{"title":"社会保障残障保险项目的结果差异:初级诊断的作用。","authors":"Javier Meseguer","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Based on the adjudicative process, the author classifies claimant-level data over an 8-year period (1997-2004) into four mutually exclusive categories: (1) initial allowances, (2) initial denials not appealed, (3) final allowances, and (4) final denials. The ability to predict those outcomes is explored within a multilevel modeling framework, with applicants clustered by state and primary diagnosis code. Variance decomposition suggests that medical diagnoses play a substantial role in explaining individual-level variation in initial allowances. Moreover, there is statistically significant high positive correlation between the predictions of an initial allowance and a final allowance across the diagnoses. This finding suggests that the ordinal ranking of impairments between these two adjudicative outcomes is widely preserved. In other words, impairments with a higher expectation of an initial allowance also tend to have a higher expectation of a final allowance.</p>","PeriodicalId":39542,"journal":{"name":"Social Security Bulletin","volume":"73 2","pages":"39-75"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Outcome variation in the social security disability insurance program: the role of primary diagnoses.\",\"authors\":\"Javier Meseguer\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Based on the adjudicative process, the author classifies claimant-level data over an 8-year period (1997-2004) into four mutually exclusive categories: (1) initial allowances, (2) initial denials not appealed, (3) final allowances, and (4) final denials. The ability to predict those outcomes is explored within a multilevel modeling framework, with applicants clustered by state and primary diagnosis code. Variance decomposition suggests that medical diagnoses play a substantial role in explaining individual-level variation in initial allowances. Moreover, there is statistically significant high positive correlation between the predictions of an initial allowance and a final allowance across the diagnoses. This finding suggests that the ordinal ranking of impairments between these two adjudicative outcomes is widely preserved. In other words, impairments with a higher expectation of an initial allowance also tend to have a higher expectation of a final allowance.</p>\",\"PeriodicalId\":39542,\"journal\":{\"name\":\"Social Security Bulletin\",\"volume\":\"73 2\",\"pages\":\"39-75\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social Security Bulletin\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Security Bulletin","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Outcome variation in the social security disability insurance program: the role of primary diagnoses.
Based on the adjudicative process, the author classifies claimant-level data over an 8-year period (1997-2004) into four mutually exclusive categories: (1) initial allowances, (2) initial denials not appealed, (3) final allowances, and (4) final denials. The ability to predict those outcomes is explored within a multilevel modeling framework, with applicants clustered by state and primary diagnosis code. Variance decomposition suggests that medical diagnoses play a substantial role in explaining individual-level variation in initial allowances. Moreover, there is statistically significant high positive correlation between the predictions of an initial allowance and a final allowance across the diagnoses. This finding suggests that the ordinal ranking of impairments between these two adjudicative outcomes is widely preserved. In other words, impairments with a higher expectation of an initial allowance also tend to have a higher expectation of a final allowance.