[Guidelines for the use of the International Classification of Radiographs of Pneumoconioses of the International Labour Office (ILO): Substantial changes in the currrent edition]

The International Classification of Radiographs of Pneumoconioses is the scheme worked out by the International Labour Office in Geneva (ILO), to register radiographic chest abnormalities in a well-ordered, reproducible and comparable way. It is used for diagnosing abnormalities caused by dust exposure. Guidelines for the use of the ILO International Classification of Radiographs of Pneumoconioses contain detailed information and recommendations on how to use the classification, as well as how the chest X-ray examination should be performed and recorded. To facilitate the diagnosis of observed abnormalities the classification is completed by the set of standard radiograms illustrating typical irregularities referring to lungs and pleura, included in the classification. The article presents the key information on classification and the most important amendments adopted in the 2000 and 2011 ILO guidelines revisions. These changes refer to radiographs quality assessment, the way of presenting abnormalities registered in standard radiographs (QUAD set, digital images) and registration of failures not related to dust exposure. Particularly important complements result from the development of radiological imaging techniques. They are concerned about the classification of radiographic images of the chest recorded digitally. Med Pr 2016;67(6):833-837.

Diagnostic Coding for Epilepsy

Accurate coding is an important function of neurologic practice. This contribution to Continuum is part of an ongoing series that presents helpful coding information along with examples related to the issue topic. Tips for diagnosis coding, Evaluation and Management coding, procedure coding, or a combination are presented, depending on which is most applicable to the subject area of the issue.

Variability in Standard Outcomes of Posterior Lumbar Fusion Determined by National Databases

OBJECTIVE

National databases are used with increasing frequency in spine surgery literature to evaluate patient outcomes. The differences between individual databases in relationship to outcomes of lumbar fusion are not known. We evaluated the variability in standard outcomes of posterior lumbar fusion between the University HealthSystem Consortium (UHC) database and the Healthcare Cost and Utilization Project National Inpatient Sample (NIS).

METHODS

NIS and UHC databases were queried for all posterior lumbar fusions (International Classification of Diseases, Ninth Revision code 81.07) performed in 2012. Patient demographics, comorbidities (including obesity), length of stay (LOS), in-hospital mortality, and complications such as urinary tract infection, deep venous thrombosis, pulmonary embolism, myocardial infarction, durotomy, and surgical site infection were collected using specific International Classification of Diseases, Ninth Revision codes.

RESULTS

Analysis included 21,470 patients from the NIS database and 14,898 patients from the UHC database. Demographic data were not significantly different between databases. Obesity was more prevalent in UHC (P = 0.001). Mean LOS was 3.8 days in NIS and 4.55 in UHC (P < 0.0001). Complications were significantly higher in UHC, including urinary tract infection, deep venous thrombosis, pulmonary embolism, myocardial infarction, surgical site infection, and durotomy. In-hospital mortality was similar between databases.

CONCLUSIONS

NIS and UHC databases had similar demographic patient populations undergoing posterior lumbar fusion. However, the UHC database reported significantly higher complication rate and longer LOS. This difference may reflect academic institutions treating higher-risk patients; however, a definitive reason for the variability between databases is unknown. The inability to precisely determine the basis of the variability between databases highlights the limitations of using administrative databases for spinal outcome analysis.

[Differential diagnostic considerations using ICD-10 in chronic back pain with special regard to persistent somatoform pain disorder with somatic and psychological factors (ICD-10 F45.41)]

It is often difficult to pass an expert opinion in cases of chronic back pain. This article analyses the differential diagnostic considerations related to coding various causes in line with ICD-10. It emphasises the I importance of making a careful distinction between orthopoedic and psychiatric conditions and disorders. Simultaneous coding of orthopoedic and psychiatric illnesses and disorders based on a distinct cluster of symptoms necessitates an interdisciplinary approach that consistently applies the ICD-10 definitions of mental an behavioural disorders in order to clearly identify the main reason for a functional impairment in the insurance and sociomedical context. Persistant somatoform pain disorder with somatic and psychological factors (ICD-10 F45.41) should be regarded as related to the underlying disease and be used primarily as an additional and descriptive diagnosis.

Accuracy of ICD-9-CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program

BACKGROUND

Epidemiological and health services research often use International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify patients with clinical conditions in administrative databases. We determined whether there are systematic variations between stroke patient clinical diagnoses and ICD-9-CM codes, stratified by hospital characteristics and stroke severity.

METHODS AND RESULTS

We used the records of patients discharged from hospitals participating in the Paul Coverdell National Acute Stroke Program in 2013. Within this stroke-enriched cohort, we compared agreement between the attending physician's clinical diagnosis and principal ICD-9-CM code and determined whether disagreements varied by hospital characteristics (presence of a stroke unit, stroke team, number of hospital beds, and hospital location). For patients with a documented National Institutes of Health Stroke Scale score at admission, we assessed whether diagnostic agreement varied by stroke severity. Agreement was generally high (>89%); differences between the physician diagnosis and ICD-9-CM codes were primarily attributed to discordance between ischemic stroke and transient ischemic attack (TIA), and subarachnoid and intracerebral hemorrhage. Agreement was higher for patients in metropolitan hospitals with stroke units, stroke teams, and >200 beds (all P<0.001). Agreement was lowest (60.3%) for rural hospitals with ≤200 beds and without stroke units or teams. Agreement was also lower for milder (94.9%) versus more-severe (96.4%) ischemic strokes (P<0.001).

CONCLUSIONS

We identified disagreements in stroke/TIA coding by hospital characteristics and stroke severity, particularly for milder ischemic strokes. Such systematic variations in ICD-9-CM coding practices can affect stroke case identification in epidemiological studies and may have implications for hospital-level quality metrics.

New ICD-10 version of the Multipurpose Australian Comorbidity Scoring System outperformed Charlson and Elixhauser comorbidities in an older population

OBJECTIVES

To translate, validate, and compare performance of an International Classification of Diseases, 10th revision (ICD-10) version of the Multipurpose Australian Comorbidity Scoring System (MACSS) against commonly used comorbidity measures in the prediction of short- and long-term mortality, 28-day all-cause readmission, and length of stay (LOS).

STUDY DESIGN AND SETTING

Hospitalization and death data were linked for 25,374 New South Wales residents aged 65 years and older, admitted with a hip fracture between 2008 and 2012. Comorbidities were identified according to the MACSS, Charlson, and Elixhauser definitions using ICD-10 coding algorithms. Regression models were fitted and area under the curve (AUC) and Akaike Information Criterion assessed.

RESULTS

The ICD-10 MACSS had excellent discriminating ability in predicting inhospital mortality (AUC = 0.81) and 30-day mortality (AUC = 0.80), acceptable prediction of 1-year mortality (AUC = 0.76) but poor discrimination for 28-day readmission and LOS. The MACSS algorithm provided better model fit than either Charlson or Elixhauser algorithm for all outcomes.

CONCLUSION

This work presents a rigorous translation of the ICD-9 MACSS for use with ICD-10 coded data. The updated ICD-10 MACSS outperformed both Charlson and Elixhauser measures in an older population and is recommended for use with large administrative data sets in predicting mortality outcomes.

Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocol

INTRODUCTION

Administrative healthcare databases are useful tools to study healthcare outcomes and to monitor the health status of a population. Patients with cancer can be identified through disease-specific codes, prescriptions and physician claims, but prior validation is required to achieve an accurate case definition. The objective of this protocol is to assess the accuracy of International Classification of Diseases Ninth Revision-Clinical Modification (ICD-9-CM) codes for breast, lung and colorectal cancers in identifying patients diagnosed with the relative disease in three Italian administrative databases.

METHODS AND ANALYSIS

Data from the administrative databases of Umbria Region (910,000 residents), Local Health Unit 3 of Napoli (1,170,000 residents) and Friuli--Venezia Giulia Region (1,227,000 residents) will be considered. In each administrative database, patients with the first occurrence of diagnosis of breast, lung or colorectal cancer between 2012 and 2014 will be identified using the following groups of ICD-9-CM codes in primary position: (1) 233.0 and (2) 174.x for breast cancer; (3) 162.x for lung cancer; (4) 153.x for colon cancer and (5) 154.0-154.1 and 154.8 for rectal cancer. Only incident cases will be considered, that is, excluding cases that have the same diagnosis in the 5 years (2007-2011) before the period of interest. A random sample of cases and non-cases will be selected from each administrative database and the corresponding medical charts will be assessed for validation by pairs of trained, independent reviewers. Case ascertainment within the medical charts will be based on (1) the presence of a primary nodular lesion in the breast, lung or colon-rectum, documented with imaging or endoscopy and (2) a cytological or histological documentation of cancer from a primary or metastatic site. Sensitivity and specificity with 95% CIs will be calculated.

DISSEMINATION

Study results will be disseminated widely through peer-reviewed publications and presentations at national and international conferences.

Validity of breast, lung and colorectal cancer diagnoses in administrative databases: a systematic review protocol

INTRODUCTION

Breast, lung and colorectal cancers constitute the most common cancers worldwide and their epidemiology, related health outcomes and quality indicators can be studied using administrative healthcare databases. To constitute a reliable source for research, administrative healthcare databases need to be validated. The aim of this protocol is to perform the first systematic review of studies reporting the validation of International Classification of Diseases 9th and 10th revision codes to identify breast, lung and colorectal cancer diagnoses in administrative healthcare databases.

METHODS AND ANALYSIS

This review protocol has been developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) 2015 statement. We will search the following databases: MEDLINE, EMBASE, Web of Science and the Cochrane Library, using appropriate search strategies. We will include validation studies that used administrative data to identify breast, lung and colorectal cancer diagnoses or studies that evaluated the validity of breast, lung and colorectal cancer codes in administrative data. The following inclusion criteria will be used: (1) the presence of a reference standard case definition for the disease of interest; (2) the presence of at least one test measure (eg, sensitivity, positive predictive values, etc) and (3) the use of data source from an administrative database. Pairs of reviewers will independently abstract data using standardised forms and will assess quality using a checklist based on the Standards for Reporting of Diagnostic accuracy (STARD) criteria.

ETHICS AND DISSEMINATION

Ethics approval is not required. We will submit results of this study to a peer-reviewed journal for publication. The results will serve as a guide to identify appropriate case definitions and algorithms of breast, lung and colorectal cancers for researchers involved in validating administrative healthcare databases as well as for outcome research on these conditions that used administrative healthcare databases.

TRIAL REGISTRATION NUMBER

CRD42015026881.

ICD-11 (JLMMS) and SCT Inter-Operation

The goal of this work is to contribute to a smooth and semantically sound inter-operability between the ICD-11 (International Classification of Diseases-11th revision Joint Linearization for Mortality, Morbidity and Statistics) and SNOMED CT (SCT). To guarantee such inter-operation between a classification, characterized by a single hierarchy of mutually exclusive and exhaustive classes, as is the JLMMS successor of ICD-10 on the one hand, and the multi-hierarchical, ontology-based clinical terminology SCT on the other hand, we use ontology axioms that logically express generalizable truths. This is expressed by the compositional grammar of SCT, together with queries on axiomsof SCT. We test the feasibility of the method on the circulatory chapter of ICD-11 JLMMS and present limitations and results.

Rationale for Quantification in Nursing Services Using the International Council of Nurses Nurse-Patient Summary

This review provides evidence that new data from nurses meets criteria that explains variation in hospital charges, length of hospital stay and end results of hospital care compared with ICD data; that nurses' data can be used to evaluate assignments of nurses to patients; that new data properly distinguishes patients' human needs within ICD categories. These new data are derived from the professional literature indexed and synthesized by Henderson. It is proposed to adopt the ICN-NPSum to standardize quantification in nursing services.

Accuracy of diagnosis codes to identify febrile young infants using administrative data

BACKGROUND

Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.

OBJECTIVE

Determine the most accurate International Classification of Diseases, Ninth Revision (ICD-9) diagnosis coding strategies for identification of febrile infants.

DESIGN

Retrospective cross-sectional study.

SETTING

Eight emergency departments in the Pediatric Health Information System.

PATIENTS

Infants aged <90 days evaluated between July 1, 2012 and June 30, 2013 were randomly selected for medical record review from 1 of 4 ICD-9 diagnosis code groups: (1) discharge diagnosis of fever, (2) admission diagnosis of fever without discharge diagnosis of fever, (3) discharge diagnosis of serious infection without diagnosis of fever, and (4) no diagnosis of fever or serious infection.

EXPOSURE

The ICD-9 diagnosis code groups were compared in 4 case-identification algorithms to a reference standard of fever ≥100.4°F documented in the medical record.

MEASUREMENTS

Algorithm predictive accuracy was measured using sensitivity, specificity, and negative and positive predictive values.

RESULTS

Among 1790 medical records reviewed, 766 (42.8%) infants had fever. Discharge diagnosis of fever demonstrated high specificity (98.2%, 95% confidence interval [CI]: 97.8-98.6) but low sensitivity (53.2%, 95% CI: 50.0-56.4). A case-identification algorithm of admission or discharge diagnosis of fever exhibited higher sensitivity (71.1%, 95% CI: 68.2-74.0), similar specificity (97.7%, 95% CI: 97.3-98.1), and the highest positive predictive value (86.9%, 95% CI: 84.5-89.3).

CONCLUSIONS

A case-identification strategy that includes admission or discharge diagnosis of fever should be considered for febrile infant studies using administrative data, though underclassification of patients is a potential limitation.

COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance

Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance qualities of biomedical ontologies by performing cross-ontology examination.

Accuracy of Electronic Health Record Data for Identifying Stroke Cases in Large-Scale Epidemiological Studies: A Systematic Review from the UK Biobank Stroke Outcomes Group

Objective

Long-term follow-up of population-based prospective studies is often achieved through linkages to coded regional or national health care data. Our knowledge of the accuracy of such data is incomplete. To inform methods for identifying stroke cases in UK Biobank (a prospective study of 503,000 UK adults recruited in middle-age), we systematically evaluated the accuracy of these data for stroke and its main pathological types (ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage), determining the optimum codes for case identification.

Methods

We sought studies published from 1990-November 2013, which compared coded data from death certificates, hospital admissions or primary care with a reference standard for stroke or its pathological types. We extracted information on a range of study characteristics and assessed study quality with the Quality Assessment of Diagnostic Studies tool (QUADAS-2). To assess accuracy, we extracted data on positive predictive values (PPV) and—where available—on sensitivity, specificity, and negative predictive values (NPV).

Results

37 of 39 eligible studies assessed accuracy of International Classification of Diseases (ICD)-coded hospital or death certificate data. They varied widely in their settings, methods, reporting, quality, and in the choice and accuracy of codes. Although PPVs for stroke and its pathological types ranged from 6–97%, appropriately selected, stroke-specific codes (rather than broad cerebrovascular codes) consistently produced PPVs >70%, and in several studies >90%. The few studies with data on sensitivity, specificity and NPV showed higher sensitivity of hospital versus death certificate data for stroke, with specificity and NPV consistently >96%. Few studies assessed either primary care data or combinations of data sources.

Conclusions

Particular stroke-specific codes can yield high PPVs (>90%) for stroke/stroke types. Inclusion of primary care data and combining data sources should improve accuracy in large epidemiological studies, but there is limited published information about these strategies.

Diagnostic change 10 years after a first episode of psychosis

BACKGROUND

A lack of an aetiologically based nosology classification has contributed to instability in psychiatric diagnoses over time. This study aimed to examine the diagnostic stability of psychosis diagnoses using data from an incidence sample of psychosis cases, followed up after 10 years and to examine those baseline variables which were associated with diagnostic change.

METHOD

Data were examined from the ÆSOP and ÆSOP-10 studies, an incidence and follow-up study, respectively, of a population-based cohort of first-episode psychosis cases from two sites. Diagnosis was assigned using ICD-10 and DSM-IV-TR. Diagnostic change was examined using prospective and retrospective consistency. Baseline variables associated with change were examined using logistic regression and likelihood ratio tests.

RESULTS

Slightly more (59.6%) cases had the same baseline and lifetime ICD-10 diagnosis compared with DSM-IV-TR (55.3%), but prospective and retrospective consistency was similar. Schizophrenia, psychotic bipolar disorder and drug-induced psychosis were more prospectively consistent than other diagnoses. A substantial number of cases with other diagnoses at baseline (ICD-10, n = 61; DSM-IV-TR, n = 76) were classified as having schizophrenia at 10 years. Many variables were associated with change to schizophrenia but few with overall change in diagnosis.

CONCLUSIONS

Diagnoses other than schizophrenia should to be regarded as potentially provisional.

Frequency and clinical relevance of inconsistent code status documentation

BACKGROUND

Accurate and complete documentation of hospitalized patients' code status is important to ensure that healthcare providers take appropriate action in the event of a cardiac arrest.

OBJECTIVE

Determine the frequency and clinical relevance of incomplete and inconsistent code status documentation.

DESIGN

Point-prevalence study.

SETTING

Academic medical centers.

PATIENTS

Patients admitted to general internal medicine wards.

MEASUREMENTS

Frequency and clinical relevance of inconsistent code status documentation across 5 documentation sources.

RESULTS

Thirty-eight (20%; 95% confidence interval [CI], 14%-26%) of 187 patients had complete and consistent code status documentation. Another 27 (14%; 95% CI, 9%-19%) patients had no code status documentation. The remaining 122 (65%; 95% CI, 58%-72%) patients had at least 1 code status documentation inconsistency. Of these, 38 (20%; 95% CI, 14%-26%) patients had a clinically relevant code status documentation inconsistency. Multivariate logistic regression analysis demonstrated that increased age (odds ratio [OR] = 1.07 [95% CI, 1.05-1.10] for every 1-year increase in age, P < 0.001) and patients receiving comfort measures (OR = 9.39 [95% CI, 1.35-65.19], P = 0.02) were independently associated with a clinically relevant code status documentation inconsistency.

CONCLUSIONS

Incomplete and inconsistent documentation of code status occurred frequently in hospitalized patients, especially elderly patients and patients receiving comfort measures. Having multiple, poorly integrated code status documentation sources leads to a significant number of concerning inconsistencies that create opportunities for healthcare providers to inappropriately deliver or withhold resuscitative measures that conflict with patients' expressed wishes. Institutions need to be aware of this potential documentation hazard and take steps to minimize code status documentation inconsistencies.

Charts versus Discharge ICD-10 Coding for Sternal Wound Infection Following Coronary Artery Bypass Grafting

BACKGROUND

Sternal wound infection (SWI) in patients undergoing coronary artery bypass grafting (CABG) can carry a significant risk of morbidity and mortality. The objective of this work is to describe the methods used to identify cases of SWI in an administrative database and to demonstrate the effectiveness of using an International Classification of Diseases, Tenth Revision (ICD-10) coding algorithm for this purpose.

METHODS

ICD-10 codes were used to identify cases of SWI within one year of CABG between April 2002 and November 2009. We randomly chose 200 charts for detailed chart review (100 from each of the groups coded as having SWI and not having SWI) to determine the utility of the ICD-10 coding algorithm.

RESULTS

There were 2,820 patients undergoing CABG. Of these, 264 (9.4 percent) were coded as having SWI. Thirty-eight cases of SWI were identified by chart review. The ICD-10 coding algorithm of T81.3 or T81.4 was able to identify incident SWI with a positive predictive value of 35 percent and a negative predictive value of 97 percent. The agreement between the ICD-10 coding algorithm and presence of SWI remained fair, with an overall kappa coefficient of 0.32 (95 percent confidence interval, 0.22-0.43). The effectiveness of identifying deep SWI cases is also presented.

CONCLUSIONS

This article describes an effective algorithm for identifying a cohort of patients with SWI following open sternotomy in large databases using ICD-10 coding. In addition, alternative search strategies are presented to suit researchers' needs.

The utility of ICD9-CM codes in identifying induction of labor

BACKGROUND

Data evaluating the accuracy of ICD9-CM codes in identifying inductions are limited. Our objective was to examine the test characteristics of ICD9-CM coding for induction of labor and to identify differences between those captured by coding and those not.

METHODS

We performed a retrospective cohort study of ICD9-CM codes in identifying charts of induced women at our institution from 2005 to 2009. Review of the medical record was the gold standard. Characteristics of the charts were compared using Mann-Whitney U tests and chi-square tests where appropriate.

RESULTS

A total of 3,263 women were included, 708 with ICD9-CM coding for induction (screen positive). A total of 422 women were randomly sampled from those not coded as induction (screen negative). The sensitivity of ICD9-CM coding for induction was 51.4%, specificity 98.8%, positive predictive value 96.6%, negative predictive value 74.7%. False negative charts (25%) were more likely to be women induced for premature rupture of membranes (40% versus 8%, p < 0.001) or with oxytocin (51% versus 33%, p < 0.001) when compared with screen positive charts.

CONCLUSIONS

It is reassuring that 97% of charts coded for induction by ICD9-CM codes are, in fact, patients that were induced. With this degree of accuracy, we can be confident that charts coded as induction are unlikely to be miscoded.

ICHI Categorial Structure: a WHO-FIC Tool for Semantic Interoperability of Procedures Classifications

Casemix grouping using procedures classifications has become an important use case for health care terminologies. There are so many different national procedures classifications used for Casemix grouping that it is not possible to agree on a worldwide standard. ICHI (International Classification of Health Interventions) is proposing an approach that standardises only the terminologies' model structure. The poster shows the use of the ICHI alpha to replace ICD9 CM Volume 3 in the UNU-CBG International Casemix grouper.