Inaccurate Coding Research Articles

Abstract 4123373: Estimating obesity-attributable cardiovascular disease burden in the United States: a Bayesian network analysis

Background: Obesity is a known contributor to the development of cardiovascular disease (CVD) and increases the risk of subsequent mortality. To fully understand the burden of obesity, accurate information regarding its effects on CVD is necessary. Current estimates are limited by a focus on direct effects, use of non-representative data sources, and a reliance on inaccurate diagnosis codes. Aim: To determine the size of CVD burden attributable to obesity in the US and identify the mechanisms through which obesity affects CVD. Methods: This study used data collected from US adults (aged ≥35 years) participating in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2020 and US Census projections. NHANES data were longitudinally adapted, and participants were excluded if they had missing data for weight history, risk factors, or a given outcome of interest. Bayesian networks (BNs) mapping out the relationship between risk factors and each outcome were constructed to estimate current CVD risk and expected CVD risk in the absence of obesity. Obesity-attributable CVD burden was then calculated for each outcome, and the direct and indirect pathways through which changes in CVD risk occur were characterized. A subgroup analysis was conducted in non-smoking participants aged ≤65 years for whom obesity is likely the primary CVD risk factor. Results: The final sample included data from approximately 29,000 participants. Of these, 1286 (4.3%) had a history of myocardial infarction (MI), 1283 (4.4%) had a history of stroke, 1092 (3.7%) had a history of heart failure (HF), and 1992 (6.7%) had a history of CVD (composite of MI, stroke, angina, coronary heart disease, and HF). Results from the fitted BN indicate that 21% of MI, 16% of stroke, 38% of HF, and 19% of CVD cases were attributable to obesity, with ≥80% of this burden due to the effect of obesity on intermediate risk factors (hypertension, type 2 diabetes, and prior cardiovascular events). In the subgroup analysis, the obesity-attributable CVD burden was approximately twice as high for non-smokers aged ≤65 years, with 39% of MI, 32% of stroke, 65% of HF, and 38% of CVD cases attributable to obesity. Conclusion: Through a sophisticated network modeling approach, we generated estimates of obesity-attributable CVD burden in the US. Results highlight the importance of obesity as a CVD risk factor, particularly in younger non-smokers, and provide insight into the nature of this relationship.

Neighborhood socioeconomic status and postpartum depression among commercial health insurance enrollees: a retrospective cohort study

BackgroundPostpartum depression (PPD) is a prevalent psychological condition. Although the effect of obstetrical and maternal complications on PPD are well described, the impact of neighborhood socioeconomic status (SES) on PPD is relatively unexplored.ObjectivesThis study examined the relationship between neighborhood SES score and PPD.MethodsA summary SES measure for each U.S. zip code was constructed using income, education, and occupational 2021 Census data and linked to national commercial claims for 2017–2023. PPD status using diagnosis codes at outpatient and inpatient visits, and prescription drug use 3, 6, 9, and 12 months postpartum, were determined. Multivariate analysis controlled for potential confounders.ResultsPPD prevalence in commercial claims was 11.48%. Patients with PPD had higher rates of obstetrical (OR: 1.555, p < .0001) and maternal complications (OR: 1.145, p < .0001), and more lifestyle risk factors (OR: 1.113, p < .0001). Comorbidity scores were higher for patients with PPD. Controlling for age and clinical factors, living in a disadvantaged neighborhood was associated with an increased incidence of PPD (OR: 1.137, p < .0001).LimitationsClaims data may include potential inaccurate coding of diagnoses/procedures. Clinical information is limited to conditions and treatments defined by ICD-10-CM codes. Area-based SES measures inevitably misclassify people on both ends of the socioeconomic spectrum (this misclassification is random; direction of bias is known).ConclusionsThe inverse and significant effect of area-based high SES on PPD rates demonstrates that preventive efforts may require interventions focusing on both the patient and the lived environment.

What does routine healthcare data tell us about the diagnostic pathway for older people with heart failure in Wales: under-testing, problems with access, or poor coding?

Abstract Background United Kingdom guidelines (NICE, NG106) for suspected chronic heart failure (HF) recommend that NT pro-BNP is performed as a first-line test. The result is also used to triage individuals; when NT pro-BNP is &amp;lt;400ng/L, a diagnosis of HF is less likely, echocardiography (echo) and specialist assessment should be performed within 6 weeks when the result is 400-2000ng/L, and within 2 weeks if &amp;gt;2000ng/L. How accurately this guidance is followed in clinical practice in Wales is not known. Purpose To examine how the current diagnostic pathway is recorded in routinely-collected electronic health record (EHR) data for older people in Wales with a diagnosis of heart failure. Methods We conducted a retrospective, population-level, observational study using linked anonymised EHR data in Wales (2015-22). We included patients aged 65y+ with a HF diagnosis in their primary or secondary care records and with a minimum of 12m pre and post-diagnosis data (for assessment of diagnostic pathway). We looked back from the point of HF diagnosis for codes associated with prior cardiovascular conditions (any time prior), symptoms (within 3 years), and key diagnostic tests (within 90 days). Results The final cohort comprised 51,020 individuals 65y and over with a diagnosis of heart failure between 2015-2022. Incidence and prevalence of heart failure increased across the study period (1.4-1.5% and 8.5-9.1% respectively). HF diagnosis was first evident in secondary care records in 54.9%, in primary care 36.3%, and in both data sources on the same day in 8.8%. Preceding cardiovascular diagnoses included hypertension (69.5%), atrial fibrillation (36.7%), myocardial infarction (30.5%), coronary artery disease (25.7%), and valve disease (17.7%). The most common recorded symptoms preceding diagnosis were breathlessness (41.4%), ankle oedema (9.8%), and fatigue (8.8%). Searched for symptoms were not recorded in 43.8%. In the 90 days preceding the diagnosis, 7-30% had recorded NT pro-BNP with the number of tests increasing throughout the study period (Figure 1). In the 90 days prior to HF diagnosis, 28-31% had an echo recorded. NT pro-BNP was &amp;gt;2000ng/L in 51.8%, 400-2000ng/L in 38.6% and &amp;lt;400ng/L in 9.6%. Conclusions In Wales, a greater number of individuals with heart failure appear to be diagnosed during hospital admission, compared with primary care. Many individuals with a code for HF in their records, do not have recorded objective evidence of cardiac dysfunction. The proportion of first-line and definitive tests appears low. It is unclear whether this is because of under-referral, difficulty accessing tests in primary care, or inaccurate coding of test referrals and results. These results are important in evaluating health service delivery and workforce planning.

Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on human interpretation, which can be expensive, time consuming, and prone to errors. With the transition from the International Classification of Diseases, Ninth Revision, to the International Classification of Diseases, Tenth Revision (ICD-10), the coding process has become more complex, highlighting the need for automated approaches to enhance coding efficiency and accuracy. Inaccurate coding can result in substantial financial losses for hospitals, and a precise assessment of outcomes generated by a natural language processing (NLP)-driven autocoding system thus assumes a critical role in safeguarding the accuracy of the Taiwan diagnosis related groups (Tw-DRGs). This study aims to evaluate the feasibility of applying an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), autocoding system that can automatically determine diagnoses and codes based on free-text discharge summaries to facilitate the assessment of Tw-DRGs, specifically principal diagnosis and major diagnostic categories (MDCs). By using the patient discharge summaries from Kaohsiung Medical University Chung-Ho Memorial Hospital (KMUCHH) from April 2019 to December 2020 as a reference data set we developed artificial intelligence (AI)-assisted ICD-10-CM coding systems based on deep learning models. We constructed a web-based user interface for the AI-assisted coding system and deployed the system to the workflow of the certified coding specialists (CCSs) of KMUCHH. The data used for the assessment of Tw-DRGs were manually curated by a CCS with the principal diagnosis and MDC was determined from discharge summaries collected at KMUCHH from February 2023 to April 2023. Both the reference data set and real hospital data were used to assess performance in determining ICD-10-CM coding, principal diagnosis, and MDC for Tw-DRGs. Among all methods, the GPT-2 (OpenAI)-based model achieved the highest F1-score, 0.667 (F1-score 0.851 for the top 50 codes), on the KMUCHH test set and a slightly lower F1-score, 0.621, in real hospital data. Cohen κ evaluation for the agreement of MDC between the models and the CCS revealed that the overall average κ value for GPT-2 (κ=0.714) was approximately 12.2 percentage points higher than that of the hierarchy attention network (κ=0.592). GPT-2 demonstrated superior agreement with the CCS across 6 categories of MDC, with an average κ value of approximately 0.869 (SD 0.033), underscoring the effectiveness of the developed AI-assisted coding system in supporting the work of CCSs. An NLP-driven AI-assisted coding system can assist CCSs in ICD-10-CM coding by offering coding references via a user interface, demonstrating the potential to reduce the manual workload and expedite Tw-DRG assessment. Consistency in performance affirmed the effectiveness of the system in supporting CCSs in ICD-10-CM coding and the judgment of Tw-DRGs.

Degradation in Binaural and Spatial Hearing and Auditory Temporal Processing Abilities as a Function of Aging.

Sensorineural hearing loss is common with advancing age, but even with normal or near normal hearing in older persons, performance deficits are often seen for suprathreshold listening tasks such as understanding speech in background noise or localizing sound direction. This suggests there is also a more central source of the problem. Objectives of this study were to examine as a function of age (young adult to septuagenarian) performance on: 1) a spatial acuity task examining lateralization ability, and a spatial speech-in-noise (SSIN) recognition task, both measured in a hemi-anechoic sound field using a circular horizontal-plane loudspeaker array, and 2) a suprathreshold auditory temporal processing task and a spectro-temporal processing task, both measured under headphones. Further, we examined any correlations between the measures.DesignSubjects were 48 adults, aged 21 to 78, with either normal hearing or only a mild sensorineural hearing loss through 4000 Hz. The lateralization task measured minimum audible angle (MAA) for 500 and 4000 Hz narrowband noise (NBN) bursts in diffuse background noise for both an on-axis (subject facing 0°) and off-axis (facing 45°) listening condition at signal-to-noise ratios (SNRs) of -3, -6, -9, and -12 dB. For 42 of the subjects, SSIN testing was also completed for key word recognition in sentences in multi-talker babble noise; specifically, the separation between speech and noise loudspeakers was adaptively varied to determine the difference needed for 40% and 80% correct performance levels. Finally, auditory temporal processing ability was examined using the Temporal Fine Structure test (44 subjects), and the Spectro-Temporal Modulation test (46 subjects). Mean lateralization performances were poorer (larger MAAs) in older compared to younger subjects, particularly in the more adverse listening conditions (4000 Hz, off-axis, and poorer SNRs). Performance variability was notably higher for older subjects than for young adults. The 4000 Hz NBN bursts produced larger MAAs than did 500 Hz NBN bursts. The SSIN data also showed declining mean performance with age at both criterion levels, with greater variability again found for older subjects. Spearman rho analyses revealed some low to moderate, but significant correlation coefficients for age versus MAA and age versus SSIN results. A low but significant correlation was also observed between the most adverse MAA and SSIN conditions. Results from both the TFS and STM assessments showed decreased mean performance with aging, and revealed moderate, significant correlations, with the strongest relationship shown with the TFS test. Finally, of note, extended-high-frequency (EHF) hearing loss (measured between 9000 and 16,000 Hz) was found in older but not young subjects, and correlated with decreasing performance on several tasks. Particularly for more adverse listening conditions, age-related deficits were found on both of the spatial hearing tasks and in temporal and spectro-temporal processing abilities. It may be that deficits in temporal processing ability contribute to poorer spatial hearing performance in older subjects due to inaccurate coding of binaural/interaural timing information sent from the periphery to the brainstem. In addition, EHF hearing loss may be a coexisting factor in the reduced performance in older subjects.

Impact of Inaccurate Clinical Coding on Financial Outcome: A Study in a local hospital in Najran, Saudi Arabia.

Coding in medical procedures is crucial for patients, and errors made by hospital administration during the coding process can have an impact on both the financial results and the course of therapy. The present study aims to assess the accuracy of diagnostic and procedural codes as recorded by the hospital's coders and to also evaluate their impact on the hospital's revenue. In a local hospital in Najran, Saudi Arabia, a cross-sectional observational analysis was conducted on patients with a clinical coder. The percentage of precision and error following the re-coding of cases was calculated using a statistical analysis. Primary diagnosis was incorrectly coded in 57 (26 per cent) records, and secondary diagnosis was incorrectly coded in 21 (9.9 per cent) records. Inaccurate medical labelling has been seen in emergency rooms, operating rooms, and gynaecology facilities. The percentage of records with the most incorrect coding was found to be 16 (7.5 per cent) in the emergency room, 10 (4.7 per cent) in the surgical clinic, and 5 (2.3 per cent) in the gynaecology/OBS clinic. Six (2.8 per cent) records in the private clinic had inaccurate secondary diagnoses, followed by four (1.9 per cent) and two (1 per cent) records in nephrology. The percentage of inaccurate clinical codes in primary diagnoses reached (26.8 per cent) and the percentage of incorrect clinical codes in secondary diagnoses reached (9.9 per cent).

(043) INACCURATE AND INADEQUATE ICD-10 CODING RELATED TO FEMALE SEXUAL HEALTH THREATENS PATIENT CARE, RESEARCH AND BILLING

Abstract Introduction The International Classification of Diseases (ICD) is an international health information system for the collection, processing, classification, and presentation of mortality statistics. The ICD 10th Edition (ICD-10) is a tool for physicians and billing professionals to accurately bill for the care provided. However, physicians who treat female sexual health (FSH) disorders report difficulty in finding appropriate codes for diagnoses and clinical syndromes (Parish et al. 2021). These issues impede the process for appropriate treatment and allotting the correct reimbursement to providers. Additionally, quantitative and qualitative research on FSH is limited due to the lack of accurate ICD codes for FSH disorders in this cohort. Objective This study aims to evaluate the ICD-10 coding system to assess the accuracy and quality of codes related to common FSH disorders. Methods A list of 50 most commonly encountered clinical FSH diagnoses was created based on clinical practice findings and ISSWSH guidelines. The list was compared against existing ICD-10 codes to characterize current FSH disorders that are recognized in ICD-10 and determine which FSH disorders are billable (ICD10data.com categorizes codes as “billable” or “non-billable”) or missing entirely. FSH diagnoses explicitly listed as an independent diagnosis or generally listed were considered ICD-10 coded. Diagnoses were considered to not have an existing code if they were not explicitly listed independently or under a more general term. Results 44% (n=22) of the diagnoses did not have existing ICD-10 codes, and 6% (n=3) of the diagnoses had appropriate ICD-10 codes but were not billable (Figure 1, Table 1). FSH diagnoses such as “clitoral adhesions”, “clitorodynia” and “persistent genital arousal disorder” were not coded in ICD-10. Many diagnoses were grouped under general terms - pelvic floor pain disorders were grouped under “R10.2: Pelvic and peroneal pain” which included both male and female diagnoses. Other codes had significant diagnostic overlap - “vulvodynia” was separately cataloged as “N94.810: vulvar vestibulitis”, “N94.818: Other vulvodynia” and “N94.819: vulvodynia, unspecified”. There were numerous common FSH diagnoses with incomplete, inaccurate, or outdated ICD codes. Conclusions These findings highlight the pressing need for an expanded, comprehensive, and precise set of ICD codes dedicated to FSH disorders. Without appropriate coding for 50% of FSH diagnoses, clinical care, research, and healthcare billing are severely impeded. It is much more difficult for physicians to accurately classify and bill for their procedures, which may create problems with clinical documentation leading to delayed treatment and poor clinical outcomes. For example, existing codes for “vulvodynia,” a common disorder affecting 16% of women, are vague and unclear, which lacks practicality for charting and billing purposes. Additionally, the limitations of ICD coding make it nearly impossible to research specific disorders, as they can not be searched in databases like TriNetX. These limitations may explain the large gaps in the literature regarding FSH disorders. Additionally, electronic medical records often have outdated ICD codes, further creating obstacles for clinicians. The current gap in classification, including ICD-10 coding and medical records, must be addressed to advance the understanding and management of FSH disorders. Disclosure No.

An algorithm to identify patients aged 0–3 with rare genetic disorders

BackgroundWith over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0–3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders.ResultsThrough expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy.ConclusionsThe PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

Completeness of Filling Out Medical Record Documents and the Accuracy of Codes at Reksodiwiryo Hospital

A hospital is an institution whose primary function is to provide health services to the community. One of the government's efforts to provide health services to the community is implementing the National Health Insurance Program (JKN), which the Social Security Program Organizing Agency organizes in the health sector. This research analyzed the factors associated with delays in BPJS claims at Dr. Hospital. Reksodiwiryo Padang. This research was a descriptive quantitative study with a cross-sectional study design. The research showed that six medical record files (6.5%) had inaccurate codes, while 86 (93.5%) used the correct ones. In addition, 91 files (98.9%) of inpatient medical records needed to be completed, and only one file (1.1%) was completed. Inaccuracy in diagnostic coding affects delays in submitting claims at Dr. Hospital. Reksodiwiryo Padang. It is hoped that officers can understand the coding rules based on ICD-10 for diagnoses and ICD-9 CM for actions or procedures to guarantee the quality of service at the hospital.

Segmentation of liver CT images based on weighted medical transformer model.

Deep convolutional neural networks have made significant strides in the field of medical image segmentation. Although existing convolutional structures enhance performance by leveraging local image information, they often lose the interdependence information between contexts. Therefore, the article utilizes the multi-attention mechanism of the Transformer structure to more comprehensively express relationships between contexts and introduced the Transformer network architecture into the field of medical image segmentation. Most models based on this Transformer structure typically require large datasets for training. However, in the medical field, the limited size of datasets makes training models with the Transformer structure challenging. To address this, the article propose a Weighted Medical Transformer (WMT) model that imposes low requirements on dataset quantity. The weighting mechanism in the WMT model aims to improve the issue of inaccurate relative positional coding when dealing with small medical datasets. Additionally, a coarse-grained and fine-grained segmentation mechanism is introduced, focusing on both the detailed aspects within image blocks and the boundary information connecting blocks. Experimental results on a liver dataset demonstrate that the model achieves F1 and IoU scores of 88.48% and 79.41%, respectively. Results on the MoNuSeg dataset show comparable high F1 and IoU scores of 79.58% and 66.19%, respectively. The model's accuracy surpasses that of U-Net++ and U-Net models. Compared to other models, this approach is applicable to scenarios with limited datasets, exhibiting high execution efficiency and accuracy.

Determining Factors For The Accuracy Of Diagnosis Codes Using ICD-10 In Obstetric Cases: Riview Systematics

Medical record coder has complete duties, responsibilities, authority and rights to carry out medical record service activities in health service units. The accuracy of the disease diagnosis code is crucial, the accuracy of the diagnosis code will affect the claim for treatment costs, the allocation of health resources and the accuracy of hospital statistical data. This research systematically reviews articles uses the PRISMA diagram to help sort articles to use, also have criteria: research data is data from Indonesia, uses Indonesian or English, the article was published 2018-2023, the article can be downloaded in full and is not a thesis. This research searched articles through the Google Scholar database, Garuda Portal and Research Gate. As a result of the review of the 7 articles, it is known that inaccurate diagnosis codes in obstetric cases are caused by 7 different factors. The most influential factors are information in MRD (Medical Record Document) is written as unclear or incomplete. The second reason is MRD is not double-checked or inspected and the last is code errors in categories and sub-categories.

A plurality of morphological characters need not equate with phylogenetic accuracy: A rare genomic change refutes the placement of Solifugae and Pseudoscorpionesin Haplocnemata.

Recent advances in higher-level invertebrate phylogeny have leveraged shared features of genomic architecture to resolve contentious nodes across the tree of life. Yet, the interordinal relationships within Chelicerata have remained recalcitrant given competing topologies in recent molecular analyses. As such, relationships between topologically unstable orders remain supported primarily by morphological cladistic analyses. Solifugae, one such unstable chelicerate order, has long been thought to be the sister group of Pseudoscorpiones, forming the clade Haplocnemata, on the basis of eight putative morphological synapomorphies. The discovery, however, of a shared whole genome duplication placing Pseudoscorpiones in Arachnopulmonata provides the opportunity for a simple litmus test evaluating the validity of Haplocnemata. Here, we present the first developmental transcriptome of a solifuge (Titanopuga salinarum) and survey copy numbers of the homeobox genes for evidence of systemic duplication. We find that over 70% of the identified homeobox genes in T. salinarum are retained in a single copy, while representatives of the arachnopulmonates retain orthologs of those genes as two or more copies. Our results refute the placement of Solifugae in Haplocnemata. Subsequent reevaluation of putative interordinal morphological synapomorphies amongchelicerates reveals a high incidence of homoplasy, reversals, and inaccurate coding within Haplocnemata and other small clades, as well as Arachnida more broadly, suggesting existing morphological character matrices are insufficient to resolve chelicerate phylogeny.

Worse Quality of Life Associated With Hyperextension Varus Tibial Plateau Fracture Pattern.

Compare patient-reported outcome measures between hyperextension varus tibial plateau (HEVTP) fracture patterns to non-HEVTP fracture patterns. Retrospective study. Single academic Level 1 Trauma Center. All patients who underwent fixation of a tibial plateau fracture from 2016 to 2021 were collected. Exclusion criteria included inaccurate Current Procedural Terminology code, ipsilateral compartment syndrome, bilateral fractures, incomplete medical records, or follow-up <10 months. In patients who underwent fixation of a tibial plateau fracture, compare Patient-Reported Outcomes Measurement Information System-Physical Function, PROMIS Preference, and Knee Injury and Osteoarthritis Outcome Score (KOOS) between patients with a HEVTP pattern with those without. Two-hundred and seven patients were included, of which 17 (8%) had HEVTP fractures. Compared with non-HEVTP fracture patterns, patients with HEVTP injuries were younger (42.6 vs. 51.0, P = 0.025), more commonly male (71% vs. 44%, P = 0.033), and had higher body mass index (32.8 vs. 28.0, P = 0.05). HEVTP fractures had significantly more ligamentous knee (29% vs. 6%, P = 0.007) and vascular (12% vs. 1%, P = 0.035) injuries. Patient-Reported Outcomes Measurement Information System-Physical Function scores were similar between groups; however, PROMIS-Preference (0.37 vs. 0.51, P = 0.017) was significantly lower in HEVTP fractures. KOOS pain, activities of daily living, and quality-of-life scores were statistically lower in HEVTP fractures, but only KOOS quality-of-life was clinically relevant (41.7 vs. 59.3, P = 0.004). The HEVTP fracture pattern, whether unicondylar or bicondylar, was associated with a higher rate of ligamentous and vascular injuries compared with non-HEVTP fracture patterns. They were also associated with worse health-related quality of life at midterm follow-up. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

In-Hospital Code Status Updates: Trends Over Time and the Impact of COVID-19.

The primary objective was to evaluate if the percentage of patients with missing or inaccurate code status documentation at a Trauma Level 1 hospital could be reduced through daily updates. The secondary objective was to examine if patient preferences for DNR changed during the COVID-19 pandemic. This retrospective study, spanning March 2019 to December 2022, compared the code status in ICU and ED patients drawn from two data sets. The first was based on historical electronic medical records (EHR), and the second involved daily updates of code status following patient admission. Implementing daily updates upon admission was more effective in ICUs than in the ED in reducing missing code status documentation. Around 20% of patients without a specific code status chose DNR under the new system. During COVID-19, a decrease in ICU patients choosing DNR and an increase in full code (FC) choices were observed. This study highlights the importance of regular updates and discussions regarding code status to enhance patient care and resource allocation in ICU and ED settings. The COVID-19 pandemic's influence on shifting patient preferences towards full code status underscores the need for adaptable documentation practices. Emphasizing patient education about DNR implications and benefits is key to supporting informed decisions that reflect individual health contexts and values. This approach will help balance the considerations for DNR and full code choices, especially during health care crises.

Assessment of clinical miscoding errors and potential financial their implications on healthcare management – A case of local hospital in Najran, Saudi Arabia

BackgroundHealthcare systems can potentially improve their safety, quality of service, and performance efficiency with a cost reduction, through the introduction and implementation of healthcare information management systems. This study aims to examine the frequency of miscoding errors in principal and secondary diagnoses, exploring demographic and coder-related factors contributing to these errors through the use of the QuadraMed system. The study also investigates the association of coding errors with patient safety and service quality to estimate the potential financial implications resulting from these inaccuracies in the healthcare system. MethodsThis analytical cross-sectional retrospective study was conducted at a local hospital in Najran, Saudi Arabia, from July 2021 to February 2022 using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) coding system. The costing and financial data were collected from the reimbursement department for eligible 750 patient cases in terms of payment mode, services availed, and length of stay. The financial claims were evaluated to estimate the impact on the quality of service and patient safety. The reimbursement amount was calculated based on codes. The data were analyzed using SPSS and the odds ratio was calculated to estimate the risk of major coding errors in different departments. ResultsPrimary codes 240 (32%) and 40 (5.3) secondary codes were reviewed and percentages and inaccuracies were calculated after recording. The percentage of inaccurate medical codes in principal diagnosis was 57(26.8%) and the percentage of inaccurate medical codes in secondary diagnosis was 21 (9.9%). The primary diagnostic codes have more coding errors with a total number of 240 (32%) coding errors with a moderate level of agreement between the original coder and independent coder with a kappa value of 0.462. The identified recording was done by the independent coder, and the secondary diagnostic code showed 40 (5.3%) cases, with a poor kappa value of 0.128. The results showed the highest number of primary diagnostic codes was among surgery clinics 79 (63.2%). The highest number of secondary diagnostic codes were reported among consultant clinics 12 (9.6%) ConclusionsThe study concludes that the identification of miscoding in the healthy population has a financial impact on the healthcare organization's infrastructure.

Hubungan Ketepatan Penulisan Diagnosis Penyakit dengan Keakuratan Kode Diagnosis pada Pasien Rawat Inap di Rumah Sakit

The accuracy of the disease diagnoses code is determined by the accuracy of writing the diagnoses. The result of observation in 10 inpatient medical record documents at the TNI-AD 05.08.04 Hospital Lawang, 5 documents were found with inaccurate codes (50%) with 3 incorrectly written diagnoses. The purpose of this study was to analyze the effect of the accuracy in writing disease diagnoses to the accuracy of the diagnoses code for inpatients at the TNI-AD 05.08.04 Hospital, Lawang. This methode of research was an analytic observational with a cross-sectional approach. The number of sample analyze were 100 inpatient medical record documents which hospitalitaion from March to August 2022 and using simple random sampling technique by lottery. The accuracy of writing diseases diagnoses of inpatient was an independent variable and the accuracy of the diagnoses code for the inpatient at the TNI-AD 05.08.04 Hospital, Lawang was dependent variable in this study. The results showed the accuracy in writing disease diagnoses was 70% and the accuracy of the disease diagnoses code was 45%. The analytic test with Chi Square showed significantly the effect of accuracy in writing diseases diagnoses to the accuracy of diagnoses code for inpatient at the TNI-AD 05.08.04 Hospital Lawang with a p-value = 0.000 (&lt;0.05). The accuracy in writing diseases diagnoses by doctor that refer to medical terminology of ICD-10 will producted an accurate diagnoses codes.

Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data

PurposeTimely and accurate data on the epidemiology of sepsis are essential to inform policy decisions and research priorities. We aimed to investigate the validity of inpatient administrative health data (IAHD) for surveillance and quality assurance of sepsis care.MethodsWe conducted a retrospective validation study in a disproportional stratified random sample of 10,334 inpatient cases of age ≥ 15 years treated in 2015–2017 in ten German hospitals. The accuracy of coding of sepsis and risk factors for mortality in IAHD was assessed compared to reference standard diagnoses obtained by a chart review. Hospital-level risk-adjusted mortality of sepsis as calculated from IAHD information was compared to mortality calculated from chart review information.ResultsICD-coding of sepsis in IAHD showed high positive predictive value (76.9–85.7% depending on sepsis definition), but low sensitivity (26.8–38%), which led to an underestimation of sepsis incidence (1.4% vs. 3.3% for severe sepsis-1). Not naming sepsis in the chart was strongly associated with under-coding of sepsis. The frequency of correctly naming sepsis and ICD-coding of sepsis varied strongly between hospitals (range of sensitivity of naming: 29–71.7%, of ICD-diagnosis: 10.7–58.5%). Risk-adjusted mortality of sepsis per hospital calculated from coding in IAHD showed no substantial correlation to reference standard risk-adjusted mortality (r = 0.09).ConclusionDue to the under-coding of sepsis in IAHD, previous epidemiological studies underestimated the burden of sepsis in Germany. There is a large variability between hospitals in accuracy of diagnosing and coding of sepsis. Therefore, IAHD alone is not suited to assess quality of sepsis care.

Impact of the COVID-19 Pandemic on the Management of Gallbladder, Biliary Tract, and Pancreatic Diseases.

Introduction Biliary diseases are a major acute general surgical burden. Laparoscopic cholecystectomy is the gold standard surgical procedure, although it was discontinued during an outbreak. Effective management permits decisive therapy, symptom alleviation, and fewer hospitalizations and complications. Throughout the initial COVID-19 situation, surgical procedures for patients were delayed. Invasive services were required to employ conservative or non-operative therapy, which could lead to increased recurring presentations and biliary-pancreatic problems. Aim Examining the impact of COVID-19 on the outcomes and hospitalizations of patients suffering from gallstone, biliary tract, and pancreatic diseases. Methods The retrospective analysis included patients with the following ICD-10 codes who presented to our unit: cholelithiasis (K80), cholecystitis (K81), and acute pancreatitis (K85). We compared the interval of the first COVID-19 pandemic wave, from March to August 2020, with the period before the pandemic, referred to as Pre-COVID-19. After applying exclusion criteria, a total of 868 patients were enrolled in the trial, having initially recruited around 1,400 individuals using these codes. Patients with inaccurate coding, cancer, or non-stone disease were excluded (e.g., alcoholic pancreatitis). The demographic information, admission details, investigations, surgical therapy, operating specifics, and postoperative complications of the patients were noted. Changes in surgical management, patient representation, and postoperative complications were the key outcomes. Results A statistically significant (p<0.05) rise was seen in repeat presentations in the COVID group, most likely due to the failure of definitive treatment. The other outcome is the distribution of presentations was comparable, patients with acute cholecystitis and gallstone pancreatitis showed statistically significant (p<0.05) lower rates of definitive therapy. Conclusion During the COVID period, all surgeries except those for cancer were halted. Unknown causes led to several consequences related to the gallbladder, biliary tract, and pancreas. Patients with cholecystitis, gallstone pancreatitis, and pancreatic inflammation experienced a lower probability of treatment. The increase in hospitalizations and self-presentations indicated that definitive therapy, designed to restrict COVID-19 exposure, actually increased patient risk. Despite this risk, we had no COVID-19 instances in our cohort. The evaluation of the long-term consequences of the pandemic on acute pancreatitis and its care will require a large-scale, multicenter investigation.

TINJAUAN KETIDAKTEPATAN KODE DIAGNOSIS PENYAKIT DAN TINDAKAN MEDIS KASUS GIGI DAN MULUT RAWAT JALAN DI RUMAH SAKIT X JAKARTA

ABSTRACT&#x0D; This research is to identify the Standard Operating Procedure (SPO) coding, calculate the number of inaccuracies in the disease diagnosis code and medical treatment in outpatient dental and oral cases and the factors causing the code inaccuracy. The research method used is descriptive analysis research method with data collection techniques by observation and interviews. The population of this study amounted to 2141 medical records, especially in the clinical summary in November 2021-April 2022, samples taken as many as 96 clinical summaries. The results of the study: the SOP has been carried out but is in the process of being revised and not yet perfect, the inaccuracy rate of the incorrect disease diagnosis code is 29 (30.20%) and the correct one is 67 (69.80%), while the inaccurate medical code of action is 18 (18.75%) and the correct one is 78 (81.25%), Causing factors: SOP steps are not perfect, the competence of coding officers is still lacking, identification of medical diagnoses and actions is less detailed, and lack of evaluation, especially periodic coding audits.&#x0D; Bibliography : 17 (2006 – 2020)&#x0D; Keywords : Code, Diagnosis, Medical Action, Clinical Summary, Dental, Oral

ANALISIS KEAKURATAN KODIFIKASI DIAGNOSIS TERHADAP KUALITAS LAPORAN MORBIDITAS RAWAT JALAN (RL 4b) DI RUMAH SAKIT UMUM HERMINA PASTEUR BANDUNG

The guidelines for writing major diagnoses have an impact on how they are coded; each diagnostic statement must be clear and informative in order to place the disease in the ICD-10 category with the highest level of specificity. The accuracy of the diagnosis, the readability of the doctor's writing, the professionalism of the doctor and the coding, and other factors all influence the quality of the coding findings. The literature review was used as the research design. The codification analysis has not been carried out ideally so that there is still inaccurate code and makes the reports that have been made less accurate and seen from the preparation and delivery of reports that have been carried out on time so that the level of relevance of the report is 92%.&#x0D; Research analysis on the accuracy of codification of diagnoses on the quality of outpatient morbidity reports (RL 4b), based on a sample of 100 medical records examined, 100 medical records that were accurate 60 or 60% and 40 medical records that were inaccurate or 40%, Reliability test results with using the Cronbachs Alpha method with a significance level of 10% (0.1), namely 0.923, was then taken into consideration. This value is greater than the r table value of 0.4409 which indicates that the reliability test was successful and the questionnaire results are reliable.&#x0D; .Keywords: Codification; diagnosis; Medical records