Identifying exceptional cystic fibrosis care services: combining statistical process control with focus groups: Influence Statistics

Expert Impact

Concepts for which they have has direct influence: Cystic fibrosis .

Key People For Cystic Fibrosis

Top KOLs in the world
#1
Bonnie Watts Ramsey
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#2
Michael W Konstan
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#3
Mary L Corey
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Lap‐Chee Tsui
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Felix A Ratjen
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Frank J Accurso
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Identifying exceptional cystic fibrosis care services: combining statistical process control with focus groups

Abstract

. Background The Cystic Fibrosis (CF) Registry collects clinical data on all patients attending specialist CF centres in the UK. These data have been used to make comparisons between centres on key outcomes such as forced expiratory volume in 1 second (FEV 1 ) using simple rankings, which promote the assumption that those with the highest measures provide ‘better’ care. Objectives To explore whether or not using statistical ‘process control’ charts that move away from league tables and adjusting for case mix (age, where appropriate; sex; CF genotype; pancreatic sufficiency; and socioeconomic status) could identify exceptional CF care services in terms of clinically meaningful outcomes. Then, using insight from patients and clinicians on what structures, processes and policies are necessary for delivering good CF care, to explore whether or not care is associated with observed differences in outcomes. Design Cross-sectional analyses. Setting Specialist CF centres in the UK. Participants Patients aged ≥ 6 years attending specialist CF centres and clinicians at these centres. Main outcome measures FEV 1 % predicted. Data sources Annual reviews taken from the UK CF Registry (2007–15). Results We studied FEV 1 in many different ways and in different periods. In our analyses of both adult and paediatric centres, we observed that some centres showed repeated evidence of ‘special-cause variation’, with mean FEV 1 being greater than the mean in some cases and lower than the mean in others. Some of these differences were explained by statistical adjustment for different measures of case mix, such as age, socioeconomic status, genotype and pancreatic sufficiency. After adjustment, there was some remaining evidence of special-cause variation for some centres. Our data at these centres suggest that there may be an association with the use of intravenous antibiotics. Workshops and focus groups with clinicians at paediatric and adult centres identified a number of structures, processes and policies that were felt to be associated with good care. From these, questionnaires for CF centre directors were developed and disseminated. However, the response rate was low, limiting the questionnaires’ use. Focus groups with patients to gain their insights into what is necessary for the delivery of good care identified themes similar to those identified by clinicians, and a patient questionnaire was developed based on these insights. Limitations Our data analyses suggest that differences in intravenous antibiotic usage may be associated with centre-level outcomes; this needs to be explored further in partnership with the centres. Our survey of centre directors yielded a low response, making it difficult to gain useful knowledge to inform further discussions with sites. Conclusions Our findings confirm that the CF Registry can be used to identify differences in clinical outcomes between centres and that case mix might explain some of these differences. As such, adjustment for case mix is essential when trying to understand how and why centres differ from the mean. Future work Future work will involve exploring with clinicians how care is delivered so that we can understand associations between care and outcomes. Patients will also be asked for their perspectives on the care they receive. Funding The National Institute for Health Research Health Services and Delivery Research programme.