估算医院层面的差异对住院康复机构与专业护理机构的使用对中风患者个体的影响》(Estimating the Impact of Hospital-Level Variation on the Use of Inpatient Rehabilitation Facilities Versus Skilled Nursing Facilities on Individual Patients with Stroke.
Kent P Simmonds, James Burke, Alan Kozlowski, Michael Andary, Zhehui Luo, Mathew J Reeves
{"title":"估算医院层面的差异对住院康复机构与专业护理机构的使用对中风患者个体的影响》(Estimating the Impact of Hospital-Level Variation on the Use of Inpatient Rehabilitation Facilities Versus Skilled Nursing Facilities on Individual Patients with Stroke.","authors":"Kent P Simmonds, James Burke, Alan Kozlowski, Michael Andary, Zhehui Luo, Mathew J Reeves","doi":"10.1161/CIRCOUTCOMES.123.010636","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There is substantial hospital-level variation in the use of Inpatient Rehabilitation Facilities (IRFs) versus Skilled Nursing Facilities (SNFs) among patients with stroke, which is poorly understood. Our objective was to quantify the net effect of the admitting hospital on the probability of receiving IRF or SNF care for individual patients with stroke.</p><p><strong>Methods: </strong>Using Medicare claims data (2011-2013), a cohort of patients with acute stroke discharged to an IRF or SNF was identified. We generated 2 multivariable logistic regression models. Model 1 predicted IRF admission (versus SNF) using only patient-level factors, whereas model 2 added a hospital random effect term to quantify the hospital effect. The statistical significance and direction of the random effect terms were used to categorize hospitals as being either IRF-favoring, SNF-favoring, or neutral with respect to their discharge patterns. The hospital's impact on individual patient's probability of IRF discharge was estimated by taking the change in individual predicted probabilities (change in individual predicted probability) between the 2 models. Hospital-level effects were categorized as small (<10%), moderate (10%-19%), or large (≥20%) depending on change in individual predicted probability.</p><p><strong>Results: </strong>The cohort included 135 415 patients (average age, 81.5 [SD=8.0] years, 61% female, 91% ischemic stroke) who were discharged from 1816 acute care hospitals to IRFs (n=66 548) or SNFs (n=68 867). Half of hospitals were classified as being either IRF-favoring (n=461, 25.4%) or SNF-favoring (n=485, 26.7%) with the remainder (n=870, 47.9%) considered neutral. Overall, just over half (n=73 428) of patients were treated at hospitals that had moderate or large independent effects on discharge settings. Hospital effects for neutral hospitals were small (ie, change in individual predicted probability <10%) for most patients (72.5%). However, hospital effects were moderate or large for 78.8% and 84.6% of patients treated at IRF- or SNF-favoring hospitals, respectively.</p><p><strong>Conclusions: </strong>For most patients with stroke, the admitting hospital meaningfully changed the type of rehabilitation care that they received.</p>","PeriodicalId":49221,"journal":{"name":"Circulation-Cardiovascular Quality and Outcomes","volume":" ","pages":"e010636"},"PeriodicalIF":6.2000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating the Impact of Hospital-Level Variation on the Use of Inpatient Rehabilitation Facilities Versus Skilled Nursing Facilities on Individual Patients With Stroke.\",\"authors\":\"Kent P Simmonds, James Burke, Alan Kozlowski, Michael Andary, Zhehui Luo, Mathew J Reeves\",\"doi\":\"10.1161/CIRCOUTCOMES.123.010636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>There is substantial hospital-level variation in the use of Inpatient Rehabilitation Facilities (IRFs) versus Skilled Nursing Facilities (SNFs) among patients with stroke, which is poorly understood. Our objective was to quantify the net effect of the admitting hospital on the probability of receiving IRF or SNF care for individual patients with stroke.</p><p><strong>Methods: </strong>Using Medicare claims data (2011-2013), a cohort of patients with acute stroke discharged to an IRF or SNF was identified. We generated 2 multivariable logistic regression models. Model 1 predicted IRF admission (versus SNF) using only patient-level factors, whereas model 2 added a hospital random effect term to quantify the hospital effect. The statistical significance and direction of the random effect terms were used to categorize hospitals as being either IRF-favoring, SNF-favoring, or neutral with respect to their discharge patterns. The hospital's impact on individual patient's probability of IRF discharge was estimated by taking the change in individual predicted probabilities (change in individual predicted probability) between the 2 models. 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Estimating the Impact of Hospital-Level Variation on the Use of Inpatient Rehabilitation Facilities Versus Skilled Nursing Facilities on Individual Patients With Stroke.
Background: There is substantial hospital-level variation in the use of Inpatient Rehabilitation Facilities (IRFs) versus Skilled Nursing Facilities (SNFs) among patients with stroke, which is poorly understood. Our objective was to quantify the net effect of the admitting hospital on the probability of receiving IRF or SNF care for individual patients with stroke.
Methods: Using Medicare claims data (2011-2013), a cohort of patients with acute stroke discharged to an IRF or SNF was identified. We generated 2 multivariable logistic regression models. Model 1 predicted IRF admission (versus SNF) using only patient-level factors, whereas model 2 added a hospital random effect term to quantify the hospital effect. The statistical significance and direction of the random effect terms were used to categorize hospitals as being either IRF-favoring, SNF-favoring, or neutral with respect to their discharge patterns. The hospital's impact on individual patient's probability of IRF discharge was estimated by taking the change in individual predicted probabilities (change in individual predicted probability) between the 2 models. Hospital-level effects were categorized as small (<10%), moderate (10%-19%), or large (≥20%) depending on change in individual predicted probability.
Results: The cohort included 135 415 patients (average age, 81.5 [SD=8.0] years, 61% female, 91% ischemic stroke) who were discharged from 1816 acute care hospitals to IRFs (n=66 548) or SNFs (n=68 867). Half of hospitals were classified as being either IRF-favoring (n=461, 25.4%) or SNF-favoring (n=485, 26.7%) with the remainder (n=870, 47.9%) considered neutral. Overall, just over half (n=73 428) of patients were treated at hospitals that had moderate or large independent effects on discharge settings. Hospital effects for neutral hospitals were small (ie, change in individual predicted probability <10%) for most patients (72.5%). However, hospital effects were moderate or large for 78.8% and 84.6% of patients treated at IRF- or SNF-favoring hospitals, respectively.
Conclusions: For most patients with stroke, the admitting hospital meaningfully changed the type of rehabilitation care that they received.
期刊介绍:
Circulation: Cardiovascular Quality and Outcomes, an American Heart Association journal, publishes articles related to improving cardiovascular health and health care. Content includes original research, reviews, and case studies relevant to clinical decision-making and healthcare policy. The online-only journal is dedicated to furthering the mission of promoting safe, effective, efficient, equitable, timely, and patient-centered care. Through its articles and contributions, the journal equips you with the knowledge you need to improve clinical care and population health, and allows you to engage in scholarly activities of consequence to the health of the public. Circulation: Cardiovascular Quality and Outcomes considers the following types of articles: Original Research Articles, Data Reports, Methods Papers, Cardiovascular Perspectives, Care Innovations, Novel Statistical Methods, Policy Briefs, Data Visualizations, and Caregiver or Patient Viewpoints.