Cathleen Mooney

Why Do Physicians Vary So Widely in Their Referral Rates

AbstractOBJECTIVE: To determine which physician practice and psychological factors contribute to observed variation in primary care physicians’ referral rates. DESIGN: Cross-sectional questionnaire-based survey and analysis of claims database. SETTING: A large managed care organization in the Rochester, NY, metropolitan area. PARTICIPANTS: Internists and family physicians. MEASUREMENTS AND MAIN RESULTS: Patient referral status (referred or not) was derived from the 1995 claims database of the managed care organization. The claims data were also used to generate a predicted risk of referral based on patient age, gender, and case mix. A physician survey completed by a sample of 182 of the physicians (66% of those eligible) included items on their practice and validated psychological scales on anxiety from uncertainty, risk aversiveness, fear of malpractice, satisfaction with practice, autonomous and controlled motivation for referrals and test ordering, and psychosocial beliefs. The relation between the risk of referral and the physician practice and psychological factors was examined using logistic regression. After adjustment for predicted risk of referral (case mix), patients were more likely to be referred if their physician was female, had more years in practice, was an internist, and used a narrower range of diagnoses (a higher Herfindahl index, also derived from the claims data). Of the psychological factors, only greater psychosocial orientation and malpractice fear was associated with greater likelihood of referral. When the physician practice factors were excluded from the analysis, risk aversion was positively associated with referral likelihood. CONCLUSIONS: Most of the explainable variation in referral likelihood was accounted for by patient and physician practice factors like case mix, physician gender, years in practice, speciality, and the Herfindahl index. Relatively little variation was explained by any of the examined physician psychological factors.

The Cost-Effectiveness of Magnetic Resonance Imaging for Patients with Equivocal Neurological Symptoms

OBJECTIVE To determine the incremental cost-effectiveness of magnetic resonance imaging (MRI) and computed tomography (CT) in young adults presenting with equivocal neurological signs and symptoms. DESIGNS AND METHODS A decision analysis of long-term survival using accuracy data from a diagnostic technology assessment of MRI and CT in patients with suspected multiple sclerosis, information from the medical literature, and clinical assumptions. MAIN RESULTS In the baseline analysis, at 30% likelihood of an underlying neurologic disease, MRI use has an incremental cost of

Invited Article: Conflicts of interest for authors of American Academy of Neurology clinical practice guidelines

101,670 for each additional quality-adjusted life-year saved compared with

Correction and update on 'priority setting in medical technology assessment'.

20,290 for CT use. As the probability of disease increases, further MRI use becomes a cost-effective alternative costing

Targeting Assessments of Magnetic Resonance Imaging in suspected Multiple sclerosis

30,000 for each quality-adjusted life-year saved. If a negative MRI result provides reassurance, the incremental costs of immediate MRI use decreases and falls below

Has competition lowered hospital prices

25,000 for each quality-adjusted life-year saved no matter the likelihood of disease. CONCLUSIONS For most individuals with neurological symptoms or signs, CT imaging is cost-effective while MR imaging is not. The cost-effectiveness of MRI use, however, improves as the likelihood of an underlying neurological disease increases. For selected patients who highly value diagnostic information, MRI is a reasonable and cost-effective use of medical resources when even the likelihood of disease is quite low (5%).

Has price competition changed hospital revenues and expenses in New York

Background: Clinical practice guidelines (CPGs) shape clinical care worldwide but are prone to potential error and bias due to conflicts of interest (COI). Objective: To explore the extent and scope of American Academy of Neurology (AAN) guideline author reported COI and implications for management; and to review process of AAN guideline COI management to highlight challenges, establish comparative benchmarks, and identify areas to be improved. Methods: Authors of AAN clinical practice guidelines with an active membership panel completed a COI reporting form. Authors were asked to report current interests including the 1 year prior to the date of completing the form. Interests include personal income relationships (consulting, speaker’s bureaus, advisory boards), equity (stocks/stock options), patent/royalties, research, clinical practice, fiduciary interest in a company, and expert testimony. Comparisons were made between the two committees that oversee CPG development at the AAN: the Quality Standards Subcommittee (QSS) and the Therapeutics and Technology Assessment (TTA) Subcommittee. Results: There were 50 CPG with an average of 8.5 authors per CPG. There were a total of 425 available authors, 351 of whom completed a COI reporting form (83% response rate). Forty-six of the 50 guidelines had at least one author with a COI. The most commonly reported COIs were research-related (45% of authors), clinical practice–related (42%), and personal income relationships (33%). Authors of QSS guidelines were more likely to have personal income COIs with pharmaceutical and medical device companies (39% vs 24%, p < 0.01), whereas authors of TTA guidelines were more likely to have clinical practice–related COIs (50% vs 38%, p < 0.05). A minority of authors had individual COIs exceeding >

The prostate: decreasing cost-effectiveness of biopsy with advancing age.

25,000 or had multiple interests (>10) that overlapped with content of the guidelines. Conclusion: Conflicts of interest are common for authors of American Academy of Neurology clinical practice guidelines across many domains of personal and professional interests. More research is needed to improve the methods to identify and quantify the types of conflicts and their potential biasing effects on selecting guideline topics, grading research evidence, and formulating practice recommendations.

The Cost Effectiveness of Implantable Cardioverter-Defibrillators: Results From the Multicenter Automatic Defibrillator Implantation Trial (MADIT)-II

assist in the process of choosing where to use research resources best. While the index proposed by Phelps and Parente is not definitive, it does provide a reproducible and objective measure of the potential gains from research in technology and medical practice assessment. In the actual implementation of the methods proposed in Phelps and Parente, we have found two errors, one of which affects only a few of the categories reported. The other affects calculations on the priority ranking for every procedure reported, but almost invariably, in an unimportant way. The purpose of this note is to clarify the nature of these errors, provide corrected tables for priority setting (which, with only a few exceptions that we will note, provide the same priority setting advice as did the original work), and to reaffirm the basic integrity of the previously published results.

Is travel distance a barrier to veterans' use of VA hospitals for medical surgical care?

Decision-analytic methods can be valuable for targeting research in technology assessment. They can indicate whether further evaluation of a technology is warranted, and if so, which variables are key determinants of its clinical utility and cost-effectiveness. This approach was tested on a salient issue—whether magnetic resonance imaging (MR) should be used in evaluating patients with mild neurologic symptoms who might have multiple sclerosis (MS). The authors developed a decision-analytic model to assess the expected utility and costs associated with immediately using MR in this situation, compared with waiting for further symptoms to emerge before testing. Sensitivity analyses demonstrated that priorities for technology assessment research include estimating the value of information to patients in resolving uncertainty, evaluating the impact on patients of being labeled with a diagnosis of MS, and measuring the test characteristics of MR. Key words: cost-benefit analysis; multiple sclerosis; magnetic resonance imaging; decision analysis; Markov models. (Med Decis Making 1990;10:77-94)