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The basic design, measurement and analytical components of clinical trials are frequently difficult to extract from published reports. Precedent indicates that this type of information is amenable to codification. An alphabetical international coding system (ICS) is proposed and its advantages discussed and illustrated.
In clinical routine there is a growing need to encode medical concepts with available standard coding systems. The coding process can be time consuming and may significantly add to daily paperwork, particularly regarding patients with multiple diagnoses and in busy clinical environments with a high turnover of patients. We have developed a generic computerised encoding tool--the PADS encoder--to ensure rapid, correct and complete coding of diagnoses in daily routine. The tool is integrated into an electronic patient record system (PADS, Patient Archiving & Documentation System) and takes full advantage of the user friendly Macintosh interface. The tool was tested in a controlled experiment by 18 clinicians who encoded a total of 666 medical concepts in each protocol (study protocol vs. control). The following positive findings were significantly associated with the use of the computerised coding tool: the number of correctly encoded medical concepts was higher (99.55% vs. 86.1%), coding errors were lower (0% vs. 10.81%), more modifier codes were encoded correctly (increase by up to 43%), less coding errors were made (decrease by up to 43%), the overall rate of correctly encoded and complete main and modifier codes was increased by 31.27% (97.29% vs. 66.02%), coding time was reduced by 50%. This paper presents data to suggest that a computerised coding tool can produce more complete data of higher quality and can save time compared with the traditional approach to encode medical concepts.
BACKGROUND: Subspecialty-specific normative values for clinical productivity of practicing pediatric hematologist/oncologists have not been well established. This information could be a useful adjunct in administrative decision-making in areas such as necessary levels of physician staffing and development of compensation plans. METHODS: Current procedural terminology (CPT) coding information was obtained from 27 pediatric hematology/oncology groups. Clinical productivity was assessed by overall number of patient encounters and the total number of physician work relative value units (RVU) as defined by the resource-based relative value scale. The average physician productivity within each individual program was calculated. To determine uniformity of CPT coding, an additional survey solicited mock patient encounter documentation and CPT coding for a simple clinical vignette. RESULTS: A broad range of clinical productivity was observed for both numbers of patient encounters and RVU. Evaluation of the CPT coding data of the surveyed groups revealed differences in usage of certain evaluation and management (E/M) codes and procedural and specimen interpretation codes. Within individual categories of E/M service codes, a wide variation in assigned CPT code levels was also observed. This observation was supported by differences in the E/M coding for the clinical vignette. CONCLUSIONS: Assessment and tracking of physician productivity can provide useful information for the administrative management of pediatric hematology/oncology programs. Caution must be exercised, however, when making productivity comparisons with other subspecialties or even between pediatric hematology/oncology programs. Such comparisons should take into account the number of patient encounters, characteristics of E/M coding patterns, the use of physician extenders, as well as overall RVU production.
OBJECTIVE: To determine the accuracy of routine data coding in a large multispeciality urological unit. Materials and methods From the clinical records, the diagnosis and procedure codes were ascribed to 106 finished consultant episodes (FCEs) in urology, by two urological trainees. The codes were compared with those ascribed by professional hospital coders (and of which the trainees were unaware) from information written on the audit form by junior medical staff. Where there were discrepancies in codes an error was recorded and the stage in the coding process in which it occurred was determined. RESULTS: Forty-eight coding errors were found in 38 of the 106 (36%) FCEs; 34 (71%) were caused by inaccurate coding and 14 (29%) were the result of the incorrect completion of audit forms. CONCLUSION: The clinical codes generated from the authors' department do not accurately reflect the clinical practice. If coding errors of this magnitude are typical of urology units in general, the concept of hospital performance tables (which will be generated using routine clinical data) is untenable unless data recording is given higher priority.
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CONTEXT: Comorbidity measures are designed to exclude complications when they map International Classification of Diseases (ICD-9-CM) codes to diagnostic categories. The use of data fields that indicates whether each secondary diagnosis was present at the time of hospital admission may lead to the more accurate identification of preexisting conditions. OBJECTIVE: To examine the rate of misclassification of ICD-9-CM codes into diagnostic categories by the Dartmouth-Manitoba adaptation of the Charlson index and by the Elixhauser comorbidity algorithm. DATA SOURCE: Analysis of 178,838 patients in the California State Inpatient Database (CA SID) admitted in 2000 for one of seven major medical and surgical conditions. The CA SID includes a condition present at admission (CPAA) modifier for each ICD-9-CM code. STUDY DESIGN: The Dartmouth/Charlson index and the Elixhauser comorbidity measure were used to map the ICD-9-CM codes into diagnostic categories for patients in each study population. We calculated the misclassification rate for each mapping algorithm, using information from the CPAA as the "gold standard." PRINCIPAL FINDINGS: The Dartmouth/Charlson index underestimated the prevalence of hemiplegia/paraplegia by 70 percent, cerebrovascular disease by 70 percent, myocardial infarction by 65 percent, congestive heart failure (CHF) by 45 percent, and peptic ulcer disease by 34 percent. The Elixhauser algorithm misclassified complications as preexisting conditions for 43 percent of the coagulopathies, 25 percent of the fluid and electrolyte disorders, 18 percent of the cardiac arrhythmias, 18 percent of the cardiac arrhythmias, and 9 percent of the cases of CHF. CONCLUSION: Adding the CPAA modifier to administrative data would significantly enhance the ability of the Dartmouth/Charlson index and of the Elixhauser algorithm to map ICD-9-CM codes to diagnostic categories accurately.
MMPI responses obtained from a large random sample of midwestern adults who were 18 through 99 years old and had no physically or mentally handicapping condition yielded a pattern significantly different from the pattern of the original norms. From these data, two new kinds of normative tables have been developed: Norms that reflect, for each sex, the response pattern of the general adult population, and a set of tables, separate for each sex, that allow comparisons to be based on age. In addition, the traditional scoring procedures based on a linear transformation that maintains any underlying skewness of the raw score distribution has been replaced by procedures that yield normalized T scores. The changes that are apparent at the item and scale level are also evident in the frequency with which certain 1- and 2-point codes occur in normal and clinical samples. These changes are apt to make our interpretive statements more meaningful because they are based on contemporary norms.
The MCMI-II is becoming more widely used in both clinical practice and research settings. From a research perspective, one area that has not received a great deal of attention is high-point codes. While the MMPI has a very lengthy history of high-point code analysis and ancillary interpretative manuals, the MCMI-II has no such traditional data base. The present study determined the prevalence of single and two-point high codes in a large sample of VA patients. Additionally, associated severe personality scales and clinical syndrome scales are delineated as a function of the 20 most common profiles. These 20 common profiles accounted for 82% of the patients.
Hospital morbidity data in the form of International classification of diseases, 9th revision, clinical modification codes are often used for epidemiological studies and disease surveillance. We aimed to evaluate the reliability of the Victorian In-patient Minimum Database for use in epidemiological studies and disease surveillance. Data from 1993-94 were collected, as part of a coding audit of public hospitals in Victoria, from 7052 randomly selected records. The frequency of discrepancy in any coding field was 53 per cent, and of discrepancy in the principal diagnosis, 22 per cent. New Australian national diagnosis-related group (ANDRG) codes were assigned as a result of discrepancy in 13.6 per cent of cases. Discrepancy rates increased with increasing rarity of ANDRG, from 50 per cent to 56 per cent. Predictors of change in ANDRG assignment were discrepancy in the principal diagnosis, ANDRG frequency of over 0.6 per cent, more than three diagnoses, medical ANDRGs, length of stay over five days and rural hospitals. Rates of any discrepancy increased from 36 per cent in patients with one diagnosis to 94 per cent in patients with 12 diagnoses. The discrepancy rates were consistent with those of other studies. Coding discrepancy is likely to be caused by universal difficulties associated with the coding of hospital records, rather than any unique local problems. The predictors of discrepancy suggest that more complex cases are more prone to coding discrepancy. In areas where the database is less reliable, use of a supplementary data source, such as link-age studies, would improve reliability.
A number of researchers have called for the establishment of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) correlate literature that is based directly on investigations of the revised MMPI. The purpose of this study was to examine clinical correlates found for 9 commonly occurring 2-point codes, each of which contained a minimum of 20 patients, and for 82 profiles that were within-normal-limit (WNL) in a sample of 289 female and 308 male psychiatric inpatients. Major findings indicated that descriptors identified for MMPI-2 based codes were generally similar to the established literature for corresponding codes derived from the original MMPI (Hathaway & McKinley, 1967). In addition, correlates identified for the WNL profile suggest that these patients are less likely to exhibit more chronic symptomatology and to have psychological histories marked by less severe psychological disturbance than other inpatients. Overall, the results of this study represent an initial step in the creation of an MMPI-2 correlate literature.
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Free-text or natural language documents make up an increasing part of the computerized medical record. While they do provide accessible clinical information to health care personnel, they fail to support processes that require clinical data coded according to a shared lexicon and data structure. We have developed a natural language parser that converts free-text admitting diagnoses into a coded form. This application has proven acceptably accurate in the experimental laboratory to warrant a test in the target clinical environment. Here we describe an approach to moving this research application into a production environment where it can contribute to the efforts of the Health Information Services Department. This transition is essential if the products of natural language understanding research are to contribute to patient care in a routine and sustainable way.
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A case formulation content coding method is described and applied to the formulation section of 56 intake evaluations randomly selected from an outpatient psychiatric clinic. The coding manual showed good reliability (mean kappa = 0.86) across content and quality categories. Although 95% of the formulations included descriptive information, only 37% addressed hypothesized predisposing life events accounting for the individual's presenting problems, and 16% included a precipitating stressor. Only 43% inferred a psychological mechanism, 2% inferred a biological mechanism, and 2% mentioned sociocultural factors. Formulations were more descriptive than inferential, more simple than complex, and moderately precise in use of language. In sum, clinicians used the formulation primarily to summarize descriptive information rather than to integrate it into a hypothesis about the causes, precipitants, and maintaining influences of an individual's problems.
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