Effects of pruning of a decision-tree for the ear, nose, and throat realm in primary health care based on case-notes.

In the primary health care center of Mjölby a sample of case notes in the ear-nose- and-throat realm (N = 425) was computer processed using an inductive rule-based decision-tree generating program. As a result of incomplete information in the case-files, the decision trees were "noisy," e.g., had branches and leaves without meaning. This led to a need for "pruning." Various methods were tried. The effects of different methods of decision-tree generating and pruning are discussed. The choice of root argument and branching of the decision-trees suggested by the software was the most clinically applicable. The "statistic" approach to pruning gave the most compact and still most clinically relevant decision-tree. The pruned and edited decision trees are compared with a previously published preliminary essential data set for the ear-nose- and-throat realm in primary health care and then discussed as a possible decision support system for various primary health care groups in a practice setting.