A unidirectional mapping of ICD-8 to ICD-10 codes, for harmonized longitudinal analysis of diseases.

Periodic revisions of the international classification of diseases (ICD) ensure that the classification reflects new practices and knowledge; however, this complicates retrospective research as diagnoses are coded in different versions. For longitudinal disease trajectory studies, a crosswalk is an essential tool and a comprehensive mapping between ICD-8 and ICD-10 has until now been lacking. In this study, we map all ICD-8 morbidity codes to ICD-10 in the expanded Danish ICD version. We mapped ICD-8 codes to ICD-10, using a many-to-one system inspired by general equivalence mappings such that each ICD-8 code maps to a single ICD-10 code. Each ICD-8 code was manually and unidirectionally mapped to a single ICD-10 code based on medical setting and context. Each match was assigned a score (1 of 4 levels) reflecting the quality of the match and, if applicable, a "flag" signalling choices made in the mapping. We provide the first complete mapping of the 8596 ICD-8 morbidity codes to ICD-10 codes. All Danish ICD-8 codes representing diseases were mapped and 5106 (59.4%) achieved the highest consistency score. Only 334 (3.9%) of the ICD-8 codes received the lowest mapping consistency score. The mapping provides a scaffold for translation of ICD-8 to ICD-10, which enable longitudinal disease studies back to and 1969 in Denmark and to 1965 internationally with further adaption.

Association between antipsychotic drug dose and length of clinical notes: a proxy of disease severity?

BACKGROUND: Most structured clinical data, such as diagnosis codes, are not sufficient to obtain precise phenotypes and assess disease burden. Text mining of clinical notes could provide a basis for detailed profiles of phenotypic traits. The objective of the current study was to determine whether drug dose, regardless of polypharmacy, is associated with the length of clinical notes, and to determine the frequency of adverse events per word in clinical notes. METHODS: In this observational study, we utilized restricted-access data from an electronic patient record system. Using three methods (defined daily dose, olanzapine equivalents, and chlorpromazine equivalents) we calculated antipsychotic dose equivalents and compared these with the number of words recorded per treatment day. For each normalization method, the frequencies of adverse events per word in manually curated samples were compared to dose intervals. RESULTS: The length of clinical notes per treatment day was positively associated with the prescribed dose for all normalization methods. The number of adverse events per word was stable over the analyzed dose spectrum. CONCLUSIONS: Assuming that drug dose increases with the severity of disease, the length of clinical notes can serve as a proxy for disease severity. Due to the near-linear relationship, correction of daily word count is unnecessary when text mining for potential adverse drug reactions.

Sex differences in text-mined possible adverse drug events associated with drugs for psychosis.

BACKGROUND: Understanding sex differences in adverse drug reactions to drugs for psychosis could potentially guide clinicians in optimal drug choices. AIMS: By applying a text-mining approach, this study aimed to investigate the relationship between drugs for psychosis and biological sex differences in frequencies and co-occurrences of potential adverse drug events (ADEs). METHODS: Electronic patient records of a psychiatric population (1427 men and 727 women) were text mined for potential ADEs. The relative risk of experiencing specific ADEs and co-occurrence of ADEs were calculated for each sex. RESULTS: Findings included 55 potential ADEs with significantly different frequencies between the two sexes. Of these, 20 were more frequent in men, with relative risks of 1.10-7.64, and 35 were more frequent in women, with relative risks of 1.19-21.58. Frequent potential ADEs were psychiatric symptoms, including sexual dysfunction and disturbances in men, and gastrointestinal symptoms, suicidal and self-injurious behaviour and hyperprolactinemia-related events in women. Mention of different hyperprolactinemia-related ADEs often co-occurred in female patients but not in male patients. CONCLUSION: Several known sex-related ADEs were identified, as well as some previously not reported. When considering the risk-benefit profile of drugs for psychosis, the patient's sex should be considered.

Population-wide analysis of differences in disease progression patterns in men and women.

Sex-stratified medicine is a fundamentally important, yet understudied, facet of modern medical care. A data-driven model for how to systematically analyze population-wide, longitudinal differences in hospital admissions between men and women is needed. Here, we demonstrate a systematic analysis of all diseases and disease co-occurrences in the complete Danish population using the ICD-10 and Global Burden of Disease terminologies. Incidence rates of single diagnoses are different for men and women in most cases. The age at first diagnosis is typically lower for men, compared to women. Men and women share many disease co-occurrences. However, many sex-associated incongruities not linked directly to anatomical or genomic differences are also found. Analysis of multi-step trajectories uncover differences in longitudinal patterns, for example concerning injuries and substance abuse, cancer, and osteoporosis. The results point towards the need for an increased focus on sex-stratified medicine to elucidate the origins of the socio-economic and ethological differences.