Premium
Decision‐Analytic Modeling to Assist Decision Making in Organizational Innovation: The Case of Shared Care in Hearing Aid Provision
Author(s) -
Grutters Janneke P. C.,
Joore Manuela A.,
Van Der Horst Frans,
Stokroos Robert J.,
Anteunis Lucien J. C.
Publication year - 2008
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/j.1475-6773.2008.00872.x
Subject(s) - probabilistic logic , computer science , knowledge management , principal (computer security) , hearing aid , decision analysis , data extraction , decision model , decision aids , markov decision process , decision support system , management science , medline , medicine , data mining , markov process , machine learning , engineering , artificial intelligence , economics , mathematical economics , political science , law , operating system , statistics , alternative medicine , mathematics , pathology , audiology
Objective. To illustrate the use of decision‐analytic modeling to assist decision making in organizational innovations. Study Setting/Data Sources. Regarding an organizational innovation (shared care in hearing aid provision) available evidence from different sources was synthesized. Study Design. A probabilistic Markov model was constructed. Data Collection/Extraction. We modeled the long‐term cost‐effectiveness of different organizational formats of shared care as opposed to the current organization. We assessed the expected value of perfect information (EVPI) for several groups of parameters in the model. Principal Findings. The current organization had the highest probability of being cost‐effective. Additional research is worthwhile, especially on access to care and safety (sensitivity to detect pathology). Conclusions. Decision‐analytic modeling in an early stage of organizational innovation is a valuable tool to facilitate evidence‐based decision making.