• Title/Summary/Keyword: Academic Medical Center

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Developing a Best-Evidence Pre-employment Medical Examination: An Example from the Construction Industry

  • Gouttebarge, Vincent;van der Molen, Henk F.;Frings-Dresen, Monique H.W.;Sluiter, Judith K.
    • Safety and Health at Work
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    • v.5 no.3
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    • pp.165-167
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    • 2014
  • The Dutch construction industry has introduced a compulsory preemployment medical examination (PE-ME). Best-evidence contents related to specific job demands are, however, lacking and need to be gathered. After the identification of job demands and health problems in the construction industry (systematic literature search and expert meeting), specific job demands and related requirements were defined and instruments proposed. Finally, a work ability assessment was linked to the instruments' outcomes, resulting in the modular character of the developed PE-ME. Twenty-two specific job demands for all Dutch construction jobs were identified, including kneeling/squatting, working under time pressure, and exposure to hazardous substances. The next step was proposing self-report questions, screening questionnaires, clinical tests, and/or performance-based tests, leading to a work ability judgment. "Lifting/carrying" is described as an example. The new modular PE-ME enables a job-specific assessment of work ability to be made for more than 100 jobs in the Dutch construction industry.

ROTATOR CUFF TEAR ARTHROPATHY

  • Park jin-Young;Marra Guido;Pollock Roger G.;Flatow Evan L.;Bigliani Louis U.
    • The Academic Congress of Korean Shoulder and Elbow Society
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    • 1999.03a
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    • pp.57-57
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    • 1999
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The Association between Weather Conditions and the Number of No-Show Patients at an Academic Medical Center (기상변화와 일개 대학병원 외래환자 예약부도와의 관련성)

  • Park, Il-Soon;Jung, Sang-Jin;Shin, Hwan-Ho
    • The Korean Journal of Health Service Management
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    • v.11 no.4
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    • pp.41-51
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    • 2017
  • Objectives : This study investigates the association between weather conditions and the rate of no-shows at an academic medical center. Methods : Electronic data regarding medical appointments atover the course ofone academic year (2016.03~2017.02) were used for analysis. Characteristics of weather conditions and the daily number of no-shows were compared by Chi-square test. A logistic regression was run to determine if certain aspects of weather affected the rate of no-shows. Results : The results reveal an overall no-show rate of 6.8% that appears to vary in accordance with specific weather conditions. Lower average temperatures, in particular, corresponded with a higher rate of no-show patients. This may indicate that o-show rates in autumn and winter can be expected to exceed those during spring. Conclusions : This study investigates the association between no-show patients and weather conditions, and offers suggestions for augmenting this loss. One recommendation is to begin conducting investigations nationwide in order to provide more useful information.