[{"innerBlocks":[],"name":"core\/freeform","postId":591,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"Publicly reported hospital quality rating systems offer conflicting results that may only serve to mislead patients.That\u2019s at cross purposes to their intent of helping patients make informed decisions about medical facilities, according to the findings of an analysis<\/a>, published this week in NEJM Catalyst, by \u201cphysician scientists with methodological expertise in healthcare quality measurement.\u201dIn particular, the authors point out that \u201chospitals rated highly on one publicly reported hospital quality system are often rated poorly on another,\u201d which \u201cprovides conflicting information for patients seeking care and for hospitals attempting to use the data to identify real targets for improvement.\u201d

Researchers assessed the strengths and weaknesses of four major public hospital quality rating systems\u2014the Centers for Medicare and Medicaid Services\u2019 Hospital Compare; Healthgrades Top Hospitals; Leapfrog Hospital Safety Grade and Leapfrog Top Hospitals; and U.S. News & World Report Best Hospitals.\u201cWhile no rating system received an A or an F,\u201d researchers reported that \u201cthe highest grade received was a B by U.S. News & World Report,\u201d followed by a C for CMS Star Ratings, a C- for Leapfrog and a D+ for Healthgrades.\u201cWe qualitatively agreed that the U.S. News rating system had the least chance of misclassifying hospital performance,\u201d they added, noting that although the Consumer Reports hospital quality rating system was included in their evaluation, they deleted mention of it in the manuscript because it \u201cis no longer conducting or posting its hospital quality evaluations.\u201d <\/b>Also See<\/b>: Hospitals come up short in new CMS rating system<\/a>\u201cEach rating system had unique weaknesses that led to potential misclassification of hospital performance, ranging from inclusion of flawed measures, use of proprietary data that are not validated and methodological decisions,\u201d according to the authors.In addition, they noted that there were \u201cseveral issues that limited all rating systems,\u201d including \u201climited data and measures, lack of robust data audits, composite measure development, measuring diverse hospital types together and lack of formal peer review of their methods.\u201dTo address these shortcomings and advance the field of hospital quality measurement, the authors called for \u201cbetter data subject to robust audits, more meaningful measures, and development of standards and robust peer review to evaluate rating system methodology.\u201dSpecifically, they found fault with all the hospital quality rating systems for relying on administrative data or self-reported data, which the paper describes as having numerous limitations. \u201cAll rely heavily on Medicare claims data, which represents an important part of the population, but using all-payer data would present a more accurate and complete representation of quality,\u201d the authors contend.While they commented that the incorporation of registry data would be \u201can ideal alternative to overcome the limitations of administrative data,\u201d the researchers pointed out that \u201cthe abstraction required is laborious and expensive, and this results in only a fraction of hospitals participating in most registries, with only a fraction of a hospital\u2019s relevant cases being captured by the registry.\u201dA better solution, they said, would be \u201cobtaining data directly from the electronic health record to support valid, meaningful quality metrics.\u201d But, the authors added that despite all the talk about healthcare IT interoperability in the industry, \u201clittle has been translated to meaningful national quality measures.\u201d","saveContent":"Publicly reported hospital quality rating systems offer conflicting results that may only serve to mislead patients.That\u2019s at cross purposes to their intent of helping patients make informed decisions about medical facilities, according to the findings of an analysis<\/a>, published this week in NEJM Catalyst, by \u201cphysician scientists with methodological expertise in healthcare quality measurement.\u201dIn particular, the authors point out that \u201chospitals rated highly on one publicly reported hospital quality system are often rated poorly on another,\u201d which \u201cprovides conflicting information for patients seeking care and for hospitals attempting to use the data to identify real targets for improvement.\u201d Researchers assessed the strengths and weaknesses of four major public hospital quality rating systems\u2014the Centers for Medicare and Medicaid Services\u2019 Hospital Compare; Healthgrades Top Hospitals; Leapfrog Hospital Safety Grade and Leapfrog Top Hospitals; and U.S. News & World Report Best Hospitals.\u201cWhile no rating system received an A or an F,\u201d researchers reported that \u201cthe highest grade received was a B by U.S. News & World Report,\u201d followed by a C for CMS Star Ratings, a C- for Leapfrog and a D+ for Healthgrades.\u201cWe qualitatively agreed that the U.S. News rating system had the least chance of misclassifying hospital performance,\u201d they added, noting that although the Consumer Reports hospital quality rating system was included in their evaluation, they deleted mention of it in the manuscript because it \u201cis no longer conducting or posting its hospital quality evaluations.\u201d <\/b>Also See<\/b>: Hospitals come up short in new CMS rating system<\/a>\u201cEach rating system had unique weaknesses that led to potential misclassification of hospital performance, ranging from inclusion of flawed measures, use of proprietary data that are not validated and methodological decisions,\u201d according to the authors.In addition, they noted that there were \u201cseveral issues that limited all rating systems,\u201d including \u201climited data and measures, lack of robust data audits, composite measure development, measuring diverse hospital types together and lack of formal peer review of their methods.\u201dTo address these shortcomings and advance the field of hospital quality measurement, the authors called for \u201cbetter data subject to robust audits, more meaningful measures, and development of standards and robust peer review to evaluate rating system methodology.\u201dSpecifically, they found fault with all the hospital quality rating systems for relying on administrative data or self-reported data, which the paper describes as having numerous limitations. \u201cAll rely heavily on Medicare claims data, which represents an important part of the population, but using all-payer data would present a more accurate and complete representation of quality,\u201d the authors contend.While they commented that the incorporation of registry data would be \u201can ideal alternative to overcome the limitations of administrative data,\u201d the researchers pointed out that \u201cthe abstraction required is laborious and expensive, and this results in only a fraction of hospitals participating in most registries, with only a fraction of a hospital\u2019s relevant cases being captured by the registry.\u201dA better solution, they said, would be \u201cobtaining data directly from the electronic health record to support valid, meaningful quality metrics.\u201d But, the authors added that despite all the talk about healthcare IT interoperability in the industry, \u201clittle has been translated to meaningful national quality measures.\u201d","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

Study: Hospital quality ratings mislead, misclassify performance

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