Accuracy and Validity Outpatient Diagnosis Code Base On ICD-10 at Imogiri I Health Center Bantul Yogyakarta

Background: Analysis of accuracy and validity fill code diagnosis on medical record document is very important because if diagnosis code is not appropriate with ICD-10, will cause decline in quality services health center, generated data have this validation data level is low, because accuracy code very important for health center such as index process and statistical report, as basis for making outpatient morbidity report and top ten diseases reports, as well as influencing policies will be taken by primary health center management. This study aims to analyze accuracy and validity diagnosis disease code based on ICD-10 fourth quarter in 2020 Imogiri I Health Center Bantul.Methods: Descriptive qualitative approach, case study design. Subject is a doctor, nurse, head record medical and staff. Object is outpatients medical record document in Imogiri I Health Center Bantul. Total sample 99 medical record file. Obtaining data from this study through interviews and observations.Results: Number of complete accurate diagnosis codes is 60 (60,6%), incomplete accurate diagnosis codes is 26 (26.3%) and inaccurate diagnosis codes is 13 (13.1%). Inaccuracies include errors in determining code, errors in determining 4th character ICD-10 code, not adding 4th and 5th characters, not including external cause, and multiple diseases.Conclusions: Inaccuracy factors are not competence medical record staff, incomplete diagnosis writing and no training, no evaluation or coding audit has been carried out, and standard operational procedure is not socialized.

Sleep apnea phenotyping and relationship to disease in a large clinical biobank

Objective Sleep apnea is associated with a broad range of pathophysiology. While electronic health record (EHR) information has the potential for revealing relationships between sleep apnea and associated risk factors and outcomes, practical challenges hinder its use. Our objectives were to develop a sleep apnea phenotyping algorithm that improves the precision of EHR case/control information using natural language processing (NLP); identify novel associations between sleep apnea and comorbidities in a large clinical biobank; and investigate the relationship between polysomnography statistics and comorbid disease using NLP phenotyping. Materials and Methods We performed clinical chart reviews on 300 participants putatively diagnosed with sleep apnea and applied International Classification of Sleep Disorders criteria to classify true cases and noncases. We evaluated 2 NLP and diagnosis code-only methods for their abilities to maximize phenotyping precision. The lead algorithm was used to identify incident and cross-sectional associations between sleep apnea and common comorbidities using 4876 NLP-defined sleep apnea cases and 3× matched controls. Results The optimal NLP phenotyping strategy had improved model precision (≥0.943) compared to the use of one diagnosis code (≤0.733). Of the tested diseases, 170 disorders had significant incidence odds ratios (ORs) between cases and controls, 8 of which were confirmed using polysomnography (n = 4544), and 281 disorders had significant prevalence OR between sleep apnea cases versus controls, 41 of which were confirmed using polysomnography data. Discussion and Conclusion An NLP-informed algorithm can improve the accuracy of case-control sleep apnea ascertainment and thus improve the performance of phenome-wide, genetic, and other EHR analyses of a highly prevalent disorder.

Stable Rates of Obstructive Hypertrophic Cardiomyopathy in a Contemporary Era

Hypertrophic cardiomyopathy is the most common genetic heart disease in the US, with an estimated prevalence of 1 in 500. However, the extent to which obstructive hypertrophic cardiomyopathy is clinically recognized is not well-established. Therefore, the objective of this study was to estimate the annual prevalence of clinically diagnosed oHCM in the US from 2016 to 2018. Data from the MarketScan® database were queried from years 2016 to 2018 to identify patients with ≥1 claim of oHCM (International Statistical Classification of Disease and Related Health Problems diagnosis code: I42.1). Prevalence rates for oHCM were calculated and stratified by sex and age. In 2016, 4,612 unique patients had clinical diagnosis of oHCM, resulting in an estimated oHCM prevalence of 1.65 per 10,000. The prevalence of oHCM in males and females was 2.07 and 1.26, respectively. Prevalence of oHCM was highest in patients 55–64 years of age (4.82). Prevalence of oHCM generally increased with age, from 0.36 per 10,000 in those under 18 to 4.82 per 10,000 in those 55–65. Trends in prevalence of oHCM over time, including by sex and age group, remained similar and consistent in 2017 and 2018. The prevalence of oHCM was stable over the 3-year time period, including higher rates of oHCM in males and patients aged 55–64 years. These results suggest that the majority of privately insured patients with oHCM are undiagnosed in the US and reinforce the need for policies and research to improve the clinical identification of oHCM patients in the US.

The Michigan Genomics Initiative: a biobank linking genotypes and electronic clinical records in Michigan Medicine patients

The recent wave of biobank repositories linking individual-level genetic data with dense clinical health history has introduced a dramatic paradigm shift in phenotyping for human genetic studies. The mechanism by which biobanks recruit participants can vary dramatically according to factors such as geographic catchment and sampling strategy. These enrollment differences leave an imprint on the cohort, defining the demographics and the utility of the biobank for research purposes. Here we introduce the Michigan Genomics Initiative (MGI), a rolling enrollment, single health system biobank currently consisting of >85,000 participants recruited primarily through surgical encounters at Michigan Medicine. A strong ascertainment effect is introduced by focusing recruitment on individuals in Southeast Michigan undergoing surgery. MGI participants are, on average, less healthy than the general population, which produces a biobank enriched for case counts of many disease outcomes, making it well suited for a disease genetics cohort. A comparison to the much larger UK Biobank, which uses population representative sampling, reveals that MGI has higher prevalence for nearly all diagnosis-code-based phenotypes, and larger absolute numbers of cases for many phenotypes. GWAS of these phenotypes replicate many known findings, validating the genetic and clinical data and their proper linkage. Our results illustrate that single health-system biobanks that recruit participants through opportunistic sampling, such as surgical encounters, produce distinct patient profiles that provide an ideal resource for exploring the genetics of complex diseases.

Synchronization of Codification of Unspecified Schizophrenia Againts Back-Referral System of Mirit Public Health Center

Background: The disease classification system is a grouping of diseases following the International Statistical Classification of Diseases and Related Health Problems Tenth Revisions ICD-10. The coding application must be in accordance with ICD-10 to obtain a valid code in disease indexing, national, international reporting of morbidity and mortality, analysis of health care costs, and epidemiological and clinical research. The diagnosis of schizoaffective disorder is made if schizophrenia and affective disorder are symptoms based on the ICD-10 diagnostic criteria. This study aims to determine the synchronization of the codification of unspecified schizophrenia and determine the factors that influence it against the back-referral system at the Mirit Health Center. Method: This research is qualitative research with a descriptive approach. Respondents were four officers, i.e. one doctor, one medical record officer, one person holding a mental program, one pharmacy officer. The number of observed medical record documents was 96 data with research indicators of accuracy and completeness of the diagnosis code in patients referred from First Level Health Facilities (FKTP) to Advanced Health Facilities (FKTL). Result: The results showed 30 referrals, with nine referrals having the accuracy of the patient referral diagnosis code. The back-referral program (PRB) for mental illness at the Mirit Health Center, in collaboration with Mbah Marsio's mental health rehabilitation center, was carried out well. However, the implementation of the Chronic Disease Management program (Prolanis) for mental health was still not good. Conclusion: There are many unsynchronized codifications. It is recommended to conduct an evaluation where they communicate with each other about the patient's condition to supervise the implementation of Referback Patients, especially to specialists who write the back-referral form.

Patient Characteristics and Temporal Changes in Anticoagulation Treatment Patterns in Patients Diagnosed with Cancer-Associated Thrombosis: An Oscar-US Analysis

Background: Although guidelines include direct-acting oral anticoagulants (DOACs) as an alternative to low molecular weight heparins (LMWHs) for treatment of cancer associated venous thrombosis (CAT), specific recommendations for selection of patients for DOAC treatment vary. Recommendations for use of DOACs are driven predominantly by perceptions of risk: benefit ratio (often associated with different cancer subtypes). We sought to assess patient characteristics and temporal changes in DOAC (vs. LMWH) utilization in patients being treated in routine practice for CAT. Methods: This analysis is part of the Observational Studies in Cancer Associated Thrombosis for Rivaroxaban - United States (OSCAR-US) program. OSCAR-US is an ongoing study utilizing longitudinal patient-level medical record data from Optum for 91+ million patients seen at 700+ hospitals and 7,000+ clinics across the US. To be included in the present study, adult patients had to be diagnosed with active (primary or metastatic) cancer, undergone hospitalization, emergency department or observation unit admission associated with a primary International Classification of Diseases (ICD)-9th or -10 th revision diagnosis code for venous thromboembolism (VTE) between January 2013 and September 2020, received a DOAC or LMWH on day 7 of CAT treatment, and been active in the data set for at least 12 months prior to the CAT. Cohort assignment was based upon anticoagulant received on day 7 to increase the study's likelihood of appropriately classifying patients into their intended long-term treatment group. We defined active cancer as any cancer associated with ongoing treatment with chemotherapy, immunotherapy, radiation, or recent surgery; the presence of metastatic disease (regardless of time from initial cancer diagnosis); or provider encounter with a primary diagnosis code for cancer within the 6 months prior to the CAT. We excluded patients with an alternative indication for anticoagulation use or evidence of anticoagulation during the 12 months prior (per written prescription or patient self-report). For this analysis, year of CAT diagnosis was grouped into three mutually exclusive categories (2013-2015, 2016-2018, and 2019-2020) to represent early DOAC availability for VTE, peri-DOAC CAT trials and post-CAT guideline recommendation periods. Categorical data were reported as percentages, while continuous data were reported as means ± standard deviations (SDs). Chi-square and independent sample t-tests were used to test for differences in characteristics and treatment patterns between cohorts. Results: In total, 95,072 adult patients experiencing a VTE-related hospitalization, emergency department or observation unit visit were identified. Of these, 14,377 (15.1%) met our pre-specified criteria for active cancer; including 84.7% who received a cancer treatment modality within 6-months and/or had metastatic disease (Table). Though a majority (76.0%) of patients received parenteral therapy as their first anticoagulant upon CAT diagnosis; on day 7 of CAT management, 5325 (52.0%) were receiving a DOAC and 4925 (48.0%) a LMWH. Mean age of patients was 65.2±13.7 years, body mass index (BMI) was 29.9±7.7 kg/m2 and 55.9% were women. Pulmonary embolism (PE)±deep vein thrombosis (DVT) was present in 47.2% of patients and more frequent in patients treated with LMWH than a DOAC on day 7 (p<0.001). The most common cancer types were lung (18.3%) genitourinary (13.5%), breast (12.7%) and colorectal (10.5%) (Figure). The proportion of patients treated with a DOAC increased substantially for all cancers over the three time periods evaluated (27.5% to 55.9% to 73.2%, p<0.001). This temporal relationship of increasing DOAC use (vs. LMWH) remained consistent across individual cancer subtypes (p<0.001 for all). Mean anticoagulant treatment duration was 193±143 days for the entire cohort and was longer in patients treated with DOACs vs. LMWHs (226±138 vs. 147±138 days, p<0.001). Conclusions: In this US population, DOACs were increasingly being utilized for the management of CAT patients and for longer treatment durations than LMWHs. The finding of increasing frequency in use of DOACs vs. LMWHs appeared consistent across all major cancer subtypes. Given their common use, future analyses should evaluate the real-world effectiveness and safety of DOACs compared to LMWHs within individual cancer subtypes. Figure 1 Figure 1. Disclosures Coleman: Bayer AG: Consultancy, Honoraria, Research Funding; Janssen Scientific Affairs LLC: Consultancy, Honoraria, Research Funding; Alexion Pharmaceuticals: Research Funding. Abdelgawwad: Bayer AG: Current Employment. Psaroudakis: Bayer AG: Current Employment. Fatoba: Bayer AG: Current Employment. Rivera: Bayer AG: Current Employment. Brobert: Bayer AG: Current Employment.

Older Age Instead of Body Mass Index Predicts Cancer-Associated Thrombosis: Validation of Khorana Score in Cancer Patients Undergoing Chemotherapy with East Asian Ethnicity

Khorana score has been the most widely used for the prediction of cancer-associated thrombosis (CAT) and recent pivotal phase III trials including AVERT and CASSINI adopted Khorana score in the inclusion criteria. However, most studies in development and use of Khorana score were conducted in Western cancer patients. The prevalence of VTE is known to be substantially lower in Asians than in the Western population. In case of body mass index (BMI), experts suggest an adjusted cut-off points of the classification of weight status in Asian population since they are usually thinner than Westerners. In addition, risk of CAT according to the sites of cancer may need reassessment since the characteristics of each site of cancer varies among geographic regions or ethnicity. For those reasons, we thought that Khorana score needs to be separately validated in Asian population and conducted a retrospective real-world analysis. By using the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM), we collected de-identified data of the newly diagnosed cancer patients who underwent chemotherapy from January 2016 to June 2019 at Seoul National University Hospital (SNUH), Seoul, South Korea. Patients were eligible if they 1) had a new diagnosis code of cancer and 2) had initiated chemotherapy within 3 months after the first recoding of the cancer diagnosis. The patients undergoing chemotherapy were identified based on their prescription of chemotherapeutic agents and the procedural code for the first-time patient education for chemotherapy. Among the selected cancer patients, values of complete blood cell counts (CBC), body weight, and height on the very day of or the day closest to the chemotherapy initiation were obtained. A patient was counted as having a VTE if he or she had both newly-recorded diagnosis code of VTE and new record of anticoagulant medication code within 1 week after the emergence of VTE diagnosis code. Cumulative incidence of CAT was estimated at the time of 3, 6, and 12 months after the date of chemotherapy initiation. A total of 10,588 patients with cancer and chemotherapy were eligible and only 1.33% (141 patients) had a CAT at 6 months after the chemotherapy initiation, suggesting lower overall incidence of CAT in Asian population. Pancreas (4.9%) was the most common primary cancer site but CAT incidence rate in patients with stomach cancer was limited to 1.6%, reflecting different characteristics of the disease between the East and the West. The CAT incidences in patients with lung cancer (1.4%) and lymphoma (1.1%) were lower than expected, in line with a recent meta-analysis (Mulder at al.; Haematologica 2019), but CAT incidences in patients with liver (3.4%) and biliary (3.0%) cancer were higher than expected considering the Khorana scoring system. Among 7,431 patients who had all data for the calculation of Khorana score, 5,549 patients (74.7%) had a BMI of < 25 kg/m 2, followed by 1,633 patients (15.4%) with a BMI of 25.0-29.9 kg/m 2. Only 39 patients (0.4%) had a BMI of 35 > kg/m 2, showing the difference of BMI distribution according to the ethnicity. Moreover, BMI was not associated with CAT development at all, whereas the 3 CBC parameters and the site of cancers were associated with CAT occurrence. In addition, patients who aged ≥ 65 years had significantly higher CAT risk compared to younger group. In a multivariate regression analysis (Table 1), age ≥ 65 years, leukocyte ≥ 11 x 10 3/μL, and sites of cancers were independently associated with the development of CAT. Hemoglobin < 10 g/dL and platelet ≥ 350 x 10 3/μL showed a tendency of association but failed to reach statistical significance. When we classified the 7,431 patients according to the Khorana scoring system, 8.0% of the patients were considered as high risk group and their incidence of CAT at 6 months was 3.36% (Table 2), showing a smaller proportion of patients assigned to high risk group and their lower absolute risk of CAT compared to Western population. In conclusion, Khorana scoring system was only partially validated in Korean cancer patients who underwent first-line chemotherapy: BMI was not but older age was a good predictor for the prediction of CAT occurrence. Weighing the risk of CAT according to the sites of cancers also needs some improvement. Further studies for better CAT risk stratification reflecting ethnic or regional differences are warranted. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis

Background: Performing adequately powered clinical trials in pediatric diseases such as systemic lupus erythematosus (SLE) is challenging. Improved recruitment strategies are needed for identifying patients. Design, Setting, Participants, and Measurements: Electronic health record (EHR) algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single center EHR data to develop computable phenotypes comprised of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled SLE patient database. The highest performing phenotypes were then evaluated across institutions in PEDSnet, a national healthcare systems network of >6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (n=350) and non-cases (n=350). Results: Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included ≥2 in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, ≥1 hydroxychloroquine exposure, and either ≥3 qualifying diagnosis codes separated by ≥30 days, or ≥1 diagnosis code and ≥1 kidney biopsy procedure code. Sensitivity was 100% (95%CI, 99-100); specificity, 92% (95% CI, 88-94); positive predictive value, 91% (95%CI, 87-94); negative predictive value, 100% (95%CI, 99-100). Lupus nephritis diagnostic criteria included either ≥3 qualifying lupus nephritis diagnosis codes (or SLE codes on same day as glomerular/kidney codes) separated by ≥30 days, or ≥1 SLE diagnosis code and ≥1 kidney biopsy procedure code. Sensitivity was 90% (95%CI, 85-94); specificity, 93% (95% CI, 89-97); positive predictive value, 94% (95%CI, 89-97); negative predictive value, 90% (95%CI, 84-94). Algorithms identified 1,508 children with SLE at PEDSnet institutions (537 with LN), 809 of whom were seen in the past 12 months. Conclusions: EHR-based algorithms for SLE and Lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.

1132. Evaluating an Amoxicillin Dosing Regimen for Community Acquired Pneumonia: A Quality Improvement Initiative Using Clinical and Laboratory Data

Background Amoxicillin 90 mg/kg/day divided twice daily is recommended for children with mild community acquired pneumonia (CAP). While adequate for fully susceptible Streptococcus pneumoniae isolates, three times daily dosing allows achievement of greater amoxicillin exposure, which may be necessary for isolates with penicillin minimum inhibitory concentrations (MIC) of ≥ 2 μg/mL. We evaluated our current twice daily amoxicillin dosing strategy by characterizing 1) the MIC distribution among S. pneumoniae isolates and 2) the frequency of clinical amoxicillin treatment failures. Methods We performed a retrospective cohort study of all S. pneumoniae isolates from sterile and non-sterile sites between 2017-2020. Breakpoints established by the CLSI were used for both meningitis and non-meningitis isolates. Only the first isolate per patient was included. We also evaluated the frequency of amoxicillin treatment failure in patients diagnosed with CAP who were discharged from the ED in 2019. CAP was defined as a discharge diagnosis code for pneumonia and an antibiotic prescription. Treatment failure was defined as an ED or primary care revisit, or admission, within 14 days during which an antibiotic change was made. Results 28 S. pneumoniae isolates were identified from sterile sites between 2017-2020 and 171 isolates were identified overall. All isolates from sterile sites had penicillin MICs of ≤ 2 μg/mL and 165 (96%) of isolates overall had penicillin MICs of ≤ 2 μg/mL (Table 1). Of these, 10 isolates had MICs of 2 μg/mL, all from non-sterile sites. In 2019, 589 patients were treated for CAP in the ED; 447 (76%) received amoxicillin and 142 (24%) were treated with alternative antibiotics. Treatment failures occurred in 15 amoxicillin-treated patients (3.3%, 95% confidence interval 1.9-5.5%) and in 5 patients (3.5%, 95% confidence interval 1.2-8.0%) treated with alternative antibiotics. Conclusion In vitro penicillin resistance was rare at our institution. Further, given that S. pneumoniae is rarely identified by culture, we also demonstrated that clinical amoxicillin treatment failures were infrequent using twice daily amoxicillin dosing. Coupled with provider and family preference, these data supported continuing our current practice of twice daily amoxicillin dosing. Disclosures All Authors: No reported disclosures

477. Increased Referrals for New PFAPA (Aphthous Stomatitis, Pharyngitis, Adenitis) Diagnosis During the COVID-19 Pandemic

Background COVID-19 pandemic caused by SARS-CoV-2 resulted in a global health crisis in 2020. Quarantining, wearing masks and physical distancing- key infection prevention strategies implemented to stop the spread of COVID-19, also led to dramatic decreases in rates of common respiratory viral infection seen in young children. Due to lack of school and daycare exposure, we evaluated a larger than usual number of patients with periodic fevers without any known infectious contacts. Based on this observation, we conducted an analysis of all suspected cases of periodic fevers seen at our institution during the COVID-19 lockdown compared to prior seasons. Methods The clinical charts were queried for all patients presenting to any Lurie Children’s Hospital outpatient specialty clinic or laboratory with ICD diagnosis code of MO4.1 and MO4.8 (all recurrent and periodic fever syndromes) from June 1, 2020 through September 30, 2020, and compared to similar months the previous 2 years (2018 and 2019). Each patient chart was reviewed by the lead investigator to verify all new diagnoses of PFAPA. The number of new patients with PFAPA diagnosis were tallied and analyzed. Statistical comparisons were made using Kruskal-Wallis tests for monthly distributions in different years. Results We noted a significant increase in patients with new PFAPA diagnosis between June through August 2020 compared to similar months in 2018 and 2019 (Figure1). Experienced pediatric infectious disease physicians and rheumatologists diagnosed majority of the cases. During these months, a monthly median (IQR) of 13 (11.5, 14.5) patients were diagnosed among different Lurie specialty clinics, which is more than 2.5 folds increase in new PFAPA patients from the previous two years which were about 5 (3.5, 6) (Figure 2). Number of Patients with New PFAPA Diagnosis There was a significant increase in number of new patients diagnosed with PFAPA between June through August 2020 compared to similar months in 2018 and 2019. Monthly Distribution Summary for New PFAPA Diagnosis Statistical comparisons were made using Kruskal- Wallis tests for monthly distributions in different years Conclusion We observed a significant increase in PFAPA patients referred to our institution soon after introduction of public health measures to slow spread of COVID-19. Given that most children were not in daycare, schools, or camps, we suspect that parents and pediatricians were able to recognize patterns of periodic fevers in children much quicker than preceding years, when fevers would typically be attributed to an infectious process. Disclosures Ravi Jhaveri, MD, AstraZeneca (Consultant)Dynavax (Consultant)Elsevier (Other Financial or Material Support, Editorial Stipend as Co-editor in Chief, Clinical Therapeutics)Seqirus (Consultant)