Multi-Criteria Decision Analysis (MCDA) as the basis for thedevelopment, implementation and evaluation of interactive patientdecision aids

Abstract

BACKGROUND: In the context of the progressive movement towards patientcentred care, patient-specific decision support is an important focus of interest. Many diagnostic and treatment patient decision aids (PDAs) are now available to help patients make informed choice decisions. An increasing number of these are software-based, with some available online. Multi-Criteria Decision Analysis (MCDA) is a potentially useful technique on which to base a software-assisted PDA, especially when the decision is complex - as is the case in choosing the best treatment for non-small cell lung cancer – but it has so far been relatively little exploited in this area. The use of any from a number of existing MCDA-based software applications in the development and delivery of a MCDA-based interactive PDA can be an effective way of achieving “best-practice” or normative standards of decision making, such as 1) a well-constructed set of decision criteria or 2) logically consistent patient preferences. However, it also involves the use of resources such as the time and cognitive effort involved in decision-making. The comparative evaluation of alternative MCDA-based software applications in developing and delivering a PDA therefore involves trade-offs between decision effectiveness and decision resource criteria moving from the normative to the prescriptive. MCDA is an ideal tool for this meta-evaluation task as well as for the adoption decision itself. AIM: To analyse, as proof of concept, the use of MCDA for the development, implementation and evaluation of interactive PDAs in routine clinical practice. OBJECTIVES: 1. To assess the use with clinicians in the Spanish NHS of two alternative MCDA software applications which implement dissimilar MCDA techniques in the development of a PDA in routine clinical practice; 2. To assess the use with clinicians in the Spanish NHS of the same two alternative MCDA software applications in the implementation of a PDA in an environment replicating actual clinical consultations; 3. To build a meta-multi-criteria decision model based on the Decision Resources Decision Effectiveness Analysis (DRDEA) framework and assess the use of this model by clinicians in the Spanish NHS to make the choice between the two MCDA applications as the basis for a PDA. METHODS: 1) Two dissimilar MCDA software applications served as a basis for the development of a lung cancer clinical management PDA in close collaboration with two different groups of three clinicians from two different Spanish NHS hospitals (H1 and H2): 1) Expert Choice, which implements the Analytic Hierarchy Process (AHP) MCDA approach; 2) Annalisa in Elicia (ALEL), which implements the Simple Attribute Weighting (SAW) MCDA approach. The process of codevelopment of the PDA in hospitals H1 and H2 was documented; 2) Expert Choice was used to implement (i.e. deliver) the lung cancer clinical management PDA in three hypothetical consultations in hospital H1. In each consultation, one of the three clinicians involved in the development of the tool, with support by this researcher, guided a proxy patient (a non-clinical member of hospital staff) through the PDA. The same process was repeated with the MCDA software ALEL in hospital H2. The process of delivery of the PDA in hospitals H1 and H2 was documented; 3) This researcher built a meta-multi-criteria decision model based on the DRDEA framework to help clinicians choose between different MCDA software applications as the basis of a PDA. The MCDA approach used for this meta-model was Multi- Attribute Value Theory (MAVT). The model was implemented, using the software HiView 3, with three clinicians from hospital H3 for the choice between Expert Choice and ALEL as the basis of a lung cancer clinical management PDA. RESULTS: The thesis makes a three-fold contribution to research in patient-centred decision support. First, it presents two new MCDA software-based approaches to clinical decision support, based on joint work with clinicians in the Spanish NHS, for developing an interactive PDA for the clinical management of non-small cell lung cancer. Second, it describes the use of these decision support tools in the delivery of 5 an interactive PDA for the clinical management of non-small cell lung cancer in a hospital environment via simulated consultations between actual clinicians, with support from this researcher, and proxy lung cancer patients. Third, it presents and applies a new MCDA-based methodology for evaluating the use of alternative MCDA software applications in the development and delivery of interactive PDAs.