	Background

		Patient Record Matching

Patient record matching is the process of comparing patient information in  different health records to determine if the records refer to the same  patient. Examples of stakeholders include the following:
Health care providers, such as physicians, hospitals, and their staffs  may receive records from another provider that need to be matched to  existing patient records. Health IT vendors also play a role in matching patient records. Importance of Accurate Patient Record Matching

ONC and others have reported that the ability to accurately match patient  medical records across different providers is a critical part of effective  health information exchange, which can benefit patient care. ONC developed certification criteria for EHRs and other  health IT systems that include the ability for health IT systems to capture  and exchange various types of information, including clinical data such as  information on patients’ allergies, as well as the patient’s name, sex, and  date of birth. Stakeholders Described Patient Record Matching Approaches and Associated Challenges

		Providers and HIE Organizations Described Using Both Manual and Automated Approaches to Patient Record Matching

All seven provider representatives we interviewed described manual  matching as one of the ways that they match patient records when  exchanging health information with other providers. For example, an outpatient practice representative  said that to match records that the practice receives by fax, a staff  member must manually review information such as name and DOB to  identify the correct patient and add the new information to the correct  patient’s electronic record. Representatives said that when the patients’ records contain  similar but not identical demographic information, the HIE organizations  rely on staff or additional software to review potential matches and  determine whether the records belong to the same patient. Stakeholders Said That Inaccurate, Incomplete, and Inconsistently Formatted Data Can Pose Challenges for Patient Record Matching

Representatives from providers, HIE organizations, and the other  stakeholders we interviewed emphasized the importance of using quality  patient demographic data when matching patients’ medical records. According to  stakeholders, provider staff sometimes make transcription errors when entering  information into electronic records, patients do not always provide correct information (e.g., they register  with a nickname rather than a legal name), and patient demographic information can change, such as when a patient  moves to a new address or changes her last name, but this  information is not consistently updated in all of the patient’s medical  records. Stakeholders Identified Efforts Underway to Improve Patient Record Matching as Well as Additional Efforts ONC and Others Could Undertake

		Stakeholders Have Undertaken Efforts to Improve the Demographic Data and Methods Used to Match Records

Officials from ONC, selected provider representatives, and other  stakeholders we interviewed described a variety of efforts they have  undertaken or are currently undertaking to improve the ability to match  patients’ medical records accurately. Several stakeholders told us they have worked to improve the  consistency with which they record and format demographic data in their  EHRs. They told us the following:  In 2017, 23 providers in Texas reached agreement on, and then  implemented, standards for how staff should record patients’ names,  addresses, and other data in order to improve record matching and  facilitate health information exchange. They said that they have seen a significant  decrease in the need for those manual reviews since implementing  the data standards. For example, ONC officials  described the following two efforts to improve patient record matching  methods:  In 2017, ONC held a Patient Matching Algorithm Challenge in which  participants competed to develop an algorithm that most accurately  matched patient records in a test data set. ONC  officials told also us they plan to publish a report on their analysis of  the challenge data. The stakeholders  identified several efforts that could improve matching, and had varying  views on the roles ONC and others should play in these efforts. Among  the examples of efforts stakeholders identified that could improve  matching were implementing common standards for demographic data;  developing a data set to test the accuracy of matching methods; sharing  best practices and other resources; implementing a national unique  patient identifier; and developing a public-private collaboration effort to  improve patient record matching. Multiple stakeholders noted that no  single effort would be sufficient to improve matching, given the factors  that contribute to matching challenges. Some stakeholders said it can be costly for providers to  update or upgrade their EHRs. Several, for example, said that standardizing data would not  prevent inaccurate or outdated data. For example, representatives from one industry  association said that ONC could provide information about the types of  identifiers that could be used to facilitate matching, such as cell phone  numbers or driver’s license numbers. Agency Comments

We provided a draft of this report to HHS for review and comment. HHS  provided technical comments, which we incorporated as appropriate.
Why GAO Did This Study

Health care providers are increasingly sharing patients' health records electronically. When a patient's records are shared with another provider, it is important to accurately match them to the correct patient. GAO and others have reported that accurately matching patient health records is a barrier to health information exchange and that inaccurately matched records can adversely affect patient safety or privacy. At the federal level, ONC is charged with coordinating nationwide efforts to implement and use health IT.
The 21st Century Cures Act included a provision for GAO to study patient record matching. In this report, GAO describes (1) stakeholders' patient record matching approaches and related challenges; and (2) efforts to improve patient record matching identified by stakeholders.
To do its work, GAO reviewed reports by ONC and others about patient record matching. GAO also interviewed various stakeholders that play a role in exchanging health records, including representatives from physician practices, hospitals, health systems, health information exchange organizations, and health IT vendors. GAO also interviewed other stakeholders, such as ONC officials, provider and industry associations, and researchers. GAO selected stakeholders based on background research and input from other stakeholders, and interviewed 37 stakeholders in total. The information from stakeholders is not generalizable. HHS provided technical comments on a draft of this report, which GAO incorporated as appropriate.

What GAO Found

Stakeholders GAO interviewed, including representatives from physician practices and hospitals, described their approaches for matching patients' records—that is, comparing patient information in different health records to determine if the records refer to the same patient. Stakeholders explained that when exchanging health information with other providers, they match patients' medical records using demographic information, such as the patient's name, date of birth, or sex. This record matching can be done manually or automatically. For example, several provider representatives said that they rely on software that automatically matches records based on the records' demographic information when receiving medical records electronically. Stakeholders said that software can also identify potential matches, which staff then manually review to determine whether the records correspond to the same patient. Stakeholders also said that inaccurate, incomplete, or inconsistently formatted demographic information in patients' records can pose challenges to accurate matching. They noted, for example, that records don't always contain correct information (e.g., a patient may provide a nickname rather than a legal name) and that health information technology (IT) systems and providers use different formats for key information such as names that contain hyphens.
Stakeholders GAO interviewed identified recent or ongoing efforts to improve the data and methods used in patient record matching, such as the following:
Several stakeholders told GAO they worked to improve the consistency with which they format demographic data in their electronic health records (EHR). In 2017, 23 providers in Texas implemented standards for how staff record patients' names, addresses, and other data. Representatives from three hospitals said this increased their ability to match patients' medical records automatically. For example, one hospital's representatives said they had seen a significant decrease in the need to manually review records that do not match automatically.
Stakeholders also described efforts to assess and improve the effectiveness of methods used to match patient records. For example, in 2017 the Office of the National Coordinator for Health Information Technology (ONC) hosted a competition for participants to create an algorithm that most accurately matched patient records. ONC selected six winning submissions and plans to report on their analysis of the competition's data.
Stakeholders said more could be done to improve patient record matching, and identified several efforts that could improve matching. For example, some said that implementing common standards for recording demographic data; sharing best practices and other resources; and developing a public-private collaboration effort could each improve matching. Stakeholders' views varied on the roles ONC and others should play in these efforts and the extent to which the efforts would improve matching. For example, some said that ONC could require demographic data standards as part of its responsibility for certifying EHR systems, while other stakeholders said that ONC could facilitate the voluntary adoption of such standards. Multiple stakeholders emphasized that no single effort would solve the challenge of patient record matching.