Annals of internal medicine
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Administrative data result from administering health care delivery, enrolling members into health insurance plans, and reimbursing for services. The primary producers of administrative data are the federal government, state governments, and private health care insurers. Although the clinical content of administrative data includes only the demographic characteristics and diagnoses of patients and codes for procedures, these data are often used to evaluate the quality of health care. ⋯ In addition, questions about the accuracy and completeness of administrative data abound. Current administrative data are probably most useful as screening tools that highlight areas in which quality should be investigated in greater depth. The growing availability of electronic clinical information will change the nature of administrative data in the future, enhancing opportunities for quality measurement.
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The Institute of Medicine defines health care quality as increasing "the likelihood of desired health outcomes" using "services ... consistent with current professional knowledge." This definition implies that quality measures can be based on either achieving health care outcomes or completing processes that experts agree have been shown by scientific evidence to improve outcomes. Process-based measures are especially suitable when the user needs to know how to improve quality, when provider comparisons show equivalent outcomes but all providers should improve processes, when measures are needed to evaluate health care that is intended to improve long-term outcomes, or when the contribution of individual providers (especially providers who have a small number of cases) needs to be defined. However, many different process-based measures are needed to comprehensively assess quality, and many process-based measures require detailed clinical data currently found only in medical records. ⋯ The merging of existing inpatient and outpatient databases with pharmacy and laboratory databases is an important step toward obtaining data that link all patient admissions, appointments, diagnostic procedures, and prescriptions with diagnoses and test results. Other data that are valuable for process-based measures must still be obtained by abstracting data from records, including clinical findings, patient preferences, and medical and family history. In the future, such data may be added to large databases to create computerized medical records.
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Current methods for detecting mediastinal lymph node involvement with non-small-cell lung cancer can be inaccurate and are often invasive and expensive. ⋯ Endoscopic ultrasonography alone or with fine-needle aspiration biopsy adds useful diagnostic information in determining metastasis to posterior mediastinal or subcarinal lymph nodes in patients with non-small-cell lung-cancer. These procedures are especially helpful in the preoperative evaluation of patients with suspicious contralateral mediastinal or "bulky" subcarinal nodes.
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Treatment preferences established before life-threatening Illness occurs may differ from actual decisions because of changes in preferences or poor understanding of the link between prospective preferences and outcomes. ⋯ Prospective life-sustaining treatment preferences show high convergent validity. For most persons, treatment preferences are grounded in a consistent belief system. Concordance and discordance between treatment preferences and health state ratings offer clinicians the opportunity to explore patients' values and reasoning.
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After thoroughly searching the potentially relevant literature for a systematic review, reviewers face the sequential tasks of selecting studies for inclusion and appraising these studies. Methodical, impartial, and reliable strategies are necessary for these two tasks because systematic reviews are retrospective exercises and are therefore prone to both bias and random error. To plan for study selection, reviewers begin with a focused clinical question and choose selection criteria that reflect this question. ⋯ After choosing methods for evaluating study quality, reviewers construct customized appraisal forms and an explicit protocol for the actual evaluation. Some of the techniques commonly used to minimize the potential for error in study appraisal include duplicate, independent examination; blinding to study results and other identifying features of each article; and correspondence with study authors to clarify issues. Ultimately, primary studies should be selected, appraised, and reported in sufficient detail to allow readers to judge the applicability of the review to clinical practice and to clarify the strength of the inferences that can be drawn from the review.