Accuracy Of Coding Research Articles

Training Programs for Improving Speech Perception in Noise: A Review.

Understanding speech in the presence of noise is difficult and challenging, even for people with normal hearing. Accurate pitch perception, coding and decoding of temporal and intensity cues, and cognitive factors are involved in speech perception in noise (SPIN); disruption in any of these can be a barrier to SPIN. Because the physiological representations of sounds can be corrected by exercises, training methods for any impairment can be used to improve speech perception. This study describes the various types of bottom-up training methods: pitch training based on fundamental frequency (F0) and harmonics; spatial, temporal, and phoneme training; and top-down training methods, such as cognitive training of functional memory. This study also discusses music training that affects both bottom-up and top-down components and speech training in noise. Given the effectiveness of all these training methods, we recommend identifying the defects underlying SPIN disorders and selecting the best training approach.

Diagnostic and sentinel surveillance process for amebiasis in the emergency department

BackgroundThis study aimed to determine amebiasis incidence, explore diagnostics, investigate physician practices, and understand surveillance perspectives. MethodsThis mixed-method study employs hospital-based sentinel surveillance, combining quantitative analysis of diagnostic tests and qualitative interviews with ED physicians. Using an exploratory case study approach, data were systematically collected to understand amoebiasis diagnosis and surveillance. Retrospective cross-sectional analysis included adults with gastroenteritis symptoms at the ED. Blood data and amebiasis test results were compared between patient groups. Ten ED physicians were interviewed to explore diagnostic practices and patient care. Interviews were transcribed, analyzed for themes, and assessed for reliability. ResultsOver the study duration, 676 ED patients exhibited gastroenteritis symptoms, with 293 providing stool samples for amebiasis antigen testing. Among them, 65 (22.2 %) showed positive amebiasis antigen presence. No significant age or gender differences were observed. August had the most tests (31.1 %), while September showed the highest positive rates (21.5 %). Blood parameter analyses revealed lower urea levels in the amebiasis (+) group (p = 0.018). Eosinophil counts were lower (p = 0.023) and MCHC was significantly reduced in the amebiasis (+) group (p = 0.039). Interviews unveiled physician considerations for testing and discharge protocols. EDs played a vital role in surveillance due to their initial contact status. Challenges included time constraints, limited facilities, and high patient numbers. Recommendations for improved ED surveillance involved training, accurate coding, strategic examinations, inter-departmental cooperation, and community awareness. ConclusionSentinel surveillance in EDs offers a promising approach for infection monitoring, advancing early detection and management strategies. Insights highlight EDs' potential in enhancing infectious disease surveillance.

Ophthalmology Operation Note Encoding with Open-Source Machine Learning and Natural Language Processing

Introduction: Accurate assignment of procedural codes has important medico-legal, academic, and economic purposes for healthcare providers. Procedural coding requires accurate documentation and exhaustive manual labour to interpret complex operation notes. Ophthalmology operation notes are highly specialised making the process time-consuming and challenging to implement. This study aimed to develop natural language processing (NLP) models trained by medical professionals to assign procedural codes based on the surgical report. The automation and accuracy of these models can reduce burden on healthcare providers and generate reimbursements that reflect the operation performed. Methods: A retrospective analysis of ophthalmological operation notes from two metropolitan hospitals over a 12-month period was conducted. Procedural codes according to the Medicare Benefits Schedule (MBS) were applied. XGBoost, decision tree, Bidirectional Encoder Representations from Transformers (BERT) and logistic regression models were developed for classification experiments. Experiments involved both multi-label and binary classification, and the best performing model was used on the holdout test dataset. Results: There were 1,000 operation notes included in the study. Following manual review, the five most common procedures were cataract surgery (374 cases), vitrectomy (298 cases), laser therapy (149 cases), trabeculectomy (56 cases), and intravitreal injections (49 cases). Across the entire dataset, current coding was correct in 53.9% of cases. The BERT model had the highest classification accuracy (88.0%) in the multi-label classification on these five procedures. The total reimbursement achieved by the machine learning algorithm was $184,689.45 ($923.45 per case) compared with the gold standard of $214,527.50 ($1,072.64 per case). Conclusion: Our study demonstrates accurate classification of ophthalmic operation notes into MBS coding categories with NLP technology. Combining human and machine-led approaches involves using NLP to screen operation notes to code procedures, with human review for further scrutiny. This technology can allow the assignment of correct MBS codes with greater accuracy. Further research and application in this area can facilitate accurate logging of unit activity, leading to reimbursements for healthcare providers. Increased accuracy of procedural coding can play an important role in training and education, study of disease epidemiology and improve research ways to optimise patient outcomes.

The Transformative Potential of Artificial Intelligence in Medical Billing: A Global Perspective

This paper explores the transformative potential of Artificial Intelligence (AI) in revolutionizing medical billing processes worldwide. As healthcare systems face increasing complexities and challenges, AI offers innovative solutions to streamline billing operations, enhance accuracy, and improve financial outcomes. By automating the claims processing workflow, AI can significantly reduce the administrative burden on healthcare providers, allowing them to focus more on patient care. AI-powered coding accuracy systems can analyze medical records and suggest appropriate billing codes, reducing coding errors and claim rejections. AI can also optimize reimbursement strategies by analyzing historical data and identifying patterns to ensure optimal reimbursement rates for healthcare providers. To address the growing concern of healthcare fraud, AI algorithms can analyze vast amounts of data, detect suspicious patterns, and flag potentially fraudulent activities, thus preventing financial losses. Moreover, AI-powered chatbots and virtual assistants can enhance patient engagement by providing personalized support, answering billing-related queries, and guiding patients through the payment process. Adoption of AI in medical billing brings various benefits, it also presents challenges such as data privacy, algorithm bias, and the need for robust infrastructure and training. Successful case studies from various healthcare settings worldwide demonstrate the tangible advantages of AI implementation, such as reduced billing errors, accelerated reimbursement cycles, and improved patient satisfaction. By harnessing the power of AI, healthcare systems can achieve greater efficiency, financial sustainability, and improved patient experiences.

Coding and applying injury claims data to implement and sustain effective safe patient handling and mobility solutions

Investigating and accurately categorizing employee injury claims are essential for identifying trends and implementing effective solutions. This process is especially important for injuries associated with patient handling injuries (PHIs) for which data is often lacking. This study summarizes how improved coding of injuries for 15 years of workers’ compensation (WC) data was used to improve system-wide injury prevention efforts, in particular those related to safe patient handling and mobility (SPHM) practices across an 11-hospital region within the system. Accurate coding of caregiver injuries and implementing SPHM solutions based on this data had a significant impact on accurately identifying risk, implementing injury prevention strategies, and decreasing frequency and severity of employee injuries related to outdated manual patient handling practices.

Accuracy of ICD-10 Coding for Femoral Head Bearing Surfaces in Hip Arthroplasty

BackgroundThe International Classification of Diseases-10 Procedure Code System (ICD-10-PCS) introduced oxidized zirconium (OxZi) and niobium procedural codes to the types of femoral head bearing surfaces in 2017. These codes aimed to increase procedural specificity in coding and improve data collection through administrative claims databases. This study aimed to assess the accuracy of ICD-10-PCS coding for femoral head bearing surfaces (cobalt chrome/metal, ceramic, and OxZi) in hip procedures. MethodsA retrospective analysis of 6,204 procedures utilizing femoral heads performed between October 1, 2017 and August 26, 2021 at a large, urban academic hospital was conducted. Operative reports and implant logs were queried to determine the femoral head bearing surface, which was used during the total hip arthroplasty. These results were then compared to the ICD-10-PCS codes in the billing records. Coding accuracy was subsequently determined and statistical differences between the three groups were evaluated. ResultsThe ICD-10-PCS coding was accurate for 90.8% (5,634/6,204) of cases. Coding accuracy for ceramic femoral heads (95.4%, 4,171/4,371) was significantly greater than that of both cobalt chrome/metal (73.7%, 606/822; P < .001) and OxZi (84.8%, 857/1,011; P < .001) femoral heads. ConclusionWhile coding for ceramic femoral heads was very accurate, OxZi and cobalt chrome/metal femoral heads were miscoded at a rate of approximately 20%. These inaccuracies call for further evaluation of the ICD-10-PCS coding process to ensure that conclusions drawn from clinical research performed through administrative claims databases are not subject to error.

HPB P40 Assessing The Cholecystectomy Pathway: Are Standards Being Truly Met?

Abstract Background Research suggests better outcomes for patients having cholecystectomy &amp;lt;8 days of presenting with symptoms1. Locally collected data from the GI surgery department at Royal Surrey County Hospital (RSCH) reported that 94% of eligible cases with acute biliary pathology underwent cholecystectomy &amp;lt;8 days of presentation. However, Hospital episode statistics (HES) data suggest it's lower. RSCH participates in a national project evaluating the care of patients presenting acutely with biliary pathology (the CholoeQuic-ER study), and the latest outcomes from that study indicate that we are in the top 5 trusts nationally for acute management of gallstone disease, with a median time from admission to surgery of 3 days, resulting in significant improvements in bed occupancy and patient experience The primary aim was to ascertain what proportion of patients; 1) were eligible for an acute cholecystectomy or deemed unfit. 2) were eligible for cholecystectomy but were not referred during the inpatient admission, 3) were coded as having acute biliary pathology but had an alternative primary diagnosis. The secondary aim was to ascertain whether they met the standard of undertaking cholecystectomy &amp;lt;8 days of presentation with gallstone disease and why there was a discrepancy between the departmental data and HES data. Methods The hospital coding department provided a list of patients discharged from RSCH in September 2019 with a coding suggesting acute biliary pathology. ICD-10 codes covering cholelithiasis, cholecystitis, other diseases of the gallbladder and acute pancreatitis were used (the same methodology as the CholeQuic-ER study). Results There were 118 patients who were discharged in September 2019 with ICD-10 codes diagnostic of acute biliary pathology. Of the 118 patients, 48 (40.7%) were correctly coded with biliary pathology and 70 (59.3%) were not. Twenty-eight (58.3%) of those patients who were correctly coded had a surgical/ procedural intervention. Twenty (41.7%) of the correctly coded patients did not have surgical/procedural intervention, 9 (45%) discharged with outpatient surgical/AEC review pertaining to the biliary pathology. Nine (45%) discharged with alternative primary diagnosis, 2 (10%) discharged with a primary biliary pathology and no surgical intervention/follow-up. Of the original 118 patients, 70 (59.3%) patients did not have biliary pathology; 31 (44.2%) had no data specifically for September 2019, for the further 39 (55.7%) patients, there was incorrect coding e.g. Pneumonia Using the ICD codes employed by the CholeQuic-ER study, 66.9% of cases identified were inappropriately classified as primary biliary pathology and were not eligible for cholecystectomy. The final outcomes were 28/48 (58.3%) had underwent appropriate procedure for their primary biliary pathology at index admission. 20/48 (41.7%) did not have definitive treatment at their index admission. Conclusions The results demonstrate a high number of patients with acute biliary pathology who did not undergo definitive treatment at their index admission or within 8 days of presentation. Use of the methodology employed by the CholeQuic-ER study using HES data was inaccurate in correctly identifying patients with acute biliary pathology. Accurate coding of patients requires liaison between coding and clinical teams to help narrow discrepancies between HES data and RSCH data not only in the field of general surgery but in other departments. We plan to work with the coding department to improve the outcome coding to help reflect the excellent outcomes we are achieving for these patients.

10. Audit Reviewing the Accuracy of Coding for Temporal Artery Biopsies at a Large Teaching Hospital

North Manchester General Hospital (NMGH) has recently undergone a change in parent trust from the Pennine Acute Hospitals NHS Trust (PAT) to Manchester University NHS Foundation Trust (MFT). Temporal Artery Biopsy (TABx), a procedure not infrequently performed at the OMFS unit, follows urgent referral from Rheumatology colleagues for suspected Giant Cell Arteritis (GCA). A review of coding applied to these procedures is performed, aiming to establish whether payments been appropriate. The gold standard is met if the the correct code/correct payment are applied.

Surgical site infection in thoracic and lumbar fractures: incidence and risk factors in 11,401 patients from a nationwide administrative database

BACKGROUND CONTEXTThe rate of surgical site infection (SSI) following elective spine surgery ranges from 0.5%‒10%. Published reports suggest a higher SSI rate in non-elective spine surgery such as spine trauma; however, there is a paucity of large database studies examining this issue. PURPOSEThe objective of this study was to investigate the incidence and risk factors of SSI in patients undergoing spine surgery for thoracic and lumbar fractures in a large population database. STUDY DESIGN/SETTINGThis is a retrospective study utilizing the PearlDiver Patient Claims Database. PATIENT SAMPLEPatients undergoing spine surgery for thoracic and lumbar fractures between 2015-2020 were identified in the PearlDiver Patient Claims Database using ICD-10 codes. Patients were excluded who had another surgery either 14 days before or 21 days after the index spine surgery, or pathologic fracture. OUTCOME MEASURESRate of surgical site infection. METHODSClinical data collected from the PearlDiver database based on ICD-10 codes included gender, age, diabetes, smoking status, obesity, Elixhauser Comorbidity Index (ECI), Charlson Comorbidity Index (CCI), and SSI. Univariate analysis was used to assess the association of potential risk factors and SSI. Multivariable analysis was used to identify independent risk factors of SSI. The authors have no conflicts of interest or funding sources to declare. RESULTSA total of 11,401 patients undergoing spine surgery for thoracic and lumbar fractures met inclusion criteria, and 1,065 patients were excluded. 860 patients developed SSI (7.5%). Risk factors significantly associated with SSI in univariate analysis included diabetes (OR 1.50; 95% CI, 1.30‒1.73; p<.001), obesity (OR 1.66; 95% CI, 1.44‒1.92; p<.001), increased age (p<.001), ECI (p<.001), and CCI (p<.001). On multivariable analysis, obesity and ECI were independently associated with SSI (p<.001 and p<.001, respectively). CONCLUSIONSNon-elective surgery for thoracic and lumbar fractures is associated with a 7.5% risk of SSI. Obesity and ECI are independent predictors of SSI in this population. Limitations include the reliance on accurate insurance coding which may not fully capture all SSI, and in particular superficial SSI. These findings provide a broad overview of the risk of SSI in this population at a national level and may also help counsel patients regarding risk.

Community-based, Hospital-Affiliated Medical Group Becomes a Successful Accountable Care Organization.

Leadership of a multispecialty group practice within a health system recognized in 2015 that population health management requires quality performance improvement and organizational culture change. While blueprints for building successful Accountable Care Organizations (ACOs) exist in the literature, few describe the journey to achieving both shared savings and high quality outcomes achieved by a medical group within an academic health system. Clinician education and engagement, prioritizing prevention and achieving benchmarks, developing supportive roles, more precise documentation of accurate diagnostic coding, and risk stratification constituted the approach. When first participating as an ACO, the medical group built programs and teams to improve quality, while CMS simultaneously changed quality measurements from pay-for-reporting to pay-for-performance. Quality scores initially dipped, though scores have since risen to 98.44% in 2020. Between 2015 and 2017, financial results were more than $10 million below the threshold, while in performance years 2018 to 2020, Northeast Medical Group achieved $24 million in aggregate in shared savings.

Administrative Data Relationship with The Accuracy of Disease Diagnosis Codes of Inpatients in Pariaman Public Hospital

ABSTRACTÂ Medical records are one of the means to support the achievement of an administrative order in the context of efforts to improve health services in hospitals. An important thing that must be considered by medical record personnel is the accuracy in providing diagnosis and procedure codes. The research problem is the accuracy of the coding of the Diagnosis &amp; Procedure on the medical records of inpatients at the Pariaman Regional General Hospital. The research objective was to describe the general characteristics and accuracy of disease coding based on diagnosis and service procedures as well as the impact of the accuracy of disease coding with inpatient disease diagnosis on the quality of service at the Pariaman Regional General Hospital. The research method is mixed methods. A quantitative approach to the patient's medical record file and a qualitative approach were obtained through FGDs with medical record management officers. The results showed that the accuracy of the main Diagnosis coding has shown results that exceed 80% of all medical records of patients selected as the study sample. However, the accuracy of the secondary diagnosis code is only 50%. Procedure code acceleration is still very low at only 15.4%, and secondary procedure only at 1.8%. The conclusion of the study, the accuracy of the diagnosis code and procedures is closely related to the quality of service. Inaccuracy of diagnosis codes as well as procedures will affect patient satisfaction, especially in payments that are not in accordance with the services they receive. Â Keywords : Encoding, Diagnosis, Procedure, Medical records

Development and testing of diagnostic algorithms to identify patients with acromegaly in Southern Italian claims databases

Acromegaly is a rare disease characterized by an excessive production of growth-hormone and insulin-like growth factor 1, typically resulting from a GH-secreting pituitary adenoma. This study was aimed at comparing and measuring accuracy of newly and previously developed coding algorithms for the identification of acromegaly using Italian claims databases. This study was conducted between January 2015 and December 2018, using data from the claims databases of Caserta Local Health Unit (LHU) and Sicily Region in Southern Italy. To detect acromegaly cases from the general target population, four algorithms were developed using combinations of diagnostic, surgical procedure and co-payment exemption codes, pharmacy claims and specialist’s visits. Algorithm accuracy was assessed by measuring the Youden Index, sensitivity, specificity, positive and negative predictive values. The percentage of positive cases for each algorithm ranged from 7.9 (95% CI 6.4–9.8) to 13.8 (95% CI 11.7–16.2) per 100,000 inhabitants in Caserta LHU and from 7.8 (95% CI 7.1–8.6) to 16.4 (95% CI 15.3–17.5) in Sicily Region. Sensitivity of the different algorithms ranged from 71.1% (95% CI 54.1–84.6%) to 84.2% (95% CI 68.8–94.0%), while specificity was always higher than 99.9%. The algorithm based on the presence of claims suggestive of acromegaly in ≥ 2 different databases (i.e., hospital discharge records, copayment exemptions registry, pharmacy claims and specialist visits registry) achieved the highest Youden Index (84.2) and the highest positive predictive value (34.8; 95% CI 28.6–41.6). We tested four algorithms to identify acromegaly cases using claims databases with high sensitivity and Youden Index. Despite identifying rare diseases using real-world data is challenging, this study showed that robust validity testing may yield the identification of accurate coding algorithms.

33455 Utilizing a residency manual to improve dermatology residents’ accuracy in billing, coding, and order placement

Background: New residents unfamiliar with dermatology codes can take additional time to input orders, costing clinic valuable time and money. Resident coding and billing errors persist into PGY-4 and occur in as many as 7.6% of orders based on a standard dermatology clinic. Objectives: To evaluate if a custom orientation handbook outlining billing and procedure codes helps to decrease the number of Epic errors made by SLU dermatology residents. Methods: An evidence-based handbook with stepwise instructions for navigating Epic orders and coding was created and disseminated to all SLU dermatology residents in July 2020. Residents and attendings were surveyed about handbook use and error prevention. SLUCare Clinical Informatics Operations Manager comparison of July 2020 to July 2019 was obtained to assess number of errors corrected. Results: In July 2020, the handbook was referenced daily most frequently by first-year dermatology residents. Attending physicians corrected LOS or other codes on average less frequently in July 2020 compared with July 2019. Nine of nine (100%) resident respondents and 5 of 5 (100%) attending respondents replied “Definitely yes” to continuing to have this resident handbook for future years of incoming residents. Billing and coding errors statistically significantly decreased from July 2019 to July 2020 (P = .01). Discussion: The resident handbook was found to be helpful by both attendings and residents, and was a successful tool in reducing resident errors in billing and coding. Such an intervention can be useful in a clinical setting to boost efficiency and timeliness of patient care.

CORRELATION OF SUPPORTING INFORMATION COMPLETENESS FACTORS WITH THE ACCURACY OF DISEASE CODING AT 'AISYIYAH SITI FATIMAH HOSPITAL OF SIDOARJO

Based on the data obtained from the observation on the inpatient medical record file of the Hospital 'Aisyiyah Siti Fatimah Tulangan Sidoarjo that the initial data shows that there are still medical record files with inaccurate diagnosis codes that do not match as much as (33%). The purpose of this study is to determine the relationship between the completeness of supporting information factors that affect the accuracy of disease coding in inpatient medical record files at the 'Aisyiyah Siti Fatimah Hospital, Tulangan Sidoarjo. This research method uses quantitative research with correlational research which has the aim of determining whether or not there is a relationship between two or more measurable variables. Data collection was carried out in August-October using a check list sheet by observing the inpatient medical record data. The population in this study were all inpatient medical record files in August-October 2021 and the sample in this study was 231 inpatient medical record files at the Hospital 'Aisyiyah Siti Fatimah Tulangan Sidoarjo with random sampling which was presented in the frequency table and cross tabulation, then tested using the Chi Square Test.The results of the Chi Square test of this study indicate that the supporting information completeness factor variable has a relationship with the accuracy of disease coding because the p value &lt;0.05, which means Ho is rejected. The results show that the p value of the completeness of supporting information factor = 0.022.In this study, it is recommended to improve the quality of coding by increasing the completeness of the file, and can produce an accurate data by conducting coding training and evaluating coding audits to support the accuracy of disease coding.

63. Bone morphogenetic protein and cancer in spinal fusion: a propensity matched analysis

<h3>BACKGROUND CONTEXT</h3> Since its FDA approval in 2002, recombinant human bone morphogenetic protein-2 (rhBMP-2) has been increasingly used in spinal surgery to promote arthrodesis and avoid the morbidity of autologous iliac crest bone graft harvest. Recent data estimate its utilization in 25% of spinal fusions. Because growth factors such as rhBMP-2 stimulate cellular proliferation, the association of rhBMP-2 with tumorigenesis in spinal fusion is an area of concern. Previous research has generated conflicting conclusions on the risk of cancer in patients receiving rhBMP-2 for spinal fusion. <h3>PURPOSE</h3> The purpose of this study is to compare the incidence of new solid organ and hematopoietic malignancies in patients undergoing spinal arthrodesis with or without BMP in a large administrative database. <h3>STUDY DESIGN/SETTING</h3> Retrospective propensity-matched analysis. <h3>METHODS</h3> Patients undergoing thoracolumbar fusion with or without BMP utilization between 2015-2020 were identified from the PearlDiver Mariner Patient Claims Database (PearlDiver Technologies, Colorado Springs, CO, USA) using ICD-10 codes. Patients with pre-existing malignancy diagnosis were excluded. Data were analyzed for incidence of solid organ malignancy (lung, breast, kidney, prostate, thyroid) and hematopoietic malignancy (lymphoma, myeloma, leukemia) diagnosed after spinal surgery. Propensity score matching was performed between patients who did and did not receive BMP. Propensity matched variables were selected a priori and included age, sex, and year of surgery. <h3>RESULTS</h3> Among patients without a history of solid organ malignancy undergoing thoracolumbar fusion, BMP was used in 9,593 patients and was not used in 193,713. In the propensity matched group, 1.5% of the BMP group developed solid organ malignancy following surgery compared to 1.9% of the non-BMP group. The odds ratio of developing solid organ malignancy in the BMP group compared to the control group was 0.80 (95% CI 0.64-1.00); P=0.056. Among patients without a history of hematopoietic malignancy undergoing thoracolumbar fusion, BMP was used in 9,913 patients and was not used in 191,006 patients. In the propensity matched group, 0.3% of the BMP group developed hematopoietic malignancy compared to 0.5% of the non-BMP group. The odds ratio of developing hematopoietic malignancy in the BMP group compared to the control group was 0.69 (95% CI 0.44-1.07); P=0.12. <h3>CONCLUSIONS</h3> BMP use in a large patient population undergoing thoracolumbar fusion was not associated with increased risk of new solid organ or hematopoietic malignancy. Limitations of this study include its reliance on accurate documentation and coding, including documentation of BMP use which may not be as robust as CPT coding since BMP coding may not be reimbursable. However, for the subset of patients with clear documentation of BMP use, this study further supports emerging data on the lack of a causal relationship between BMP use and malignancy. <h3>FDA DEVICE/DRUG STATUS</h3> Bone morphogenetic protein: Approved for certain types of spinal fusion.

184. Surgical site infection in thoracolumbar fractures: Incidence and risk factors in a series of 11,401 patients

<h3>BACKGROUND CONTEXT</h3> Surgical site infection (SSI) is relatively uncommon following elective spine surgery with reported rates ranging from 0.5-5%. Published reports have suggested a higher SSI rate in nonelective spine surgery such as spinal trauma though there is a paucity of large database studies examining this issue. <h3>PURPOSE</h3> The purpose of this study is to investigate the incidence and risk factors of SSI in patients undergoing spinal surgery for thoracic and lumbar fractures in a large administrative database. <h3>STUDY DESIGN/SETTING</h3> Retrospective. <h3>METHODS</h3> Patients undergoing spinal surgery for thoracic and lumbar fractures between 2015-2020 were identified in the PearlDiver Mariner Patient Claims Database (PearlDiver Technologies, Colorado Springs, CO, USA) using ICD-10 codes. Clinical data was collected based on ICD-10 codes. Collected data included gender, age, diabetes, smoking status, obesity, Elixhauser comorbidity index (ECI) and SSI. Patients were excluded who had another surgery either 14 days before or 21 days after the index spinal surgery. Univariate analysis was used to assess the association of potential risk factors and SSI. Multivariate analysis was used to identify independent risk factors of SSI. <h3>RESULTS</h3> Of 10,769 patients undergoing spinal surgery for thoracic and lumbar fractures, 9,848 met inclusion criteria and 921 were excluded. Of these, 736 patients developed SSI (7.5%). Risk factors significantly associated with SSI in univariate analysis included diabetes (OR 1.55; 95% CI 1.33-1.81; P=1.43e-8), obesity (OR 1.41; 95% CI 1.30-1.54; P=3.36e-13), increased age (P=0.00015) and ECI (P=2.2e-16). On multivariate analysis, obesity and ECI were independently associated with SSI (P=1.2e-4 and P=2.23e-10 respectively). <h3>CONCLUSIONS</h3> Nonelective spinal surgery for thoracic and lumbar fractures is associated with a 7.5% risk of surgical site infection. Obesity and ECI are independent predictors of SSI in this patient population. By establishing the rate of SSI in a large, nationwide database this study gives providers a broad overview of the risk of SSI in this population and may also help counsel patients regarding risk. Limitations of the study include its retrospective nature and its dependency on accurate ICD-10 database coding. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

This Month in Pediatric Urology

You have accessJournal of UrologyThis Month in Pediatric Urology1 Oct 2022This Month in Pediatric Urology Julian Wan Julian WanJulian Wan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002899AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Diagnostic Code-Based Screening for Identifying Children with Primary Hyperoxaluria Before hypotheses could be generated, observation and data were needed. These conjectures could then be tested and their results collated. The interpretation of these new data restarts the cycle; hypotheses are discarded, revised, and reformulated. New tests are run and so on and so forth. Arthur Conan Doyle’s Sherlock Holmes, the famous fictional detective notable for his deductive acumen, identified a key weakness to this method: it needed reliable observations. In “The Adventure of the Copper Beeches,” he exclaims “Data! Data! Data! … I can’t make bricks without clay.”1 The near ubiquity of the computers, the Internet, and electronic medical records offer the hope that data could be gathered from vast physical and virtual networks. Reports of rare and unusual conditions that would take hundreds of years to collate by any single practitioner or institution could be gathered easily. Common conditions could likewise be accumulated and subjected to new analysis. In a multi-institutional study, Tasian et al (page 898) investigated this idea by evaluating the use of diagnostic clinical codes for primary hyperoxaluria.2 They obtained data from PEDSnet, a clinical research network that gathers electronic medical records comprising millions of children from a consortium of large children’s hospitals. They found, unfortunately, that there are weaknesses in the accuracy of coding and discovered the data not to be as useful as they might hope. The diagnostic codes for primary hyperoxaluria have poor positive predictive value; only those patients who had additional coding were most predictive. This suggests caution and preparations are needed when using large administrative data sets—one cannot simply presume accuracy and validity despite the relative ease of acquisition and transmission.

Utility of data linkage for orthopaedic service planning in the paediatric population with cerebral palsy at Starship Children's Hospital.

To determine the accuracy of orthopaedic surgical procedure coding (ICD-10-AM/ACHI/ACS) for children with cerebral palsy (CP) at Starship Children's Hospital, use data linkage with the New Zealand Cerebral Palsy Register (NZCPR) to obtain demographic and clinical information for children with CP requiring orthopaedic surgical services in the Auckland District Health Board catchment area, and to determine if trends in the clinical and demographic data are useful for future service planning for children with CP. Surgical admission data for children with CP aged 0-18 years at the time of their first procedure were extracted from Auckland District Health Board records for 2013-2018, and information on demographics and Gross Motor Function Classification System level were obtained from the NZCPR. The ICD-10-AM/ACHI/ACS codes for surgery/intervention were matched with the operation notes in the electronic health records using NHI numbers and assessed for accuracy. During the study period, 261 paediatric patients with CP underwent orthopaedic procedures, which could be grouped broadly into five categories (spine, upper limb, lower limb, Botulinum-A toxin injection only, and other) with a coding accuracy of 95%. Clinical and demographic data could be obtained from the NZCPR for 232 (88.9%) of the 261 patients. Using orthopaedic surgical procedure codes, we could identify broad categories of procedures received by children with CP and the demographic and clinical characteristics of these children, which will assist with service planning and identify trends in care delivery.

How Well Do ICD-9-CM Codes Predict True Congenital Heart Defects? A Centers for Disease Control and Prevention-Based Multisite Validation Project.

BackgroundThe Centers for Disease Control and Prevention's Surveillance of Congenital Heart Defects Across the Lifespan project uses large clinical and administrative databases at sites throughout the United States to understand population‐based congenital heart defect (CHD) epidemiology and outcomes. These individual databases are also relied upon for accurate coding of CHD to estimate population prevalence.Methods and ResultsThis validation project assessed a sample of 774 cases from 4 surveillance sites to determine the positive predictive value (PPV) for identifying a true CHD case and classifying CHD anatomic group accurately based on 57 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) codes. Chi‐square tests assessed differences in PPV by CHD severity and age. Overall, PPV was 76.36% (591/774 [95% CI, 73.20–79.31]) for all sites and all CHD‐related ICD‐9‐CM codes. Of patients with a code for complex CHD, 89.85% (177/197 [95% CI, 84.76–93.69]) had CHD; corresponding PPV estimates were 86.73% (170/196 [95% CI, 81.17–91.15]) for shunt, 82.99% (161/194 [95% CI, 76.95–87.99]) for valve, and 44.39% (83/187 [95% CI, 84.76–93.69]) for “Other” CHD anatomic group (X 2=142.16, P<0.0001). ICD‐9‐CM codes had higher PPVs for having CHD in the 3 younger age groups compared with those >64 years of age, (X 2=4.23, P<0.0001).ConclusionsWhile CHD ICD‐9‐CM codes had acceptable PPV (86.54%) (508/587 [95% CI, 83.51–89.20]) for identifying whether a patient has CHD when excluding patients with ICD‐9‐CM codes for “Other” CHD and code 745.5, further evaluation and algorithm development may help inform and improve accurate identification of CHD in data sets across the CHD ICD‐9‐CM code groups.

The emerging infrastructure of US firearms injury data

For every fatal shooting in the United States, detailed information from reports of coroners or medical examiners, police departments, and other sources is recorded in the National Violent Death Reporting System. There is no such system in place for nonfatal shootings, which far outnumber fatalities. Hospital data systems are in place that could, with some improvements, provide access to reliable local, state and national estimates of firearm injuries. Such estimates are possible because most firearms injuries are treated in hospitals, and hospitals routinely assign “external cause of injury” codes to all injury encounters. Federal health agencies supervise a number of data systems that centralize hospital data. Challenges currently being addressed are public access, timeliness, and accuracy of coding of intent. (Hospitals misclassify many firearm assaults as accidents.)Law enforcement agencies provide detailed data on shootings in criminal circumstances, including shootings that are not treated in a hospital. The FBI's Uniform Crime Reports (UCR) system aggregates data from agencies. The FBI instituted a radical reform of this system beginning in 2021, resulting in a sharp agency participation drop that prevents valid national estimates. The reform requires agencies to report incident-level data instead of summary counts, which is all that was required for the previous 90 years. There are ongoing efforts to increase participation in the new system and restore its former status as the leading source of national crime estimates. In the meantime, data on nonfatal gunshot cases are available from a number of police departments.We discuss additional reforms needed to generate timely, accurate, publicly accessible data from hospitals and police.