Information heterogeneity between progress notes by physicians and nurses for inpatients with digestive system diseases.

This study focused on the heterogeneity in progress notes written by physicians or nurses. A total of 806 days of progress notes written by physicians or nurses from 83 randomly selected patients hospitalized in the Gastroenterology Department at Kagawa University Hospital from January to December 2021 were analyzed. We extracted symptoms as the International Classification of Diseases (ICD) Chapter 18 (R00-R99, hereinafter R codes) from each progress note using MedNER-J natural language processing software and counted the days one or more symptoms were extracted to calculate the extraction rate. The R-code extraction rate was significantly higher from progress notes by nurses than by physicians (physicians 68.5% vs. nurses 75.2%; p = 0.00112), regardless of specialty. By contrast, the R-code subcategory R10-R19 for digestive system symptoms (44.2 vs. 37.5%, respectively; p = 0.00299) and many chapters of ICD codes for disease names, as represented by Chapter 11 K00-K93 (68.4 vs. 30.9%, respectively; p < 0.001), were frequently extracted from the progress notes by physicians, reflecting their specialty. We believe that understanding the information heterogeneity of medical documents, which can be the basis of medical artificial intelligence, is crucial, and this study is a pioneering step in that direction.

Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET®) in Japan.

BACKGROUND: The Medical Information Database Network (MID-NET®) in Japan is a vast repository providing an essential pharmacovigilance tool. Gastrointestinal perforation (GIP) is a critical adverse drug event, yet no well-established GIP identification algorithm exists in MID-NET®. METHODS: This study evaluated 12 identification algorithms by combining ICD-10 codes with GIP therapeutic procedures. Two sites contributed 200 inpatients with GIP-suggestive ICD-10 codes (100 inpatients each), while a third site contributed 165 inpatients with GIP-suggestive ICD-10 codes and antimicrobial prescriptions. The positive predictive values (PPVs) of the algorithms were determined, and the relative sensitivity (rSn) among the 165 inpatients at the third institution was evaluated. RESULTS: A trade-off between PPV and rSn was observed. For instance, ICD-10 code-based definitions yielded PPVs of 59.5%, whereas ICD-10 codes with CT scan and antimicrobial information gave PPVs of 56.0% and an rSn of 97.0%, and ICD-10 codes with CT scan and antimicrobial information as well as three types of operation codes produced PPVs of 84.2% and an rSn of 24.2%. The same algorithms produced statistically significant differences in PPVs among the three institutions. Combining diagnostic and procedure codes improved the PPVs. The algorithm combining ICD-10 codes with CT scan and antimicrobial information and 80 different operation codes offered the optimal balance (PPV: 61.6%, rSn: 92.4%). CONCLUSION: This study developed valuable GIP identification algorithms for MID-NET®, revealing the trade-offs between accuracy and sensitivity. The algorithm with the most reasonable balance was determined. These findings enhance pharmacovigilance efforts and facilitate further research to optimize adverse event detection algorithms.

Using Natural Language Processing Techniques to Detect Adverse Events From Progress Notes Due to Chemotherapy.

Objective: In recent years, natural language processing (NLP) techniques have progressed, and their application in the medical field has been tested. However, the use of NLP to detect symptoms from medical progress notes written in Japanese, remains limited. We aimed to detect 2 gastrointestinal symptoms that interfere with the continuation of chemotherapy-nausea/vomiting and diarrhea-from progress notes using NLP, and then to analyze factors affecting NLP. Materials and methods: In this study, 200 patients were randomly selected from 5277 patients who received intravenous injections of cytotoxic anticancer drugs at Kagawa University Hospital, Japan, between January 2011 and December 2018. We aimed to detect the first occurrence of nausea/vomiting (Group A) and diarrhea (Group B) using NLP. The NLP performance was evaluated by the concordance with a review of the physicians' progress notes used as the gold standard. Results: Both groups showed high concordance: 83.5% (95% confidence interval [CI] 74.1-90.1) in Group A and 97.7% (95% CI 91.3-99.9) in Group B. However, the concordance was significantly better in Group B (P = .0027). There were significantly more misdetection cases in Group A than in Group B (15.3% in Group A; 1.2% in Group B, P = .0012) due to negative findings or past history. Conclusion: We detected occurrences of nausea/vomiting and diarrhea accurately using NLP. However, there were more misdetection cases in Group A due to negative findings or past history, which may have been influenced by the physicians' more frequent documentation of nausea/vomiting.

Validity of identification algorithms combining diagnostic codes with other measures for acute ischemic stroke in MID-NET®.

PURPOSE: We aimed to develop a reliable identification algorithm combining diagnostic codes with several treatment factors for inpatients with acute ischemic stroke (AIS) to conduct pharmacoepidemiological studies using the administrative database MID-NET® in Japan. METHODS: We validated 11 identification algorithms based on 56 different diagnostic codes (International Classification of Diseases, Tenth Revision; ICD-10) using Diagnosis Procedure Combination (DPC) data combined with information on AIS therapeutic procedures added as "AND" condition or "OR" condition. The target population for this study was 366 randomly selected hospitalized patients with possible cases of AIS, defined as relevant ICD-10 codes and diagnostic imaging and prescription or surgical procedure, in three institutions between April 1, 2015 and March 31, 2017. We determined the positive predictive values (PPVs) of these identification algorithms based on comparisons with a gold standard consisting of chart reviews by experienced specialist physicians. Additionally, the sensitivities of them among 166 patients with the possible cases of AIS at a single institution were evaluated. RESULTS: The PPVs were 0.618 (95% confidence interval [CI]: 0.566-0.667) to 0.909 (95% CI: 0.708-0.989) and progressively increased with adding or limiting information on AIS therapeutic procedures as "AND" condition in the identification algorithms. The PPVs for identification algorithms based on diagnostic codes I63.x were >0.8. However, the sensitivities progressively decreased to a maximum of ~0.2 after adding information on AIS therapeutic procedures as "AND" condition. CONCLUSIONS: The identification algorithms based on the combination of appropriate ICD-10 diagnostic codes in DPC data and other AIS treatment factors may be useful to studies for AIS at a national level using MID-NET®.

Identification of gastrointestinal perforation based on ICD-10 code in a Japanese administrative medical information database and associated drug exposure risk factors.

PURPOSE: The purpose of this study is to evaluate the accuracy of gastrointestinal (GI) perforation ICD-10 coding in the Diagnosis Procedure Combination (DPC) database and to examine drug exposure risk factors for GI perforation. METHODS: A total of 100 patients with GI perforation ICD-10 codes were selected randomly from Kagawa University Hospital's DPC database between April 2011 and December 2016. Two experienced specialist physicians independently reviewed the medical records and classified cases as "definite A," "definite B," "probable," or "no GI perforation." The positive predictive values (PPVs) of "definite A/B" cases were calculated after stratification by sex, age, ICD-10 code, and diagnostic information in the DPC data. The number of prescribed drugs with side effects of GI perforation according to historical data was compared between "definite A/B" and "no GI perforation" cases. RESULTS: The overall PPV was 47.0% (95% confidence interval [CI], 36.9-57.2). However, the PPVs for the three categories of diagnostic information in the DPC data ("main diagnosis," "diagnosis causing admission," and "most resource-intensive diagnosis") were each more than 70% after excluding inappropriate patients. Additionally, the PPV focused on these three categories was 76.3% (95% CI, 59.8-88.6). Prescribed drugs with side effects of GI perforation were more frequently detected in "definite A/B" cases (P = .028). CONCLUSIONS: Although the overall PPV for GI perforation based on ICD-10 code was low, our results suggest that the PPV could be improved by appropriate selection of DPC diagnosis category and that use of multiple medications enhances the risk of GI perforation.

Medication-taking behavior in hypertensive patients with a single-tablet, fixed-dose combination in Japan.

Non-persistence rate (defined as not remaining on treatment) in patients taking a renin angiotensin system inhibitor plus calcium channel blocker was studied in three integrated 12-weeks surveys by matching separate drug combination therapy (CT) and fixed-dose combination (FDC). We also investigated medication adherence measured by proportion of days covered by using a claims database. The non-persistence rate was significantly lower in FDC than CT (p = 0.0074). In the database study, the medication adherence was higher in FDC than CT for 3, 6, and 12 months (all p < 0.001). In conclusion, use of single-tablet FDC antihypertensive therapy was associated with better medication-taking behavior.

Clinical efficacy of long-acting neuraminidase inhibitor laninamivir octanoate hydrate in postmarketing surveillance.

Laninamivir octanoate hydrate (laninamivir) is a long-acting neuraminidase inhibitor which requires only a single inhaled dose to fully treat infection by the influenza virus. In Japan, this drug was launched in October 2010 as a new treatment for the influenza virus. A postmarketing surveillance study was conducted in the 2010/2011 influenza season to assess the efficacy of this drug in clinical settings. For 3542 patients evaluated for efficacy (type A, n = 3179; type B, n = 342, unknown type, n = 3), including the day of drug administration, the median duration to fever resolution was three days, and the median duration to relief from influenza symptoms was four days. Based on the judgment of participating physicians, the efficacy rate was 97.6 % for type A influenza, 93.3 % for type B influenza, and 100 % in unknown types. "Treatment failure," as judged by participating physicians, was most closely correlated with the inhalation status of laninamivir. Despite laninamivir requiring only the administration of a single dose, it was confirmed to be an effective treatment in more than 90 % of patients with type A or type B influenza virus infections. This drug was considered to be useful for the treatment of influenza infections due to ease of use and its improvement of compliance. It became clear that the efficacy of laninamivir depended strongly on the status of inhalation, and thus careful and detailed instructions on the correct method of inhalation were considered to be important in order to obtain reliable therapeutic effects.

Safety of the long-acting neuraminidase inhibitor laninamivir octanoate hydrate in post-marketing surveillance.

Laninamivir octanoate hydrate (laninamivir) is a long-acting neuraminidase inhibitor (NAI) that completes treatment with only a single inhalation. It was launched in Japan in October 2010 as an anti-influenza agent. A post-marketing surveillance study was conducted in the 2010/2011 influenza season to assess the safety of this drug in clinical settings. Adverse drug reactions (ADRs) were observed in 50 patients (59 events) out of 3542 patients subjected to safety evaluation (incidence 1.41%). Commonly reported ADRs were psychiatric disorders (abnormal behaviour, etc.), gastrointestinal disorders (diarrhoea, nausea, etc.) and nervous system disorders (dizziness, etc.), with incidences of 0.48% (n=17), 0.45% (n=16) and 0.17% (n=6), respectively. No serious ADRs occurred. ADRs usually emerged on the day on which laninamivir was inhaled (52.5%) and ADRs emerged within 3 days after inhalation in >90% of adversely affected patients. ADRs resolved or improved within 3 days in >85% of patients. The incidence of adverse events involving abnormal behaviour was 3.1% (30/959) among patients <10 years of age, 0.7% (8/1088) among patients aged 10-19 years, 0.1% (2/1431) among adult patients aged 20-64 years and 0.0% (0/64) among patients aged ≥65 years. It was confirmed that laninamivir is unlikely to cause delayed ADRs or a prolonged duration of ADRs despite this drug being a long-acting NAI. Furthermore, the incidence of ADRs was not found to have increased compared with that observed during clinical trials, and the types of ADR observed during this study were similar to those previously observed. Thus, laninamivir octanoate hydrate was confirmed to have no noticeable problem with safety.