Molecular genetics: from bench to bedside.

Diligent work performed at the laboratory bench during the 20th century has resulted in advances in the health care industry and benefits for the patients it serves. Time-saving laboratory techniques such as DNA isolation and polymerase chain reaction (PCR) have helped molecular biologists and geneticists learn more about genes and their function. Information resulting from genetic research is currently used by medical researchers to develop genetic testing, genetic engineering, and gene therapy procedures that will benefit patients with genetic needs. This article provides basic information regarding several of these procedures, including DNA isolation, PCR, gel electrophoresis, and restriction enzyme techniques. In addition, the article explores the experiences of a clinical nurse, who by learning genetic laboratory techniques, developed an appreciation of the nursing implications related to genetic laboratory procedures.

Chronic conditions and risk of in-hospital death.

OBJECTIVE: This study examined the relationship of in-hospital death and 13 conditions likely to have been present prior to the patient's admission to the hospital, defined using secondary discharge diagnosis codes. DATA SOURCES AND STUDY SETTING: 1988 California computerized hospital discharge abstract data, including 24 secondary diagnosis coding slots, from all general, acute care hospitals. STUDY DESIGN: The odds ratio for in-hospital death associated with each of 13 chronic conditions was computed from a multivariable logistic regression using patient age and all chronic conditions to predict in-hospital death. DATA EXTRACTION: All 1,949,276 general medical and surgical admissions of persons over 17 years of age were included. Patients were assigned to four groups according to the mortality rate of their reason for admission; some analyses separated medical and surgical hospitalizations. PRINCIPAL FINDINGS: Overall mortality was 4.4 percent. For all cases, mortality varied by chronic condition, ranging from 5.3 percent for coronary artery disease to 18.6 percent for nutritional deficiencies. The odds ratios associated with the presence of a chronic condition were generally highest for patients in the rare mortality group. Although chronic conditions were more commonly listed for medical patients, the associated odds ratios were generally higher for surgical patients, particularly in lower mortality groups. CONCLUSIONS: Studies examining death rates need to consider the influence of chronic conditions. Chronic conditions had a particularly significant association with the likelihood of death for admission types generally associated with low mortality rates and for surgical hospitalizations. The accuracy and completeness of discharge diagnoses require further study, especially relating to chronic illnesses.

Identifying complications of care using administrative data.

The Complications Screening Program (CSP) is a method using standard hospital discharge abstract data to identify 27 potentially preventable in-hospital complications, such as post-operative pneumonia, hemorrhage, medication incidents, and wound infection. The CSP was applied to over 1.9 million adult medical/surgical cases using 1988 California discharge abstract data. Cases with complications were significantly older and more likely to die, and they had much higher average total charges and lengths of stay than other cases (P < 0.0001). For most case types, 13 chronic conditions, defined using diagnosis codes, increased the relative risks of having a complication after adjusting for patient age. Cases at larger hospitals and teaching facilities generally had higher complication rates. Logistic regression models to predict complications using demographic, administrative, clinical, and hospital characteristics variables, had modest power (C statistics = 0.64 to 0.70). The CSP requires further evaluation before using it for purposes other than research.

Using administrative data to screen hospitals for high complication rates.

Medicare's Peer Review Organizations (PROs) now are required to work with hospitals to improve patient outcomes. Which hospitals should be targeted? We used 1988 California discharge data to identify hospitals with higher-than-expected rates of complications in six adult, medical-surgical patient populations. Relative hospital complication rates generally were correlated across clinical areas, although correlations were lower between medical and surgical case types. Higher relative rates of complications were associated with larger size, major teaching facilities, and provision of open heart surgery, as well as with coding more diagnoses per case. Complication rates generally were not related significantly to hospital mortality rates as calculated by the Health Care Financing Administration. Different hospitals may be chosen for quality review depending on the method used to identify poor outcomes.

A method for screening the quality of hospital care using administrative data: preliminary validation results.

Applying a computerized algorithm to administrative data to help assess the quality of hospital care is intriguing. As Iezzoni and colleagues point out, there are major differences of opinion as to the worth of such efforts. This article significantly advances the state of the art in using administrative data to screen for potential quality-of-care problems. In addition, this work on identifying complications of care goes well beyond the emphasis of many government organizations on hospital mortality rates. One question, however, not raised in the paper is: What is a practical upper limit to the sensitivity and specificity in comparing computerized screen results with the consensus judgments of a group of independent physicians? Advanced statistical techniques (such as bootstrapping) might be used to estimate the stability of consensus judgments by physician groups. When the judgments of two groups of physicians are compared with each other, the resulting sensitivity and specificity will not be .99! In addition, more training of members of the physician panels would probably have increased interrater reliability. While acknowledging this problem, the researchers' detailed analysis of the panel results is intriguing and represents a model for such studies. It is hoped that the authors will follow up on the avenues opened here. Furthermore, what degree of accuracy is necessary to identify facilities with higher-than-expected rates of complications? The authors discuss problems involved in using administrative data to target hospitals and departments for more costly in-depth reviews of quality. It is hoped that the promising findings that are reported here will be validated in other studies. Certainly their algorithms should find a ready audience in insurers and hospitals willing to try them out. Finally, should we expect additional research to lead to improvement in the authors' algorithms? I believe the algorithms will prove difficult to improve upon; but perhaps we should not worry about this. At some point, however, the cost of trying to identify and correct quality problems in "minimally outlier" hospitals will exceed the benefits, particularly given alternative uses for the funds. Might we now be close the the "flat of the curve" in the development of such systems for identification of quality problems? This issue should be discussed much further in future studies.

Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?

OBJECTIVE: Incomplete coding of secondary diagnoses may bias assessments of patient risks of poor outcomes using administrative health care databases, most of which allow only five diagnoses. The Medicare program is expanding the number of possible diagnoses from five to nine, aiming to improve coding completeness. We examined the impact of having more diagnosis codes available on assessments of risk of death. DESIGN: We used 1988 computerized hospital discharge abstract data from California, which allow up to 25 diagnoses per discharge, to select a sample of hospitalized patients and assessed the relationship between the presence of 29 specific secondary diagnoses and the risk of in-hospital death. SETTING: Nonfederal acute-care hospitals in California. STUDY POPULATION: All patients at least 65 years of age who were hospitalized for stroke, pneumonia, acute myocardial infarction, or congestive heart failure in California in 1988 (N = 162,790). MAIN OUTCOME MEASURES: Relative risk of death for each specific secondary diagnosis. RESULTS: Many conditions that on a clinical basis would be expected to increase the risk of death, such as adult-onset diabetes mellitus, previous myocardial infarction, angina, and ventricular premature beats, were associated with a lower risk of in-hospital death. CONCLUSIONS: Bias against coding of chronic or comorbid conditions on the computerized discharge abstracts of patients who die best explains these results. Efforts to improve diagnosis coding completeness solely by increasing the number of available coding spaces may not succeed.

An epidemic of infection with Trichophyton tonsurans revealed in a 20-year survey of fungal infections in Chicago.

Trichophyton tonsurans has long been recognized as an important, but hitherto uncommon, cause of tinea capitis in the United States. Today it is known to be more common, but infection of the glabrous skin by this organism is still not well appreciated. In an epidemiologic study during the two decades from 1961 to 1980, 1,292 isolates of thirteen species of dermatophytes were obtained from patients at Cook County Hospital, Chicago. During the last 3 years of study, T. tonsurans accounted for 207 cases (96%) of tinea capitis and ninety-seven cases (75%) of tinea corporis. Ninety-five percent of cases of tinea capitis caused by T. tonsurans occurred in children (59% girls, 41% boys). By contrast, 62% of cases of tinea corporis caused by that organism occurred in adults. Substantially more women than men were affected in a ratio of nearly six to one. The majority of the women were between 15 and 29 years of age; about half of all had lesions on the arm. Over the past 20 years, T. tonsurans has emerged as a major cause of both tinea capitis and tinea corporis in Chicago. The disproportionate number of cases of tinea corporis in women of childbearing age may be due to their more frequent contact with infected children.