{'fraction_non_alphanumeric': 0.02716914986853637, 'fraction_numerical': 0.0017528483786152498, 'mean_word_length': 5.415730337078652, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Identification of e-Health reference architecture using a bi-objective medical informatics decision support framework: the optimal lean and six sigma alignment

Because of the trade-off between e-Health Lean and Six Sigma, their independent implementation does not ensure the optimality of patient-centric service deliver in e-Health architectures. There is a significant gap in the current research literature to utilize the optimal Lean and Six Sigma alignment in e-Health architectures. Therefore, this paper develops a fuzzy group bi-objective medical informatics decision support framework to optimize Lean and Six Sigma alignment in the identification of e-health reference architecture. As The e-Health architecture is made up of the best-practice e-Health modules and layers, a fuzzy group bi-objective Linear Programming technique for Multidimensional Analysis of Preference (LINMAP) is presented: (1) to demonstrate conformity of core modules and layers of e-Health architectures with Lean criteria and Six Sigma criteria; and (2) to optimize the strategic Lean and Six Sigma alignment and identify e-Health reference architecture.