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Biomedical subjects

M H Ebell

Publications and source records attributed to M H Ebell.

At least 19 recordsLinked to original sources
PubMed1998

Survival after in-hospital cardiopulmonary resuscitation. A meta-analysis.

OBJECTIVE: To determine the rates of immediate survival and survival to discharge for adult patients undergoing in-hospital cardiopulmonary resuscitation, and to identify demographic and clinical variables associated with these outcomes. MEASUREMENTS AND MAIN RESULTS: The MEDLARS database of the National Library of Medicine was searched. In addition, the authors' extensive personal files and the bibliography of each identified study were searched for further studies. Two sets of inclusion criteria were used, minimal (any study of adults undergoing in-hospital cardiopulmonary resuscitation) and strict (included only patients from general ward and intensive care units, and adequately defined cardiopulmonary arrest and resuscitation). Each study was independently reviewed and abstracted in a nonblinded fashion by two reviewers. The data abstracted were compared, and any discrepancies were resolved by consensus discussion. For the subset of studies meeting the strict criteria, the overall rate of immediate survival was 40.7% and the rate of survival to discharge was 13.4%. The following variables were associated with failure to survive to discharge: sepsis on the day prior to resuscitation (odds ratio [OR] 31.3; 95% confidence interval [CI] 1.9, 515), metastatic cancer (OR 3.9; 95% CI 1.2, 12. 6), dementia (OR 3.1; 95% CI 1.1, 8.8), African-American race (OR 2. 8; 95% CI 1.4, 5.6), serum creatinine level at a cutpoint of 1.5 mg/dL (OR 2.2; 95% CI 1.2, 3.8), cancer (OR 1.9; 95% CI 1.2, 3.0), coronary artery disease (OR 0.55; 95% CI 0.4, 0.8), and location of resuscitation in the intensive care unit (OR 0.51; 95% CI 0.4, 0.8). CONCLUSIONS: When talking with patients, physicians can describe the overall likelihood of surviving discharge as 1 in 8 for patients who undergo cardiopulmonary resuscitation and 1 in 3 for patients who survive cardiopulmonary resuscitation.

Adult↗
PubMed1997

Test characteristics and decision rules.

We have demonstrated using several examples how different test characteristics can be used to assist clinicians in making better decisions for their patients. These probabilistic models may seem confusing and difficult to implement. Some general rules may help, such as SnNout and SpPin. Clinicians should know the test characteristics and decision rules for the acute problems they may face. For chronic conditions, advanced planning may be helpful. Electronic medical record systems may be able to incorporate these at the user interface. The improvements in hand-held computers may bring clinical decision-support systems directly to the point of service. We may also begin to see laboratories report test characteristics for important conditions as likelihood ratios (we already see estimates of the risk of heart disease corresponding to different lipid ratios). We also suspect that the medical literature will report likelihood ratios more frequently. As practice networks develop more sophisticated disease-tracking mechanisms, clinicians will be able to obtain estimates of disease prevalence more appropriate to their practice. Ultimately, for physicians to make better decisions, appropriate data are needed, including accurate estimates of test characteristics and of disease probability.

Clinical Laboratory Techniques↗
PubMed1997

Evaluation of suspected urinary tract infection in ambulatory women: a cost-utility analysis of office-based strategies.

BACKGROUND: The purpose of this study was to determine the most cost-effective strategy for managing suspected urinary tract infections in otherwise healthy adult women presenting to their primary care physician with dysuria and no symptoms or signs of pyelonephritis. Several office-based management strategies are considered: empiric therapy, use of dipstick analysis, use of complete urinalysis, and several strategies using office or laboratory cultures. METHODS: We constructed a decision tree using model probabilities obtained from the literature. Where published probabilities were unavailable, we used extensive sensitivity analyses. Utilities were obtained from the Index of Well-Being. We obtained costs by surveying hospitals, physicians, and pharmacies. RESULTS: The most cost-effective strategy is to treat empirically ($71.52 per quality-adjusted life month, QALM). When the cost of antibiotics exceeds $74.50 or if the prior probability of having a UTI is under 0.30, then treatment guided by the results of a complete urinalysis is preferred. While it was the preferred strategy, other strategies (complete urinalysis, culture and treat, and dipstick testing only) were associated with greater utility. The marginal cost-effectiveness of these strategies compared with empiric therapy ranged from $2964 to $48,460 per additional QALM. CONCLUSIONS: The preferred strategy of empiric therapy is robust over a wide range of sensitivity analyses. While empiric therapy is associated with the best cost-utility ratio, doing a culture yields the greatest utility at greater incremental cost per QALM. Many primary care physicians already treat UTIs empirically with antibiotics. This study confirms that empiric therapy, while frowned upon by some, is a cost-effective strategy. Other strategies may be considered, but at greater marginal cost. Ultimately these findings need to be confirmed in clinical trials.

Adolescent↗
PubMed1997

Evaluation of the dyspeptic patient: a cost-utility study.

BACKGROUND: Traditionally, patients presenting with uncomplicated dyspepsia have been managed using empiric antisecretory therapy, followed by endoscopy in the event of persistent symptoms or complication. Since Helicobacter pylori is now accepted as an important and potentially reversible cause of ulcer disease, it is important to reevaluate the management of dyspepsia. The goal of this study is to evaluate seven outpatient strategies for the management of dyspeptic patients using a cost-utility analysis. METHODS: The study design was that of a cost-utility analysis. The model assumes that an adult patient with signs of dyspepsia but no signs of complication presents to the outpatient office of a primary care physician. Seven strategies are modeled: empiric antisecretory therapy; empiric H pylori eradication using oral omeprazole (20 mg [corrected] twice daily), clarithromycin (500 mg twice daily), and amoxicillin (1000 mg twice daily); use of either upper endoscopy, an upper gastrointestinal barium study (an upper GI), or the serum titer for H pylori as a diagnostic test to identify patients for H pylori eradication; or use of an initial diagnostic test followed by the serum titer for H pylori. The primary outcome was the cost per quality-adjusted life year (QALY) for each strategy for a 1-year period from presentation; secondary outcomes included the probability of symptomatic ulcer recurrence, cost per ulcer cure, and mortality. RESULTS: Three strategies were similarly cost-effective: empiric H pylori eradication ($1198 per QALY), use of a serum H pylori titer as an initial diagnostic test ($1214 per QALY), and empiric antisecretory therapy ($1288 per QALY). Empiric antisecretory therapy, however, was associated with significantly more symptomatic ulcer recurrences and deaths than any other strategy. CONCLUSIONS: This cost-utility analysis suggests that two strategies are reasonable for patients presenting with dyspepsia: (1) empiric H pylori eradication and (2) use of a serum H pylori titer to identify patients who might benefit from H pylori eradication. The latter strategy may be preferable because it is less likely to lead to antibiotic resistance. Strategies utilizing an upper GI or upper endoscopy (either with or without serum H pylori titer) or empiric antisecretory therapy do not improve outcomes and are associated with greater cost, morbidity, and/or mortality.

Adult↗
PubMed1997

Family physicians' preferences for computerized decision-support hardware and software.

BACKGROUND: While computers are now widely used by family physicians for billing and patient registration purposes, their use as decision-support tools is still quite limited. The purpose of this study was to determine the current use of computer hardware and software by family physicians, and the characteristics these physicians desire in computerized decision-support hardware and software. METHODS: A cross-sectional survey of a random sample of 250 Michigan family physicians was undertaken in mid-1995. These physicians were asked about their current use of a variety of computer hardware and software. They were also asked to rate the value of different kinds of decision-support information potentially available by computer. The survey instrument also gathered the family physicians' preferences for design factors (both hardware and software), such as the size of a computer, the time needed to access information, and the frequency of updates. RESULTS: Word processing on desktop computers and hospital information systems are the most widely used computer applications by family physicians. Physicians are most interested in computer-based information on drugs, storage and generation of patient education materials, and accessing treatment recommendations. Most feel that semiannual or annual updates of information are adequate, and would like a uniform interface. A high percentage of physicians (84.5% of all physicians and 94.1% of younger physicians) stated that they would consider carrying a handheld computer. CONCLUSIONS: There is significant interest in several types of clinical decision-support software. Based on the results of this study, such software should have following characteristics: (1) be available for handheld as well as networked and desktop computers, (2) include drug information (particularly warnings, interactions, and side effects), (3) include overviews of treatment recommendations, (4) include patient education materials, and (5) have a uniform user interface and be updated at least annually.

Adult↗
PubMed1996

The inability of physicians to predict the outcome of in-hospital resuscitation.

OBJECTIVE: To measure the accuracy, reliability, and discrimination of physicians' predictions of the outcome of in-hospital cardiopulmonary resuscitation (CPR), using a large series of detailed clinical vignettes of patients with known outcomes. DESIGN: Faculty and resident physicians at three university-affiliated generalist training programs were given one-page summaries of admission data for patients who later underwent in-hospital CPR. These summaries included all pre-arrest variables known to be related to the outcome of CPR. Physicians were asked to estimate the probability that patients would survive the resuscitation long enough to be stabilized, and the probability of survival to discharge. SETTING: Patient cases were derived from a consecutive series of patients undergoing CPR at two urban teaching hospitals in Detroit, Michigan. PARTICIPANTS: Faculty members and residents at a university-based department of internal medicine and two university-based departments of family medicine were surveyed. INTERVENTIONS: Accuracy of the physician predictions was assessed by comparing the mean predicted probability of survival with the percentage of patients who actually survived. The reliability of probability estimates of survival was evaluated by assessing the numerical proximity of the estimates to the actual outcome of the resuscitative effort. The ability to discriminate between survivors and nonsurvivors was measured by comparing the mean predicted probability of survival for those patients who survived CPR with that for those who did not, and by stratifying physician predictions and measuring the area under a receiver operating characteristic (ROC) curve. MEASUREMENTS AND MAIN RESULTS. Physicians (n = 51) made a total of 713 estimates, and showed poor accuracy, reliability, and discrimination in predicting the outcome of in-hospital CPR. The mean predicted probability of survival to discharge did not differ between patients who actually survived to discharge and those who did not (29.5% vs 26.4%, z = 0.35, p = .73). Similarly, the mean predicted probabilities of surviving resuscitation were the same for patients who actually survived long enough to be stabilized and those who did not (37.8% vs 39.9%, z = 0.55, p = .58). Accounting for type of physician and institution by analysis of variance did not change this finding. The area under the ROC curve for the prediction of arrest survival was 0.476, which is not significantly different from 0.5, and is consistent with an ability to discriminate between survivors and nonsurvivors that is no better than random choice. CONCLUSIONS: Physicians were no better at identifying patients who would survive resuscitation than would be expected by chance alone. Further work is needed to establish which variables are used by physicians in the decision-making process, and to design educational interventions that will make physicians more accurate prognosticators.

Adult↗
PubMed1995

When everything is too much. Quantitative approaches to the issue of futility.

Although physicians agree broadly that there is no obligation to provide futile care, there is no consensus, of which I am aware, regarding a definition of futility. Two quantitative approaches to determining futility are proposed, neither of which involves financial costs. First, based on the number of consecutive failures of an intervention, it is possible to calculate the probability of success for the next attempted treatment. The second method uses quality-adjusted life years to balance the burden and benefit of a specific treatment and to determine the probability of success beneath which the treatment is futile. When applied to the use of in-hospital cardiopulmonary resuscitation in patients with metastatic cancer, both of these methods confirm the futility of this intervention.

Cardiopulmonary Resuscitation↗
PubMed1995

Hand-held computers for family physicians.

Hand-held computers such as the Apple Newton MessagePad, HP 200LX, Psion 3a, and Franklin DBS-2 are now powerful enough to be useful to family physicians in their care of patients. Each fits in a laboratory coat pocket, weighs a pound or less, costs less than $700, turns on instantly, and has excellent battery life. A wide variety of software, including computerized medical records, medical calculators, and medical references, is available.

Family Practice↗
PubMed1995

Using decision rules in primary care practice.

Decision rules help physicians make more accurate predictions about diagnosis, prognosis and response to treatment. In this article, guidelines for finding decision rules are outlined. A mnemonic is presented (Pre-Dic-TiVe) that assists physicians in evaluation of decision rules for clinical practice. A survey of decision rules for primary care physicians is also presented.

Decision Support Techniques↗