[{"innerBlocks":[],"name":"core\/freeform","postId":994,"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":"Standardizing address information and last names could help to link patient health records by as much as 8 percent in the United States.

Such relatively simple standardization efforts could result in more than 2 billion additional records matched to patients, research suggests.

That\u2019s the finding of a study<\/a>, published in the Journal of the American Medical Informatics Association<\/i>, from researchers at the Regenstrief Institute, Indiana University Richard M. Fairbanks School of Public Health at IU\u2013Purdue University Indianapolis, IU School of Medicine and The Pew Charitable Trusts.

Researchers tested patient matching accuracy using standardized addresses, full birthdates, last names, Social Security numbers and telephone numbers with four real-world datasets\u2014health information exchange records, public health registry records, Social Security Death Master File records and newborn screening records.

What they discovered is that standardizing addresses had the greatest impact on data matching across all four use cases, while last names had a smaller effect.

\u201cAddress is a field rife for variation, so this is a great opportunity for standardization,\u201d says Shaun Grannis, MD, lead author and director of the Regenstrief Center for Biomedical Informatics. \u201cStandardizing data on a broader scale would ensure that patients and clinicians have better data on which to make decisions, which would enhance both the quality of care and patient safety.\u201d

\u201cThis first-of-its-kind research shows that setting standards for demographic data\u2014addresses in particular\u2014could put a significant dent in healthcare\u2019s perennial problem with correctly matching records for the same patient,\u201d says Ben Moscovitch, project director of the health IT initiative at The Pew Charitable Trusts. \u201cNow it\u2019s time for the federal government to require the standardization of data that help link an individual\u2019s medical records\u2014which is a key step to fully realizing the safer, well-coordinated care that electronic health records promise.\u201d

Patients are often matched to their medical records through demographic information, such as name, date of birth or sex. However, a recent Government Accountability Office audit found that \u201cinaccurate, incomplete or inconsistently formatted demographic information in patients\u2019 records\u201d is posing challenges to matching medical records.

Also See<\/b>: Patient matching hampered by demographic data<\/a>

Particularly problematic is the matching of medical records for newborns and multiple-birth siblings such as twins, according to the report.

Specifically, auditors noted that EHRs \u201cdon\u2019t always contain correct information (for example, a patient may provide a nickname rather than a legal name) and that health information technology systems and providers use different formats for key information such as names that contain hyphens.\u201d","saveContent":"Standardizing address information and last names could help to link patient health records by as much as 8 percent in the United States.

Such relatively simple standardization efforts could result in more than 2 billion additional records matched to patients, research suggests.

That\u2019s the finding of a study<\/a>, published in the Journal of the American Medical Informatics Association<\/i>, from researchers at the Regenstrief Institute, Indiana University Richard M. Fairbanks School of Public Health at IU\u2013Purdue University Indianapolis, IU School of Medicine and The Pew Charitable Trusts.

Researchers tested patient matching accuracy using standardized addresses, full birthdates, last names, Social Security numbers and telephone numbers with four real-world datasets\u2014health information exchange records, public health registry records, Social Security Death Master File records and newborn screening records.

What they discovered is that standardizing addresses had the greatest impact on data matching across all four use cases, while last names had a smaller effect.

\u201cAddress is a field rife for variation, so this is a great opportunity for standardization,\u201d says Shaun Grannis, MD, lead author and director of the Regenstrief Center for Biomedical Informatics. \u201cStandardizing data on a broader scale would ensure that patients and clinicians have better data on which to make decisions, which would enhance both the quality of care and patient safety.\u201d

\u201cThis first-of-its-kind research shows that setting standards for demographic data\u2014addresses in particular\u2014could put a significant dent in healthcare\u2019s perennial problem with correctly matching records for the same patient,\u201d says Ben Moscovitch, project director of the health IT initiative at The Pew Charitable Trusts. \u201cNow it\u2019s time for the federal government to require the standardization of data that help link an individual\u2019s medical records\u2014which is a key step to fully realizing the safer, well-coordinated care that electronic health records promise.\u201d

Patients are often matched to their medical records through demographic information, such as name, date of birth or sex. However, a recent Government Accountability Office audit found that \u201cinaccurate, incomplete or inconsistently formatted demographic information in patients\u2019 records\u201d is posing challenges to matching medical records.

Also See<\/b>: Patient matching hampered by demographic data<\/a>

Particularly problematic is the matching of medical records for newborns and multiple-birth siblings such as twins, according to the report.

Specifically, auditors noted that EHRs \u201cdon\u2019t always contain correct information (for example, a patient may provide a nickname rather than a legal name) and that health information technology systems and providers use different formats for key information such as names that contain hyphens.\u201d","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

Study: Data standardization improves patient matching

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