{"title":"疾病管理项目评估中的样本量:证明统计上显著减少入院人数的挑战。","authors":"Ariel Linden","doi":"10.1089/dis.2008.1120019","DOIUrl":null,"url":null,"abstract":"<p><p>Prior to implementing a disease management (DM) strategy, a needs assessment should be conducted to determine whether sufficient opportunity exists for an intervention to be successful in the given population. A central component of this assessment is a sample size analysis to determine whether the population is of sufficient size to allow the expected program effect to achieve statistical significance. This paper discusses the parameters that comprise the generic sample size formula for independent samples and their interrelationships, followed by modifications for the DM setting. In addition, a table is provided with sample size estimates for various effect sizes. Examples are described in detail along with strategies for overcoming common barriers. Ultimately, conducting these calculations up front will help set appropriate expectations about the ability to demonstrate the success of the intervention.</p>","PeriodicalId":51235,"journal":{"name":"Disease Management : Dm","volume":"11 2","pages":"95-101"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1089/dis.2008.1120019","citationCount":"5","resultStr":"{\"title\":\"Sample size in disease management program evaluation: the challenge of demonstrating a statistically significant reduction in admissions.\",\"authors\":\"Ariel Linden\",\"doi\":\"10.1089/dis.2008.1120019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Prior to implementing a disease management (DM) strategy, a needs assessment should be conducted to determine whether sufficient opportunity exists for an intervention to be successful in the given population. A central component of this assessment is a sample size analysis to determine whether the population is of sufficient size to allow the expected program effect to achieve statistical significance. This paper discusses the parameters that comprise the generic sample size formula for independent samples and their interrelationships, followed by modifications for the DM setting. In addition, a table is provided with sample size estimates for various effect sizes. Examples are described in detail along with strategies for overcoming common barriers. Ultimately, conducting these calculations up front will help set appropriate expectations about the ability to demonstrate the success of the intervention.</p>\",\"PeriodicalId\":51235,\"journal\":{\"name\":\"Disease Management : Dm\",\"volume\":\"11 2\",\"pages\":\"95-101\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1089/dis.2008.1120019\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Disease Management : Dm\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1089/dis.2008.1120019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Disease Management : Dm","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/dis.2008.1120019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sample size in disease management program evaluation: the challenge of demonstrating a statistically significant reduction in admissions.
Prior to implementing a disease management (DM) strategy, a needs assessment should be conducted to determine whether sufficient opportunity exists for an intervention to be successful in the given population. A central component of this assessment is a sample size analysis to determine whether the population is of sufficient size to allow the expected program effect to achieve statistical significance. This paper discusses the parameters that comprise the generic sample size formula for independent samples and their interrelationships, followed by modifications for the DM setting. In addition, a table is provided with sample size estimates for various effect sizes. Examples are described in detail along with strategies for overcoming common barriers. Ultimately, conducting these calculations up front will help set appropriate expectations about the ability to demonstrate the success of the intervention.