Validating use of diagnostic codes in Canadian administrative data for identification of adverse drug events.

AIMS: While diagnostic codes from administrative health data might be a valuable source to identify adverse drug events (ADEs), their ability to identify unintended harms remains unclear. We validated claims-based diagnosis codes for ADEs based on events identified in a prospective cohort study and assessed whether key attributes predicted their documentation in administrative data. METHODS: This was a retrospective analysis of 3 prospective cohorts in British Columbia, from 2008 to 2015 (n = 13 969). We linked prospectively identified ADEs to administrative insurance data to examine the sensitivity and specificity of different diagnostic code schemes. We used logistic regression to assess which key attributes (e.g., type of event, symptoms and culprit medications) were associated with better documentation of ADEs in administrative data. RESULTS: Among 1178 diagnosed events, the sensitivity of the diagnostic codes in administrative data ranged from 3.4 to 52.6%, depending on the database and codes used. We found that documentation was worse for certain types of ADEs (dose-related: odds ratio [OR]: 0.32, 95% confidence interval [CI]: 0.15, 0.69; nonadherence events (OR: 0.35, 95% CI: 0.20, 0.62), and better for those experiencing arrhythmias (OR: 4.19, 95% CI: 0.96, 18.28). CONCLUSION: ADEs were not well documented in administrative data. Alternative methods should be explored to capture ADEs for health research.

Cause of death coding in asthma.

BACKGROUND: While clinical coding is intended to be an objective and standardized practice, it is important to recognize that it is not entirely the case. The clinical and bureaucratic practices from event of death to a case being entered into a research dataset are important context for analysing and interpreting this data. Variation in practices can influence the accuracy of the final coded record in two different stages: the reporting of the death certificate, and the International Classification of Diseases (Version 10; ICD-10) coding of that certificate. METHODS: This study investigated 91,022 deaths recorded in the Scottish Asthma Learning Healthcare System dataset between 2000 and 2017. Asthma-related deaths were identified by the presence of any of ICD-10 codes J45 or J46, in any position. These codes were categorized either as relating to asthma attacks specifically (status asthmatic; J46) or generally to asthma diagnosis (J45). RESULTS: We found that one in every 200 deaths in this were coded as being asthma related. Less than 1% of asthma-related mortality records used both J45 and J46 ICD-10 codes as causes. Infection (predominantly pneumonia) was more commonly reported as a contributing cause of death when J45 was the primary coded cause, compared to J46, which specifically denotes asthma attacks. CONCLUSION: Further inspection of patient history can be essential to validate deaths recorded as caused by asthma, and to identify potentially mis-recorded non-asthma deaths, particularly in those with complex comorbidities.

Undercounting diagnoses in Australian general practice: a data quality study with implications for population health reporting.

BACKGROUND: Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including organisations that deliver incentivised primary care quality improvement programs, frequently utilise coded data only and often ignore free-text entries. Diagnosis data are reported for population healthcare planning including resource allocation for patient care. This study sought to determine if diagnosis counts based on coded diagnosis data only, led to under-reporting of disease prevalence and if so, to what extent for six common or important chronic diseases. METHODS: This cross-sectional data quality study used de-identified EMR data from 84 general practices in Victoria, Australia. Data represented 456,125 patients who attended one of the general practices three or more times in two years between January 2021 and December 2022. We reviewed the percentage and proportional difference between patient counts of coded diagnosis entries alone and patient counts of clinically validated free-text entries for asthma, chronic kidney disease, chronic obstructive pulmonary disease, dementia, type 1 diabetes and type 2 diabetes. RESULTS: Undercounts were evident in all six diagnoses when using coded diagnoses alone (2.57-36.72% undercount), of these, five were statistically significant. Overall, 26.4% of all patient diagnoses had not been coded. There was high variation between practices in recording of coded diagnoses, but coding for type 2 diabetes was well captured by most practices. CONCLUSION: In Australia clinical decision support and the reporting of aggregated patient diagnosis data to government that relies on coded diagnoses can lead to significant underreporting of diagnoses compared to counts that also incorporate clinically validated free-text diagnoses. Diagnosis underreporting can impact on population health, healthcare planning, resource allocation, and patient care. We propose the use of phenotypes derived from clinically validated text entries to enhance the accuracy of diagnosis and disease reporting. There are existing technologies and collaborations from which to build trusted mechanisms to provide greater reliability of general practice EMR data used for secondary purposes.

Observational Behavioral Coding in the Pediatric Emergency Department: Development of the Emergency Department Child Behavior Coding System.

BACKGROUND: Despite improvements over the past decade, children continue to experience significant pain and distress surrounding invasive procedures in the emergency department (ED). To assess the impact of newly developed interventions, we must create more reliable and valid behavioral assessment tools that have been validated for the unique settings of pediatric EDs. OBJECTIVE: This study aimed to create and test the Emergency Department Child Behavior Coding System (ED-CBCS) for the assessment of child distress and nondistress behaviors surrounding pediatric ED procedures. METHODS: Via an iterative process, a multidisciplinary expert panel developed the ED-CBCS, an advanced time-based behavioral coding measure. Inter-rater reliability and concurrent validity were examined using 38 videos of children aged from 2 to 12 years undergoing laceration procedures. Face, Legs, Activity, Cry, Consolability (FLACC) scale scores were used to examine concurrent validity. RESULTS: The final ED-CBCS included 27 child distress and nondistress behaviors. Time-unit κ values from 0.64 to 0.98 and event alignment κ values from 0.62 to 1.00 indicated good to excellent inter-rater reliability for all but one of the individual codes. ED-CBCS distress (B = 1.26; p < 0.001) and nondistress behaviors (B = -0.69, p = 0.025) were independently significantly associated with FLACC scores, indicating concurrent validity. CONCLUSIONS: We developed a psychometrically sound tool tailored for pediatric ED procedures. Future work could use this measure to better identify behavioral targets and test the effects of interventions to relieve pediatric ED pain and distress.

[Evaluation of a coding guide on social determinants of health in primary care consultations: A mixed study]. / Evaluación de una guía de codificación de determinantes sociales de la salud en las consultas de atención primaria: Estudio mixto.

OBJECTIVE: To evaluate a coding guide for social determinants of health in primary care consultations as an effective tool in the professional's daily workflow. DESIGN: Mixed sequential explanatory study. Formed by a quantitative part (experimental) and a qualitative part (descriptive-evaluative). LOCATION: All the primary care teams of the Central Catalonia Management (32 teams). PARTICIPANTS AND SETTING: All nursing, social work and medical professionals working in the 32 primary care teams of the Catalan Institute of Health in Central Catalonia from February 2023 to July 2023. METHODS: A social determinants of health coding guide was developed. This guide was created in a multidisciplinary and multicenter manner. Purposive sampling. Quantitatively, the number of diagnoses recorded by the experimental group versus the control group was counted. Qualitatively, a thematic analysis was carried out from a socio-constructivist perspective. RESULTS: The results were significant and satisfactory. Using a quantitative methodology, the effectiveness of the use of the guide was assessed. A significant increase in the use of the social determinants was observed in the intervention group vs. the control group, with a percentage of post-intervention use of 19.53% in the control group and 32.26% in the intervention group (P < .001). The number of diagnoses recorded increased from 312 to 1322 in the intervention group, while it remained the same in the control group. The main factors identified through qualitative methodology that may explain the effectiveness of the guideline were: 1) the effectiveness of the guideline among primary care professionals, 2) the appropriateness of the guideline by assessing its usefulness and practicality, 3) feasibility and 4) specific contributions to the improvement of the guideline. CONCLUSIONS: The social determinants of health coding guide is effective, appropriate and can be implemented in the workflow of primary health care professionals for good recording of the social determinants of health.

Administrative Coding in Electronic Health Care Record-Based Research of NAFLD: An Expert Panel Consensus Statement.

BACKGROUND AND AIMS: Electronic health record (EHR)-based research allows the capture of large amounts of data, which is necessary in NAFLD, where the risk of clinical liver outcomes is generally low. The lack of consensus on which International Classification of Diseases (ICD) codes should be used as exposures and outcomes limits comparability and generalizability of results across studies. We aimed to establish consensus among a panel of experts on ICD codes that could become the reference standard and provide guidance around common methodological issues. APPROACH AND RESULTS: Researchers with an interest in EHR-based NAFLD research were invited to collectively define which administrative codes are most appropriate for documenting exposures and outcomes. We used a modified Delphi approach to reach consensus on several commonly encountered methodological challenges in the field. After two rounds of revision, a high level of agreement (>67%) was reached on all items considered. Full consensus was achieved on a comprehensive list of administrative codes to be considered for inclusion and exclusion criteria in defining exposures and outcomes in EHR-based NAFLD research. We also provide suggestions on how to approach commonly encountered methodological issues and identify areas for future research. CONCLUSIONS: This expert panel consensus statement can help harmonize and improve generalizability of EHR-based NAFLD research.

Comparing reliability of ICD-10-based COVID-19 comorbidity data to manual chart review, a retrospective cross-sectional study.

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD-10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. OBJECTIVE: Compare COVID-19 cohort manual-chart-review and ICD-10-based comorbidity data; characterize the accuracy of different methods of extracting ICD-10-code-based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. DESIGN: Retrospective cross-sectional study. MEASUREMENTS: ICD-10-based-data performance characteristics relative to manual-chart-review. RESULTS: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79-0.85; comorbidity range: 0.35-0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69-0.76; range: 0.44-0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63-0.71; range: 0.47-0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54-0.63; range: 0.30-0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43-0.53; range: 0.30-0.56). CONCLUSIONS AND RELEVANCE: ICD-10-based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual-chart-review.

Advancements in the National Vital Statistics System to Meet the Real-Time Data Needs of a Pandemic.

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133-2140. https://doi.org/10.2105/AJPH.2021.306519).

Out-of-Hospital COVID-19 Deaths: Consequences for Quality of Medical Care and Accuracy of Cause of Death Coding.

Objectives. To examine age and temporal trends in the proportion of COVID-19 deaths occurring out of hospital or in the emergency department and the proportion of all noninjury deaths assigned ill-defined causes in 2020. Methods. We analyzed newly released (March 2021) provisional COVID-19 death tabulations for the entire United States. Results. Children (younger than 18 years) were most likely (30.5%) and elders aged 64 to 74 years were least likely (10.4%) to die out of hospital or in the emergency department. In parallel, among all noninjury deaths, younger people had the highest proportions coded to symptoms, signs, and ill-defined conditions, and percentage symptoms, signs, and ill-defined conditions increased from 2019 to 2020 in all age-race/ethnicity groups. The majority of young COVID-19 decedents were racial/ethnic minorities. Conclusions. The high proportions of all noninjury deaths among children, adolescents, and young adults that were coded to ill-defined causes in 2020 suggest that some COVID-19 deaths were missed because of systemic failures in timely access to medical care for vulnerable young people. Public Health Implications. Increasing both availability of and access to the best hospital care for young people severely ill with COVID-19 will save lives and improve case fatality rates.

Identifying options for oncology therapy regimen codification to improve standardization-combined results of an expert panel and a review.

WHAT IS KNOWN AND OBJECTIVE: Chemotherapy drugs are often administered in combinations with predefined interdependent doses and cycle intervals. As yet, there is no global standardization system to describe these complex regimens in a universally comprehensive manner. The aim of this review is to identify which efforts for standardization have been undertaken and which recommendations for databases and nomenclature of chemotherapy regimens are available. METHODS: A literature review was performed to identify all peer-reviewed full-text articles about oncology therapy regimen codification. In addition, the results of this search were evaluated and consensus recommendations from a European expert panel were subsequently added. RESULTS: This review gives an overview of attempts to standardize chemotherapy nomenclature described in the literature, as well as of previously published identified gaps in regimen codification. In addition, we summarized the suggestions for improvement of chemotherapy codification found in the available literature, combining them with the expertise from a European expert panel of oncology pharmacists. WHAT IS NEW AND CONCLUSIONS: We believe that one of the most important error-prevention measures is standardization. However, there is a paucity of data how it may be achieved. Currently available data suggest that standardization has a positive impact on usability for data networks, prescription software, safety and the measurement of the quality of cancer care delivery. Standardization is also a strong pre-requisite for all discussions including oncology pharmacists and oncologists when evaluating chemotherapy regimen in countries in Europe but also all over the world. The recommendations compiled in this review can help to support overdue standardization efforts in this important therapeutic area.

Accuracy and reliability of injury coding in the national Dutch Trauma Registry.

OBJECTIVE: Injury coding is well known for lack of completeness and accuracy. The objective of this study was to perform a nationwide assessment of accuracy and reliability on Abbreviated Injury Scale (AIS) coding by Dutch Trauma Registry (DTR) coders and to determine the effect on Injury Severity Score (ISS). Additionally, the coders' characteristics were surveyed. METHODS: Three fictional trauma cases were presented to all Dutch trauma coders in a nationwide survey (response rate 69%). The coders were asked to extract and code the cases' injuries according to the AIS manual (version 2005, update 2008). Reference standard was set by three highly experienced coders. Summary statistics were used to describe the registered AIS codes and ISS distribution. The primary outcome measures were accuracy of injury coding and inter-rater agreement on AIS codes. Secondary outcome measures were characteristics of coders: profession, work setting, experience in injury coding and training level in injury coding. RESULTS: The total number of different AIS codes used to describe 14 separate injuries in the three cases was 89. Mean accuracy per AIS code was 42.2% (range 2.4-92.7%). Mean accuracy on number of AIS codes was 23%. Overall inter-rater agreement per AIS code was 49.1% (range 2.4-92.7%). The number of assigned AIS codes varied between 0 and 18 per injury. Twenty-seven percentage of injuries were overlooked. ISS was correctly scored in 42.4%. In 31.7%, the AIS coding of the two more complex cases led to incorrect classification of the patient as ISS < 16 or ISS ≥ 16. Half (47%) of the coders had no (para)medical degree, 26% were working in level I trauma centers, 37% had less than 2 years of experience and 40% had no training in AIS coding. CONCLUSIONS: Accuracy of and inter-rater agreement on AIS injury scoring by DTR coders is limited. This may in part be due to the heterogeneous backgrounds and training levels of the coders. As a result of the inconsistent coding, the number of major trauma patients in the DTR may be over- or underestimated. Conclusions based on DTR data should therefore be drawn with caution.

Validity of Antineoplastic Procedure Codes in the Danish National Patient Registry: The Case of Colorectal Cancer.

BACKGROUND: Procedure codes in the Danish National Patient Registry are used for administrative purposes and are a potentially valuable resource for epidemiologic research. To our knowledge, the validity of antineoplastic procedure codes has only been evaluated in one study. METHODS: We randomly extracted a sample of 420 patients in the Southern Region of Denmark with a diagnosis of colorectal cancer and an oncology contact during 2016-2018. Using the medical record as gold standard, we computed the positive predictive value (PPV) and sensitivity of antineoplastic procedure codes recorded in the Danish National Patient Registry. RESULTS: We identified 2,243 codes for antineoplastic treatments in the registry and 2,299 in the medical records. We confirmed that 213 of 214 patients with registered therapies in the Danish National Patient Registry received therapy, corresponding to a PPV of "any registration" of 1.00 (95% confidence interval [CI] = 0.97, 1.00). Considering single registrations, the overall PPV was 0.95 (95% CI = 0.94, 0.95), and the overall sensitivity was 0.90 (95% CI = 0.89, 0.91). Number of recorded treatments and treatments administered were strongly correlated. Considering the most frequent single antineoplastic regimens, PPV ranged from 0.90 (95% CI = 0.87, 0.92) for capecitabine to 0.98 (95% CI = 0.95, 1.00) for cetuximab, whereas sensitivity ranged from 0.81 (95% CI = 0.75, 0.87) for 5-fluorouracil and irinotecan (FOLFIRI) regimen to 0.97 (95% CI = 0.94, 0.99) for bevacizumab. Analysis per hospital showed the highest validity of registrations at the University Hospital. CONCLUSION: The validity of antineoplastic procedure codes in the Danish National Patient Registry is generally high and thus usable for epidemiologic research.

Development and Testing of Compatible Diagnosis Code Lists for the Functional Comorbidity Index: International Classification of Diseases, Ninth Revision, Clinical Modification and International Classification of Diseases, 10th Revision, Clinical Modification.

BACKGROUND: The Functional Comorbidity Index (FCI) was developed for community-based adult populations, with function as the outcome. The original FCI was a survey tool, but several International Classification of Diseases (ICD) code lists-for calculating the FCI using administrative data-have been published. However, compatible International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and ICD-10-CM versions have not been available. OBJECTIVE: We developed ICD-9-CM and ICD-10-CM diagnosis code lists to optimize FCI concordance across ICD lexicons. RESEARCH DESIGN: We assessed concordance and frequency distributions across ICD lexicons for the FCI and individual comorbidities. We used length of stay and discharge disposition to assess continuity of FCI criterion validity across lexicons. SUBJECTS: State Inpatient Databases from Arizona, Colorado, Michigan, New Jersey, New York, Utah, and Washington State (calendar year 2015) were obtained from the Healthcare Cost and Utilization Project. State Inpatient Databases contained ICD-9-CM diagnoses for the first 3 calendar quarters of 2015 and ICD-10-CM diagnoses for the fourth quarter of 2015. Inpatients under 18 years old were excluded. MEASURES: Length of stay and discharge disposition outcomes were assessed in separate regression models. Covariates included age, sex, state, ICD lexicon, and FCI/lexicon interaction. RESULTS: The FCI demonstrated stability across lexicons, despite small discrepancies in prevalence for individual comorbidities. Under ICD-9-CM, each additional comorbidity was associated with an 8.9% increase in mean length of stay and an 18.5% decrease in the odds of a routine discharge, compared with an 8.4% increase and 17.4% decrease, respectively, under ICD-10-CM. CONCLUSION: This study provides compatible ICD-9-CM and ICD-10-CM diagnosis code lists for the FCI.

Utilization of Social Determinants of Health ICD-10 Z-Codes Among Hospitalized Patients in the United States, 2016-2017.

BACKGROUND: The inclusion of Z-codes for social determinants of health (SDOH) in the 10th revision of the International Classification of Diseases (ICD-10) may offer an opportunity to improve data collection of SDOH, but no characterization of their utilization exists on a national all-payer level. OBJECTIVE: To examine the prevalence of SDOH Z-codes and compare characteristics of patients with and without Z-codes and hospitals that do and do not use Z-codes. RESEARCH DESIGN: Retrospective cohort study using 2016 and 2017 National Inpatient Sample. PARTICIPANTS: Total of 14,289,644 inpatient hospitalizations. MEASURES: Prevalence of SDOH Z-codes (codes Z55-Z65) and descriptive statistics of patients and hospitals. RESULTS: Of admissions, 269,929 (1.9%) included SDOH Z-codes. Average monthly SDOH Z-code use increased across the study period by 0.01% per month (P<0.001). The cumulative number and proportion of hospitals that had ever used an SDOH Z-code also increased, from 1895 hospitals (41%) in January 2016 to 3210 hospitals (70%) in December 2017. Hospitals that coded at least 1 SDOH Z-code were larger, private not-for-profit, and urban teaching hospitals. Compared with admissions without an SDOH Z-code, admissions with them were for patients who were younger, more often male, Medicaid recipients or uninsured. A higher proportion of admissions with SDOH Z-codes were for mental health (44.0% vs. 3.3%, P<0.001) and alcohol and substance use disorders (9.6% vs. 1.1%, P<0.001) compared with those without. CONCLUSIONS: The uptake of SDOH Z-codes has been slow, and current coding is likely poorly reflective of the actual burden of social needs experienced by hospitalized patients.

Are coding systems of frontal sinuses anatomically reliable? A study of correlation among morphological and metrical features.

Frontal sinuses are of special interest for personal identification thanks to their high variability. A common procedure for comparing ante-mortem and post-mortem material is based on coding systems classifying frontal sinuses according to their morphological and metrical characteristics. However, the calculation of possible combinations is performed on the hypothesis that all the classified features are independent one from each other. This study aims at analysing the correlation among morphological and metrical characteristics of frontal sinuses. Two hundred CT scans of patients equally divided between males and females were segmented through the ITK-SNAP software. Number of accessory septations, scalloping and supra-orbital cells, side asymmetry and superiority, breadth, height, length and volume were extracted from the frontal sinuses of each subject. A possible relationship among morphological and metrical features was analysed through Pearson's correlation test, Mann-Whitney test or chi-square test according to the type of compared data (p < 0.05). In general, a positive correlation was found for all comparisons among metrical measurements (breadth, height, depth and volume) and number of septations, scalloping and supra-orbital cells (p < 0.05), but not between the number of scalloping and supra-orbital cells. In addition, side of asymmetry was positively related with side of superiority of the upper profile of frontal sinuses (p < 0.05). This study proved that morphological and metrical characteristics of frontal sinuses are strictly related one with each other: therefore, the coding systems based on these features should be applied with caution for personal identification, as the number of possible combinations is lower than reported by literature.

Physician code creep after the initiation of outpatient volume control program and implications for appropriate ICD-10-CM coding.

BACKGROUND: Most studies on the physician code creep (i.e., changes in case mix record-keeping practices to improve reimbursement) have focused on episodes (inpatient hospitalizations or outpatient procedures). Little is known regarding changes in diagnostic coding practices for better reimbursement among a fixed cohort of patients with chronic diseases. METHODS: To examine whether physicians in tertiary medical centers changed their coding practices after the initiation of the Outpatient Volume Control Program (OVCP) in Taiwan, we conducted a retrospective observational study of four patient cohorts (two interventions and two controls) from January 2016 to September 2017 in Taiwan. The main outcomes were the number of outpatient visits with four coding practices: 1) OVCP monitoring code recorded as primary diagnosis; 2) OVCP monitoring code recorded as secondary diagnosis; 3) non-OVCP monitoring code recorded as primary diagnosis; 4) non-OVCP monitoring code recorded as secondary diagnosis. RESULTS: The percentage change of the number of visits with coding practice 1 between 2016Q1 and 2017Q3 was - 74% for patients with hypertension and - 73% with diabetes in tertiary medical centers and - 23% and - 17% in clinics, respectively. By contrast, the percentage changes of coding practice 3 were + 73% for patients with hypertension and + 46% for patients with diabetes in tertiary medical centers and - 19% and - 2% in clinics, respectively. CONCLUSIONS: Physician code creep occurred after the initiation of the OVCP. Education regarding appropriate outpatient coding for physicians will be relatively effective when proper coding is related to reimbursement.

Problems and Barriers during the Process of Clinical Coding: a Focus Group Study of Coders' Perceptions.

Coded data are the basis of information systems in all countries that rely on Diagnosis Related Groups in order to reimburse/finance hospitals, including both administrative and clinical data. To identify the problems and barriers that affect the quality of the coded data is paramount to improve data quality as well as to enhance its usability and outcomes. This study aims to explore problems and possible solutions associated with the clinical coding process. Problems were identified according to the perspective of ten medical coders, as the result of four focus groups sessions. This convenience sample was sourced from four public hospitals in Portugal. Questions relating to problems with the coding process were developed from the literature and authors' expertise. Focus groups sessions were taped, transcribed and analyzed to elicit themes. Variability in the documents used for coding, illegibility of hand writing when coding on paper, increase of errors due to an extra actor in the coding process when transcribed from paper, difficulties in the diagnoses' coding, coding delay and unavailability of resources and tools designed to help coders, were some of the problems identified. Some problems were identified and solutions such as the standardization of the documents used for coding an episode, the adoption of the electronic coding, the development of tools to help coding and audits, and the recognition of the importance of coding by the management were described as relevant factors for the improvement of the quality of data.

'Caveat emptor': the cautionary tale of endocarditis and the potential pitfalls of clinical coding data-an electronic health records study.

BACKGROUND: Diagnostic codes from electronic health records are widely used to assess patterns of disease. Infective endocarditis is an uncommon but serious infection, with objective diagnostic criteria. Electronic health records have been used to explore the impact of changing guidance on antibiotic prophylaxis for dental procedures on incidence, but limited data on the accuracy of the diagnostic codes exists. Endocarditis was used as a clinically relevant case study to investigate the relationship between clinical cases and diagnostic codes, to understand discrepancies and to improve design of future studies. METHODS: Electronic health record data from two UK tertiary care centres were linked with data from a prospectively collected clinical endocarditis service database (Leeds Teaching Hospital) or retrospective clinical audit and microbiology laboratory blood culture results (Oxford University Hospitals Trust). The relationship between diagnostic codes for endocarditis and confirmed clinical cases according to the objective Duke criteria was assessed, and impact on estimations of disease incidence and trends. RESULTS: In Leeds 2006-2016, 738/1681(44%) admissions containing any endocarditis code represented a definite/possible case, whilst 263/1001(24%) definite/possible endocarditis cases had no endocarditis code assigned. In Oxford 2010-2016, 307/552(56%) reviewed endocarditis-coded admissions represented a clinical case. Diagnostic codes used by most endocarditis studies had good positive predictive value (PPV) but low sensitivity (e.g. I33-primary 82% and 43% respectively); one (I38-secondary) had PPV under 6%. Estimating endocarditis incidence using raw admission data overestimated incidence trends twofold. Removing records with non-specific codes, very short stays and readmissions improved predictive ability. Estimating incidence of streptococcal endocarditis using secondary codes also overestimated increases in incidence over time. Reasons for discrepancies included changes in coding behaviour over time, and coding guidance allowing assignment of a code mentioning 'endocarditis' where endocarditis was never mentioned in the clinical notes. CONCLUSIONS: Commonly used diagnostic codes in studies of endocarditis had good predictive ability. Other apparently plausible codes were poorly predictive. Use of diagnostic codes without examining sensitivity and predictive ability can give inaccurate estimations of incidence and trends. Similar considerations may apply to other diseases. Health record studies require validation of diagnostic codes and careful data curation to minimise risk of serious errors.

Accuracy of Administrative Coding to Identify Reduced and Preserved Left Ventricular Ejection Fraction.

BACKGROUND: Coding of systolic function in heart failure is important, but the accuracy is uncertain. METHODS AND RESULTS: We used data from a chart review of VA heart failure hospitalizations from 2006 to 2013. Trained abstractors determined the documented diagnosis of heart failure and the left ventricular ejection fraction (LVEF). We compared this LVEF with the primary and secondary International Classification of Disease, 9th edition, codes for heart failure for the same hospitalization. Among 43,044 hospitalizations for heart failure, the primary discharge diagnosis was coded as systolic heart failure in 18%, diastolic heart failure in 17%, and other heart failure codes in 65%. For an LVEF <40%, a systolic heart failure code had a sensitivity of 29% and a positive predictive value of 76%. The code for systolic heart failure was used more frequently over time, with sensitivity increasing from 16% to 37% but at the expense of the positive predictive value, which decreased from 80% to 74%. The overall area under the receiver operating characteristic curve for the relationship between LVEF and the systolic heart failure code was 0.71. Using LVEF >50% to define diastolic heart failure led to a sensitivity of 29% for a diastolic heart failure code, with a positive predictive value of 78%. In multivariate analysis, a systolic heart failure code had an odds ratio for 1-year mortality of 1.1 (95% confidence interval 1.03-1.17) compared to not having a systolic heart failure code. CONCLUSIONS: Coding for systolic and diastolic heart failure is associated with LVEF, but the accuracy is too poor to substitute for the documented LVEF in performance measurement.

ICD-10 Coding Will Challenge Researchers: Caution and Collaboration may Reduce Measurement Error and Improve Comparability Over Time.

BACKGROUND: The October 1, 2015 US health care diagnosis and procedure codes update, from the 9th to 10th version of the International Classification of Diseases (ICD), abruptly changed the structure, number, and diversity of codes in health care administrative data. Translation from ICD-9 to ICD-10 risks introducing artificial changes in claims-based measures of health and health services. OBJECTIVE: Using published ICD-9 and ICD-10 definitions and translation software, we explored discontinuity in common diagnoses to quantify measurement changes introduced by the upgrade. DESIGN: Using 100% Medicare inpatient data, 2012-2015, we calculated the quarterly frequency of condition-specific diagnoses on hospital discharge records. Years 2012-2014 provided baseline frequencies and historic, annual fourth-quarter changes. We compared these to fourth quarter of 2015, the first months after ICD-10 adoption, using Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse (CCW) ICD-9 and ICD-10 definitions and other commonly used definitions sets. RESULTS: Discontinuities of recorded CCW-defined conditions in fourth quarter of 2015 varied widely. For example, compared with diagnosis appearance in 2014 fourth quarter, in 2015 we saw a sudden 3.2% increase in chronic lung disease and a 1.8% decrease in depression; frequency of acute myocardial infarction was stable. Using published software to translate Charlson-Deyo and Elixhauser conditions yielded discontinuities ranging from -8.9% to +10.9%. CONCLUSIONS: ICD-9 to ICD-10 translations do not always align, producing discontinuity over time. This may compromise ICD-based measurements and risk-adjustment. To address the challenge, we propose a public resource for researchers to share discovered discontinuities introduced by ICD-10 adoption and the solutions they develop.