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Identifying cardiac surgery operations in hospital episode statistics administrative database, with an OPCS-based classification of procedures, validated against clinical data.

ABSTRACT: OBJECTIVES:Administrative databases with dedicated coding systems in healthcare systems where providers are funded based on services recorded have been shown to be useful for clinical research, although their reliability is still questioned. We devised a custom classification of procedures and algorithms based on OPCS, enabling us to identify open heart surgeries from the English administrative database, Hospital Episode Statistics, with the objective of comparing the incidence of cardiac procedures in administrative and clinical databases. DESIGN:A comparative study of the incidence of cardiac procedures in administrative and clinical databases. SETTING:Data from all National Health Service Trusts in England, performing cardiac surgery. PARTICIPANTS:Patients classified as having cardiac surgery across England between 2004 and 2015, using a combination of procedure codes, age >18 and consultant specialty, where the classification was validated against internal and external benchmarks. RESULTS:We identified a total of 296?426 cardiac surgery procedures, of which majority of the procedures were coronary artery bypass grafting (CABG), aortic valve replacement (AVR), mitral repair and aortic surgery. The matching at local level was 100% for CABG and transplant, >90% for aortic valve and major aortic procedures and >80% for mitral. At national level, results were similar for CABG (IQR 98.6%-104%), AVR (IQR 105%-118%) and mitral valve replacement (IQR 86.2%-111%). CONCLUSIONS:We set up a process which can identify cardiac surgeries in England from administrative data. This will lead to the development of a risk model to predict early and late postoperative mortality, useful for risk stratification, risk prediction, benchmarking and real-time monitoring. Once appropriately adjusted, the system can be applied to other specialties, proving especially useful in those areas where clinical databases are not fully established.

SUBMITTER: Bortolussi G

PROVIDER: S-EPMC6475180 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Identifying cardiac surgery operations in hospital episode statistics administrative database, with an OPCS-based classification of procedures, validated against clinical data.

Bortolussi Giacomo G McNulty David D Waheed Hina H Mawhinney Jamie A JA Freemantle Nick N Pagano Domenico D

BMJ open 20190323 3

<h4>Objectives</h4>Administrative databases with dedicated coding systems in healthcare systems where providers are funded based on services recorded have been shown to be useful for clinical research, although their reliability is still questioned. We devised a custom classification of procedures and algorithms based on OPCS, enabling us to identify open heart surgeries from the English administrative database, Hospital Episode Statistics, with the objective of comparing the incidence of cardia ...[more]

PMID: 30904838

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Project description:BackgroundArthroscopic partial meniscectomy is one of the most common orthopaedic procedures worldwide. Clinical trial evidence published in the past 6 years, however, has raised questions about the effectiveness of the procedure in some patient groups. In view of concerns about potential overuse, we aimed to establish the true risk of serious complications after arthroscopic partial meniscectomy.MethodsWe analysed national Hospital Episode Statistics data for all arthroscopic partial meniscectomies done in England between April 1, 1997, and March 31, 2017. Simultaneous or staged (within 6 months) bilateral cases were excluded. We identified complications occurring in the 90 days after the index procedure. The primary outcome was the occurrence of at least one serious complication within 90 days, which was defined as either myocardial infarction, stroke, pulmonary embolism, infection requiring surgery, fasciotomy, neurovascular injury, or death. Logistic regression modelling was used to identify factors associated with complications and, when possible, risk was compared with general population data.FindingsDuring the study period 1 088 782 arthroscopic partial meniscectomies were done, 699 965 of which were eligible for analysis. Within 90 days, serious complications occurred in 2218 (0·317% [95% CI 0·304-0·330]) cases, including 546 pulmonary embolisms (0·078% [95% CI 0·072-0·085]) and 944 infections necessitating further surgery (0·135% [95% CI 0·126-0·144]). Increasing age (adjusted odds ratio [OR] 1·247 per decade [95% CI 1·208-1·288) and modified Charlson comorbidity index (adjusted OR 1·860 per 10 units [95% CI 1·708-2·042]) were associated with an increased risk of serious complications. Female sex was associated with a reduced risk of serious complications (adjusted OR 0·640 [95% CI 0·580-0·705). The risk of mortality fell over time (adjusted OR 0·965 per year [95% CI 0·937-0·994]). Mortality, myocardial infarction, and stroke occurred less frequently in the study cohort than in the general population. The risks of infection and pulmonary embolism did not change during the study, and were significantly higher in the study cohort than in the general population. For every 1390 (95% CI 1272-1532) fewer knee arthroscopies done, one pulmonary embolism could be prevented. For every 749 (95% CI 704-801) fewer procedures done, one native knee joint infection could be prevented.InterpretationOverall, the risk associated with undergoing arthroscopic partial meniscectomy was low. However, some rare but serious complications (including pulmonary embolism and infection) are associated with the procedure, and the risks have not fallen with time. In view of uncertainty about the effectiveness of arthroscopic partial meniscectomy, an appreciation of relative risks is crucial for patients and clinicians. Our data provide a basis for decision making and consent.FundingUK National Institute for Health Research.

Project description:Background Administrative hospital diagnostic coding data are increasingly used in "big data" research and to assess complication rates after surgery or acute medical conditions. Acute stroke is a common complication of several procedures/conditions, such as carotid interventions, but data are lacking on the sensitivity of administrative coding in identifying acute stroke during inpatient stay. Methods and Results Using all acute strokes ascertained in a population-based cohort (2002-2017) as the reference, we determined the sensitivity of hospital administrative diagnostic codes ( International Classification of Diseases, Tenth Revision; ICD-10) for identifying acute strokes that occurred during hospital admission for other reasons, stratified by coding strategies, study periods, and stroke severity (National Institutes of Health Stroke Score</≥5). Of 3011 acute strokes, 198 (6.6%) occurred during hospital admissions for procedures/other diseases, including 122 (61.6%) major strokes. Using stroke-specific codes ( ICD-10=I60-I61 and I63-I64) in the primary diagnostic position, 66 of the 198 cases were correctly identified (sensitivity for any stroke, 33.3%; 95% CI, 27.1-40.2; minor stroke, 30.3%; 95% CI, 21.0-41.5; major stroke, 35.2%; 95% CI, 27.2-44.2), with no improvement of sensitivity over time ( Ptrend=0.54). Sensitivity was lower during admissions for surgery/procedures than for other acute medical admissions (n/% 17/23.3% versus 49/39.2%; P=0.02). Sensitivity improved to 60.6% (53.6-67.2) for all and 61.6% (50.0-72.1) for surgery/procedures if other diagnostic positions were used, and to 65.2% (58.2-71.5) and 68.5% (56.9-78.1) respectively if combined with use of all possible nonspecific stroke-related codes (ie, adding ICD-10=I62 and I65-I68). Conclusions Low sensitivity of administrative coding in identifying acute strokes that occurred during admission does not support its use alone for audit of complication rates of procedures or hospitalization for other reasons.

Project description:BackgroundTo effectively use administrative claims for healthcare research, clinical events must be inferred from coding data according to validated algorithms. In October 2015, the United States transitioned from the International Classification of Diseases Ninth Revision (ICD-9) to the Tenth Revision (ICD-10). We describe our method to derive new ICD-10 codes for outcomes after vascular procedures from our prior, validated ICD-9 codes.MethodsWe began with validated ICD-9 coding lists known to represent outcomes after lower extremity revascularization, thoracic aortic endograft placement, abdominal aortic aneurysm reintervention, and carotid revascularization. We used the publicly available general equivalence mapping tools to derive corresponding ICD-10 codes for each of the ICD-9 codes in our current lists. The resulting lists were then manually reviewed by multiple authors to ensure clinical relevance for appropriate event detection. Clinically nonrelevant and duplicated codes were removed.ResultsA total of 475 ICD-9 codes were translated to ICD-10 with a 98-fold increase (n = 46,630) in the total number of codes. Overall, we found that 77% of codes (n = 35,833) were either duplicated or not clinically relevant upon manual review. For example, for thoracic aortic endograft placement, 97 ICD-9 codes mapped to 14,661 ICD-10 codes in total. A total of 890 codes were removed as duplicates and 9035 codes were removed during manual clinical review. The resultant, reviewed list contained 4736 ICD-10 codes representing a 49-fold increase from the initial ICD-9 list. Findings were similar across the other procedures studied.ConclusionsICD-10 has expanded the number of codes necessary to describe outcomes after vascular procedures. More than 75% of the codes obtained using the general equivalence mapping database were either duplicated or not clinically relevant. Manual review of codes by researchers with clinical knowledge of the procedures is imperative.

Dataset Information

Identifying cardiac surgery operations in hospital episode statistics administrative database, with an OPCS-based classification of procedures, validated against clinical data.

Publications

Identifying cardiac surgery operations in hospital episode statistics administrative database, with an OPCS-based classification of procedures, validated against clinical data.

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