POINT: Is ICD-10 Diagnosis Coding Important in the Era of Big Data? Yes

Application of problem based learning (PBL) and case based learning (CBL) in the teaching of international classification of diseases encoding

To study the application of PBL combined with CBL teaching mode in the teaching of international classification of diseases (ICD) encoding, so as to improve students' grasp of ICD encoding knowledge. From March 2020 to June 2020, 50 students majoring in health information management who were interns in a Grade A general hospital were selected as the research participants and randomly divided into experimental group and control group, 25 in each group. The experimental group and the control group adopted the PBL combined CBL teaching mode and the traditional teaching mode respectively to carry out the classification and coding teaching. The academic achievement of the two groups of students was evaluated by means of achievement assessment and questionnaire survey based on information processing theory. The scores of theoretical knowledge in the experimental group and the control group were 79.78 ± 8.55 and 70.92 ± 10.81, respectively, and the scores of skill operation in the two groups were 79.76 ± 8.28 and 70.00 ± 10.41, respectively. The test scores of the experimental group were higher than those of the control group, and the difference was statistically significant (P < 0.05). The scores of knowledge acquisition ability of experimental group and control group were 16.72 ± 1.79 and 16.60 ± 2.36, the scores of knowledge sharing ability were 24.20 ± 2.61 and 21.00 ± 2.65, the scores of knowledge storage ability were 20.80 ± 2.47 and 17.24 ± 4.90, respectively. The scores of knowledge application ability were 14.00 ± 1.80 and 11.00 ± 2.69, the scores of knowledge innovation ability were 20.16 ± 2.34 and 18.08 ± 3.70, and the total scores were 95.88 ± 6.08 and 83.92 ± 11.30, respectively. The scores of all questionnaires in the experimental group were higher than those in the control group. The scores of knowledge sharing ability, knowledge storage ability, knowledge application ability, knowledge innovation ability and total score between the two groups were higher than those of the control group, and the differences were statistically significant (P < 0.05). PBL combined with CBL teaching model has good academic achievement in ICD encoding teaching, which can significantly improve academic performance and learning ability, and is worthy of promotion.

COVID-19 Outcomes in a US Cohort of Persons Living with HIV (PLWH)

Reported coronavirus disease 2019 (COVID-19) outcomes in persons living with HIV (PLWH) vary across cohorts. We examined clinical characteristics and outcomes of PLWH with COVID-19 compared with a matched HIV-seronegative cohort in a mid-Atlantic US healthcare system. Multivariate logistic regression was used to explore factors associated with hospitalization and death/mechanical ventilation among PLWH. Among 281 PLWH with COVID-19, the mean age was 51.5 (SD 12.74) years, 63% were male, 86% were Black, and 87% had a HIV viral load <200 copies/mL. Overall, 47% of PLWH versus 24% (p < 0.001) of matched HIV-seronegative individuals were hospitalized. Rates of COVID-19 associated cardiovascular and thrombotic events, AKI, and infections were similar between PLWH and HIV-seronegative individuals. Overall mortality was 6% (n = 18/281) in PLWH versus 3% (n = 33/1124) HIV-seronegative, p < 0.0001. Among admitted patients, mortality was 14% (n = 18/132) for PLWH and 13% (n = 33/269) for HIV-seronegative, p = 0.75. Among PLWH, hospitalization associated with older age aOR 1.04 (95% CI 1.01, 1.06), Medicaid insurance aOR 2.61 (95% CI 1.39, 4.97) and multimorbidity aOR 2.98 (95% CI 1.72, 5.23). Death/mechanical ventilation associated with older age aOR 1.06 (95% CI 1.01, 1.11), Medicaid insurance aOR 3.6 (95% CI 1.36, 9.74), and multimorbidity aOR 4.4 (95% CI 1.55, 15.9) in adjusted analyses. PLWH were hospitalized more frequently than the HIV-seronegative group and had a higher overall mortality rate, but once hospitalized had similar mortality rates. Older age, multimorbidity and insurance status associated with more severe outcomes among PLWH suggesting the importance of targeted interventions to mitigate the effects of modifiable inequities.

Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics

Intelligent health diagnosis for young children aims at maintaining and promoting the healthy development of young children, aiming to make young children have a healthy state and provide a better future for their physical and mental health development. The biological basis of intelligence is the structure and function of human brain and the key to improve the intelligence level of infants is to improve the quality of brain development, especially the early development of brain. Based on machine learning and health information statistics, this paper studies the development of infant health diagnosis and intelligence, physical and mental health. Pre-process the sample data, and use the filtering method based on machine learning and health information statistics for feature screening. Compared with traditional statistical methods, machine learning and health information statistical methods can better obtain the hidden information in the big data of children's physical and mental health development, and have better learning ability and generalization ability. The machine learning theory is used to analyze and mine the infant's health diagnosis and intelligence development, establish a health state model, and intuitively show people the health status of their infant's physical and mental health development by means of data. Moreover, the accumulation of these big data is very important in the field of medical and health research driven by big data.

Acute Dental Periapical Abscess and New-Onset Atrial Fibrillation: A Nationwide, Population-Based Cohort Study

There are limited data on the relationship of acute dental infections with hospitalisation and new-onset atrial fibrillation (AF). This study aimed to assess the relationship between acute periapical abscess and incident AF. This was a retrospective cohort study from a French national database of patients hospitalized in 2013 (3.4 million patients) with at least five years of follow up. In total, 3,056,291 adults (55.1% female) required hospital admission in French hospitals in 2013 while not having a history of AF. Of 4693 patients classified as having dental periapical abscess, 435 (9.27%) developed AF, compared to 326,241 (10.69%) without dental periapical abscess that developed AF over a mean follow-up of 4.8 ± 1.7 years. Multivariable analysis indicated that dental periapical abscess acted as an independent predictor for new onset AF (p < 0.01). The CHA₂DS₂VASc score in patients with acute dental periapical abscess had moderate predictive value for development of AF, with Area Under the Curve (AUC) 0.73 (95% CI, 0.71–0.76). An increased risk of new onset AF was identified for individuals hospitalized with dental periapical abscess. Careful follow up of patients with severe, acute dental periapical infections is needed for incident AF, as well as investigations of possible mechanisms linking these conditions.

Assessment of the Accuracy of Identification of Selected Disabilities and Conditions in Hospital Discharge Data for Pregnant Women

BACKGROUND

Linked birth certificate-hospital discharge records are a valuable resource for examining pregnancy outcomes among women with disability conditions. Few studies relying on these data have been able to assess the accuracy of identification of preexisting disability conditions. We assessed the accuracy of International Classification of Diseases version 9 (ICD9) codes for identifying selected physical, sensory, and intellectual conditions that may result in disability. As ICD9 codes were utilized until recently in most states, this information is useful to inform analyses with these records.

METHODS

We reviewed 280 of 311 (90%) medical records of pregnant women with disabilities based on ICD9 codes and 390 of 8,337 (5%) records of pregnant women without disabilities who had deliveries at a large university medical center. We estimated sensitivity, specificity, and positive predictive values (PPV) using the medical record as gold standard. We adjusted for verification bias using inverse probability weighting and imputation.

RESULTS

The estimated sensitivity of ICD9 codes to identify women with disabilities with deliveries 2009-2012 was 44%; PPV was 98%, improving over time. Although sensitivity was <50% for some conditions, PPVs were 87%-100% for all conditions except intellectual disability (67%). Many physical conditions had complete verification and no underreporting.

CONCLUSIONS

These results are helpful for new studies using historical data comparing outcomes among women with and without these conditions and to inform interpretation of results from earlier studies. Assessment of the accuracy of disabilities as identified by ICD version 10 codes is warranted.

Impact of single and combined rare diseases on adult inpatient outcomes: a retrospective, cross-sectional study of a large inpatient population

Background

Little is known about the impact of rare diseases on inpatient outcomes.

Objective

To compare outcomes of inpatients with 0, 1, or > 1 rare disease. A catalogue of 628 ICD-10 coded rare diseases was applied to count rare diseases.

Design

Retrospective, cross-sectional study.

Subjects

165,908 inpatients, Swiss teaching hospital.

Main measures

Primary outcome: in-hospital mortality. Secondary outcomes: length of stay (LOS), intensive care unit (ICU) admissions, ICU LOS, and 30-day readmissions. Associations with single and combined rare diseases were analyzed by multivariable regression.

Key results

Patients with 1 rare disease were at increased risk of in-hospital death (odds ratio [OR]: 1.80; 95% confidence interval [CI]: 1.67, 1.95), combinations of rare diseases showed stronger associations (OR 2.78; 95% CI 2.39, 3.23). Females with 1 rare disease had an OR of 1.69 (95% CI 1.50, 1.91) for in-hospital death, an OR of 2.99 (95% CI 2.36, 3.79) if they had a combination of rare diseases. Males had an OR of 1.85 (95% CI 1.68, 2.04) and 2.61 (95% CI 2.15, 3.16), respectively. Rare diseases were associated with longer LOS (for 1 and > 1 rare diseases: increase by 28 and 49%), ICU admissions (for 1 and > 1: OR 1.64 [95% CI 1.57, 1.71] and 2.23 [95% CI 2.01, 2.48]), longer ICU LOS (for 1 and > 1 rare diseases: increase by 14 and 40%), and 30-day readmissions (for 1 and > 1: OR 1.57 [95% CI 1.47, 1.68] and 1.64 [95% CI 1.37, 1.96]).

Conclusions

Rare diseases are independently associated with worse inpatient outcomes. This might be the first study suggesting even stronger associations of combined rare diseases with in-hospital deaths, increased LOS, ICU admissions, increased ICU LOS, and 30-day readmissions.

Evaluation of poor prognostic factors of respiratory related death in microscopic polyangiitis complicated by interstitial lung disease

The prognosis of microscopic polyangiitis (MPA) with interstitial lung disease (ILD) is significantly worse than that of MPA without ILD. However, the clinical characteristics in MPA-ILD, especially poor prognostic factors, are not elucidated. We evaluated demographic, clinical, laboratory, and radiological findings, treatments, and outcomes of 80 patients with MPA, and investigated prognostic factors of respiratory-related death in patients with myeloperoxidase (MPO)-anti-neutrophil cytoplasmic antibody (ANCA) positive MPA-ILD. Ground-glass opacity and fibrosis were evaluated as scores on high-resolution computed tomography (HRCT). The presence of ILD was consistent with a high risk of respiratory-related death (hazard ratio, 4.8; P = 0.04). Multivariable logistic regression analyses using propensity scoring showed right or left lower lobe fibrosis score to be significantly associated with respiratory-related death (P = 0.0005 and 0.0045, respectively). A right or left lower lobe fibrosis score ≥ 2, indicating the presence of honeycombing at 1 cm above the diaphragm, was determined to be the best cut-off value indicating a poor prognosis. The 5-year survival rate was significantly lower in patients with right or left lower lobe fibrosis score ≥ 2 (survival rates: 37% and 19%, respectively) than those with a score < 2 (71% and 68%, respectively) (P = 0.002 and 0.0007, respectively). These findings suggest that the presence of honeycomb lesions in bilateral lower lobes on chest HRCT was associated with respiratory-related death in patients with MPO-ANCA positive MPA-ILD.

A Bibliometric Analysis of the Development of ICD-11 in Medical Informatics

The International Classification of Diseases (ICD), which is used to group and report health conditions and factors, provides a basis for healthcare statistics. The 11th revision of the ICD (ICD-11) released by the World Health Organization provides stakeholders with novel perspectives on solving the complexity of critical problems in medical informatics. This study conducts a bibliometric analysis of research published over the period of 1989-2018 to examine the development of ICD-related research and its trends. First, over 4000 ICD-related papers spanning the 30-year period are retrieved from the Web of Science database. Then, based on the meta data of the selected papers, time trend analysis is performed to examine the development of different ICD revisions. Finally, the keywords and topics of these papers are analyzed and visualized using VOSViewer and CiteSpace. Our findings indicate that ICD-11-related research has grown rapidly in recent years compared with studies on ICD-9 and ICD-10. Moreover, the most popular research directions of ICD-11 include the topics psychiatry, psychology, information science, library science, and behavioral science. In terms of perspectives, information system-related research is more common than big data- and knowledge discovery-related work. However, the popularity of big data- and knowledge discovery-related developments has grown in recent years. The use of ICD-11 facilitates the development of medical informatics from the perspectives of information systems, big data, and knowledge discovery.

Data Talks: Obesity-Related Influences on US Mortality Rates

BACKGROUND

In the US, obesity is an epidemiologic challenge and the population fails to comprehend this complex public health issue. To evaluate underlying obesity-impact patterns on mortality rates, we data-mined the 1999-2016 Center for Disease Control WONDER database's vital records.

METHODS

Adopting SAS programming, we scrutinized the mortality and population counts. Using ICD-10 diagnosis codes connected to overweight and obesity, we obtained the obesity-related crude and age-adjusted causes of death. To understand divergent and prevalence trends we compared and contrasted the tabulated obesity-influenced mortality rates with demographic information, gender, and age-related data.

KEY RESULTS

From 1999 to 2016, the obesity-related age-adjusted mortality rates increased by 142%. The ICD-10 overweight and obesity-related death-certificate coding showed clear evidence that obesity factored in the male age-adjusted mortality rate increment to 173% and the corresponding female rate to 117%. It also disproportionately affected the nation-wide minority population death rates. Furthermore, excess weight distributions are coded as contributing features in the crude death rates for all decennial age-groups.

CONCLUSIONS

The 1999-2016 data from ICD-10 death certificate coding for obesity-related conditions indicate that it is affecting all segments of the US population.