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ABSTRACT: Objective
In preference-sensitive conditions such as back pain, there can be high levels of variability in the trajectory of patient care. We sought to develop a methodology that extracts a realistic and comprehensive understanding of the patient journey using medical and pharmaceutical insurance claims data.Materials and methods
We processed a sample of 10 000 patient episodes (comprised of 113 215 back pain-related claims) into strings of characters, where each letter corresponds to a distinct encounter with the healthcare system. We customized the Levenshtein edit distance algorithm to evaluate the level of similarity between each pair of episodes based on both their content (types of events) and ordering (sequence of events). We then used clustering to extract the main
SUBMITTER: Bobroske K
PROVIDER: S-EPMC7647282 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature