An Overview of EHI Legislation and Its Economic Impact

Of the approximately 2.5 x 10(to the power of 18) bytes of information created each day,(1) health information is often considered the most important. Consequently, legislators have enacted laws to govern and protect individuals’ health information. Such legislation includes the 1996 Health Insurance Portability and Accountability Act (HIPAA),(2) the American Recovery and Reinvestment Act of 2009 (ARRA),(3) and the Patient Protection and Affordable Care Act (ACA).(4) The ARRA and the ACA contain significant stipulations regarding electronic health information (EHI) and together represent the most profound impact on health information technology (HIT) to date.

New interoperability legislation, namely the Interoperability and Patient Access final rule and the 21st Century Cures Act final rule, go into effect in 2021 and have the potential to significantly change the HIT market. This health legislation has also dramatically affected health economics.

Health economics research has focused on the impact of general technological change on health outcomes and care costs and has shown that approximately 50% of the increase in healthcare expenditures is due to expanding technology.(5-7) Another major focus in healthcare economics is the effect of insurance on health outcomes and expenditures.(8,9) Research demonstrates that health insurance expansion is responsible for more than 40% of medical care expenditure growth.(7,10) This information is important because health insurance and HIT are inseparably intertwined.

Little research has been conducted, however, on the economics or clinical effects of EHI systems, the impact of EHI legislation, or optimal EHI system configuration. It is critical to understand these factors and to identify strategies that may reduce healthcare expenditures and improve patient access to high-quality and high-value healthcare.

Overview of Electronic Health Information Systems

An EHI system contains individuals’ health information, including medical history, clinical notes, and laboratory and imaging diagnostic test results. EHI systems can be homegrown, meaning that they are produced and used by the same provider, or as is increasingly common, can be leased through private firms in the form of software-as-a-service.

Development of electronic health records began at academic institutions in the 1960s and 1970s. Among the first developers was the University of Utah which, coordinating with 3M, built the Health Evaluation through Logical Processing (HELP) system.(11) Around 1968, Harvard and Massachusetts General Hospital developed the Computer Stored Ambulatory Record (COSTAR) system.(11) These original systems were hybrids of paper and electronic data with limited capabilities and were intended to improve medical care and facilitate medical research.(12) Clinical information systems were not prevalent at the time and included only basic health information.

In the 1980s and 1990s, EHI systems became more common and were developed in the private sector. However, these systems were used in hospitals for the most part and not widely used by independent practices. By 1987, the need for standards in EHI was apparent and the nonprofit organization Health Level 7 (HL7)(13) formed to facilitate data standardization across electronic platforms. By 1992, HL7 was the primary interface standard for EHI(12) and is currently in use today.

Healthcare providers that use an EHI system establish a unique record for each patient. A patient can have multiple EHI records if they have visited more than one provider system. This segmentation of personal health information across multiple providers is one of the primary obstacles in healthcare delivery. As of July 2017, 684 unique HIT developers operate in the United States.(14) Despite HL7 standards, these disparate data systems have no functional interoperability.

The Affordable Care Act and Ancillary Legislation

During the Obama Administration, legislators passed many laws that profoundly affected EHI, particularly, the ACA in 2010 and the ARRA in 2009, which included grants and laws that incentivized EHI system development, adoption, and “meaningful use.”(4,3) Both laws built on the protected health information guidelines set forth in HIPAA.

HIPAA established national standards for electronic healthcare transactions in the Administration Simplification provisions of Title II.(2) These provisions stipulate that protected health information (PHI) can be shared without patient consent only for a defined set of operations between certified entities (CE) or one CE and another CE’s business associate, provided that both CEs have, or had in the past, a relationship with the patient; the PHI requested pertains to the entities’ relationship; and the discloser provides only the minimum information necessary for the operation at hand. The U.S. Department of Health and Human Services created a document entitled “Permitted Uses and Disclosures: Exchange for Health Care Operations” that summarizes some of the main points of the HIPAA of 1996, including the appropriate uses of protected health information (www.hhs.gov/sites/default/files/exchange_health_care_ops.pdf).

Intended as an economic stimulus, the ARRA allocated $787 billion to help the post-recession economy.(3) The portion of the ARRA affecting EHI is the Health Information Technology for Economic and Clinical Health (HITECH) Act. The HITECH Act allocated $49 billion “in both discretionary appropriations and mandatory spending to support and promote the adoption, implementation, and use of interoperable EHRs while at the same time establishing an overarching system of federal governance and oversight.”(15) Of these funds, $19.2 billion were for cash incentives to hospitals and physicians that demonstrate “meaningful use” of certified electronic health record technology (CEHRT).(16)

The Centers for Medicare & Medicaid Services (CMS) established the Promoting Interoperability Programs (PIP), previously known as the Medicare and Medicaid Electronic Health Records Incentive Programs, to govern the distribution of funds based on meaningful use. PIP organized meaningful-use criteria into three stages: (1) capturing medical data, (2) improving clinical processes, and (3) improving health outcomes. Cash incentives were distributed to hospitals and physicians based on their adherence to these criteria. Each physician could receive up to $65,000 and each hospital up to $11 million for demonstrating meaningful use of CEHRT.(16)

The ACA also profoundly affected EHI. Section 1104 sets forth provisions governing electronic healthcare transactions and establishes penalties for health plans that fail to comply with requirements. Section 3002 mandates quality measures and annual quality measure reporting. Section 3003 requires specified new types of reports and data analysis under the physician feedback program. Section 3506 promotes Clinical Decision Support technology to help both patients and providers. Section 6301 establishes the Patient-Centered Outcomes Research Institute for the purpose of facilitating comparative effectiveness research. A summary of the ACA sections relevant to EHI can be found in Figure 1.

Figure 1. A summary of the ACA sections relevant to EHI

The listed sections of the ACA are those that most directly influenced EMRs and HIT markets according to inclusion criteria formed during this research. These inclusion criteria are (1) the legislation directly mentions electronic medical records, electronic health records, or health information technology; (2) the legislation directly affects the collection, analysis, or transaction of protected health information or health care data; and (3) the legislation directly impacts the use of EMR data for research or report creation. Hence, the included legislation may not be exhaustive but likely includes the most impactful legislation relevant to EMRs.

Affordable Care Act and Ancillary Legislation Effects on EHI Systems

Of the numerous laws governing HIT before 2020, the ACA and ARRA are the most significant. The major impacts of these legislations can be summarized by the introduction of market entry into the EHI system marketplace; the impact on EHI system functionality; structural changes to market incentives and information symmetry; and the increase in market complexity.

Market Entry

The ARRA, in conjunction with Sections 3002 and 3003 of the ACA, incentivized firms to enter the HIT market. Through the HITECH Act, the ARRA awarded significant cash incentives for the adoption and meaningful use of CEHRT.(3) The HITECH Act provided up to $65,000 and $11 million to physicians and hospitals respectively for implementing EHI systems and using them in pre-defined meaningful ways.

These cash incentives likely induced market entrance into the EHI system market, a claim that is supported by related research and basic intertemporal analysis of the number of available EHI systems. The number of distinct EHI systems increased from just a handful to 684 unique HIT developers as of July 2017, and the upward trend in the number of unique EHI systems can be plausibly proxied by EHI system adoption rates over time (see Figure 2). A significant number of HIT developers entered the market following the Obama-era legislation around 2010 (in addition to existing suppliers increasing their number of customers). Note that the rate of EHI system adoption nearly doubled from 2010 to 2011.

Figure 2. Non-federal acute care hospital EMR adoption

Section 3002 of the ACA also directly incentivized EHI system adoption by extending through 2013 incentive payments under the physician quality reporting system and prescribing a penalty beginning in 2015 for providers who do not report quality measures satisfactorily.(4) These incentives, negative and positive, increased EHI system adoption and meaningful use.

Section 3003 is similar in effect. Section 3003 requires the creation of a resource utilization report of physicians and hospitals beginning in 2012. EHI system adoption and meaningful use is included in this report and the creation of this report is facilitated through EHI systems, which serves as two direct incentives for the adoption of EHI systems. In other words, providers must report to the government how and to what extent they use EHI systems. Furthermore, creating these reports is much easier using an EHI system since all the relevant quality metrics can be digitally stored in EHI systems and readily accessed and analyzed. Thus, Section 3003 creates two direct incentives for EHI system adoption and meaningful use.

EHI System Functionality

In addition to affecting market entrance, the ACA also appears to have affected the (marginal) functionality of EHI systems through Sections 3002, 3506, and 6301. Marginal analysis involves examining the effects or behaviors of data just before and just after a threshold or exogenous occurrence. A common practice in economics, analysis at the margin provides the most accurate and realistic model for a given variable of interest. In this case, the marginal EHI system functionality is the additional (and not necessarily improved) EHI system functionality of the n+1 EHI software or software version.

Section 3002 requires providers to report “quality measures” to the federal government — including EHI system adoption and meaningful use.(4) Providers that fail to report or meet these quality measures incur a penalty. Therefore, providers have an incentive to use EHI systems with better functionality to ensure more accurate and timely reporting of quality metrics and avoid incurring the penalty.

Another benefit derived from reporting quality measures is improved interoperability. Interoperability describes the degree to which various HIT systems, such as EMRs, can cohesively interact. Following passage of the ACA and ARRA, however, our healthcare system still faces significant interoperability issues. Under the Trump administration, further steps were made to promote interoperability of healthcare data.

The meaningful use criteria on which providers must report include interoperability metrics, so providers are incentivized, at least to some degree, to use/develop interoperational EHI systems. Following the passage of the ACA and ARRA, however, a severe lack of interoperability in healthcare persists despite the incentives for interoperability.

Section 3506 of the ACA also aims to improve EHI system functionality by facilitating patient-provider collaboration through Clinical Decision Support technology. Section 3506 provides grants for Shared Decision-making Resource Centers and establishes governing bodies and processes by amending Part D of Title IX of the Public Health Service Act. These grants and other regulations began in 2010 with ACA ratification.

It may be that EHI systems produced at the margin exhibit negative returns. Evidence suggests that copycat technologies, specifically pharmaceuticals, provide diminishing returns to health.(17) As another type of healthcare technology, EHI systems may also plausibly exhibit negative marginal returns.

Additionally, survey data and a review of the literature further corroborate the position that the marginal EHI system functionality exhibits diminishing marginal returns. The data in Figure 3 illustrate that the marginal return is zero or negative for some EHI systems. Further support for this idea can be found in a recent study led by the American Medical Association. This study found that physicians gave EHI systems a usability score of “F,” a failing score. The study was conducted by the AMA and published in a recent report by the Mayo Clinic. The scoring system used in the study ranged from A (best) to F (worst), the same scoring used by traditional academic institutions.(18)

Figure 3. Effects of meaningful use functionalities on healthcare quality, safety, and efficiency, by study outcomes result (% of studies)

These data indicate that future research should examine what functionalities characterize an optimal EHI system. Such research could be carried out using EHI system activity logs that contain data on time spent in each functionality and categorical error rates. Data from multiple EHI platforms should be used.

Section 6301 of the ACA has a more indirect effect on EHI system functionality. Section 6301 establishes the Patient-Centered Outcomes Research Institute (PCORI) to “...assist patients, providers, and policy-makers in making informed health decisions by…” evaluating medical treatments, services, and technologies through comparative effectiveness research. The concept of an industry-specific technology assessment organization was suggested in the mid-1990s.(6) In theory, the PCORI should identify optimal EHI technology and disseminate their empirical findings throughout the industry, which ought to improve marginal EHI system functionality. Further research into this subject is required to determine if PCORI is fulfilling this purpose.

Market Incentives and Asymmetric Information

The ACA also aims to “[provide] as much uniformity in the implementation of electronic standards as possible.”(4) It does so via Section 1104 paragraph G subparagraph 2, which creates a nonprofit entity tasked with developing the operating rules that govern the transaction of electronic data. This nonprofit entity is organized under the following criteria: (1) the entity consists of a multi-stakeholder consensus-based process for developing rules; (2) the entity has a public set of guiding principles; and (3) the entity uses HIPAA as a basis for establishing operating rules.

In theory, this stipulation appears logical and capable of delivering on the goal of providing EHI uniformity; however, the specifics of this legislation may have the opposite effect by creating perverse market incentives. Common to economic knowledge is that asymmetric information, which is analogous in some respects to market power, results in market inefficiencies including a lack of competitive equilibria.(19,20) In other words, asymmetric information can enable individuals or companies to sell sub-optimal products or services at higher prices.

The potential problem lies in the creation of the “multi-stakeholder entity.” Section 1104 creates this governing body from the very firms that are being governed; hence, a clear conflict of interest exists. This governing structure, to some extent, enables firms to establish rules that favor their own interests and, given the tremendous costs of data standardization, profit-maximizing firms may be incentivized to maintain discretized data systems.

In a simplified analogy, this type of behavior is exhibited by computer companies such as Apple and Microsoft, that maintain disparate operating systems to increase consumer switching costs and maximize profits. This type of misaligned structure may incentivize data discretization and could likely be an underlying inhibitor to interoperability in healthcare.

Research suggests that “improved financial incentives can reduce healthcare spending without negative consequences for industry profits or patient health.”(21) Ideally, health data uniformity can be achieved without significant negative and long-term consequences for industry profits. For such to be accomplished, an unbiased entity with the proper incentives must govern electronic data transactions in healthcare. The magnitude of benefits from health data uniformity is yet unknown but likely monumental for medical research, clinical processes, and patient outcomes. Substantial benefit lies in research on EHI standardization.

Market Complexity

Benefits aside, the ACA and ancillary legislation represent enormous increases in regulatory and legal complexity to the healthcare (and HIT) market(s). Just as taxation is a form of regulation, regulation can be considered a form of taxation. Adding regulation to an industry requires firms to increase their capacity to comply with the added regulatory complexity, usually by increasing the output of existing workers or hiring additional workers. The ACA is an indirect, but effective tax on the healthcare market, and the ACA legislation governing electronic data is therefore an effective tax on the HIT market. Recognizing that market regulation is characteristically similar to a market tax enables complexity in healthcare to be analyzed by a basic economic tax model.

This taxation framework can roughly describe two layers of the HIT market. First, EHI system users (e.g., hospitals or other providers) can be thought of as consumers, with HIT firms as suppliers. In this case, providers bear the bulk of lost surplus (costs), which could take the form of reduced physician wages.(22) This scenario is likely, as much study has demonstrated that physicians’ wages have been shrinking over the past few decades.(23)

In the second case, patients can be thought of as the consumers and providers as the suppliers. In this instance, the burden largely falls on patients and could possibly manifest as increased premiums, which is a plausible conclusion since health insurance premiums have been significantly rising for many years. These conclusions are based on a simple economic model.

A more robust econometric model is likely the best tool by which to analyze the effects of regulatory complexity in healthcare. A primary challenge in answering such a question is how to model complexity. It may be possible to model market complexity using a metric representing the number and/or extent of regulatory laws governing the industry, the number of inter-organizational dependencies, or the number of organizational layers within a typical firm in the industry. Further empirical investigation into the effects of regulatory complexity on the HIT (and health) market(s) would be an interesting and possibly valuable focus for future research.

In addition to monetary costs, regulatory complexity is also accompanied by other costs such as lack of interoperability and fraud. Lack of interoperability costs are primarily incurred in the additional worker-hours required to overcome interoperational frictions, which merits further research but will not be discussed here.

Fraud thrives in obscurity, and added regulatory complexity provides that obscurity. In its end-of-year 2017 report, the Government Accountability Office (GAO) estimated that of the $1.1 trillion in CMS outlays for 2016, approximately $95 billion in fraudulent claims were identified but only $2.5 billion was recovered.(24) The dangers of regulatory complexity are not novel to this paper; in this same report, the GAO warned Congress that “the complexities of [CMS] programs...pose challenges to CMS oversight and present opportunities to be exploited for fraud. We have designated Medicare and Medicaid as high-risk programs due to their size, complexity, and vulnerability to fraud and waste.”(24)

According to this report, fraud primarily occurs by way of “upcoding,” which means that the number or magnitude of medical codes are exaggerated in the EHI system to increase reimbursement rates for providers. For example, a doctor could overstate the medical complexity or the extent of services provided to a patient to increase his or her revenue. Due to the substantial amount of fraud and how fraud is generally committed, research focusing on fraud reduction and EHI systems has the potential to save billions of dollars annually.

Simplified EHI systems and decreased data-transaction complexity are likely key to reducing healthcare fraud. Worth noting is the increased prevalence of patient-centric medical records, which enable patient access. This type of EHI system exhibits the promising results of improved patient engagement and decreased fraud in a few studies. These studies involving patient-centric EMRs are still in their infancy and non-economic in nature, but have each shown some promising, or at the very least interesting, results.(25-27)

New Interoperability Legislation and EHI Systems

While the ACA and ARRA contained provisions to promote interoperability in healthcare, a significant lack of healthcare interoperability remained following their enactment and strongly persists today. In May 2020, two final rules were published to further promote interoperability and information symmetry. The Interoperability and Patient Access final rule (IPA final rule) and the 21st Century Cures Act final rule (21CA final rule) went into effect on January 1, 2021, and April 5, 2021, respectively.(28,29)

The Information Blocking provisions of the Cures Act final rule took effect on April 5, 2021. The remainder of the provisions in the Cures Act final rule are supposed to be fully implemented by December 31, 2023. Details can be found at www.healthit.gov/cures/sites/default/files/cures/2020-10/IFC_FactSheet_Certification.pdf.

The Interoperability and Patient Access final rule also has a distributed rollout that concludes in 2022, which information can be found at www.cms.gov/newsroom/fact-sheets/interoperability-and-patient-access-fact-sheet.

While unified in purpose, the IPA and 21CA final rules differ in focus.

Among seven primary provisions, the IPA final rule focuses on data integrity and exchange. Without going into undue detail, these provisions stipulate updating patient and provider databases more frequently, standardizing APIs, and improving physician and patient access to EHI.(28) The IPA final rule applies specifically to CMS entities, such as Medicare Advantage, Medicaid, CHIP, and Qualified Health Plans; hence, it applies to a narrower field of healthcare entities than the 21CA final rule.

Complementary but distinct to the IPA final rule, the 21CA final rule has wider applicability and focuses on improving HIT certification and restricting information blocking.(29) Detailed in Sections IV-VII of the 21CA final rule, improvements to HIT certification come primarily through mandated API standards, which govern all certifying HIT entities. In Section VIII, the information blocking provisions apply to all healthcare players and facilitate secure access, use, and exchange of EHI for both providers and patients. Any practice by a HIT developer that “…interfere[s] with access, exchange or use of EHI” is considered information blocking. The 21CA final rule permits information blocking if at least one of eight exceptions are fulfilled. These exceptions are designed to protect patients and mitigate unreasonable strain on data providers.(29)

An example of this would be providing a physician who requested medical records for a new patient with EHI that is in a disorganized, non-standard format.

Both final rules, however, are implementations of the Cures Act passed in 2016. As such, the two share numerous similarities, including a foundation on the United States Core Data for Interoperability (USCDI) standard. Based on HL7, the USCDI replaces its antiquated predecessor, the Common Clinical Data Set (CCDS), and establishes a standard “set of data classes and constituent data elements required to support interoperability nationwide.”(29) The USCDI standard is the common syntax that serves as the basis for standardized APIs and is therefore vital to both the IPA and 21CA final rules.

In theory, these new legislations should have several effects, foremost of which are improved interoperability and information symmetry in healthcare. The USCDI and API standards together should create a common language among all healthcare entities through which patient and provider data can be more readily communicated. This, in turn, will enable healthcare firms and third-party software developers to not only build virtual bridges between previously siloed health data systems, but also create platforms that give physicians and patients better access to their data. With more accessible and standardized EHI, physicians will be equipped to provide patients with more continuous care. Standardized EHI would also be a tremendous boon to research that uses EMRs.

Another byproduct of this legislation could be increased competition in the EHI software market because more interoperability translates to lower EHI system switching costs. Furthermore, a more competitive market leads to lower consumer prices. As discussed earlier in this paper, more interoperability of healthcare data also decreases data transaction costs, improves care transparency, empowers patients, and reduces market complexity.

One estimate of interoperability value conservatively projects annual savings of about $77.8 billion.(30) Measures to promote interoperability will provide these benefits in full as long as data security can be balanced with data accessibility and standardization.

Conclusion

Using a thorough examination of the economics of the ACA, ARRA, and other legislation governing EHI and EHI systems, this overview laid a foundation for future research involving EHI and subsequent legislation. It is apparent that the ACA and ARRA have had some expected and possibly unforeseen effects. They likely induced market entry by HIT firms through monetary and mandated incentives. They also affected marginal EHI system functionality, which likely exhibits diminishing marginal returns and negative returns in some cases. In other cases, EHI system functionality likely improved clinical operations.

The ACA and ARRA also affected market incentives. Some incentives promoted quality improvements in healthcare, but others may be perverse and inhibit interoperability and incentivize undue profits. This Obama-era legislation definitively and monumentally increased regulatory complexity in HIT and therefore EHI systems.

The level of complexity that now characterizes our healthcare system represents a tremendous cost, both public and private. In concordance with the GAO’s 2017 report, complexity and cost must be decreased in the healthcare industry. In this data-driven world, improved interoperability and information symmetry not only can decrease healthcare complexity and cost, but also pave the path of progress for healthcare.

The new interoperability rules have the potential to greatly empower physicians and patients with better and more accessible health data. These rules also implicitly bestow a responsibility upon physicians and patients to demand and work toward better EHI systems. Patients ought to demand, use, and review their EHI and EHI systems. They can also donate to EHI technology research through organizations such as PCORI.

Since the EMR is a vital tool used almost universally by all healthcare professionals, physicians also can and should advocate for and help shape better EHI technology. This can be achieved by formal research, hospital or provider committees charged with reviewing/acquiring technology, or a number of other channels.

Any properly functioning and complex system, like the human body, has effective feedback loops and controllers. As healthcare professionals, we must engage in this feedback loop to improve EHI systems and promote a more robust healthcare system. Improved and interoperable EHI systems are key to higher value and lower cost healthcare.

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Appendix A: Stages of Reporting Interoperability Programs

From cms.gov

The Centers for Medicare & Medicaid Services (CMS) established the Promoting Interoperability Programs (formally named the EHR Incentive Programs) in 2011 to encourage eligible [providers] to adopt, implement, upgrade and successfully demonstrate meaningful use of certified electronic health record technology (CEHRT). The Medicare and Medicaid PI Programs were designed to measure the use of CEHRT in three stages:

• Stage 1 established requirements for the electronic capture of clinical data, including providing patients with electronic copies of health information.

• Stage 2 expanded upon the Stage 1 criteria with a focus on advancing clinical processes and ensuring that the meaningful use of EHRs supported the aims and priorities of the National Quality Strategy.

• Stage 2 criteria encouraged use of CEHRT for continuous quality improvement at the point of care and the exchange of information in the most structured format possible. In October 2015, CMS released the Medicare and Medicaid Programs Electronic Health Record Incentive Program-Stage 3 and Modifications to Meaningful Use in 2015 through 2017 final rule, which modified Stage 2 requirements to streamline reporting requirements on measures that had become redundant, duplicative, or topped out.

• Stage 3 was established in 2017 as a result of the 2015 final rule and focuses on using CEHRT to improve health outcomes.