’Donnell C, Mair F, MacFarlane A. A qualitative systematic review of studies using the normalization process theory to research implementation processes. Implement Sci. 2014;9:2.PubMedCentralCrossRefPubMed
23.
go back to reference Murray E, Treweek S, Pope C, MacFarlane A, Ballini L, Dowrick C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med. 2010;8:63.PubMedCentralCrossRefPubMed Murray E, Treweek S, Pope C, MacFarlane A, Ballini L, Dowrick C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med. 2010;8:63.PubMedCentralCrossRefPubMed
24.
go back to reference Moore G, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. ‘Process evaluation of complex interventions: Medical Research Council guidance’. BMJ. 2015;350:h1258.PubMedCentralCrossRefPubMed Moore G, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. ‘Process evaluation of complex interventions: Medical Research Council guidance’. BMJ. 2015;350:h1258.PubMedCentralCrossRefPubMed
25.
go back to reference Bradley EH, Curry LA, Devers KJ. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory. Health Serv Res. 2007;42:1758–72.PubMedCentralCrossRefPubMed Bradley EH, Curry LA, Devers KJ. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory. Health Serv Res. 2007;42:1758–72.PubMedCentralCrossRefPubMed
26.
go back to reference Corbin J, Strauss A. Basics of qualitative research. 3rd ed. San Jose: Sage; 2008. Corbin J, Strauss A. Basics of qualitative research. 3rd ed. San Jose: Sage; 2008.
27.
go back to reference Silverman D. Doing Qualitative Research. 3rd ed. London: Sage; 2010. Silverman D. Doing Qualitative Research. 3rd ed. London: Sage; 2010.
28.
go back to reference Darzi A. High Quality Care for All. London: Department of Health; 2008. Darzi A. High Quality Care for All. London: Department of Health; 2008.
29.
go back to reference Dixon-Woods M, Amalberti R, Goodman S, Bergman B, Glasziou P. Problems and promises of innovation: why healthcare needs to rethink its love/hate relationship with the new. BMJ QualSafe. 2011;20 Suppl 1:i47–51.CrossRef Dixon-Woods M, Amalberti R, Goodman S, Bergman B, Glasziou P. Problems and promises of innovation: why healthcare needs to rethink its love/hate relationship with the new. BMJ QualSafe. 2011;20 Suppl 1:i47–51.CrossRef
30.
go back to reference Elwyn G, Légaré F, van der Weijden T, Edwards A, May C. Arduous implementation: does the Normalisation Process Model explain why it’s so difficult to embed decision support technologies for patients in routine clinical practice. Implement Sci. 2008;3:57.PubMedCentralCrossRefPubMed Elwyn G, Légaré F, van der Weijden T, Edwards A, May C. Arduous implementation: does the Normalisation Process Model explain why it’s so difficult to embed decision support technologies for patients in routine clinical practice. Implement Sci. 2008;3:57.PubMedCentralCrossRefPubMed
31.
go back to reference Lloyd A, Joseph-Williams N, Edwards A, Rix A, Elwyn G. Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC). Implement Sci. 2013;8:102.PubMedCentralCrossRefPubMed Lloyd A, Joseph-Williams N, Edwards A, Rix A, Elwyn G. Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC). Implement Sci. 2013;8:102.PubMedCentralCrossRefPubMed
32.
go back to reference Sanders T, Foster N, Ong BN. Perceptions of general practitioners towards the use of a new system for treating back pain: a qualitative interview study. BMC Med. 2011;9:49.PubMedCentralCrossRefPubMed Sanders T, Foster N, Ong BN. Perceptions of general practitioners towards the use of a new system for treating back pain: a qualitative interview study. BMC Med. 2011;9:49.PubMedCentralCrossRefPubMed
33.
go back to reference Ross S, Curry N, Goodwin N. Case management. What it is and how it can best be implemented. London: The King's Fund; 2011. Ross S, Curry N, Goodwin N. Case management. What it is and how it can best be implemented. London: The King's Fund; 2011.
34.
go back to reference Lewis G. ‘Impactibility models’: identifying the sub-group of high risk patients most amenable to hospital avoidance programs. Milbank Q. 2010;88(2):240–55.PubMedCentralCrossRefPubMed Lewis G. ‘Impactibility models’: identifying the sub-group of high risk patients most amenable to hospital avoidance programs. Milbank Q. 2010;88(2):240–55.PubMedCentralCrossRefPubMed
35.
Metadata
Title
It could be a ‘Golden Goose’: a qualitative study of views in primary care on an emergency admission risk prediction tool prior to implementation
Authors
Alison Porter
Mark Rhys Kingston
Bridie Angela Evans
Hayley Hutchings
Shirley Whitman
Helen Snooks
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Primary Care / Issue 1/2016
Electronic ISSN: 2731-4553
DOI
https://doi.org/10.1186/s12875-015-0398-3

Other articles of this Issue 1/2016

BMC Primary Care 1/2016 Go to the issue