TY - CHAP
T1 - Incorporating local information and prior expert knowledge to evidence-informed mental health system research
AU - Salvador-Carulla, Luis
AU - Garcia-Alonso, Carlos
AU - Gibert, Karina
AU - Vázquez-Bourgon, Javier
N1 - Publisher Copyright:
© 2013 by John Wiley & Sons, Ltd. All rights reserved.
PY - 2013/6/12
Y1 - 2013/6/12
N2 - We discuss the problems in limiting the evidence base to randomised controlled trials (RCTs) alone in the evaluation of complex and innovative mental care services and systems. The classical evidence-based care (EBC) approach is characterised by an 'aversion to complexity' which could be identified by four axioms: (a) the experimental method is regarded as the gold standard of EBC, (b) observational data are included in the same dimension of evidence as experimental data, and therefore observational studies are rated in a lower grade than RCT, (c) the use of classical statistics is based on algebraic formalism as the reference techniques for data analysis and (d) expert knowledge is regarded as a source of bias and it is excluded from the data processing. We suggest a new method, the Expert-based Cooperative Analysis (EbCA), as a general framework suitable for research in very complex medical problems aimed at reducing uncertainty and increasing the strength of local decision-making. We present here a case study of its applicability in the analysis of mental health systems. The technical efficiency of the small health areas of Andalusia (Spain) has been studied using Data Envelopment Analysis, Bayesian networks and EbCA. The incorporation of prior expert knowledge, local data and modelling of natural phenomena are critical to ground priority setting and policy formation combined with the traditional evidence-based approach.
AB - We discuss the problems in limiting the evidence base to randomised controlled trials (RCTs) alone in the evaluation of complex and innovative mental care services and systems. The classical evidence-based care (EBC) approach is characterised by an 'aversion to complexity' which could be identified by four axioms: (a) the experimental method is regarded as the gold standard of EBC, (b) observational data are included in the same dimension of evidence as experimental data, and therefore observational studies are rated in a lower grade than RCT, (c) the use of classical statistics is based on algebraic formalism as the reference techniques for data analysis and (d) expert knowledge is regarded as a source of bias and it is excluded from the data processing. We suggest a new method, the Expert-based Cooperative Analysis (EbCA), as a general framework suitable for research in very complex medical problems aimed at reducing uncertainty and increasing the strength of local decision-making. We present here a case study of its applicability in the analysis of mental health systems. The technical efficiency of the small health areas of Andalusia (Spain) has been studied using Data Envelopment Analysis, Bayesian networks and EbCA. The incorporation of prior expert knowledge, local data and modelling of natural phenomena are critical to ground priority setting and policy formation combined with the traditional evidence-based approach.
KW - Evidence-based care
KW - Expert knowledge
KW - Expert-based cooperative analysis
KW - Information systems
KW - Mental health
KW - Randomised controlled trials
KW - RCTs
UR - http://www.scopus.com/inward/record.url?scp=85015433730&partnerID=8YFLogxK
U2 - 10.1002/9781118337981.ch14
DO - 10.1002/9781118337981.ch14
M3 - Chapter
AN - SCOPUS:85015433730
SN - 9781118337974
SP - 211
EP - 228
BT - Improving Mental Health Care
PB - Wiley
ER -