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<p><strong>You Are Here:</strong> <span class="crumb_link"><a href="/" class="crumb_link">AHRQ Archive Home</a> &gt; <a href="/research/resarch.htm" class="crumb_link"><em>Research Activities</em> Archive</a> &gt; <a href="." class="crumb_link">May 1999</a>
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<td><h1><a name="h1" id="h1"></a>Research Briefs </h1>
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<p>This information is for reference purposes only. It was current when produced and may now be outdated. Archive material is no longer maintained, and some links may not work. Persons with disabilities having difficulty accessing this information should contact us at: <a href="https://info.ahrq.gov/">https://info.ahrq.gov</a>. Let us know the nature of the problem, the Web address of what you want, and your contact information. </p>
<p>Please go to <a href="https://www.ahrq.gov/">www.ahrq.gov</a> for current information.</p></div>
<a name="head1"></a><p><strong>Davidson, P.L., Cunningham, W.E., Nakazono, T.T., and Anderson, R.M. (1999, March). "Evaluating the effect of usual source of dental care on access to dental services: Comparisons among diverse populations." (AHCPR grant HS07084). <em>Medical Care Research and Review</em> 56(1), pp. 74-93.</strong></p>
<p>These investigators used a behavioral model of health service use to test the effect of a usual source of dental care (USDC) on use of dental services by people in Baltimore, San Antonio, and regions served by the Indian Health Service (IHS). USDC was the strongest and most consistent predictor of a recent dental visit. Adults having a USDC in San Antonio were 10 times as likely and adults in Baltimore with a USDC were 16 times as likely to have made a visit to the dentist in the past year as people without a USDC. American Indians with a USDC were two times more likely to report a dental visit as those without a USDC, even though there were major problems with access to dental care in the IHS system. Oral pain or discomfort increased the probability of visiting a dentist for adults in every location. Race/ethnicity, lower education (9 to 11 years), and total tooth loss reduced the likelihood of a dental visit in at least two research locations. Predisposing oral health beliefs also influenced dental visits. Adults who believed in the importance of oral health, were not afraid of oral pain, and were not too busy to visit a dentist were significantly more likely to have visited a dentist in the past year. Household income and dental insurance benefits were not significant predictors of a dental visit.</p>
<a name="head2"></a><p><strong>Hripcsak, G., Kuperman, G.J., Friedman, C., and Heitjan, D.F. (1999, March). "A reliability study for evaluating information extraction from radiology reports." (AHCPR grant HS08927). <em>Journal of the American Medical Informatics Association</em> 6(2), pp. 143-150.</strong></p>
<p>Evaluators often compare the output of a knowledge-based system to a set of correct answers, known as the reference standard. In this study, the researchers use the ability of physicians to draw conclusions from radiology reports to estimate the number of expert raters needed to generate a reliable reference standard. Twenty-four physician raters from two sites and two specialties judged whether clinical conditions were present based on reading chest radiograph reports. In these evaluations, physician raters were able to judge very reliably the presence of clinical conditions based on text reports. One to two raters were needed to achieve a reliability of 0.70, and six raters, on average, were required to achieve a reliability of 0.95. The researchers conclude that six raters would be needed to create a reference standard sufficient to assess an information system on a case-by-case basis.</p>
<a name="head3"></a><p><strong>Iezzoni, L.I., Mackiernan, Y.D., Cahalane, M.J., and others (1999, April). "Screening inpatient quality using post-discharge events." (AHCPR grant HS08248). <em>Medical Care</em> 37(4), pp. 384-398.</strong></p>
<p>Increasingly shorter hospital stays hamper efforts to detect and definitively treat complications of hospital care. Patients leave before some complications are identified. These researchers have developed a computerized method to screen for hospital complications using diagnosis and procedure codes from Medicare claims to define 50 complication screens. The method, the Complications Screening Program for Outpatient Data (CSP-O) algorithm, examined outpatient, physician office, home health agency, and hospice claims within 90 days following discharge of 739,248 Medicare patients from 515 hospitals nationwide in 1994. The 33 general screens (for all adult, acute, medical or surgical hospitalizations) flagged 13.6 percent of all cases. However, only 1.8 percent of procedural cases were flagged by the 17 procedural screens. The researchers conclude that while several CSP-O findings have construct validity, limitations of claims data raise concerns.</p>
<a name="head4"></a><p><strong>Murray, M.D., Loos, B., Tu, W., and others (1999, February). "Work patterns of ambulatory care pharmacists with access to electronic guideline-based treatment suggestions." (AHCPR grant HS07763). <em>American Journal of Health-System Pharmacology</em> 56, pp. 225-232.</strong></p>
<p>Improvements in prescription processing, increased access to patient-specific clinical data, and integration of prescription data and patient-specific clinical data have changed the work of pharmacists. Yet in many health care settings, it has been difficult for pharmacists to shift roles from dispensers of medications to counselors of patients and providers of advice and information to physicians. However, this study shows that an electronic display of guideline-based, patient-specific treatment suggestions at the time of drug dispensing had a significant positive impact on pharmacist work patterns. A total of 28 pharmacists at a hospital-based outpatient pharmacy were randomly assigned either to receive or not receive electronic treatment suggestions. From 9 to 19 months later, pharmacists who received the suggestions spent significantly more of their time discussing information and advising, informing, and solving problems as pharmacists in the control group. They spent significantly less of their time checking and filling prescriptions.</p>
<a name="head5"></a><p><strong>Schadow, G., McDonald, C.J., Suico, J.G., and others (1999, March). "Units of measure in clinical information systems." (AHCPR grant HS08750). <em>Journal of the American Medical Informatics Association</em> 6(2), pp. 151-162.</strong></p>
<p>Health care workers typically leave out units of measure in medical chart notes (for example, an infant's weight may be entered as 5 rather than 5 pounds or 5 kilograms), and these units often are not standardized in computer systems. Within a single care institution, where most measurements tend to be reported consistently in the same units, users correctly infer the units when they are omitted. Nonetheless, such omissions could lead to mistakes when patients move between care facilities. These authors surveyed existing standard codes for units of measures, such as ISO 2955, ANSI X3.50, and Health Level 7s ISO+. Because these standards specify only the character representation of units, the authors developed a semantic model for units based on dimensional analysis. Through this model, conversion between units and calculations with dimensioned quantities become as simple as calculating with numbers.</p>
<a name="head6"></a><p><strong>Schmid, C.H. (1999). "Exploring heterogeneity in randomized trials via meta-analysis." (AHCPR grant HS08532). <em>Drug Information Journal</em> 33, pp. 211-224.</strong></p>
<p>Heterogeneity of treatment effects need not be viewed as an argument against meta-analysis of clinical trials. When it does not arise because of inadequate design or incomplete publication of results, treatment heterogeneity should be seen as an opportunity to learn about variations in treatment effectiveness, suggest these researchers. Rather than computing a single summary estimate of a series of trials, it may be more informative to explore the effects that different study characteristics may have on treatment efficacy. The authors note that regression analysis offers a tool for these analyses. They outline and apply hierarchical Bayesian models for this purpose and present two examples of meta-regression using summary data. They conclude that investigators should search for the causes of heterogeneity related to patient characteristics and treatment protocols to determine when treatment is most beneficial. </p>
<p>Select <a href="/research/">AHCPR research programs</a> to access more information online.</p>
<p class="size2"><a href=".">Return to Contents</a></p>
<p class="size2"><em>AHCPR Publication No. 99-0033</em></p>
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<p class="size2"><em>Research Activities</em> newsletter. May 1999, No. 226. Agency for Health Care Policy and Research, Rockville, MD. https://www.ahrq.gov/research/may99/</p>
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