Challenges Meeting 21st Century Cures Act Patient Identity Interoperability and Information Blocking Rules

Featured in the Journal for Healthcare Quality

Abstract

Objective: 

Gather insights into healthcare organization (HCO) preparedness for new 21st Century Cures Act information blocking disincentives and challenges in achieving greater accuracy /interoperability of patient identity/data.

Methods: 

Survey of 197 U.S. healthcare executives (54.7% response rate), included 46 health systems (23.4%), 141 hospitals (71.6%), and 10 payer organizations (5.1%), evaluated organizational gaps in patient identity data management/interoperability and preparation for information deblocking.

Results: 

Healthcare organizations are unprepared to meet information deblocking requirements and manage increased data influx/exchange. Although 61% have invested in meeting requirements, only 36% have capabilities in place. Majorities reported inability to comply with information blocking rules (59%), communicate electronic patient activity notifications to other organizations (56%), or share/receive patient-level information with patients and other HCOs (57%). Across 12 critical functionalities, 57% lacked key capabilities; 97% reported inadequate patient data/identity management/interoperability as data volume expands, adversely affecting care quality/safety and outcomes; and 57% envision patient data-matching errors precipitating a healthcare crisis in 5–10 years.

Conclusions: 

Many HCOs are unprepared to meet new Cures Act information blocking requirements and resultant increase of internal/external patient data volumes. Next generation master data management, enterprise master patient index, and referential matching technologies can improve HCO patient identity and data management, and information interoperability.

Introduction

U.S. healthcare organizations (HCOs) and their leaders face growing challenges and imperatives to improve operational effectiveness and financial efficiency, enhance patient care quality/safety, and enhance satisfaction while improving care outcomes.^1-6 These strategies depend on accurately identifying patients and effectively managing their information and data. Patient misidentification and lack of patient identity and information or data interoperability remain problematic.⁷

Essential to improving patient identity accuracy is achieving patient information and data interoperability, in which patient information flows securely but freely across different healthcare organizations. Since the implementation of the Health Information Technology for Economic and Clinical Health Act, a greater volume of information is shared between healthcare organizations. Healthcare information-sharing increased substantially over the past decade, accelerated by electronic health record (EHR) adoption. Yet, in 2015, the Office of National Coordinator for Health Information Technology reported to Congress increased healthcare information blocking among HCOs, which undermines the interoperability of patient information/data and identity, a concern given that at least 10% of patient records are duplicated.⁸ Information blocking interferes with the access, exchange, or use of electronic health information (EHI).⁹

In 2016, the U.S. Government introduced the 21st Century Cures Act, which emphasized sharing EHI as the expected norm in healthcare, but the problem has persisted.¹⁰ As a result, in late 2023, U.S. Health and Human Services proposed new disincentives for information blocking, penalizing practices that can cause patient harm or affect care delivery.¹¹ Under the rules, if the Office of Inspector General determines a hospital engaged in information blocking, it may be excluded from incentives within the Medicare Promoting Interoperability Program, the Quality Payment Program, and the Medicare Shared Savings Program. The Cures Act information blocking rules are expected to drive much increased data exchange and flow between HCOs.

As sources of often siloed patient information/data proliferate, internal need for accurate and comprehensive identity data management increases, as does need to efficiently share complete and accurate information about patients externally. A comprehensive, single integrated patient/member identity must be assembled from numerous disparate internal and external sources by matching all available information about the individual patient/member without omitting important data or comingling data from individuals with similar names or demographics.

Patient identity and data matching accurately links/maps all available data within and across data sources to the appropriate person, matching a patient to care interventions and communicating accurate information about the patient’s identity consistently across all care sites. Each patient needs a single, accurate, and comprehensive health record to facilitate informed, clinically effective, and safe care decision-making. As HCOs begin to comply with new information blocking rules, the influx and export volume of patient information will increase by orders of magnitude and risk of patient misidentification increases.

Patient misidentification occurs from duplication of patient records, overlay of patient data from different patients into a single record, and incorrect matching of patient data and identity from disparate data sources. Errors in patient identification disrupt care and harm patients in every stage of care delivery, including diagnostic testing and medication administration.^12-28 Since 2014, the Joint Commission designated improving accuracy of patient identification as the most important National Patient Safety Goal.¹² Healthcare data sources, such as EHRs, imaging or laboratory data frequently contain errors, and incomplete or redundant patient data. Identity errors or incomplete patient data can negatively affect patient safety/outcomes,^6,7,12-27 impede HCO financial performance, affect quality scores tied to value-based reimbursement, and public reputation/trust.²⁸ Rates of patient identity duplication range from 4 to 10% or more, with average overlay rates of 1.9%.^7,13,28

Clearly, information sharing within healthcare promises to enhance care effectiveness and safety, whether between HCOs and patients/members or between HCOs. New Cures Act information blocking rules will increase the complexity and stakes for HCOs in managing patient identity. EHRs, which many HCOs rely upon to manage patient identity, typically have an integrated matching technology functionality focused on improving accuracy of patient identity/data. EHRs have reduced duplication, inappropriate merging, and misidentification of patient identity/data, but have intrinsic limitations and are designed to deliver a different set of care/transactional capabilities. However, EHRs cannot achieve the highest possible level of accuracy and reduction of misidentification required.

Healthcare organizations manage high volumes of complex patient data, including personal health information, billing and claims data, imaging and laboratory data, and other critical information across numerous departments and hundreds of systems, and ingest patient data from other organizations. To manage such complexity, HCOs are increasingly using specialized systems to manage data, such as master data management (MDM) and healthcare master data management (hMDM) technology. Master data management applications identify, link, and integrate data from different sources into a single central system, which requires extensive tuning. An hMDM platform matches and manages the data of every individual data stream—including from patients or plan members, care providers, and employees—with one solution.

Accuracy in patient identity is critical to improving patient experience and satisfaction. Patients receiving incorrect information from a provider often switch to a new provider.²⁸ Inaccurate patient identity/data result in unnecessary, inappropriate clinical testing and imaging, care delays, and reimbursement claim denials and delays (72% of HCOs report delays in billing/reimbursement from inaccurate patient information).^20-23,28 This survey of U.S. healthcare leaders evaluated perceived HCO management challenges in patient identity/data management with a focus on preparedness to meet Cures Act requirements to stop information blocking.

Methods

Study Objectives

This survey evaluated HCO preparedness efforts and capabilities to comply with new information blocking rules as advanced by the 21st Century Cures Act. More generally, the survey sought to assess current HCO readiness to achieve greater accuracy of patient identity and information/data interoperability as the volume of exchanged patient information expands. We sought HCO perceptions of critical strategic objectives affected by the existing lack of patient identity and information/data interoperability, and anticipated from the new Cures Act information blocking disincentives.

Study Design and Survey Respondent Selection

An online fully deidentified, anonymous survey of patient data/information management and quality executives and leaders within HCOs was conducted. The survey sampled respondents from health systems, hospitals, and payers to assess readiness and capabilities to manage new Cures Act proposed disincentives or requirements, and the resultant increased volume of patient data exchanged. Eligibility criteria for survey participation included respondents having an active senior role in managing patient information/data and interoperability at their respective organizations. Survey respondents had to be involved in managing their organization’s patient data linkages, connections, storage, management, and utilization by healthcare delivery personnel.

Potential survey respondents were drawn from a cross-section of representative U.S. HCOs within the DashMR database. Initial identification and selection of survey respondents were based on position title or role within the healthcare organization, including titles that indicated a responsibility for and understanding of existing gaps in accuracy of patient identification, patient information/data interoperability, and need to reduce rates of patient misidentification. Executives met an eligibility requirement of their positional title within the organization indicating a senior enterprise, facility, or pertinent departmental or leadership role in health/patient/member information technology and data management, or quality and patient safety. Roles and titles were included that suggested responsibility for organizational clinical, operational, or financial performance impacted directly by accuracy and interoperability of patient identity or information, and/or preparedness to meet the information blocking requirements of the Cures Act.

Data Captured and Analyses Completed

The survey captured healthcare executive responses to questions about their organization’s characteristics, strategic priorities, and performance metrics and capabilities. Questions included a specific focus on managing the challenges of meeting the new Cures Act objectives, and the expected much enlarged influx or exchange of new external patient data, volume growth in internal patient data, and the increased need to share patient data with other HCOs.

Survey data were analyzed using stratified contingency tables describing key variables and responses of greatest pertinence to understanding HCO current status of and gaps in patient identity accuracy and data management capabilities. Analyses focused on describing resultant concerns, challenges and needs across organizational strategic, clinical, patient engagement/satisfaction, operational and financial priorities and readiness to meet new patient identity and data interoperability requirements of Cures Act.

Institutional Review Board Approval

This study did not involve patients or patient data, and the survey of healthcare executives was completed on an opt-in basis where respondents explicitly agreed to have their data published in aggregate, deidentified form. As such, a waiver of Institutional Review Board approval was granted.

Results

Survey Response Rate and Participating Healthcare Organizations

The survey was offered to 1,648 potentially eligible respondents. Of these, 1,283 were screened out as ineligible because of various exclusion criteria in addition to the above, such as not being currently employed, issues with data quality in survey response, and failure to complete all survey items. Of the remaining 360 eligible respondents, 197 completed the survey by the closing date of October 23, 2023, yielding a survey response rate of 54.7%. Respondents worked in 46 health systems (23.3%), 141 hospitals (71.6%), and 10 payer organizations (5.1%). Healthcare organization survey respondents identified a diverse range of internally created patient data streams, as well as those derived externally from third parties and other organizations (Table 1).

Table 1. – Internal and External Patient Data Streams Managed by Healthcare Organizations

Current and Future Anticipated Impact of Inaccurate, Unmatched, and Incomplete Patient Data

As summarized in Table 2, substantial minorities of respondents reported diverse concerns about the current and anticipated future negative impact of inaccurate, unmatched, and incomplete patient identity data when the exchange volume increases after Cures Act information blocking disincentives take effect (range from 23 to 44%). Interestingly, future levels of concern about these issues were not increased relative to current levels, and most responses by specific issue or concern were cited among one-third to two-fifths of respondents. The mean response frequency across the spectrum of current issues and challenges faced was identical to that for anticipated future concerns (35%).

Table 2. – Perceived Current and Anticipated Future Negative Impact of Inaccurate, Unmatched, and Incomplete Patient Identity Data and Poor Patient Information Interoperability^a

^aAs of survey closure on October 23, 2023.

Respondents agreed (92%) that patient identity is integral to data management and interoperability efforts and that successful patient data matching is extremely or very important in accomplishing their strategic initiatives. Almost one-half (49%) reported that their patient data are still stored in fragmented, siloed systems. Nearly all respondents agreed that information blocking rules within the 21st Century Cures Act will substantially increase the volume of data transmitted between HCOs. Virtually all respondents (98%) expect an increase in data sharing requests from other organizations, and 97% predict a large increase in incoming data from external sources. With this influx of data, 57% of respondents agreed that patient data-matching errors will result in a healthcare crisis within the next 5–10 years. Healthcare organizations reported being better prepared to share data within their organization than to exchange data externally. Almost all HCOs (97%) anticipate negative impacts of poor data management as the amount of data coming into their organization increases in the future—including a negative effect on patient outcomes, possible deterioration in care quality, and more problematic billing.

Current Level of Preparation for Increased Patient Data Volume Exchange and Management

Overall, although most HCOs have begun preparing for an anticipated data influx, many report being unprepared, with just 22% stating they are completely prepared and half (51%) indicating that while they have made progress, more is required. With respect to HCO current state of organizational preparedness to comply specifically with Cures Act information blocking requirements, 61% of respondents stated their organization was expending a great deal of effort to do so and 28% stated organizational efforts were moderate. Only 7% indicated little preparatory effort was underway, and in 1%, no effort has occurred. When asked about whether their HCO had implemented a comprehensive program to ensure data exchange capabilities and patient data interoperability to comply with the requirements of the Cures Act, one-third (36%) reported having such a program, with half (50%) indicating some program aspects were in place but others in development, and 13% having none yet in place.

Respondents were asked about specific capabilities in place to meet patient information or data interoperability requirements of the Cures Act. Across 12 functionalities, more than half (57% on average) of HCOs reported lacking key capabilities (Table 3).

Table 3. – Percentage of Healthcare Organizations Unprepared for Compliance With Provisions of the Cures Act^a

Abbreviation: API, application programming interface.

^aAs of survey closure on October 23, 2023.

Limitations

The survey results are limited by sample size. However, HCO respondents acknowledged current and anticipated negative impact of inadequate preparedness to accurately identify patients, match their patient data, and achieve information interoperability. If these data are representative and generalizable, a substantial percentage of HCOs are underprepared or unprepared. It can be reasonably assumed that social desirability would likely cause respondents to understate, rather than overstate, the magnitude of preparedness concerns. Given this, it is remarkable that over half (57%) of respondent HCOs acknowledged their organizations being unprepared for compliance with new Cures Act requirements to advance patient identity and information/data interoperability by eliminating information blocking.

With more than 5,000 hospitals and 1,000 health plans in the United States, it is conceivable that a greater range of Cures Act preparedness might be found in a larger sample of respondents. A more specific limitation that warrants future research is whether there are major differences in readiness to advance patient information and identity interoperability between HCOs located in urban versus rural areas. Given the greater concentration and density of HCOs in urban areas, it is likely that patients in these areas may have more opportunity to create multiple identities across different HCOs, and as such the challenges to be faced ahead with respect to achieving greater interoperability in urban HCOs may exceed those facing rural ones. In addition, given that the information blocking rules compliance deadline has not yet been announced, and that meeting the new requirements will likely require HCOs years to fully satisfy through new technology implementation, we recommend that similar survey data be gathered again on an annual basis to monitor HCO perceived progress, which will also further validate the findings of this particular survey.

The survey data presented were gathered in the fall of 2023, and presumably, with the announcement of new penalties for information blocking, HCOs are progressing their preparations to meet the new requirements. Thus, to some extent, the findings of this survey may represent a less prepared state and associated level of organizational concern about their readiness to comply with the new rules. However, weighing against this potential biasing of the results to a higher level of concern and lower readiness is the reality that many of the needed capabilities to improve the accuracy of patient identity and information are not readily achievable within the 6-month period since the survey data were collected. Furthermore, the public comment period for the new disincentives only concluded in January 2024, and we suspect that significant HCO progress in meeting the new information blocking has not occurred in the last 4 months.

Discussion

The survey data illustrate that despite significant efforts, few HCOs have a comprehensive Cures Act compliance program in place, limiting their ability to improve patient-level data management, identity accuracy, and information interoperability. Respondents agreed that MDM capabilities to improve patient data management will be critical given the large influx of additional patient data expected when information blocking rules are in place. Among the benefits that HCOs may derive from an MDM solution are improved patient care and safety, enhanced operational efficiency, and compliance and regulatory advantages. Master data management helps HCOs maintain precise patient records, enabling healthcare providers to make better, more informed clinical decisions to personalize treatment plans, and reduce medical errors.²⁹ Access to comprehensive and reliable patient data enhances diagnostics, supports improved preventive care strategies and outreach, and increases the timeliness of interventions, which leads to improved patient outcomes and increased patient satisfaction.²⁹

These findings parallel those of the Patient ID Now coalition of hospitals.²⁸ Healthcare leaders understand the foundational contribution of accurate patient identity and information interoperability to excellence in clinical care, operational, and financial performance. Most indicated existing technological solutions are inadequately resolving patient data/identity accuracy challenges. Innovative, next generation technologies capable of exceeding the performance of basic MPI functionality in current EHRs are needed.

Conventional patient matching technologies use algorithms to compare the demographic data from two patient records to determine whether those records belong to the same person. The technology that automatically matches and links all of a patient’s data, flagging any duplicate records created across the EHR, is the MPI. Master patient index functionality is incorporated into most EHRs. Master patient indexes use either deterministic algorithms that seek a perfect match between each data element to match two records, or probabilistic algorithms that use statistics, weights, thresholds, and rules to calculate the probability that two records belong to the same person. If the demographic data are the same or very close, the technology evaluates if there is a potential match, and if so, this will be presented to a human, most likely a data steward working in the health information management department, who has the ability to correct the patient identity in the system. Probabilistic algorithms in MPI technology have been used since the 1970s with little advancement, and their functional capabilities are increasingly limited in today’s complex healthcare information ecosystem, where expanding volumes of diverse patient data must be linked across complex provider organizations.

Healthcare organizations may also invest in enterprise master patient index technology that helps link each patient’s data not just within an EHR but also across multiple EHRs, facilities, and other technology systems. Electronic health record MPI functionality improves accuracy of patient identity, but may face the dynamic data challenges. Although the ubiquity of EHRs have reduced patient misidentification, EHRs are designed to achieve different care and operational objectives. Patient identity technology solutions have emerged that seek to ensure high identity accuracy and reduce misidentification, and as a result, HCOs are increasingly engaging novel identity solutions.

Unprecedented patient identity and information/data interoperability is possible through new technologies such as hMDM using a referential patient identity database. Healthcare organizations need more complete patient information, including but beyond that within EHRs, and using identity data from other sectors beyond healthcare. Healthcare master data management capabilities enable record matching within the EHR and from other systems to create accurate patient records. Halting information blocking implies meeting information requests without delay, and rapidly accessing all pertinent patient information/data systems as internal and external requests for information exports increase.

Referential database patient matching technology more accurately ascertains identity by integrating identity data beyond the healthcare sector to include commercially and publicly available local, state and federal governmental, legal, financial and credit, telecommunication system, and other nonhealthcare personal records.³⁰ It increases accuracy and interoperability of patient identity by matching demographic data from each record to a comprehensive, continuously updated and curated cross-sector reference database of identities. The referential database algorithm and logic uses probabilistic matching techniques and a curated reference data set of all U.S. adults, with additional logic adapted to the data characteristics that vary when combining patient and reference data. Reference data are derived from commercially available, nonhealthcare sources, such as credit header data and federal, state, and local government person records. Matching against a referential database demonstrably increased resolution of misidentified duplicate and overlay identities versus existing technologies.³⁰

Because a referential identity database draws upon data sources beyond those typically used in healthcare, it can more accurately ascertain patient identity by systematically integrating identity data from multisector data streams.³⁰ In Figure 1, referential matching enables Identity A to be matched accurately to Identity B, a level of data synthetic integration and resulting patient identity matching performance, which traditional technology solutions cannot achieve.³⁰ This capability enables exchange of healthcare information with high patient identity integrity between different clinical systems at previously unseen levels of accuracy.³⁰ The survey results indicate that patient identity and information/data interoperability is a pervasive challenge adversely affecting many HCO operating functions, and surveyed executives agreed (89%) that hMDM functionality is critical in effectively managing the imminent surge in shared patient data with reduced information-blocking.

Powerful existing technological solutions that deploy referential patient matching are currently available to enable healthcare delivery organizations to dramatically increase the accuracy of patient identity, reducing patient record duplication and overlay rates.³⁰ HITRUST-certified, next generation cloud-based identity platforms exist which enable interoperability across the complex digital healthcare ecosystem with unprecedented accuracy of patient identity. These technology solutions can ensure that HCOs get patient identity right—from the very start of their digital health journeys and into the future where the criticality of accuracy of patient identity will only increase. Indeed, it is likely that many of the patient safety concerns about inaccuracy of patient identity and identity interoperability highlighted by the Joint Commission in 2024 remain largely unchanged.¹² However, existing evidence suggests that if organizations implement an hMDM system, these risks can be substantially mitigated.³⁰

Conclusions

In sum, this survey of 197 HCO data and information-quality management executives regarding readiness to meet Cure Act requirements yielded sobering results: Although most have invested in meeting requirements, only 36% have comprehensive capabilities in place. More than half of respondent HCOs (57%) acknowledged their organizations being unprepared for compliance with the new Cures Act measures seeking to advance patient identity and information or data interoperability by eliminating information blocking. Majorities reported inability to comply with information blocking rules, communicate electronic patient activity notifications to other organizations, protect patient data integrity, or share or receive patient-level information with patients and other HCOs. As patient data volume mounts, virtually all anticipate that inadequate patient data and identity management will adversely affect care quality or safety and outcomes. Half (57%) believe patient data-matching errors will precipitate a healthcare crisis within 5–10 years.

Implications

Because accuracy of patient identity/data is foundational to safe and effective healthcare delivery, continuing failure in U.S. healthcare to overcome the interoperability challenge undermines the benefits derived from existing health information systems. The promise of evolving artificial intelligence within the EHR, for example, depends centrally on correctly identifying patients across different, often siloed systems. EHR adoption digitized healthcare EHI and progressed the national distribution of evidence-based medical practice, while establishing a national EHI system to effectively manage patients across their lifetime of healthcare utilization. The latter goal remains largely unrealized. Preventable healthcare related errors may be responsible for 210,000–400,000 U.S. deaths per year, and error-related morbidity may be orders of magnitude greater.^31,32 Failure to accurately identify patients and their data results in clinicians managing patients with incomplete EHR clinical data or data drawn from the medical records of more than one individual. Existing solutions deploying MDM, enterprise master patient index, and referential database patient matching technologies can help HCOs increase the accuracy of patient identity and data, reducing patient record duplication and overlay rates and enabling improved patient identity interoperability across an increasingly complex digital healthcare ecosystem.³⁰

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