Administrative data in pediatric critical care research-Potential, challenges, and future directions.

Heterogenous patient populations with small case numbers constitute a relevant barrier to research in pediatric critical care. Prospective studies bring along logistic barriers and-if interventional-ethical concerns. Therefore, retrospective observational investigations, mainly multicenter studies or analyses of registry data, prevail in the field of pediatric critical care research. Administrative health care data represent a possible alternative to overcome small case numbers and logistic barriers. However, their current use is limited by a lack of knowledge among clinicians about the availability and characteristics of these data sets, along with required expertise in the handling of large data sets. Specifically in the field of critical care research, difficulties to assess the severity of the acute disease and estimate organ dysfunction and outcomes pose additional challenges. In contrast, trauma research has shown that classification of injury severity from administrative data can be achieved and chronic disease scores have been developed for pediatric patients, nurturing confidence that the remaining obstacles can be overcome. Despite the undoubted challenges, interdisciplinary collaboration between clinicians and methodologic experts have resulted in impactful publications from across the world. Efforts to enable the estimation of organ dysfunction and measure outcomes after critical illness are the most urgent tasks to promote the use of administrative data in critical care. Clever analysis and linking of different administrative health care data sets carry the potential to advance observational research in pediatric critical care and ultimately improve clinical care for critically ill children.

Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references.

BACKGROUND: To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). METHODS: A proportional random sampling of 10,000 patients aged ≥ 20 years in a health care system in Southern Taiwan were enrolled as study participants. We used three hierarchical RSs (RS1: having positive results of laboratory tests; R2: having RS1 or having prescriptions of anti-HBV or anti-HCV medications; R3: having R1 or R2 or having textual diagnosis recorded in electrical medical records) with three SPs (4-, 8-, and 12-years) to calculate positive predictive value (PPV) and sensitivity (Sen) of 6 coding algorithms using HBV- and HCV-related International Classification of Disease Tenth Revision Clinical Modification (ICD-10-CM) codes in Taiwan National Health Insurance claims data for years 2016-2019. RESULTS: Of 10,000 enrolled participants, the number of participants had confirmed HBV and HCV was 146 and 165, respectively according to RS1 with 4-years SP and increased to 729 and 525, respectively according to RS3 with 12-years SP. For both HBV and HCV, the PPV was lowest according to RS1 and highest according to RS3. The longer the SP, the higher the PPV. However, the Sen was highest according to RS2 with 4-years SP. For both HBV and HCV, the coding algorithm with highest PPV and Sen was " ≥ 3 outpatient codes" and " ≥ 2 outpatient or ≥ 1 inpatients codes," respectively. CONCLUSIONS: In conclusion, using different RSs with different SPs would result in different estimation of PPV and Sen. To achieve the best yield of both PPV and Sen, the optimal coding algorithm is " ≥ 2 outpatients or ≥ 1 inpatients codes" for identifying people with HBV or HCV.

Factors affecting clinicians' adherence to principles of diagnosis documentation: A concept mapping approach for improved decision-making.

BACKGROUND: The quality of data in electronic health records (EHRs) depends on adherence of clinicians to principles of diagnosis documentation. OBJECTIVE: A concept mapping (CM) approach was used to extract factors related to quality of clinicians' documentation that govern EHR data quality. METHOD: Influential factors extracted from brainstorming sessions were sorted by individual participants, followed by a quantitative analysis using multidimensional scaling and cluster analysis to categorise sorted factors. Finally, a questionnaire was used to elicit the importance-feasibility of the extracted factors. Results were visualised by cluster maps and Go-Zone plots. RESULT: Factors were classified into seven clusters: "knowledge about International Classification of Diseases and clinical coding," "need for facilitators and guidelines," "explaining the importance of the issue and defining responsibilities," "cooperation of other personnel," "codify legal requirements," "workload" and "clinical obstacles," as ranked by importance. CONCLUSION: To enhance the quality of EHR data, a collaboration between physicians, nurses, managers and EHR developers is required. CM is an acceptable approach to meet this objective. Our findings highlight the significance of clinical coding knowledge, awareness about its importance and applicability and use of well-structured information systems. In combination, these three factors can have a strong positive impact on the quality of EHR data. IMPLICATIONS: A list of solutions is provided for policymakers, and two interventions suggested, based on the findings of this study, including the adoption of EHRs that incorporate documentation guidelines. We further propose updated clinical training programs and a monitoring and feedback mechanism to facilitate the EHR documentation process.

Automated grouping of medical codes via multiview banded spectral clustering.

OBJECTIVE: With its increasingly widespread adoption, electronic health records (EHR) have enabled phenotypic information extraction at an unprecedented granularity and scale. However, often a medical concept (e.g. diagnosis, prescription, symptom) is described in various synonyms across different EHR systems, hindering data integration for signal enhancement and complicating dimensionality reduction for knowledge discovery. Despite existing ontologies and hierarchies, tremendous human effort is needed for curation and maintenance - a process that is both unscalable and susceptible to subjective biases. This paper aims to develop a data-driven approach to automate grouping medical terms into clinically relevant concepts by combining multiple up-to-date data sources in an unbiased manner. METHODS: We present a novel data-driven grouping approach - multi-view banded spectral clustering (mvBSC) combining summary data from multiple healthcare systems. The proposed method consists of a banding step that leverages the prior knowledge from the existing coding hierarchy, and a combining step that performs spectral clustering on an optimally weighted matrix. RESULTS: We apply the proposed method to group ICD-9 and ICD-10-CM codes together by integrating data from two healthcare systems. We show grouping results and hierarchies for 13 representative disease categories. Individual grouping qualities were evaluated using normalized mutual information, adjusted Rand index, and F1-measure, and were found to consistently exhibit great similarity to the existing manual grouping counterpart. The resulting ICD groupings also enjoy comparable interpretability and are well aligned with the current ICD hierarchy. CONCLUSION: The proposed approach, by systematically leveraging multiple data sources, is able to overcome bias while maximizing consensus to achieve generalizability. It has the advantage of being efficient, scalable, and adaptive to the evolving human knowledge reflected in the data, showing a significant step toward automating medical knowledge integration.

Association between delivery of small-for-gestational age neonate and long-term pediatric ophthalmic morbidity.

OBJECTIVE: To investigate whether delivery of small for gestational age (SGA) neonate poses a risk for subsequent long-term ophthalmic morbidity. METHODS: In this population-based study, all deliveries between 1991 and 2014 were included. Congenital malformations and multiple gestations were excluded from the analysis. Offspring were defined as either SGA (weight below the 5th percentile for gestational age) or non-SGA. Comparison was performed regarding the incidence of long-term ophthalmic morbidity in a cohort of neonates who were born SGA and those who were not. Ophthalmic morbidity was documented during any encounter with the hospital for a period of up to 18 years after delivery. Ophthalmic morbidity included infections of the eye or the adnexa, inflammation of any cause requiring admission, visual disturbances, and other hospital admissions carrying an ICD-9 code of ophthalmic designation. A Cox proportional hazards model was used to estimate the adjusted hazards ratio (HR) for ophthalmic morbidity During the study period, 243,682 deliveries met the inclusion criteria, of which 11,290 (4.63%) were defined as SGA. RESULTS: During the follow-up period, SGA neonates had higher rates of ophthalmic-related hospitalizations (1.2% versus 1.0%; OR = 1.22, 95% CI 1.02-1.46; p = 0.026). In a Cox proportional hazards model, adjusted for confounders such as maternal age, gestational age at delivery, child birth year, low 5 min Apgar scores (< 7), gestational diabetes, maternal hypertensive disorders, placental abruption and placenta previa, SGA neonate was independently associated with subsequent long-term ophthalmic morbidity (adjusted HR = 1.22; 95% CI 1.02-1.47; p = 0.024). CONCLUSION: Delivery of an SGA neonate is an independent risk factor for long-term ophthalmic morbidity.

Demographic characteristics of blood and blood components transfusion recipients and pattern of blood utilization in a tertiary health institution in southern Nigeria.

BACKGROUND: An insight into the utilization pattern helps in future planning of blood drive. This study was conducted to describe the demographic characteristics of the transfusion recipients and pattern of blood and blood product utilization in Nigeria. METHODS: Blood bank registers of University of Calabar Teaching Hospital (UCTH) Calabar were analysed for a 12 month period. Number of blood units requested, number of units issued, Cross-match to transfusion ratio (C/T), age, gender, blood group, blood components received, patients ward and clinical diagnosis were computed. Diagnoses were grouped into broad categories according to the disease headings of International Classification of Diseases (ICD-10). RESULTS: Majority of the 2336 transfusion recipients studied were females (69.09%) and are in the reproductive age group; 15-49 years (75.23%). The median age of the recipients was 35 years (range, 0-89). Most of the recipients (n = 1636; 70.04%) received whole blood transfusion. Majority (94.46%) of the cross-matched units were issued giving C/T ratio of 1.06. The common blood group type was O Rhesus positive (62.63%). Obstetrics and Gynecology had the highest blood requisition (41.40%). The majority of the patients were diagnosed with conditions related to pregnancy and childbirth (38.70%), conditions originating in prenatal period (14.38%). The age range of 25-54 years had the highest blood transfusion requests (n = 501; 51.07%), of these, females were majority (n = 390;77.84%). CONCLUSIONS: Our study recorded mostly young patients who received mostly whole blood. Most of the patients in the reproductive age group received transfusion for pregnancy and child-birth related cases.

Reliability of the ICD-10 International Personality Disorder Examination (Urdu Translation): A preliminary study.

OBJECTIVE: To test the reliability and applicability of Urdu translation of the International personality disorder examination (IPDE) in a psychiatric outpatient population in Pakistan. METHODS: This study was conducted at the outpatient department of Fatima Memorial Hospital Lahore from April 2012 to March 2013. Patients considered to have a personality disorder by a psychiatrist were initially screened by the IPDE screening questionnaire. Those who scored positive on screening were evaluated in a detailed interview using IPDE. Two interviewers conducted the interviews simultaneously, to ensure inter-rater reliability. For translation, permission was taken from World Health Organization. Linguistic equivalence was assessed through back- translation and conceptual equivalence through opinion of mental health experts. The final Urdu draft was obtained after incorporating modifications suggested by experts following a feasibility study. The analysis was carried out using SPSS v.20. RESULTS: Out of 30 enrolled patients, 25(83.3%) were females. The mean age of the sample was 28.5+6.08 years. Majority of patients had more than one personality disorder. Most prevalent personality disorder was emotionally unstable borderline type with a phi correlation of 0.831, followed by emotionally unstable impulsive type and anankastic personality disorder with phi correlations of 0.930 and 0.867, respectively, for definite cases. Correlation coefficient for dimensional scores between the two raters was 0.392 for paranoid personality disorder, 0.842 for anankastic and around 0.9 for the rest of the personality disorders, each. CONCLUSION: Urdu translation of IPDE is a reliable tool to screen and diagnose personality disorders in population of Pakistan.

How Accurate Are International Classification of Diseases-10 Diagnosis Codes in Detecting Influenza and Pertussis Hospitalizations in Children?

Influenza and pertussis are major causes of pediatric morbidity. We measured the accuracy of their International Classification of Diseases (ICD-10-AM) diagnosis codes using linked population-based laboratory and hospital data in 245,249 children. Influenza diagnosis codes had high specificity (98.6%) and modest positive predictive value (PPV; 84.1%) and sensitivity (86.1%, 95% CI: 83.4%-88.6%) for a laboratory-confirmed episode. For pertussis diagnosis codes, PPV (86.8%) and specificity (98.9%) were high, but sensitivity was poor (27.8%, 95% CI: 23.5%-32.4%). Measures varied according to age, remoteness, Aboriginality, severity, and detection method. Both laboratory and hospitalization data are needed to accurately determine the burden of pediatric influenza and pertussis.

Analysis of Blood Use at Dankook University Hospital according to International Statistical Classification of Diseases (ICD)-10 / 대한혈액학회지

BACKGROUND: A few recent studies have been conducted to analyzing the blood usage with regard to diagnosis of Korean recipients. We performed a study to analyze the usage of blood components. METHODS: Transfused components such as packed red blood cells (RBC), whole blood (WB), fresh frozen plasma (FFP), and platelet components (PLT) were estimated by the principal diagnoses of the patients, who were discharged from February 1998 to January 1999, according to the International Statistical Classification of Diseases (ICD)-10. RESULTS: Eleven percentage (2,227/20,650) of inpatients were transfused. The transfusion rate of hospitalized patients for RBCs, WBs, FFPs, and PLTs was 10.1%, 0.4%, 4.0% and 16.2 %, respectively. There was a difference in the sex ratio (1.6 male/female) in all blood components transfused. Of all investigated blood components (22,523 units), 10,729 units (47.6%) of RBCs, 240 units (1.1%) of WBs, 5,355 units (23.8%) of FFPs, and 6,199 units (27.5%) of PLTs were transfused. The hospitalized patients who received 1 unit of RBCs was 12.9%, and 2 units were most frequent transfused units (25.6%). Seventy-four percent of all 22,523 units were used in four diagnostic categories of highest blood usage; injury and poisoning (29.2%), nonhematologic neoplasms (16.3%), digestive system disease (16.1%) and circulatory system disease (12.5%). CONCLUSION: We performed usage analysis of blood components with regard to diagnosis, comparing the previous studies in other hospitals. This study could provide baseline transfusion information in relation to diagnosis, and help improve the quality control of blood utilization and transfusion practice.