Coding of clinical diagnoses. Persevere with Körner system.
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During the testing of the Read Clinical Codes in general practice medical records in Australia, it became apparent that the pharmaceutical section of the codes was not applicable in a country with different brand names, pack sizes and forms. For pharmacoepidemiological studies, structured classification of both morbidity and pharmaceuticals is required for meaningful analysis. The search for a suitable pharmaceutical classification proved fruitless. While the Australian Government has recently adopted the Anatomical Therapeutic Chemical (ATC) Classification as the national standard, this only classifies drugs to the generic level. None of the extended coding systems used in hospital pharmacies, by community pharmacists, or by Government are hierarchically structured. The extension code we have developed, is an analytical algorithm comprising independent fields for: dosage; strength; manufacturer and brand; and pack size. The codes within each field are also structured in a hierarchical manner. The result is an extension code of 21 digits, each digit or group of digits having a meaning. The structure of this classification will allow analysis of any aspect of the drug prescribed. This system is designed for computerised entry of text and transparent coding of the data--not for manual coding on paper nor manual code entry to the computer.
BACKGROUND: This study identified and compared the prevalence of new-onset atrial fibrillation (AFIB) following standard coronary artery bypass grafting (SCABG) with cardiopulmonary bypass (CPB) and minimally invasive direct vision coronary artery bypass grafting (MIDCAB) without CPB. A further comparison was made between AFIB prevalence in SCABG and MIDCAB subjects with two or fewer bypasses. METHODS: This is a retrospective, comparative survey. Patients with new-onset AFIB who underwent SCABG or MIDCAB alone were identified electronically using a triangulated method (International Classification of Diseases, 9th revision, Clinical Modification [ICD-9 CM] code; clinical database word search; and pharmacy database drug search). RESULTS: The total sample (n = 814; 94 MIDCAB, 720 SCABG) exhibited a trend toward lower AFIB prevalence in MIDCAB (23.4%) versus SCABG (33.1%) subjects (p = 0.059). AFIB prevalence in the SCABG subset with two or less vessel bypasses (n = 98; n = 18 single vessel, n = 80 double vessels) and MIDCAB subjects (n = 94; n = 90 single vessels, n = 4 double vessels) was almost identical (SCABG subset 24.5% versus MIDCAB 23.4%, p = 0.860). Slightly more than half (56.9%) of new-onset AFIB subjects were identified by ICD-9 CM codes, with the remainder by word search (37.7%) or procainamide query (5.4%). CONCLUSIONS: In this sample, the number of vessels bypassed seemed to have a greater influence on AFIB prevalence than the application of CPB or the surgical approach. Retrospective identification of AFIB cases by ICD-9 CM code grossly underestimated AFIB prevalence.
Amplitude-coded color Doppler sonography (ACD) has become an useful adjunct to gray-scale US and conventional color Doppler sonography (CD) for the assessment of vascular diseases and pathologic conditions that might affect or alter tissue vascularization or perfusion. Basically, all US units that generate conventional color Doppler information through autocorrelation technique are capable of displaying ACD. This technique is also referred to as power Doppler, amplitude-mode color Doppler US, color Doppler energy (CDE), or US angiography. Amplitude-coded color Doppler sonography has already emerged as a valuable adjunct to conventional CD, particularly for evaluating flow in parts of the body where CD signal is weak because of slow flow, small blood vessels, or both.
The main aims were to determine how much diabetes is under-recorded on death certificates, the influence of demographic variables and to what extent New Zealand Health Information Service (NZHIS) coding is able to compensate for deficiencies. A retrospective review of 600 death certificates (during 1999) from the Mortality Review Database in Christchurch Hospitals was carried out. Clinical data, laboratory results, coroner's reports, hospital clinical coding and NZHIS coding were collated and analysed. One hundred and four cases (17%) had clinically documented diabetes, of which only 47 (45%) had diabetes recorded on either the death certificate or the coroner's report. Diabetes was recognised in NZHIS coding in 45 (43%) of cases and in 94 (90%) cases in hospital clinical coding. Diabetes was more likely to be recorded on the death certificate in males and in subjects treated with insulin (P<0.05). Of the 496 subjects without documented diabetes, 159 (32%) had a highest random plasma glucose >11.1 mmol/l. Documented diabetes is thus under-reported on more than 50% of death certificates and this is not compensated by NZHIS coding. In addition, there is likely to be a significant number of cases with undiagnosed diabetes. This may adversely affect the reliability of mortality statistics.
A basic overview of bar code technology is presented with a focus on applications in the clinical laboratory. Bar codes operate based on symbology, a pattern of bars and white spaces that define alphanumeric characters. The codes are read by scanners, which may be stationary or handheld. Bar codes may be printed using any of several available methods. Bar codes are currently being implemented in several areas of health care, including materials management, clinical laboratory, pharmacy, medical records, and asset management. Planning for implementation of a bar code system is very much like computer installation, in terms of systems analysis and design, procedures, and training. Clinical laboratories should consider use of bar code systems, as they often are faster, better, and more cost-effective than available alternatives.
Confidentiality is a fundamental rule of medicine and has been specifically defined in many codes of medical ethics. A changing clinical environment both because of diseases such as AIDS, which were not anticipated when these clinical codes were created, and because of the changing relationship between the physician, the patient, and the payor for the physician's care creates dilemmas concerning the rule of confidentiality.
The cessation of the adenovirus vaccination program for military trainees has resulted in several recent acute respiratory disease (ARD) outbreaks. In the absence of vaccination, rapid detection methods are necessary for the timely implementation of measures to prevent adenovirus transmission within military training facilities. To this end, we have combined a fluorogenic real-time multiplex PCR assay with four sets of degenerate PCR primers that target the E1A, fiber, and hexon genes with a long oligonucleotide microarray capable of identifying the most common adenovirus serotypes associated with adult respiratory tract infections (serotypes 3, 4, 7, 16, and 21) and a representative member of adenovirus subgroup C (serotype 6) that is a common cause of childhood ARD and that often persists into adulthood. Analyses with prototype strains demonstrated unique hybridization patterns for representative members of adenovirus subgroups B(1), B(2), C, and E, thus allowing serotype determination. Microarray-based sensitivity assessments revealed lower detection limits (between 1 and 100 genomic copies) for adenovirus serotype 4 (Ad4) and Ad7 cell culture lysates, clinical nasal washes, and throat swabs and purified DNA from clinical samples. When adenovirus was detected from coded clinical samples, the results obtained by this approach demonstrated an excellent concordance with those obtained by the more established method of adenovirus identification as well as by cell culture with fluorescent-antibody staining. Finally, the utility of this method was further supported by its ability to detect adenoviral coinfections, contamination, and, potentially, recombination events. Taken together, the results demonstrate the usefulness of the simple and rapid diagnostic method developed for the unequivocal identification of ARD-associated adenoviral serotypes from laboratory or clinical samples that can be completed in 1.5 to 4.0 h.
A number of clinical coding and vocabulary schemes are in use in healthcare enterprises today. Most of them are weak in light of the qualities that characterize adequate controlled medical terminologies, as outlined in Part One of this review. Here we look at the major code and terminology sets with a critical eye, as well as suggest practical steps to enable health industry information system purchasers and users to move forward with their effort to use common terminology to improve the quality, service, and knowledge in their enterprise.