The aim of this study was to evaluate the concordance between claims records in the National Health Insurance Research Database and patient self-reports on clinical diagnoses, medication use, and ...health system utilization.
In this study, we used the data of 15,574 participants collected from the 2005 Taiwan National Health Interview Survey. We assessed positive agreement, negative agreement, and Cohen's kappa statistics to examine the concordance between claims records and patient self-reports.
Kappa values were 0.43, 0.64, and 0.61 for clinical diagnoses, medication use, and health system utilization, respectively. Using a strict algorithm to identify the clinical diagnoses recorded in claims records could improve the negative agreement; however, the effect on positive agreement and kappa was diverse across various conditions.
We found that the overall concordance between claims records in the National Health Insurance Research Database and patient self-reports in the Taiwan National Health Interview Survey was moderate for clinical diagnosis and substantial for both medication use and health system utilization.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Antipsychotics have been linked to prolongation of the QT interval. However, little is known about the risk of ventricular arrhythmia (VA) and/or sudden cardiac death (SCD) associated with individual ...antipsychotic drug use. This study was designed to investigate the association between specific antipsychotic drugs and the risk of VA and/or SCD.
We conducted a case-crossover study using a nation-wide population-based sample obtained from Taiwan's National Health Insurance Research Database. A total of 17 718 patients with incident VA and/or SCD were enrolled. Conditional logistic regression models were applied to examine the effects of antipsychotic drug use on the risk of VA/SCD during various case and control time windows of 7, 14, and 28 days. The effect of the potency of a human ether-à-go-go-related gene (hERG) potassium channel blockade was also assessed. Antipsychotic drug use was associated with a 1.53-fold increased risk of VA and/or SCD. Antipsychotic drugs with increased risk included clothiapine, haloperidol, prochlorperazine, thioridazine, olanzapine, quetiapine, risperidone, and sulpiride. The association was significantly higher among those with short-term use. Antipsychotics with a high potency of the hERG potassium channel blockade had the highest risk of VA and/or SCD.
Use of antipsychotic drugs is associated with an increased risk of VA and/or SCD. Careful evaluations of the risks and benefits of antipsychotic treatment are highly recommended.
•The accuracy of the diagnostic code in Taiwan's claims database for major depressive disorder, schizophrenia, and dementia was acceptable.•Text mining approach could extract depressive symptoms ...almost perfectly but not functional impairment.•Using text mining approach to identify major depressive disorder, the sensitivity was acceptable but precision was less satisfactory.
Many studies have used Taiwan's National Health Insurance Research database (NHIRD) to conduct psychiatric research. However, the accuracy of the diagnostic codes for psychiatric disorders in NHIRD is not validated, and the symptom profiles are not available either. This study aimed to evaluate the accuracy of diagnostic codes and use text mining to extract symptom profile and functional impairment from electronic health records (EHRs) to overcome the above research limitations.
A total of 500 discharge notes were randomly selected from a medical center's database. Three annotators reviewed the notes to establish gold standards. The accuracy of diagnostic codes for major psychiatric illness was evaluated. Text mining approaches were applied to extract depressive symptoms and function profiles and to identify patients with major depressive disorder.
The accuracy of the diagnostic code for major depressive disorder, schizophrenia, and dementia was acceptable but that of bipolar disorder and minor depression was less satisfactory. The performance of text mining approach to recognize depressive symptoms is satisfactory; however, the recall for functional impairment is lower resulting in lower F-scores of 0.774–0.753. Using the text mining approach to identify major depressive disorder, the recall was 0.85 but precision was only 0.69.
The accuracy of the diagnostic code for major depressive disorder in discharge notes was generally acceptable. This finding supports the utilization of psychiatric diagnoses in claims databases. The application of text mining to EHRs might help in overcoming current limitations in research using claims databases.
A series of new 2,2fluorenophanes has been synthesized and characterized; among them, molecules of crystallographically asymmetric anti‐2.2(1,4)(4,1)fluorenophane (K2C‐2) aggregate to form ...one‐dimensional supramolecular chain structures through effective intermolecular π‐π overlapping. This, in combination with the synergistic intramolecular π‐π interaction, leads to prominent dual emission mediated by charge transfer (CT) exciton delocalization. Support of this new insight is given by mapping the transition density along the π‐π packing direction where the intramolecular excitation and intermolecular CT coexist in K2C‐2.
Excitation, delocalization, emission: Molecules of crystallographically asymmetric anti‐2.2(1,4)(4,1)fluorenophane (K2C‐2) aggregate to form one‐dimensional supramolecular chain structures through effective intermolecular π‐π overlapping. Crystals exhibit prominent dual emission caused by the intramolecular excitation and intermolecular charge transfer‐mediated exciton delocalization along the π‐π packing direction.
Major depressive disorder (MDD), anxiety disorders, and somatic symptom disorder (SSD) are associated with quality of life (QoL) reduction. This cross-sectional study investigated the relationship ...between these conditions as categorical diagnoses and related psychopathologies with QoL, recognizing their frequent overlap.
We recruited a total of 403 clinical patients and healthy individuals, administering diagnostic interviews based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. QoL and psychopathologies were assessed using the WHO Quality of Life-BREF (WHOQOL-BREF) and several self-administered questionnaires, respectively. Multiple linear regression analyses examined the associations between psychiatric diagnoses, psychopathologies, and QoL.
SSD and MDD were independently associated with impaired global (β = −0.318 and − 0.287) and all QoL domains (β = −0.307, −0.150, −0.125, and − 0.133, in physical, psychological, social, and environmental domains respectively for SSD; β = −0.278, −0.344, −0.275, and − 0.268 for MDD). The Beck Depression Inventory-II score showed pervasive associations with QoL (β = −0.390, −0.408, −0.685, −0.463, and − 0.420, in global, physical, psychological, social, and environmental domains). The Patient Health Questionnaire-15 and Health Anxiety Questionnaire scores were associated with global (β = −0.168 and − 0.181) and physical (β = −0.293 and − 0.121) QoL domain, while the Cognitions About Body and Health Questionnaire score was only associated with environmental QoL domain (β = −0.157).
SSD and MDD were independently associated with QoL impairment. Depressive symptoms were associated with all QoL domains, whereas somatic symptom burden and health anxiety primarily affected the physical QoL domain. Clinicians should consider concomitant psychopathologies when managing patients with depression, anxiety, or somatic symptoms.
•SSD was associated with impairment across all domains of WHOQOL-BREF.•MDD and BDI-II were associated with all domains of QoL impairment.•The PHQ-15 and HAQ were associated with global/physical domains of QoL impairment.
Rodent infestations are a common problem that can result in several issues, including diseases, damage to property, and crop loss. Conventional methods of controlling rodent infestations often ...involve using mousetraps and applying rodenticides manually, leading to high manpower expenses and environmental pollution. To address this issue, we introduce a system for remotely monitoring rodent infestations using Internet of Things (IoT) nodes equipped with Long Range (LoRa) modules. The sensing nodes wirelessly transmit data related to rodent activity to a cloud server, enabling the server to provide real-time information. Additionally, this approach involves using images to auxiliary detect rodent activity in various buildings. By capturing images of rodents and analyzing their behavior, we can gain insight into their movement patterns and activity levels. By visualizing the recorded information from multiple nodes, rodent control personnel can analyze and address infestations more efficiently. Through the digital and quantitative sensing technology proposed at this stage, it can serve as a new objective indicator before and after the implementation of medication or other prevention and control methods. The hardware cost for the proposed system is approximately USD 43 for one sensor module and USD 17 for one data collection gateway (DCG). We also evaluated the power consumption of the sensor module and found that the 3.7 V 18,650 Li-ion batteries in series can provide a battery life of two weeks. The proposed system can be combined with rodent control strategies and applied in real-world scenarios such as restaurants and factories to evaluate its performance.
Individuals with autism spectrum disorder are often diagnosed with at least one or more accompanying disorders. Most studies reported prevalence of the psychiatric comorbidities among these ...individuals; however, the incidence of developing comorbidities is unclear. This study used Taiwan's claims database and aimed to investigate the incidence of developing major psychiatric comorbidities in individuals with autism spectrum disorder and whether the incidence was moderated by gender, autism‐spectrum disorder subtypes, and autism‐associated neurodevelopmental conditions. A total of 3,837 individuals with autism spectrum disorder (2,929 autistic disorder, 447 Asperger syndrome, 461 pervasive developmental disorder‐not otherwise specified) and 38,370 comparison subjects, who were matched by age and gender, were included. The incidences of schizophrenia spectrum, bipolar, and major depressive disorders was examined. The results showed that the incidences of schizophrenia spectrum (9.7 per 1,000 person‐year), bipolar disorder (7.0 per 1,000 person‐year), and major depressive disorder (3.2 per 1,000 person‐year) were significantly higher than the comparison group across all three subtypes of autism‐spectrum disorder. Individuals with pervasive developmental disorder‐not otherwise specified had higher risk for major depressive disorder than autistic disorder. Females with Asperger syndrome had significant higher risk for schizophrenia spectrum than males. The comorbidity rate dramatically dropped when the autism‐associated neurodevelopmental conditions were taken into account. Our findings suggested that the incidences of major psychiatric comorbidities were higher in autism spectrum disorder and influenced by autism subtypes, gender, and autism‐associated neurodevelopmental conditions.
Lay Summary
We examined whether people with autism spectrum disorder (ASD) have higher incidence of schizophrenia, bipolar disorders, and major depression using a large claims database. The results showed the incidences of these mental illness among individual with ASD were significantly higher than those without ASD. In addition, the incidences were influenced by autism subtypes, gender, and comorbid neurodevelopmental conditions.
The widespread use of electronic health records in the clinical and biomedical fields makes the removal of protected health information (PHI) essential to maintain privacy. However, a significant ...portion of information is recorded in unstructured textual forms, posing a challenge for deidentification. In multilingual countries, medical records could be written in a mixture of more than one language, referred to as code mixing. Most current clinical natural language processing techniques are designed for monolingual text, and there is a need to address the deidentification of code-mixed text.
The aim of this study was to investigate the effectiveness and underlying mechanism of fine-tuned pretrained language models (PLMs) in identifying PHI in the code-mixed context. Additionally, we aimed to evaluate the potential of prompting large language models (LLMs) for recognizing PHI in a zero-shot manner.
We compiled the first clinical code-mixed deidentification data set consisting of text written in Chinese and English. We explored the effectiveness of fine-tuned PLMs for recognizing PHI in code-mixed content, with a focus on whether PLMs exploit naming regularity and mention coverage to achieve superior performance, by probing the developed models' outputs to examine their decision-making process. Furthermore, we investigated the potential of prompt-based in-context learning of LLMs for recognizing PHI in code-mixed text.
The developed methods were evaluated on a code-mixed deidentification corpus of 1700 discharge summaries. We observed that different PHI types had preferences in their occurrences within the different types of language-mixed sentences, and PLMs could effectively recognize PHI by exploiting the learned name regularity. However, the models may exhibit suboptimal results when regularity is weak or mentions contain unknown words that the representations cannot generate well. We also found that the availability of code-mixed training instances is essential for the model's performance. Furthermore, the LLM-based deidentification method was a feasible and appealing approach that can be controlled and enhanced through natural language prompts.
The study contributes to understanding the underlying mechanism of PLMs in addressing the deidentification process in the code-mixed context and highlights the significance of incorporating code-mixed training instances into the model training phase. To support the advancement of research, we created a manipulated subset of the resynthesized data set available for research purposes. Based on the compiled data set, we found that the LLM-based deidentification method is a feasible approach, but carefully crafted prompts are essential to avoid unwanted output. However, the use of such methods in the hospital setting requires careful consideration of data security and privacy concerns. Further research could explore the augmentation of PLMs and LLMs with external knowledge to improve their strength in recognizing rare PHI.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
AbstractObjectiveTo investigate the associations between exposure to antenatal corticosteroids and serious infection in children during the first three, six, and 12 months of life.DesignNationwide ...cohort study.SettingNational Health Insurance Research Database, Birth Reporting Database, and Maternal and Child Health Database, 1 January 2008 to 31 December 2019, to identify all pregnant individuals and their offspring in Taiwan.Participants1 960 545 pairs of pregnant individuals and their singleton offspring. 45 232 children were exposed and 1 915 313 were not exposed to antenatal corticosteroids.Main outcome measuresIncidence rates were estimated for overall serious infection, sepsis, pneumonia, acute gastroenteritis, pyelonephritis, meningitis or encephalitis, cellulitis or soft tissue infection, septic arthritis or osteomyelitis, and endocarditis during the first three, six, and 12 months of life in children exposed versus those not exposed to antenatal corticosteroids. Cox proportional hazards models were performed to quantify adjusted hazard ratios with 95% confidence intervals for each study outcome.ResultsThe study cohort was 1 960 545 singleton children: 45 232 children were exposed to one course of antenatal corticosteroids and 1 915 313 children were not exposed to antenatal corticosteroids. The adjusted hazard ratios for overall serious infection, sepsis, pneumonia, and acute gastroenteritis among children exposed to antenatal corticosteroids were significantly higher than those not exposed to antenatal corticosteroids during the first six months of life (adjusted hazard ratio 1.32, 95% confidence interval 1.18 to 1.47, P<0.001, for overall serious infection; 1.74, 1.16 to 2.61, P=0.01, for sepsis; 1.39, 1.17 to 1.65, P<0.001, for pneumonia; and 1.35, 1.10 to 1.65, P<0.001, for acute gastroenteritis).Similarly, the adjusted hazard ratios for overall serious infection (P<0.001), sepsis (P=0.02), pneumonia (P<0.001), and acute gastroenteritis (P<0.001) were significantly higher from birth to 12 months of life. In the sibling matched cohort, the results were comparable with those observed in the whole cohort, with a significantly increased risk of sepsis in the first six (P=0.01) and 12 (P=0.04) months of life.ConclusionsThis nationwide cohort study found that children exposed to one course of antenatal corticosteroids were significantly more likely to have an increased risk of serious infection during the first 12 months of life. These findings suggest that before starting treatment, the long term risks of rare but serious infection associated with antenatal corticosteroids should be carefully weighed against the benefits in the perinatal period.
Background
The co‐occurrence of depression and diabetes mellitus has been linked to an increased risk of developing cancer. This study aimed to investigate whether depression further amplifies the ...risk of cancer among individuals with diabetes.
Methods
This population‐based matched cohort study utilized Taiwan's National Health Insurance claims database. A total of 85,489 newly diagnosed diabetic patients with depressive disorders were selected, along with 427,445 comparison subjects. The matching process involved age, sex, and the calendar year of diabetes onset. The average follow‐up duration for the two cohorts was 6.4 and 6.5 years, respectively. The primary outcome of interest was the occurrence of overall cancer or cancer at specific anatomical sites.
Results
The adjusted hazard ratios for overall cancer incidence were 1.08 (95% CI, 1.05–1.11). For site‐specific cancers, depression exhibited significant associations with oropharyngeal, esophageal, liver, gynecological, prostate, kidney, and hematologic malignancies among patients with diabetes. Notably, a severity‐response relationship was observed, indicating that patients with recurrent episodes of major depressive disorders exhibited a higher incidence of cancer compared to those diagnosed with dysthymia or depressive disorder not otherwise specified. Furthermore, the strength of the association between depression and cancer risk was more pronounced among younger patients with diabetes as opposed to older adults. However, no significant relationship was observed between adherence to antidepressant treatment and cancer risk.
Conclusions
The findings of this study indicate a significant association between depression and an elevated risk of cancer among individuals diagnosed with diabetes. Future investigations should replicate our findings, explore the effects of pharmacological and non‐pharmacological treatments on cancer risk, and identify the underlying mechanisms.
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