Lower respiratory tract viral infection (LRTI) is a significant cause of morbidity-mortality in older people worldwide. We analyzed the association between short-term exposure to environmental factors (climatic factors and outdoor air pollution) and hospital admissions with a viral LRTI diagnosis in older adults.
We conducted a bidirectional case-crossover study in 6367 patients over 65 years of age with viral LRTI and residential zip code in the Spanish Minimum Basic Data Set. Spain\'s State Meteorological Agency was the source of environmental data. Associations were assessed using conditional logistic regression. P-values were corrected for false discovery rate (q-values).
Almost all were hospital emergency admissions (98.13%), 18.64% were admitted to the intensive care unit (ICU), and 7.44% died. The most frequent clinical discharge diagnosis was influenza (90.25%). LRTI hospital admissions were more frequent when there were lower values of temperature and O3 and higher values of relative humidity and NO2. The regression analysis adjusted by temperatures and relative humidity showed higher concentrations at the hospital admission for NO2 [compared to the lag time of 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)] and O3 [compared to the lag time of 3-days (q-value< 0.001), 1-week (q-value< 0.001), and 2-weeks (q-value< 0.001)] were related to a higher odds of hospital admissions due to viral LRTI. Moreover, higher concentrations of PM10 at the lag time of 1-week (q-value = 0.023) and 2-weeks (q-value = 0.002), and CO at the lag time of 3-days (q-value = 0.023), 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)], compared to the day of hospitalization, were related to a higher chances of hospital admissions with viral LRTI.
Unfavorable environmental factors (low temperatures, high relative humidity, and high concentrations of NO2, O3, PM10, and CO) increased the odds of hospital admissions with viral LRTI among older people, indicating they are potentially vulnerable to these environmental factors.

UNASSIGNED: Taiwan\'s national health insurance (NHI) database is a valuable resource for large-scale epidemiological and long-term survival research for out-of-hospital cardiac arrest (OHCA). We developed and validated case definition algorithms for OHCA based on the International Classification of Diseases (ICD) diagnostic codes and billing codes for NHI reimbursement.
UNASSIGNED: Claims data and medical records of all emergency department visits from 2010 to 2020 were retrieved from the hospital\'s research-based database. Death-related diagnostic codes and keywords were used to identify potential OHCA cases, which were ascertained by chart reviews. We tested the performance of the developed OHCA algorithms and validated them on an external dataset.
UNASSIGNED: The algorithm defining OHCA as any cardiac arrest (CA)-related ICD code in the first three diagnosis fields performed the best with a sensitivity of 89.5% (95% confidence interval [CI], 88.2-90.7%), a positive predictive value (PPV) of 90.6% (95% CI, 89.4-91.8%), and a kappa value of 0.900 (95% CI, 0.891-0.909). The second-best algorithm consists of any CA-related ICD code in any diagnosis field with a billing code for triage acuity level 1, achieving a sensitivity of 85.6% (95% CI, 84.1-87.0%), a PPV of 93.6% (95% CI, 92.5-94.5), and a kappa value of 0.894 (95% CI, 0.884-0.903). Both algorithms performed well in external validation. In subgroup analyses, the former algorithm performed the best in adult patients, outpatient claims, and during the ICD-9 era. The latter algorithm performed the best in the inpatient claims and during the ICD-10 era. The best algorithm for identifying pediatric OHCAs was any CA-related ICD code in the first three diagnosis fields with a billing code for triage acuity level 1.
UNASSIGNED: Our results may serve as a reference for future OHCA studies using the Taiwan NHI database.

UNASSIGNED: Severe maternal morbidity (SMM) is considered as a near miss for maternal death, therefore it is crucial to identify and prevent SMM. Medical insurance claims can be used to identify SMM. There was a national transition from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to International Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) in October 2015.
UNASSIGNED: This study investigates the impact of transition from ICD-9-CM to ICD-10-CM on the rates of SMM in the state of Arkansas using birth certificates linked with insurance claims data in the Arkansas All-Payer Claims Database (APCD).
UNASSIGNED: Birth certificates between January 1, 2013, and December 31, 2017, were linked to insurance claims data from the APCD. SMM was defined using the algorithm provided by the Centers for Disease Control and Prevention, using ICD-9 codes for births before October 1, 2015, and ICD-10-CM codes for births on or after October 1, 2015.
UNASSIGNED: The incidence of SMM increased after transition to the ICD-10-CM system in Arkansas. The relatively higher rate of SMM in ICD-10-CM versus ICD-9-CM was greater in magnitude on the delivery day and throughout the 42-day postpartum period (odds ratio [OR]: 1.30; 95% confidence interval [CI]: 1.20-1.42) compared with the rate on the day of delivery (OR: 1.20; 95% CI: 1.06-1.36). When excluding blood transfusions, the higher rate of SMM during the ICD-10 era was even greater both in the delivery day and 42-day postpartum period (OR: 1.66; 95% CI: 1.49-1.85) and on the day of delivery (OR: 1.58; 95% CI: 1.31-1.90).

This study evaluated the association of the short-term exposure to environmental factors (relative humidity, temperature, NO2, SO2, O3, PM10, and CO) with hospital admissions due to acute viral lower respiratory infections (ALRI) in children under two years before the COVID-19 era.
We performed a bidirectional case-crossover study in 30,445 children with ALRI under two years of age in the Spanish Minimum Basic Data Set (MBDS) from 2013 to 2015. Environmental data were obtained from Spain\'s State Meteorological Agency (AEMET). The association was assessed by conditional logistic regression.
Lower temperature one week before the day of the event (hospital admission) (q-value = 0.012) and higher relative humidity one week (q-value = 0.003) and two weeks (q-value<0.001) before the day of the event were related to a higher odds of hospital admissions. Higher NO2 levels two weeks before the event were associated with hospital admissions (q-value<0.001). Moreover, higher concentrations on the day of the event for SO2 (compared to lag time of 1-week (q-value = 0.026) and 2-weeks (q-value<0.001)), O3 (compared to lag time of 3-days (q-value<0.001), 1-week (q-value<0.001), and 2-weeks (q-value<0.001)), and PM10 (compared to lag time of 2-weeks (q-value<0.001)) were related to an increased odds of hospital admissions for viral ALRI.
Short-term exposure to environmental factors (climatic conditions and ambient air contaminants) was linked to a higher likelihood of hospital admissions due to ALRI. Our findings emphasize the importance of monitoring environmental factors to assess the odds of ALRI hospital admissions and plan public health resources.

BACKGROUND: The transition from International Classification of Diseases, 9th Edition (ICD-9) to the 10th edition (ICD-10) in 2015 increased the number and specificity of diagnostic codes with the goal of facilitating clinical care and research possibilities.Considering the potential to default to less specified ICD-10 codes, the current study evaluated the number of codes utilized for spine-related conditions before versus after the transition to ICD-10.
METHODS: The numbers of patients with an index encounter for a primary spine-related non-deformity diagnosis codes indexed as \"dorsopathies\" were abstracted from the Humana PearlDiver dataset. As the transition from ICD-9 to ICD-10 occurred in 2015, the current study compared the year prior (ICD-9) to the year after (ICD-10). The number of ICD-9 and ICD-10 codes was assessed, and distribution of utilization was compared using the Kolmogorov-Smirnov test.
RESULTS: In 2014, 848,623 patients were assigned one of the 100 unique ICD-9 dorsopathy codes, of which 17 codes (17% of available codes) were used for more than 1% of the patients. In 2016, 840,310 patients were assigned one of the 504 unique ICD-10 dorsopathy codes, of which 21 (4% of available codes) were used for more than 1% of the patients. The top 20 codes in 2014 (ICD-9) and the top 20 codes in 2016 (ICD-10) both represented the majority of the patient population and were not statistically differently represented (p = 0.819). Further, analysis of ICD-10 codes demonstrated a clear bias toward utilizing less specified codes.
CONCLUSIONS: Despite a five-fold increase in available diagnostic codes for spine conditions in ICD-10, in the year after implementation providers continued to select a small proportion of less specific diagnostic codes when treating spine patients.

OBJECTIVE: To evaluate the effect of diagnostic coding system transition on the identification of common conditions recorded in Taiwan\'s national claims database.
METHODS: Using the National Health Insurance Research Database, we estimated the 3-month prevalence of recorded diagnosis of 32 conditions based on the ICD-9-CM codes in 2014-2015 and the ICD-10-CM codes in 2016-2017. Two algorithms were assessed for ICD-10-CM: validated ICD-10 codes in the literature and codes translated from ICD-9-CM using an established mapping algorithm. We used segmented regression analysis on time-series data to examine changes in the 3-month prevalence (both level and trend) before and after the ICD-10-CM implementation.
RESULTS: Significant changes in the level were found in 19 and 11 conditions when using the ICD-10 codes from the literature and mapping algorithm, respectively. The conditions with inconsistent levels by both of the algorithms were valvular heart disease, peripheral vascular disease, mild liver disease, moderate to severe liver disease, metastatic cancer, rheumatoid arthritis and collagen vascular diseases, coagulopathy, blood loss anemia, deficiency anemia, alcohol abuse, and psychosis. Nine conditions had significant changes in the trend when using the ICD-10 codes from the literature or mapping algorithm.
CONCLUSIONS: Less than half of the 32 conditions studied had a smooth transition between the ICD-9-CM and ICD-10-CM coding systems. Researchers should pay attention to the conditions where the coding definitions result in inconsistent time series estimates.

BACKGROUND: Administrative health data capture diagnoses using the International Classification of Diseases (ICD), which has multiple versions over time. To facilitate longitudinal investigations using these data, we aimed to map diagnoses identified in three ICD versions - ICD-8 with adaptations (ICDA-8), ICD-9 with clinical modifications (ICD-9-CM), and ICD-10 with Canadian adaptations (ICD-10-CA) - to mutually exclusive chronic health condition categories adapted from the open source Clinical Classifications Software (CCS).
METHODS: We adapted the CCS crosswalk to 3-digit ICD-9-CM codes for chronic conditions and resolved the one-to-many mappings in ICD-9-CM codes. Using this adapted CCS crosswalk as the reference and referring to existing crosswalks between ICD versions, we extended the mapping to ICDA-8 and ICD-10-CA. Each mapping step was conducted independently by two reviewers and discrepancies were resolved by consensus through deliberation and reference to prior research. We report the frequencies, agreement percentages and 95% confidence intervals (CI) from each step.
RESULTS: We identified 354 3-digit ICD-9-CM codes for chronic conditions. Of those, 77 (22%) codes had one-to-many mappings; 36 (10%) codes were mapped to a single CCS category and 41 (12%) codes were mapped to combined CCS categories. In total, the codes were mapped to 130 adapted CCS categories with an agreement percentage of 92% (95% CI: 86%-98%). Then, 321 3-digit ICDA-8 codes were mapped to CCS categories with an agreement percentage of 92% (95% CI: 89%-95%). Finally, 3583 ICD-10-CA codes were mapped to CCS categories; 111 (3%) had a fair or poor mapping quality; these were reviewed to keep or move to another category (agreement percentage = 77% [95% CI: 69%-85%]).
CONCLUSIONS: We developed crosswalks for three ICD versions (ICDA-8, ICD-9-CM, and ICD-10-CA) to 130 clinically meaningful categories of chronic health conditions by adapting the CCS classification. These crosswalks will benefit chronic disease studies spanning multiple decades of administrative health data.

This population-based study explored the associations between childhood adversity and admission to emergency departments (EDs) with non-suicidal self-injury (NSSI) and with a suicide attempt.
A nationally representative cross-sectional sample of 5-17-year-olds admitted to EDs (N = 143,113,677) from 2006 to 2015 was utilized to assess the associations between childhood adversities, NSSIs, and suicide attempts.
ED admissions with NSSI and admissions with a suicide attempt were associated with greater odds of exposure to individual childhood adversities (aORs: 1.34 to 5.86; aORs: 2.37 to 15.69, respectively). ED admissions with a suicide attempt were associated with greater odds of exposure to childhood adversities that might be perceived as less extreme or harmful (separation or divorce aOR: 15.69) than other adversities (death of a family member aOR: 13.38; history of physical abuse aOR: 9.56) as well as greater odds of exposure to three or more childhood adversities (aOR: 20.98).
Early detection of childhood adversities is important for identifying potential risk factors for self-harm. ED admission data can provide population-level surveillance to aid in these efforts and lead to more targeted and effective interventions aimed at reducing the negative effects of toxic stress that can result from exposure to childhood adversities.

Pneumonia is a common cause of morbidity and sepsis worldwide, mainly in the elderly. We evaluated the impact of short-term exposure to environmental factors on hospital admissions for sepsis-related pneumonia in a nationwide study in Spain.
We conducted a bidirectional case-crossover study in patients who had sepsis-related pneumonia in 2013. Data were obtained from the Minimum Basic Data Set (MBDS) and the State Meteorological Agency (AEMET) of Spain. Conditional logistic regressions were used to evaluate the association between environmental factors (temperature, relative humidity, NO2, SO2, O3, PM10, and CO) and hospital admissions with sepsis-related pneumonia.
A total of 3,262,758 hospital admissions were recorded in the MBDS, of which, 253,467 were patients with sepsis. Among those, 67,443 had sepsis-related pneumonia and zip code information. We found inverse associations [adjusted odds ratio (aOR) values < 1] between short-term exposure to temperature and hospital admissions for sepsis-related pneumonia. Moreover, short-term exposure to higher levels of relative humidity, NO2, SO2, O3, PM10, and CO were directly associated (aOR values > 1) with a higher risk of hospital admissions for sepsis-related pneumonia. Overall, the impact of environmental factors was more prominent with increasing age, mainly among the elderly aged 65 or over.
Short-term exposure to environmental factors (temperature, relative humidity, NO2, SO2, O3, CO, and PM10) was associated with a higher risk of hospital admissions for sepsis-related pneumonia. Our findings support the role of environmental factors in monitoring the risk of hospital admissions for sepsis-related pneumonia and can help plan and prepare public health resources.

The quality of clinical data held in administrative databases is crucial for appropriate funding of health care services. As Diagnosis-Related Groups (DRGs) continue to play an important role in hospital payment mechanisms, proper coding of diagnoses and procedures is of most concern. This study used an administrative, nationwide Portuguese inpatient database to characterize and assess coding patterns in burn-related hospitalization data, with a special focus on identifying suspected miscoding practices that could be affecting APR-DRG (All-Patient Refined Diagnosis-Related Groups) classification. Using coded clinical data of 4,182 burn-related admissions occurred between 2011 and 2015, we compared APR-DRG and Severity of Illness (SOI) frequencies between hospitals with a burn unit in Portugal. The frequencies of individual diagnosis and procedure codes among episodes grouped within the same APR-DRG were also compared. Hospitals with a burn unit in Portugal differed significantly in the frequencies of APR-DRGs 842 and 844. Proper coding of extensive third-degree burns might be related with the observed discrepant frequencies of APR-DRGs across the evaluated hospitals. Facilities also differed significantly concerning the proportions of SOI levels in certain APR-DRGs. Significant differences in reporting certain comorbidities and common hospital procedures, especially non-operating room procedures, might have influenced the observed discrepancies in SOI levels. Moreover, there seems to be a lack of standard in coding debridement procedures among the evaluated hospitals. Overall, we found some suspected coding patterns that could potentially be associated with miscoding practices impacting APR-DRG classification. Those findings could not only be relevant for planning future audit processes and improving medical coding practices, but also for discussing quality and desirable features of burn-related clinical data, keeping in mind their use for other purposes beyond DRG grouping, namely clinical and health care services research, as well as health care management.