Electronic Prescribing: CMS Should Address Inconsistencies in Its Two Incentive Programs That Encourage the Use of Health Information Technology
Released: 2011-02-17T00:00:00

Letter

Background

HHS and others have promoted electronic prescribing as one way to improve the quality of health care that beneficiaries receive and as one way to reduce costs. Health care costs are typically paid for by health care payers, such as CMS in the Medicare Program. In traditional, or paper- based, prescribing, health care providers that are licensed to issue prescriptions for drugs (e.g., physicians or physician assistants in some states) write a prescription, and the beneficiary takes that prescription to a dispenser (e.g., pharmacy) to be filled. In contrast, electronic prescribing consists of a licensed health care provider using a computer or hand-held device to write and transmit a prescription directly to the dispenser. Before doing so, the health care provider can request the beneficiary’s eligibility, formulary, benefits, and medication history. This information can be used to improve quality and reduce costs. For example, a health care provider can use this information to avoid potentially adverse drug events such as drug-to-drug or drug-to-allergy interactions and to prescribe less-expensive medications, such as lower-cost generic drugs. Figure 1 illustrates the flow of information during the electronic prescribing process and identifies areas in this process that may result in improvements in the quality of health care provided to beneficiaries and reductions in costs to health care payers. Appendix II provides information from studies measuring whether or to what extent electronic prescribing improves quality or reduces costs.

Eligibility for the Electronic Prescribing and EHR Programs

The types of Medicare providers eligible to earn incentive payments or who may be subject to penalties in the EHR and Electronic Prescribing Programs were established in statute, and although they overlap they are not identical. Specifically, only physicians, who are the largest population among each program’s eligible providers, can earn incentive payments or be subject to penalties from both programs, but they cannot receive incentive payments or be subject to penalties from both programs during the same year. Other health care providers, such as nurse practitioners and physician assistants, are only eligible to receive incentive payments or are subject to penalties from the Electronic Prescribing Program. (See fig. 2.)

Incentive Payments and Penalties in the Electronic Prescribing and EHR Programs

There is some overlap in the time frames for incentive payments and penalties for the Electronic Prescribing and EHR Programs. Incentive payments for the Electronic Prescribing Program are available from 2009 through 2013. Incentive payments for the EHR Program begin in 2011 and may be available until 2016, depending on which calendar year the provider initially receives an incentive payment from the program. Incentive payments for both programs are determined by multiplying the provider’s total allowed charges for provider services covered by Medicare Part B for the year by the incentive percent authorized by statute. However, in the EHR Program the year in which the provider first adopts and meaningfully uses the EHR technology determines the maximum annual incentive payment a provider can earn and the total number of years incentive payments are available. For both programs, incentive payments are disbursed after providers demonstrate that they met the applicable program requirements. Figure 3 displays the timeline and maximum incentive payments and penalties for both programs. (App. IV provides additional detail on the annual and total incentive payments an eligible provider could receive from the EHR Program based on the initial year the provider receives an incentive payment.) By law, providers cannot receive an incentive payment for both programs during the same year.

Penalties for the Electronic Prescribing Program and the EHR Program may be automatically applied to providers that fail to meet the programs’ requirements. Penalties for the Electronic Prescribing Program begin in 2012 and end after 2014. Penalties for the EHR Program begin in 2015, and there is no statutory end-point provided for when the penalties will end. Since the Electronic Prescribing Program ends after 2014 and penalties for the EHR Program do not begin until 2015, providers will not receive penalties from both programs during the same year. However, providers who are subject to penalties from the Electronic Prescribing Program in 2014 and who are subject to penalties from the EHR Program in 2015 will face a higher penalty from the EHR Program—2 percent instead of 1 percent. Similar to the incentive payments, penalties for not adopting a program’s technologies are also calculated by multiplying the provider’s total allowed charges for provider services covered by Medicare Part B by the penalty percent authorized by statute. Penalties will be assessed by reducing the reimbursement that the provider would ordinarily receive for furnishing Part B services by the applicable penalty percentage.

The amount of incentive payments or penalties eligible providers may receive depends on the year in which the provider chooses to begin participating in—that is, meeting the requirements of—either or, if eligible, both programs. In general, the earlier a provider begins participating in the program, the more incentive payments the provider will earn and the fewer penalties the provider will be assessed. Figure 4 below presents three scenarios of participation in the Electronic Prescribing and EHR Programs between 2009 and 2018. In each scenario, we assume that the provider is eligible for both programs and has $24,000 in total allowed Medicare Part B charges each year.

Reporting Requirements for the EHR Program

CMS will develop the reporting requirements that providers will have to meet for the EHR Program in three stages. To date, CMS has only developed the reporting requirements that eligible providers will have to meet to receive incentive payments for the first stage, which will apply to providers first obtaining incentive payments from the EHR Program from 2011 through 2014. By the end of 2011, CMS expects to develop reporting requirements for receiving incentives in the second stage and, by the end of 2013, develop reporting requirements for receiving incentives in the third stage. CMS has stated that it may include information on the reporting requirements that eligible providers must meet to avoid penalties at the same time it issues regulations describing the third-stage requirements. CMS intends to make the reporting requirements more stringent over time as EHR technology and providers’ use of that technology becomes more sophisticated.

To receive an incentive payment for the EHR Program, eligible providers must meet or exceed a total of 20 reporting requirements established by CMS. Of the 20 reporting requirements, 15 are mandatory, and providers must choose an additional 5 from a menu of 10 other reporting requirements. The reporting requirements encompass a variety of activities related to the delivery of health care to encourage providers to capture the following types of information in their EHR systems: patient demographics and clinical conditions, use of clinical decision support, and the coordination of care across health care settings. See app. V for a complete list of the stage-one reporting requirements for receiving incentive payments.

The reporting requirements that CMS develops for the second and third stages of the EHR Program may be influenced by the Patient Protection and Affordable Care Act of 2010 (PPACA), which directed CMS to develop a plan to integrate the reporting requirements used in the EHR Program with the information that CMS collects from eligible providers in the Physician Quality Reporting System (PQRS). Similar to the EHR and Electronic Prescribing Programs, CMS, as directed by Congress, implemented PQRS to provide incentive payments to eligible providers who satisfactorily reported data on various quality measures and impose penalties on those providers who did not. Specifically, PPACA directed CMS to develop an integration plan by January 1, 2012, that would identify reporting requirements that could be used to demonstrate meaningful use for the EHR Program and also be used to demonstrate quality of care provided to individuals for PQRS.

CMS Analyzed Medicare Part B Claims to Pay Electronic Prescribing Program Incentive Payments to about 8 Percent of Certain Medicare Providers for 2009

To determine which providers should receive the Electronic Prescribing Program’s incentive payments, CMS analyzes information reported by providers on their Medicare Part B claims, which are used to submit charges for covered services. To determine which providers are subject to penalties, which begin in 2012, CMS will also analyze information reported by providers on their Part B claims, but the requirements for avoiding penalties are different than those for obtaining incentive payments. In 2009, CMS paid incentive payments to about 8 percent of certain Medicare providers—that is, of the over 597,000 Medicare providers who had at least one applicable visit during 2009—and another 7 percent of those same Medicare providers participated in the Electronic Prescribing Program but did not receive incentive payments.

CMS Analyzes Information Reported by Providers on Part B Claims to Determine Which Providers Should Receive Incentive Payments and Avoid Penalties

Incentive payments for the Electronic Prescribing Program are available from 2009 through 2013, and to determine which providers meet the program’s requirements and should receive the payments, CMS analyzes information reported by providers on their Part B claims. Specifically, for 2009, CMS first examined 2009 Part B claims to determine whether, after each applicable patient visit, providers marked any one of three electronic prescribing reporting codes used to report information on the adoption and use of electronic prescribing systems. For 2009, the three electronic prescribing reporting codes were: the provider had a qualified electronic prescribing system and used it to generate all prescriptions during the visit; the provider had a qualified electronic prescribing system but did not use it to generate one or more prescriptions during the visit for one of the following reasons: the patient requested a paper prescription, the pharmacy could not receive an electronic transmission, or the prescription was for a narcotic or other controlled substance and could therefore not be electronically prescribed; and the provider had a qualified electronic prescribing system but did not generate any prescriptions during the visit.

By submitting any one of the three electronic prescribing reporting codes to CMS, providers attested that they met the program’s technology requirement by adopting a qualified electronic prescribing system and are eligible to earn incentive payments from the program.

Second, CMS analyzed the 2009 Part B claims to determine which of the providers who submitted the electronic prescribing reporting codes also met or exceeded both components of the following reporting requirement: the provider submitted one of the three electronic prescribing reporting codes at least 50 percent of the time that the provider had an applicable visit; and at least 10 percent of the provider’s total allowed Medicare Part B charges for the year were from the services designated as applicable patient visits.

If the provider met or exceeded the reporting requirement, CMS gave the provider an incentive payment for 2009, which the agency calculated as 2 percent of the provider’s total allowed Medicare Part B charges for the year and by applying a small adjustment factor.

For 2010, to increase the adoption of electronic prescribing technology, CMS made some changes to the Electronic Prescribing Program’s reporting requirement that providers had to meet in order to receive an incentive payment. CMS eliminated the three electronic prescribing reporting codes for 2009 and replaced them with a single code for providers to submit to CMS. The new code indicates that after each applicable visit the provider generated and transmitted at least one prescription during the visit using a qualified electronic prescribing system. The agency stated that it believed that this change would simplify reporting. CMS also changed the first portion of the reporting requirement related to how frequently providers must submit the new electronic prescribing code in order to receive an incentive payment. Instead of requiring that providers submit the electronic prescribing reporting code at least 50 percent of the time that they had an applicable visit—the requirement in 2009—CMS required that an individual provider submit the new electronic prescribing reporting code for at least 25 visits. CMS noted that the agency believes that meeting the 2010 reporting requirement is achievable by a majority of eligible providers. If providers participated in the Electronic Prescribing Program as a group practice containing 200 or more providers—a new option in 2010—the practice had to submit the electronic prescribing reporting code for at least 2,500 applicable visits before all of the providers in the practice could receive incentive payments. When it proposed the change to at least 25 and at least 2,500 visits for individual providers and group practices, respectively, CMS noted that it assumed that once a provider has invested in an electronic prescribing system, integrated the use of that system into the practice’s work flows, and used that system to some extent, the provider is likely to continue to use the electronic prescribing system for most of the prescriptions generated. The other component of the reporting requirement remained unchanged from 2009: at least 10 percent of the provider’s or practice’s total allowed Medicare Part B charges for the year were from the services designated as applicable visits. Finally, as an individual or as part of a group practice, providers could report the electronic prescribing code on their Part B claims, as they did in 2009, or they could do so using one of two alternative reporting mechanisms CMS created.

CMS has described how it will determine which providers should receive incentive payments for 2011, but the agency has not yet indicated how it will determine which providers should receive incentive payments for 2012 or 2013. CMS will determine which providers meet the program’s requirements and should receive an incentive payment in 2011 generally using the same methods the agency used in 2010. However, one important change CMS made for 2011—one that is consistent with changes the agency is making to PQRS—is that CMS expanded the definition of group practice to include practices containing 2 through 199 individuals and will require those group practices to report the electronic prescribing code for a minimum of between 75 and 1,875 applicable visits, depending on the size of the group practice. The requirement for group practices of 200 or more providers is unchanged; those practices must report the code for at least 2,500 applicable visits.

From 2012 through 2014, the Electronic Prescribing Program will assess penalties on individual providers and group practices that do not adopt and use electronic prescribing. To avoid these penalties in 2012, individual providers and group practices will have to meet certain reporting requirements. Individual providers will have to submit the electronic prescribing reporting code on their Part B claims for at least 10 applicable visits between January 1, 2011, and June 30, 2011. However, CMS will not penalize certain individuals in 2012 if they do not prescribe or do so infrequently. In addition, both individual providers and groups that practice in rural areas or areas with a limited number of pharmacies that accept electronic transmissions will be exempt from penalties. The reporting requirement for individuals and the exemption criteria are consistent with the agency’s statement that it does not want to penalize providers with low prescribing volumes. Group practices will have to submit the electronic prescribing reporting code on their Part B claims the same number of times required to receive incentive payments in 2011, but they must do so within the 6-month period from January 1, 2011, through June 30, 2011. For example, group practices containing 200 or more providers will have to submit the electronic prescribing reporting code at least 2,500 times from January 1, 2011, through June 30, 2011. CMS has noted that it did not think that group practices would be disadvantaged by having to meet the reporting requirement in a 6-month period to avoid the penalty in 2012 rather than in a 12-month period to earn an incentive in 2011 because the agency requires group practices to submit the electronic prescribing reporting code fewer times on average to earn an incentive payment than it requires for individual providers to submit to earn an incentive payment.

CMS has not yet established all the requirements for providers to avoid penalties in 2013 or 2014. However, for 2013, CMS has indicated that it will not penalize individual providers or group practices that year if they reported the electronic prescribing code the minimum number of times required to qualify for incentive payments in 2011. Additionally, CMS indicated that it may publish an alternative reporting requirement that providers could meet to avoid penalties in 2013. A CMS official that we interviewed told us that the agency could, for example, require individual providers to submit the electronic prescribing reporting code at least 10 times between January 1, 2012, and June 30, 2012, in order to avoid penalties in 2013.

CMS is exploring an alternative to using electronic prescribing code submissions to determine which providers should receive incentive payments or penalties. As a part of CMS’s Medicare Part D, which provides outpatient prescription drug benefits for Medicare beneficiaries, CMS has required that Part D plan sponsors submit additional data on the claims they send to Medicare for reimbursement. CMS officials believe that Medicare Part D data could be used at some point instead of the electronic prescribing reporting code to determine which providers should receive incentive payments. However, CMS officials have concerns about the reliability of data from Part D claims, and note that these concerns should be resolved before the data can be used. CMS does not have specific plans or a time frame for implementing such a change.

CMS Paid about 8 Percent of Certain Medicare Providers Electronic Prescribing Program Incentive Payments for 2009

CMS paid Electronic Prescribing Program incentive payments for 2009 to about 8 percent (about 47,500) of the over 597,000 Medicare providers who had at least one applicable visit during 2009. Each of these approximately 47,500 providers received incentive payments equal to 2 percent of their total allowable Medicare Part B charges in 2009, with payments totaling approximately $148 million. The mean payment was about $3,120, the median payment was about $1,700, and the five highest payments were between about $54,500 and $67,500. CMS disbursed these payments to providers for 2009 in September and October 2010. CMS officials expect that the number of Medicare providers reporting the electronic prescribing reporting code in 2010 will increase over 2009 and noted that lowering the reporting requirement for 2010 to submitting the applicable electronic prescribing reporting code for at least 25 visits may increase the number of providers receiving incentive payments. CMS officials also told us that the penalties, which do not begin until 2012, might have a bigger effect on participation than the incentive payments.

For the 2009 Electronic Prescribing Program, the percentage of Medicare providers who received incentive payments and the average incentive payment varied by state. (See fig. 5 and fig. 6.) Although Minnesota and Wisconsin had the largest share of providers receiving incentive payments at about 17 and 15 percent, respectively, providers in those two states also received the lowest mean incentive payment at about $740 and $1,500, respectively. Alaska and North Dakota had the smallest share of providers receiving incentive payments at about 2 percent each. Providers in Florida and South Carolina had the highest mean incentive payments at about $5,800 and $4,700, respectively. According to a report prepared for CMS about the 2009 Electronic Prescribing Program, the physician specialties with the largest number of providers that earned incentive payments were family practice and internal medicine, and the nonphysician specialties with the largest number of providers that earned incentive payments were nurse practitioners and physician assistants.

About 87,500 Medicare providers—approximately 15 percent of Medicare providers who had at least one applicable visit during 2009—participated in the program in 2009 by reporting the electronic prescribing reporting codes to CMS. However, about 40,000 of those participating providers— approximately 7 percent of Medicare providers who had at least one applicable visit during 2009—did not receive incentive payments because they did not meet or exceed both components of the reporting requirement. (See fig. 7.) Specifically, these providers (a) submitted the electronic prescribing reporting codes less than 50 percent of the time that they had an applicable visit, (b) had less than 10 percent of their total allowed Medicare Part B charges for the year from the services designated as applicable visits, or (c) both (a) and (b) occurred. The vast majority of the about 40,000 Medicare providers that participated in the program but did not receive incentive payments submitted the electronic prescribing escribing codes less than 50 percent of the time they had an applicable visit. codes less than 50 percent of the time they had an applicable visit.

While the Requirements in the EHR and Electronic Prescribing Programs Are Similar in Some Cases, Aspects of These Requirements Are Not Consistent

We compared the electronic prescribing–related technology and reporting requirements in the EHR Program with the requirements in the Electronic Prescribing Program. The EHR Program provides incentives from 2011 to 2016 and introduces penalties beginning in 2015, while the Electronic Prescribing Program provides incentives from 2009 to 2013 and introduces penalties beginning in 2012. In comparing the programs’ requirements, we found some similarities but also areas where the requirements of the programs are not consistent.

Technology requirement. Both the EHR and Electronic Prescribing Programs require eligible providers to adopt and use technology that meets certain requirements. The EHR Program requires providers to adopt certified EHR technology and the Electronic Prescribing Program requires providers to adopt qualified electronic prescribing systems. (For more details, see fig. 8.)

Certified EHR systems and qualified electronic prescribing systems must be able to perform similar electronic prescribing–related activities. For example, both types of systems must be able to generate and transmit prescriptions electronically, check for potential drug and allergy interactions, and provide formulary information.

The technology that providers must adopt and use for the EHR Program must pass a certification process, which is used to designate a technology as having met the program’s technology requirements. For the EHR Program, HHS’s ONC, through the work of several advisory committees, established a set of standards and specifications for EHR technology and then created a program that will certify EHR technology for use in the EHR Program based upon those standards and specifications. According to ONC’s Web site, the certification process will ensure that the EHR technology that providers adopt and use has the technological capabilities necessary for providers to obtain incentive payments or avoid penalties from the EHR Program. Further, the agency notes that certifying EHR technology to these standards enhances the interoperability of health information technology—that is, the ability of different systems or components to exchange information and to use the information that has been exchanged. EHRs that conform to interoperability standards allow health information to be created, managed, and consulted by authorized health care providers across more than one health care organization, thus providing patients and their caregivers the necessary information required for optimal care.

The EHR Program’s certification process is designed to produce a list of certified EHR systems and certified EHR modules, which ONC has made available to the public on its Web site. Accordingly, this information should allow providers to identify and adopt systems that meet the EHR Program’s technological requirements. A module is a component of an EHR system that meets at least one of the certification criteria established by ONC. Individual EHR modules can be certified and integrated with other certified EHR modules to form a complete, certified EHR system. At the time of our review, technologies certified for use in the EHR Program—that is, complete EHR systems or combinations of modules that collectively can perform the capabilities that constitute a qualified electronic prescribing system—appeared to also meet the Electronic Prescribing Program’s technological requirements. Although according to ONC officials, certified EHR technology is not required to provide information on lower-cost alternatives—which is a component of the Electronic Prescribing Program’s technology requirement—CMS has indicated that an electronic prescribing system that does not conform to that component of the Electronic Prescribing Program’s technology requirement would still meet the definition of a qualified system in 2011 and until this function is more widely available in the marketplace.

Although providers seeking incentive payments or trying to avoid penalties from the Electronic Prescribing Program must adopt and use qualified electronic prescribing systems, according to a CMS official the Electronic Prescribing Program does not have a process like the EHR Program’s to identify and certify which electronic prescribing systems meet the requirements of a qualified system. As a result, providers may not be certain which systems meet the program’s technological requirement.

Reporting requirements. Both the EHR Program and Electronic Prescribing Program require eligible providers to report certain information about their electronic prescribing activities to CMS in order to receive incentive payments, which began in 2009 for the Electronic Prescribing Program and began in 2011 for the EHR Program. (See fig. 9 for a summary of the two programs’ electronic prescribing–related reporting requirements.) However, we also found that the electronic prescribing–related reporting requirements in the EHR Program are more rigorous. Providers seeking incentive payments from the EHR Program have at least five reporting requirements related to electronic prescribing, while providers in the Electronic Prescribing Program h Moreover, the EHR Program requires only one reporting requirement. providers to report more-detailed information—namely, information on their use of various electronic prescribing–related technological capabilities—a requirement that should increase their use of these capabilities. Additionally, while CMS has established reporting ave requirements providers must meet in order to avoid the penalties under the Electronic Prescribing Program that begin in 2012, CMS has not yetidentified what providers must report in order to avoid penalties under the EHR Program, but plans to do so in future rulemakings.

We also found that the two programs’ reporting requirements are not consistent because they make certain Medicare providers subject to both programs’ reporting requirements during the same year. Specifically, physicians—the largest population among each program’s eligible providers—may choose to participate in the EHR Program in 2011 because the potential incentive payment will likely be higher under that program than under the Electronic Prescribing Program in 2011. However, to avoid the penalty assessed by the Electronic Prescribing Program in 2012, CMS will require physicians to meet the Electronic Prescribing Program’s reporting requirement in 2011, even if they elect to participate in the EHR Program in 2011. Public comments on the agency’s proposed requirements for the 2011 Electronic Prescribing Program included the concern that providers are burdened by having to submit electronic prescribing data more than once. In response, CMS stated that it will study possible methods of aligning the two programs and will include this information in the integration plan it is already required to develop by January 1, 2012, to integrate the reporting requirements in the EHR Program and PQRS, CMS’s quality measures program. However, if CMS adheres to this schedule, the agency will not be able to remove the reporting burden placed on physicians subject to penalties from the Electronic Prescribing Program in 2013, given that the requirements for avoiding penalties in 2013 would likely be proposed in July 2011 and finalized in November 2011. If CMS includes possible methods of aligning the two programs in the integration plan, any action to propose and finalize requirements will take place sometime after January 1, 2012, well beyond the date for making changes to the program in 2013. In technical comments provided on a draft of this report, HHS noted that it plans to include possible methods of aligning the two programs for the 2012 program year (and possibly for the 2013 program year) in rulemaking during 2011.

Both the EHR Program and Electronic Prescribing Program require providers seeking incentive payments to attest that they have met the programs’ reporting requirements. In the EHR Program, providers will submit the results of their performance on each of the reporting requirements once per program year, while providers in the Electronic Prescribing Program attest that they adopted and used a qualified electronic prescribing system by reporting the electronic prescribing code to CMS. At least with reference to the EHR Program, CMS has acknowledged that attestation may create a potential for fraud and abuse and noted that the agency is developing an audit strategy to address this risk. CMS officials from the Office of E-Health Standards and Services told us they plan to make guidance on this strategy available by May 2011.

In the case of the Electronic Prescribing Program, an official from CMS’s Office of Clinical Standards and Quality, which administers that program, told us that the agency did not audit electronic prescribing codes submitted by providers for 2009 and does not have plans to develop an audit strategy for the program. However, this official did tell us that CMS reserves the right to audit any program participant.

Conclusions

Health information technology, such as electronic prescribing, has the potential to improve the quality of care received by patients and also reduce costs for the health care system. To help encourage the adoption of such technologies among Medicare providers, Congress first established the Electronic Prescribing Program and then the EHR Program, both of which provide incentive payments to eligible providers that adopt and use the appropriate health information technologies and impose penalties on those eligible providers that fail to do so.

Despite both programs having a goal to expand the adoption and use of health information technologies by health providers, and in particular, physicians—the largest and only group of providers eligible to earn incentive payments in both programs—we found inconsistencies in the requirements. We believe these inconsistencies may limit the programs’ effectiveness in encouraging the use of health information technologies. First, we found that because the Electronic Prescribing Program lacks a certification process like that established for the EHR Program, physicians and other health care providers who want to obtain incentive payments or avoid penalties from the former program have no assurance that the systems they invest in will meet that program’s technology requirements. In contrast, physicians who invest in certified EHR systems can be assured that in doing so they would meet the current requirements of both programs. In addition, physicians that invest in certified EHR modules integrated together to perform the electronic prescribing–related capabilities could also be assured that they meet the current requirements of the Electronic Prescribing Program and that the adopted technology could later be integrated with other certified modules to form a complete, certified EHR system. This inconsistency between the programs has the potential to create uncertainty among physicians as to what technology they should adopt, because although the Electronic Prescribing Program ends after 2014, the EHR Program continues; encouraging physicians to adopt certified electronic prescribing technology now may also help facilitate their later transition between the programs. Nonphysician health care providers who are not eligible to earn incentive payments from the EHR Program could adopt certified technology and in so doing could have assurance that the electronic prescribing technology they invest in meets the Electronic Prescribing Program’s technology requirements. Second, we also found that the two programs have established separate reporting requirements related to electronic prescribing, requiring some physicians who elect to report to the EHR Program to report to both programs in 2011 and potentially requiring physicians to report to both programs through 2014, when penalties for the Electronic Prescribing Program end. CMS recognizes that this duplication places additional burden on physicians, and we believe this duplication could affect the decision of physicians to adopt and use health information technology. However, CMS is still in the process of studying possible ways to address this duplication, and if the agency wants to eliminate the burden for providers in 2012, it would need to do so during its 2011 rulemaking. In addition, CMS has not been consistent in the steps it has taken to ensure the appropriate use of these programs’ resources. Namely, CMS plans to establish an audit program for the EHR Program—under which the maximum incentive payment for a provider will generally not exceed $18,000 per year—to address potential fraud and abuse that might arise from the use of self- attestations, but CMS does not have plans to develop a similar approach in the Electronic Prescribing Program, under which CMS paid providers up to approximately $67,500 for 2009.

The Electronic Prescribing Program began before the EHR Program, so CMS has already had the opportunity to encounter and learn from challenges in implementation. For example, in the first year of the Electronic Prescribing Program, only about 8 percent of providers received incentive payments, and CMS changed some of the program’s requirements in the second year to encourage greater adoption and use of electronic prescribing technology. For the EHR Program, it is too soon to know how many providers will adopt EHR systems. However, given that the electronic prescribing–related reporting requirements in the EHR Program are more rigorous than the reporting requirement in the Electronic Prescribing Program, CMS may find that it needs to modify the EHR Program requirements to better encourage the adoption and use of EHR systems. Because implementation of the Electronic Prescribing Program preceded the EHR Program, CMS has an opportunity to use the experiences gained in implementing the Electronic Prescribing Program to inform its implementation of the EHR Program in order to determine how to best encourage the adoption and use of health information technology among Medicare providers. One approach could be to incorporate these experiences into the integration plan the agency is already required to develop by January 1, 2012, to integrate the reporting requirements in the EHR Program and PQRS.

Recommendations for Executive Action

To help improve the effectiveness of the Electronic Prescribing and EHR Programs to encourage the adoption of health information technologies among Medicare providers, the Administrator of CMS should take the following three actions: Encourage physicians and other health care providers in the Electronic Prescribing Program to adopt certified electronic prescribing technology.

Expedite efforts to remove the overlap in reporting requirements for physicians who may be eligible for incentive payments or subject to penalties under both the Electronic Prescribing and EHR Programs by, for example, aligning the reporting requirements so that successfully qualifying for incentive payments or for avoiding penalties under the EHR Program would likewise result in meeting the requirements for the Electronic Prescribing Program.

Identify factors that helped or hindered implementation of the Electronic Prescribing Program to help support the ongoing implementation of the EHR Program. CMS could include consideration of such factors in the integration plan that the agency is required to develop by January 1, 2012.

To help ensure that Electronic Prescribing Program resources are used appropriately, the Administrator of CMS should develop a risk-based strategy to audit a sample of providers who received incentive payments from the Electronic Prescribing Program to help ensure that providers who receive incentive payments meet that program’s requirements. A risk- based strategy could, for example, focus on those providers who received larger incentive payments.

Agency and External Party Comments and Our Evaluation

We obtained written comments on our draft report from HHS on behalf of CMS, which are reprinted in appendix VI. CMS agreed in full with two recommendations, agreed in principle with one recommendation, and disagreed with a fourth recommendation.

CMS disagreed with our first recommendation that the agency direct providers in the Electronic Prescribing Program to use technology certified as an EHR system or module(s). While CMS said that it concurred with the notion that eligible providers should be able to use certified EHR systems for the Electronic Prescribing Program, it did not agree that it should direct eligible providers to use prescribing technology that has been certified as an EHR system. CMS said that doing so could result in Electronic Prescribing Program participants having to replace their qualified electronic prescribing systems with systems certified under the EHR Program. We do not recommend that CMS direct those providers who are already participating in the Electronic Prescribing Program to replace their current systems with certified systems. On the contrary, the intent of our recommendation is to have CMS encourage providers in the Electronic Prescribing Program who have not yet adopted electronic prescribing systems, or who plan on upgrading their existing systems, to choose systems that have already been certified through the EHR Program’s certification process. We continue to assert our recommendation because, as we noted in our draft report, this certification process identifies a list of available systems that meet the certification requirements and provides assurance that the technology physicians and other health care providers adopt would meet the technology requirements of the Electronic Prescribing Program. Additionally, the physicians who later participate in the EHR Program could be assured that the technology also meets the requirements in the EHR Program. In our draft report, we noted that there is no comparable process in the Electronic Prescribing Program, and as a result, providers have no assurance that the systems they invest in for the EHR Program will meet that program’s technology requirements. Given that the Electronic Prescribing Program ends after 2014 while the EHR Program will continue, encouraging providers to adopt certified electronic prescribing technology now may also help facilitate physicians’ transition between the programs. We have clarified the recommendation to state that CMS should encourage physicians and other health care providers in the Electronic Prescribing Program to adopt certified electronic prescribing technology.

CMS agreed with our second recommendation that it expedite efforts to remove the overlap in reporting requirements for physicians eligible for both programs, and noted that it plans to address this overlap in rulemaking during 2011, where applicable. We support CMS’s efforts to expeditiously remove the overlap in the reporting requirements as we recommended.

CMS agreed with our third recommendation that it would be helpful for the agency to identify factors that helped or hindered implementation of the Electronic Prescribing Program to help support the ongoing implementation of the EHR Program. While CMS identified factors that may be affecting implementation of electronic prescribing, other factors that may have broader applicability to the implementation of the EHR Program could include the effect of penalties on technology adoption, measuring compliance with program requirements, and validating self- reported attestations.

CMS agreed in principle with our fourth recommendation that CMS develop a risk-based strategy to audit a sample of providers who received incentive payments from the Electronic Prescribing Program. In response CMS said that it agrees that an audit of a sample of providers may be needed, however, it disagreed that such a strategy should necessarily focus on eligible providers who received large incentive payments, noting that such an audit process, if implemented, could select providers at random. As we recommended, we believe that an audit strategy should be implemented for this program. We recommended a risk-based audit strategy because although many providers received modest incentive payments in 2009, some providers received payments at least three times as high as the maximum annual incentive payment in the EHR Program. However, if implemented by CMS, a random audit would be consistent with the intent of our recommendation. CMS also noted that because it is considering using Part D data in the future to determine which providers should receive incentive payments for this program, use of these data could also alleviate the need for an audit. However, as we noted in our draft report, CMS officials raised several concerns—concerns echoed in its comments on our draft report—about the reliability of Part D data to determine which providers receive incentive payments. As we reported, CMS officials told us that these data reliability concerns should be resolved before Part D data can be used to determine which providers should receive incentive payments for this program.

HHS has also provided technical comments, which we incorporated as appropriate. We also provided excerpts of our report to the VA, Blue Cross Blue Shield of Massachusetts, CVS Caremark, the Florida Agency for Health Care Administration, and organizations that participated in the Southeastern Michigan ePrescribing Initiative, which provided technical comments that we incorporated as appropriate.

We are sending copies of this report to the Secretary of HHS, the Administrator of CMS, and the National Coordinator for Health Information Technology in HHS and interested congressional committees. In addition, the report will be available at no charge on the GAO Web site at http://www.gao.gov.

If you or your staffs have questions about this report, please contact me at (202) 512-7114 or at kohnl@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix VII.

Appendix I: List of Committees

Appendix II: Effect of Electronic Prescribing on Quality or Cost

This appendix addresses congressional interest in how others have measured whether or to what extent electronic prescribing improves quality or reduces cost. For example, the Medicare Improvements for Patients and Providers Act of 2008 (MIPPA) directed us to report on information related to reductions in avoidable medical errors and estimated savings to Medicare resulting from the use of electronic prescribing. To address these issues, we obtained information from organizations about research they conducted, funded, or participated in that measured the effects of electronic prescribing on quality, cost, or both. Specifically, we obtained information from the following organizations: Blue Cross Blue Shield of Massachusetts, CVS Caremark, the Florida Agency for Health Care Administration, and the Southeastern Michigan ePrescribing Initiative. In addition, we reviewed 29 published studies that measured the effects of electronic prescribing on quality, cost, or both.

Our information collection, review of published studies, and summaries contained in this appendix focused on specific aspects of quality and cost that we believed were most similar to the policy goals underlying the development of the Electronic Prescribing Program and the Electronic Health Records (EHR) Program.

Quality. We included studies that reported findings related to beneficiary quality, such as reductions in avoidable medical errors.

Cost. We included studies that reported findings related to savings to health care payers, which are those parties generally responsible for paying claims for health care services, because we believed they would be the most applicable to determining the effects of electronic prescribing on costs for Medicare. We did not review studies that estimated potential savings for providers, such as savings associated with reductions in time spent writing prescriptions or resolving questions about prescriptions.

The studies evaluated the effects of a variety of different types of electronic prescribing technology, such as stand-alone electronic prescribing systems and EHR systems that include electronic prescribing– related functions. According to the Healthcare Information and Management Systems Society (HIMSS), EHR systems also typically include information such as patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports. Additionally, computerized physician order entry (CPOE) systems (also referred to as computerized provider order entry systems or computerized prescriber order entry systems) allow for electronic ordering of medications and may include other functions, such as ordering laboratory procedures and referrals. Hospitals may employ CPOE systems as part of a strategy to reduce medication errors. Some organizations and published studies evaluated the effects of electronic prescribing systems that had clinical decision support (CDS) capabilities, which can include checks for allergies, drug– drug interactions, overly high doses, clinical conditions, and other patient- specific dose checking, and can provide access to information on patient medical histories, pharmacy eligibility, and formulary and benefits. It is important to note that the electronic prescribing systems evaluated by the organizations we obtained information from and published studies we reviewed may have had technical capabilities that differ from the technological requirements in the Electronic Prescribing Program or the EHR Program.

Methodology

The studies utilized a variety of different methodologies, including the following: (1) pre-post methodologies, which compare dimensions of quality or cost before and after the implementation of electronic prescribing systems or CPOE systems; (2) comparison methodologies, which are used to compare dimensions of quality, cost, or both between a control group (i.e., one that does not electronically prescribe) and an intervention group (i.e., one that does electronically prescribe); and (3) cost simulations and cost-benefit analyses that projected the costs and savings of implementing electronic prescribing systems.

How Electronic Prescribing Was Determined

Some studies identified compared a population of providers that electronically prescribed to a population that did not (e.g., handwrote prescriptions). For example, some studies identified a population of providers who had access to electronic prescribing systems and compared them to a population of other providers who did not have access to electronic prescribing systems, while other studies identified prescriptions before CPOE implementation and compared those prescriptions to prescriptions transmitted after CPOE implementation. Other studies only looked at populations of providers known to be electronic prescribers. Other studies were designed to evaluate the effect of advanced features of the electronic prescribing system. For example, one study by Steel et al. was designed to compare medication ordering behavior when no alert was triggered by the CPOE system to ordering behavior after alerts were triggered.

Outcomes Measured

The organizations we interviewed and published studies we reviewed examined a variety of different outcomes in order to evaluate the effect on quality, cost, or both. Examples of the outcomes measured to evaluate the effect of electronic prescribing on health care quality include the following: medication order changes resulting from information provided by the electronic prescribing system, such as alerts for potentially inappropriate medications or formulary information, or changes resulting from problems with the quality of the prescription such as errors identified by the electronic prescribing system related to dosage, directions, or illegibility; changes in potential or actual adverse drug events (ADE); and provider satisfaction that the electronic prescribing system was improving safety.

Examples of the outcomes measured to evaluate the effect of electronic prescribing on cost include the following: drug costs or other outcomes that have cost implications, such as formulary compliance or generic utilization; and follow-up health care costs resulting from reductions in adverse drug events.

Reported Findings

In terms of health care quality, some studies found differences in medication error rates when electronic prescribing was used. For example, a study conducted by Weingart et al. and funded by Blue Cross Blue Shield of Massachusetts estimated that medication safety alerts prevented an estimated 402 ADEs (49 serious or life threatening, 125 significant, and 228 minor) and that alerts that resulted in physicians canceling or changing the medication order may have prevented deaths in 3 cases, permanent disability in 14 cases, and temporary disability in 31 cases. Another study by Devine et al. reported that rates of errors in prescriptions declined from 18.2 percent before to 8.2 percent after implementation of a CPOE system. However, some studies found no significant differences in medication error rates before and after the implementation of electronic prescribing systems.

Some of the evaluations that focused on prescription drug costs showed savings when electronic prescribing systems were used. For example, a cost-benefit analysis conducted by Byrne et al. estimated that the use of Veterans Health Information Systems and Technology Architecture (VistA), which includes electronic prescribing and CDS capabilities of the Department of Veterans Affairs (VA) health system electronic health records, contributed to a cumulative $4.64 billion in value due to the prevention of unnecessary hospitalizations and outpatient visits resulting from prevented ADEs. In this study, the total net value of the VA’s investments in the VistA components modeled was estimated to exceed $3.09 billion. A study by McMullin et al. of an electronic prescribing system that provided patient formulary information shifted prescriber behavior from selecting drugs from eight high-cost therapeutic groups to less- expensive alternatives. However, a study by Ross et al. found no significant difference in formulary compliance between electronic prescribers (83.2 percent) and paper prescribers (82.8 percent).

Of the studies we reviewed in which the electronic prescribing systems were reported to have CDS capabilities—such as drug–drug, drug–allergy alerts, or drug–formulary checks—most reported health care quality or cost effects. For example, a study by DesRoches et al. reported that providers who adopted EHR with electronic prescribing decision support capabilities averted potentially dangerous drug–drug interactions. One study by Galanter et al. found that the likelihood of contraindicated drugs being administered to patients of inadequate kidney function decreased by 42 percent after electronic prescribing CDS alerts were implemented. Ko et al. surveyed providers and found that the majority viewed drug–drug interaction alerts as increasing their potential to more safely prescribe medications. Another study by Kaushal et al. attributes the implementation of a CPOE with CDS as leading to an estimated $28.5 million in savings— $12.9 million from decreased adverse drug events and $6 million from decreased drug costs—however, the study also estimated that the cost to develop, implement, and operate the CPOE system was $11.8 million.

Summaries of Evaluations Obtained from Organizations Blue Cross Blue Shield of Massachusetts Beginning in 2003, Blue Cross Blue Shield of Massachusetts contracted with software vendors to provide electronic prescribing software, which included CDS, free of charge to high-volume prescribers in their provider network. Blue Cross Blue Shield of Massachusetts continues to sponsor a limited number of electronic prescribing software licenses free of charge. As of September 2010, Blue Cross Blue Shield of Massachusetts estimated that 60 percent of its network physicians were electronically prescribing.

A pre-post study comparing 1,932 Blue Cross Blue Shield of Massachusetts’s providers that were using an electronic prescribing device to the providers in the network that were not electronically prescribing (control group). The preintervention period was calendar year 2003 and the postintervention period was 2006.

Whether the prescriber used an electronic prescribing device, as determined from data obtained from Blue Cross Blue Shield of Massachusetts’s pharmacy benefits manager. (1) Prescribing patterns by drug tier. (2) Savings in drug costs as a result of different prescribing patterns. (1) Prescribers who used an electronic prescribing device prescribed more generic and on-formulary prescriptions. (2) Prescribers saved Blue Cross Blue Shield of Massachusetts 5 percent on drug costs relative to those prescribers that did not use an electronic prescribing device.

Blue Cross Blue Shield of Massachusetts noted that some of the individuals in the control group may have been electronically prescribing but they assumed in the study that they were not because of the absence of data.

Study #2: Fischer, M.A., C. Vogeli, M. Stedman, T. Ferris, M.A. Brookhart, and J.S. Weissman. “Effect of Electronic Prescribing With Formulary Decision Support on Medication Use and Cost.” Archives of Internal Medicine, vol. 168, no. 22. (2008): 2433-39.

Blue Cross Blue Shield of Massachusetts provided pharmacy claims data used by the researchers in a pre-post study of the implementation of electronic prescribing software with formulary decision support. The study consisted of an intervention group of 1,198 prescribers who wrote at least one electronic prescription, and a control group of 34,453 prescribers who did not electronically prescribe. Claims data were collected for 18 months—6 months before the intervention (October 2003 through March 2004) and 12 months postintervention (April 2004 through March 2005)—and data on electronic prescriptions were collected in the 12 month postintervention period.

Whether the prescriber wrote at least one electronic prescription, as captured by the electronic prescribing system. (1) The change in the proportion of prescriptions for three formulary tiers before and after electronic prescribing was implemented; and (2) the potential savings associated with this change. (1) Electronic prescribing led to a 3.3 percent increase in Tier 1 prescribing—that is, those medications with the lowest copayment. (2) On the basis of average costs, the study estimated that implementation of electronic prescribing software with formulary decision support could lead to a savings of $845,000 per 100,000 patients.

Study #3: Weingart, S.N., B. Simchowitz, H. Padolsky, T. Isaac, A.C. Seger, M. Massagli, R.B. Davis, and J.S. Weissman. “An Empirical Model to Estimate the Potential Impact of Medication Safety Alerts on Patient Safety, Health Care Utilization, and Cost in Ambulatory Care.” Archives of Internal Medicine, vol. 169, no. 16. (2009): 1465-73.

Blue Cross Blue Shield of Massachusetts funded and provided some data for a study that estimated the quality improvement and savings associated with medication safety alerts. The study examined 1,833,254 prescriptions written using a commercial electronic prescribing system by 2,321 clinicians for 60,352 patients. During the study period (January through June 2006), 279,476 drug–drug interaction alerts were generated. For each drug–drug interaction, expert panelists examined whether it might result in an adverse drug event and the severity of that event. The study used published sources and payer data to estimate the costs to third-party payers associated with different types of health care services due to adverse drug events.

All prescriptions were generated from the electronic prescribing system. The company that developed the electronic prescribing system provided researchers information on all drug–drug interactions generated and data on the prescribers’ action on receiving the alert. (1) The likelihood and severity of the potential ADE that the alert prevented, and (2) cost savings estimated from reduced health care utilization. (1) The study estimated that medication safety alerts prevented an estimated 402 adverse drug events (49 serious or life threatening, 125 significant, and 228 minor). Alerts that physicians “accepted,” meaning the physician either cancelled the prescription or changed to an alternative medication, may have prevented deaths in 3 cases, permanent disability in 14 cases, and temporary disability in 31 cases. (2) Due to lower utilization of health care services the study estimated annual savings to be $402,619.

Beginning in 2000, CVS Caremark made electronic prescribing available through its proprietary iScribe system to interested providers by download from a Web site. In late 2004, CVS Caremark supported electronic prescribing by providing software, hardware, installation, training, and service to providers on behalf of health care payers.

Study #1: Hutchins, D.S., M. Lewis, R. Velazquez, and J. Berger. “E-Prescribing Reduces Beers Prescribing Among the Elderly.” CVS Caremark, May 22, 2007.

A control group study of 383,855 prescription claims written for 14,557 persons over 65 years of age between April 2002 and June 2005 by over 3,700 providers, 70 of whom implemented an electronic prescribing tool that alerted them to the prescribing of “Beers List” medications to patients over 65 years of age.

Whether the prescription was dispensed before or after a provider adopted the electronic prescribing tool.

Whether use of the specific electronic prescribing tool had an effect on the prescribing of potentially inappropriate drugs from the Beers List to the elderly.

Use of the specific electronic prescribing tool that provided alerts specific to Beers List medications can reduce prescribing of those medications among the elderly.

Study #2: Hutchins, D.S., J.N. Liberman, J. Berger, S. Jan, M. M. Johnson. “The Impact of an Electronic Prescribing Solution on the Selection and Prescribing of Cost-Effective Therapeutic Options.” CVS Caremark, 2009.

A pre-post control group study of over 9 million claims in seven drug classes prescribed by one of over 29,000 providers (about 250 of which used the electronic prescribing tool) that were filled between July 2002 and December 2005.

Whether the provider used an electronic prescribing tool.

Whether the use of an electronic prescribing system has an effect on prescribing low-cost generic and mail-delivered drugs.

Across multiple drug classes, study reported a link between use of electronic prescribing systems and a greater likelihood that generic drugs were prescribed and that they were dispensed through mail order, both of which likely lower overall costs.

The Florida Agency for Health Care Administration The Florida Agency for Health Care Administration provided Medicaid providers, at no charge, access to a CDS tool called EMPOWERx, which allows for electronic prescribing and includes the following capabilities: provides comprehensive medication histories, alerts providers to drug–drug and drug–allergy interactions, and provides formulary information.

A comparison of the costs and savings for 1,000 Medicaid providers in the state in the EMPOWERx personal digital assistant program to the total population of Medicaid providers in the state.

Whether or not the provider was in the EMPOWERx personal digital assistant program. (1) The average cost per patient for all prescriptions. (2) The estimated savings for prescriptions written by providers in the EMPOWERx personal digital assistant program, based on the difference between costs for providers in the two groups and the number of patients associated with the EMPOWERx personal digital assistant program providers. (3) The estimated savings for the 1,000 Medicaid providers in the EMPOWERx personal digital assistant program based on information collected about alerts those providers received about drug interactions in response to a medication order, assumptions about avoidable hospitalizations, and assumptions about hospitalization costs.

In the fourth quarter of 2009 (1) average costs per patient for all prescriptions were about $28 to $30 lower for the providers in the EMPOWERx personal digital assistant program; (2) the cost differences between the two groups represents estimated savings of approximately $5.5 million; and (3) by assuming that 5 percent of the 12,480 high- or very-high-severity drug interactions would have led to hospitalizations and that hospitalizations resulting from preventable drug interactions are associated with an average increased cost of $4,685 per incident, the study estimated that the state Medicaid program saved approximately $2.9 million.

The Southeastern Michigan ePrescribing Initiative, a collaborative effort of employers, health plans, pharmacy benefit managers, physician groups, and others, was launched in 2005 to speed the adoption of electronic prescribing. Some of the studies that resulted from this collaboration are summarized below.

Study #1: An official with Medco described a study it conducted. Medco is a pharmacy benefit manager and member of the collaborative.

A comparison study of a group of 1,165 physicians who electronically prescribed to Medco’s mail-order drug program and 1,000 physicians that did not. Data were collected in the second quarter of 2008.

Providers were included in the electronic prescribing group if they had sent at least 20 prescriptions electronically to Medco’s mail-order drug program during the study time period. Providers were included in the nonelectronic prescribing group if they had not met this criterion and provided services in the same zip codes as the providers in the electronic prescribing group.

The average cost per prescription per group for retail and mail order prescriptions, which was calculated by dividing total costs (identified through claims data) for each category and group by the number of prescriptions for each category and group.

Providers in the electronic prescribing group saved an average of $2.11 per retail prescription and $7.44 per mail-order prescription compared to the group that did not electronically prescribe.

The Medco official noted that the findings were not tested for significance or subjected to other more-rigorous validations. It is possible that providers in the group that did not electronically prescribe were electronic prescribing, just not to Medco’s mail order service drug program. In addition, while the providers in each group were from the same geographic service areas, Medco did not examine the types of patients served by the providers, so it is possible that the groups were serving different patient populations.

Study #2: An official described a study conducted by HaldyMcIntosh, under the direction of the Southeastern Michigan ePrescribing Initiative project manager, Point-of-Care Partners.

A telephone survey of 500 providers participating in the collaborative that responded to the survey, conducted in the fourth quarter of 2007.

Only providers that were electronically prescribing were surveyed.

Providers’ perceptions of the effect of electronic prescribing on quality.

Nearly 70 percent of respondents highly agreed that electronic prescribing improves quality of care; almost 75 percent highly agreed that electronic prescribing improves patient safety; approximately 70 percent were very satisfied with the ease of identifying drug-related interactions; and more than 60 percent reported that they changed a prescription in response to a safety alert at least once.

Study #3: An official with the Health Alliance Plan described a study conducted by Henry Ford Medical Group and the Health Alliance Plan that looked at generic utilization.

A comparison study conducted in 2005 of a group of 24 physicians who electronically prescribed from eight practice sites and 26 physicians from eight comparable practice sites that did not.

Whether the practice site had converted to electronic prescribing.

Rate of generic prescribing using pharmacy claims data and associated savings.

Facilities with access to an electronic prescribing system had a 1.25 percent larger increase in their rate of generic prescribing compared with sites that did not have access to an electronic prescribing system. The study estimated that the health plan can save $800,000 per year for each 1 percentage point improvement in the rate of generic prescribing.

Study #4: An official with the Health Alliance Plan described a study conducted by Henry Ford Medical Group and the Health Alliance Plan that looked at the savings associated with adverse drug events.

A cost estimate conducted in 2006 of the savings associated with decreases in ADEs.

Whether a prescription was changed based on an alert from the electronic prescribing system, identified from internal data sources.

Estimated savings in (1) avoidable hospitalizations and (2) avoidable emergency room admissions, due to the decrease in ADEs. (1) By assuming that 2 percent of hospitalizations are attributable to ADEs, that 33 percent of those are avoidable due to use of the electronic prescribing system, and that $7,000 is saved per avoidable hospitalization, the study estimated that $441,000 was saved in 2007. (2) By assuming that 1 percent of emergency room visits are attributable to ADEs, that 33 percent of those are avoidable due to use of the electronic prescribing system, and that $500 is saved per avoidable emergency room visit, the study estimated that $99,000 was saved in 2007.

Study #5: An official with the Health Alliance Plan described a study it conducted that identified patients taking contraindicated prescription drug combinations.

A file review of pharmacy and medical claims for about 200,000 patients before implementation of electronic prescribing (in 2004) and after implementation of electronic prescribing (in 2007) to identify patients that were prescribed contraindicated drug combinations.

The study identified claims before and after implementation of electronic prescribing.

The rate of patients taking contraindicated drug combinations.

The study reported a 24 percent decrease in the incidence of patients with generally contraindicated medications and a 48 percent decrease in patients taking medications contraindicated for pregnancy 1 year after the implementation of electronic prescribing.

Study #6: An official with the Health Alliance Plan described a survey conducted by Henry Ford Medical Group and the Health Alliance Plan.

A 2006 survey about electronic prescribing attitudes. About 100 physicians in the Henry Ford Medical Group responded to the survey.

Only physicians who were electronically prescribing were included in the survey.

A variety of questions related to electronic prescribing attitudes, some of which focused on physician attitudes regarding the effect of electronic prescribing on safety.

Various findings reported including the following percentages of respondents who “strongly agreed” or “somewhat agreed”: 84.6 percent of respondents reported that electronic prescribing has improved the practice of medicine in their clinics; 77.2 percent and 74.8 percent reported that electronic prescribing improves the safety of the care and the quality of the care, respectively, provided to their patients; 66.7 percent reported that the drug–drug warnings were helpful, 80.5 percent reported that the drug–allergy warnings were helpful, and 68.3 percent reported that the formulary warnings were helpful.

Summaries of Evaluations Obtained from Literature Review Byrne, C.M., L.M. Mercincavage, E.C. Pan, A.G. Vincent, D.S. Johnston, and B. Middleton. “The Value from Investments in Health Information Technology at the U.S. Department of Veterans Affairs.” Health Affairs, vol. 29, no. 4 (2010): 629-638.

A comparison study of the VA health system and the private-sector health systems on information technology spending, adoption, and quality of care. The study also conducts a cost-benefit analysis to estimate the financial value of key components of the VA’s VistA.

Whether or not the health system surveyed had adopted health information technology and whether the health information technology system had certain capabilities as defined by six frameworks in relevant literature and internal VA and publicly available documents. (1) The information technology–related quality of care quantified using previously collected quality measures from the VA that could be compared to measures available for the private sector for 2004 to 2007. (2) Cost-benefit analysis that estimates the costs and effects of the core components of the VA VistA system from 2001 to 2007. (1) The VA was found to have higher performance on preventive care process measures from 2004 to 2007 relative to the private sector. The VA averaged about 15 percentage points higher than the private sector on preventive care for patients with diabetes and 17 percentage points higher for patients with diabetes who have well-controlled cholesterol. (2) The gross value of the investment in VistA applications was projected to be $7.16 billion. Of the gross value, the researchers estimated that cumulative reductions in unnecessary care attributable to VistA in preventing ADE- related hospitalizations and outpatient visits was valued at $4.64 billion, or 65 percent of the total estimated value.

The VA system electronically captures and reports allergies and adverse reactions, inpatient and outpatient medications, medication orders, and includes CDS such as clinical reminders and order checking.

Cunningham, T.R., E.S. Geller, and S.W. Clarke. “Impact of Electronic Prescribing in a Hospital Setting: A Process-Focused Evaluation.” International Journal of Medical Informatics, vol. 77, no. 8 (2008): 546-554.

A pre-post study reviewing the medication orders of two different hospitals, a control hospital that did not implement a CPOE system and an intervention hospital that did at each of three different phases of the study—a 4-week baseline phase, a 3-week pilot phase, and 5-week post-CPOE implementation phase. At the control hospital, 247 handwritten orders were reviewed from the baseline phase, 279 handwritten orders from the pilot phase, and 453 handwritten orders from the post-CPOE implementation phase. At the intervention hospital, 201 handwritten orders were reviewed from the baseline period, 283 electronically submitted orders were reviewed from the pilot phase, and 587 orders (276 handwritten and 311 submitted electronically) were reviewed from the post-CPOE implementation phase.

Whether or not the physicians’ medication orders were handwritten or submitted electronically in the three different phases of the study, as identified from the files of previously processed medication orders stored in the pharmacy departments of each hospital. (1) Rates of compliance with hospital medication protocols (such as recording date, time, drug name, or dosage) by examining behavioral checklists used to collect information on each prescription written; and (2) time it took for a patient to receive antibiotics, as recorded in the hospital medication ordering database. (1) Medication orders submitted electronically at the intervention hospital were compliant with hospital medication protocols 79.9 percent of the time, compared to a 62.9 percent compliance rate for paper orders written at the same hospital, and a 64.2 percent compliance rate for paper orders written at the control hospital. (2) At the intervention hospital, the average amount of time from the medication order until the first dose of antibiotics was administered was shorter for orders submitted through the CPOE system (185.0 minutes) than paper orders (326.2 minutes).

The CPOE had CDS but the specific features of the CDS system are not discussed.

DesRoches, C.M., E.G. Campbell, S.R. Rao, K. Donelan, T.G. Ferris, A. Jha, R. Kaushal, D.E. Levy, S. Rosenbaum, A.E. Shields, and D. Blumenthal. “Electronic Health Records in Ambulatory Care—A National Survey of Physicians.” New England Journal of Medicine, vol. 359, no. 1 (2008): 50-60.

A survey of 2,758 physicians conducted between September 2007 and March 2008.

Whether or not physicians reported on the survey that they adopted an EHR system, including whether the EHR system was a “fully functional” or “basic” EHR. The study defined a “fully functional” EHR as one that allows physicians to record patients’ clinical and demographic data, view and manage results of laboratory tests and imaging, manage order entry (including electronic prescriptions), and support clinical decisions (including warnings about drug interactions or contraindications). In the study, the principal differences between “fully functional” and “basic” EHRs were the absence of certain order-entry capabilities and CDS in a basic system.

The survey asked respondent a variety of questions related to EHR adoption, including questions related to quality of care.

Findings reported by the study included the following: of the respondents with fully functional EHR systems, 80 percent reported averting a potentially dangerous drug allergic reaction and 71 percent of respondents reported averting a potentially dangerous drug interaction compared to 66 percent and 54 percent of respondents with basic EHR systems.

DesRoches, C.M., E.G. Campbell, C. Vogeli, J. Xheng, S.R. Rao, A.E. Shields, K. Donelan, S. Rosenbaum, S.J. Bristol, and A.K. Jha. “Electronic Health Records’ Limited Successes Suggest More Targeted Uses.” Health Affairs, vol. 29, no. 4 (2010): 639-646.

The researchers created a survey and surveyed 4,840 acute-care general medical and surgical hospitals from March to September 2008 that were members of the American Hospital Association. The researchers linked the information gathered in their survey to information from three other data sources.

Whether the hospital had a comprehensive EHR, defined as an EHR with 24 clinical functions used across all major clinical units in the hospital, a basic EHR system, defined as a system with 10 key functions in at least one major clinical unit in the hospital, or no EHR system. (1) Performance on quality metrics based on data released from the Hospital Quality Alliance for three clinical conditions—acute myocardial infarction, congestive heart failure, and pneumonia—and prevention of surgical complications, and (2) efficiency, as measured by the hospitals’ risk-adjusted length of stay, risk-adjusted 30-day readmission rates, and risk-adjusted inpatient costs, which were determined using two sources of data, the Medicare Inpatient Impact File and the Area Resource File. (1) No relationships were found between EHR adoption and quality process measures for acute myocardial infarction, congestive heart failure, pneumonia, or 30- day risk-standardized mortality of these conditions. Hospitals with EHR had somewhat better performance on the prevention of surgical complications measures than hospitals without EHR (93.7 percent for hospitals with a comprehensive EHR, 93.3 percent for hospitals with a basic EHR, and 92.0 percent for those without EHR). (2) No relationships between the level of EHR adoption and overall risk-adjusted length of stay were found. Hospitals with comprehensive EHRs had similar rates of readmissions within 30 days of hospital discharge compared to hospitals with basic or no EHRs. The researchers found that hospitals with such systems had comparable inpatient costs to hospitals without them. Pneumonia patients in hospitals with a comprehensive EHR had a length of stay that was, on average, 0.5 days shorter than those of patients in hospitals without EHR.

In this article, CDS consisted of clinical reminders and clinical practice guidelines and was associated with marginally better performance on each of the Hospital Quality Alliance quality metrics.

Devine, E.B., R.N. Hansen, J.L. Wilson-Norton, N.M. Lawless, A.W. Fisk, D.K. Blough, D.P. Martin, and S.D. Sullivan. “The Impact of Computerized Provider Order Entry on Medication Errors in a Multispecialty Group Practice.” Journal of the American Medical Informatics Association, vol. 17, no. 1 (2010): 78-84.

A pre-post study compared prescriptions written at a multilocation clinic before and after the implementation of a CPOE system. For the pre-CPOE implementation period between March 1, 2002, and July 15, 2002, for one clinic and between January 2, 2004, and March 4, 2004, for other clinics, 5,016 prescriptions were evaluated. For the post-CPOE implementation period between January 14, 2004, and July 13, 2004, for one clinic and between July 1, 2005, and April 26, 2006, for other clinics, 5,153 prescriptions were evaluated.

Whether the prescription was written before or after the implementation of the CPOE system. (1) Rates, (2) types, and (3) severity of errors in prescriptions written before CPOE system implementation compared to prescriptions submitted electronically after the implementation of the CPOE system. (1) Rates of errors in prescriptions declined from 18.2 percent before to 8.2 percent after implementation of the CPOE system, and the adjusted odds of an error occurring postimplementation of CPOE system were 70 percent lower than preimplementation. (2) There were reductions in the adjusted odds of the following error types: illegibility (97 percent), inappropriate abbreviations (94 percent), information missing (85 percent), wrong strength (81 percent), drug–disease interaction (79 percent), and drug–drug errors (76 percent). (3) Electronic prescribing led to a 57 percent decrease in the odds of an error occurring that did not cause harm. There was a 49 percent reduction in the odds of errors occurring that caused harm. The authors note that this reduction was not significant and that the small number of errors in this category could have caused this result to not be significant.

The CPOE had limited CDS alerts that included basic dosing guidance and duplicate therapy checks.

Feldstein, A.C., D.H. Smith, N. Perrin, X. Yang, S.R. Simon, M. Krall, D.F. Sittig, D. Ditmer, R. Platt, and S.B. Soumerai. “Reducing Warfarin Medication Interactions: An Interrupted Time Series Evaluation.” Archives of Internal Medicine, vol. 166, no. 9 (2006): 1009- 1015.

A pre-post study of 239 primary care providers with 9,910 patients taking Warfarin at 15 primary care clinics that implemented medication interaction alerts for the drug Warfarin into their electronic medical records with computerized order entry and decision support. The baseline period was from January 2000 through November 2002 and the postintervention period was from April 2003 through August 2004.

The presence of electronic medical record alerts for selected coprescriptions of medications that interact with Warfarin. When Warfarin and a targeted interacting medication were coprescribed, an alert would appear, whereupon the clinician had to click “OK” to continue prescribing the interacting medication or prescribe a different drug.

The interacting prescription rate, defined as the number of coprescriptions of Warfarin-interacting medications per 10,000 Warfarin users per month.

At baseline, about a third of patients had an interacting prescription. Coinciding with the implementation of the alerts, the estimated Warfarin-interacting medication prescription rate decreased from 3,294 interacting prescriptions per 10,000 Warfarin users to 2,804 interacting prescriptions per 10,000 Warfarin users, resulting in a 14.9 percent relative reduction.

The electronic medical record had CDS in the form of medication alerts.

Galanter, W.L., R.J. Didomenico, and A. Polikaitis. “A Trial of Automated Decision Support Alerts for Contraindicated Medications Using Computerized Physician Order Entry.” Journal of the American Medical Informatics Association, vol. 12, no. 3 (2005): 269-274.

A comparison, pre-post study of a CPOE alert designed to appear when a clinician attempted to order potentially contraindicated drugs for patients with decreased kidney function through the CPOE. The study was conducted with 233 patients over an 18 month period (4-month pre-CPOE alert period and 14-month post-CPOE alert period).

Whether or not CPOE alerts were generated when contraindicated drugs were ordered electronically. (1) The likelihood of a contraindicated drug being administered before and after implementation of the CPOE alerts, as collected from electronic medical records. (2) Alert compliance. (1) Likelihood of a patient receiving at least one dose of the contraindicated medication decreased from 89 percent in the prealert period to 47 percent in the postalert period. (2) Patient gender was associated with alert compliance rate, with compliance in female patients lower than that in male patients. Alert compliance also decreased as kidney function increased. Housestaff with more than 1 year of residency training had a higher compliance rate than those with less than 1 year of training.

Gandhi, T.K., S.N. Weingart, A.C. Seger, J. Borus, E. Burdick, E.G. Poon, L.L. Leape, and D.W. Bates. “Outpatient Prescribing Errors and the Impact of Computerized Prescribing.” Journal of General Internal Medicine, vol. 20, no. 9 (2005): 837-841.

A comparison study of 1,879 prescriptions reviewed by a pharmacist and submitted at four adult primary care practices, two of which utilized electronic prescribing and two that did not, over a period of 7 months (September 1999 to March 2000).

Whether prescriptions were written at computerized or noncomputerized sites.

Rates of (1) prescribing errors and (2) potential adverse drug events as determined by the expert reviewers from conducting prescription reviews, chart reviews, and conducting patient surveys. (1) Sites with electronic prescribing contained errors in 4.3 percent of prescriptions, compared to 11.0 percent of prescriptions written at sites without electronic prescribing. (2) Sites with electronic prescribing contained potential ADEs in 2.6 percent of prescriptions, compared to 4.0 percent of prescriptions at sites without electronic prescribing. The authors note that the differences between the two groups in errors and prevented ADEs were not significant, but that the rates of prescribing errors and prevented ADEs could have been substantially reduced with more advanced CDS.

The system provided no automatic checks for correct doses, frequencies, allergies, or drug interactions, and authors found that decision support (such as drug-dose checking and drug-frequency checking) could have prevented 97 percent of prescribing errors and 95 percent of potential ADEs.

Kaushal, R., A.K. Jha, C. Franz, J. Glaser, K.D. Shetty, T. Jaggi, B. Middleton, G.J. Kuperman, R. Khorasani, M. Tanasijevic, and D.W. Bates. “Return on Investment for a Computerized Physician Order Entry System.” Journal of the American Medical Informatics Association, vol. 13, no. 3 (2006): 261-266.

A cost-benefit assessment of the implementation of CPOE with CDS at Brigham and Women’s Hospital, a 720-adult bed tertiary care medical center in Boston from 1993 through 2002. Determined the capital and operational costs of implementing a CPOE with CDS and of each CDS intervention through internal documents and interviews with the CPOE developers and reviewing published literature.

Whether or not the CDS intervention was active.

Identified cost savings associated with specific CDS interventions. GAO grouped the savings into those resulting from: (1) decreased ADEs and (2) decreased drug costs.

Of the estimated $28.5 million in estimated savings from the CPOE, (1) $12.9 million in estimated savings were due to CDS interventions that reduced ADEs, and (2) $6 million in estimated savings were due to CDS interventions that reduced drug costs. The cost to develop, implement, and operate the CPOE was $11.8 million, resulting in cumulative savings of $16.7 million.

The CPOE was equipped with CDS.

Kaushal, R., L.M. Kern, Y. Barrón, J. Quaresimo, and E.L. Abramson. “Electronic Prescribing Improves Medication Safety in Community-Based Office Practices.” Journal of General Internal Medicine, vol. 25, no. 6 (2010): 530-536.

A pre-post study of 30 ambulatory care providers (15 electronic prescribers and 15 paper prescribers) in 12 practices in Hudson Valley region of New York (conducted from September 2005 to June 2007). The researchers collected 2 weeks of carbon copies and downloads of prescriptions to identify medication errors at baseline and 1 year follow-up and compared error rates among and between the electronic and paper prescriber groups.

Whether or not the physicians’ medication orders were handwritten or submitted electronically through a stand-alone electronic prescribing system as identified through the carbon copies of prescriptions or prescription downloads. (1) Medication prescribing errors (including omitting the quantity or incorrect medication dose and duration), (2) illegibility errors, (3) near misses (i.e., potentially harmful errors that were intercepted or reached the patient but caused no harm), (4) ADEs, (5) rule violations (e.g., failing to write “po” for a medication taken orally), and (6) effects of CDS on medication errors. (1) The medication prescribing error rate among electronic prescribers decreased from 42.5/100 prescriptions at baseline to 6.6/100 prescriptions at 1 year follow-up. Electronic prescribers had a lower medication prescribing error rate than paper prescribers (6.6/100 v. 38.4/100). (2) Electronic prescribing eliminated all illegibility errors. (3) Electronic prescribers had fewer near misses (1.3/100 v. 2.7/100) than paper prescribers. (4) Rates of preventable adverse drug events trended lower among electronic prescribers (0.04 vs. 0.26 per 100 prescriptions). The authors noted that this was not a significant difference between electronic and paper prescribers. (5) Electronic prescribing eliminated nearly all types of rule violation errors. (6) Electronic prescribers had fewer errors judged preventable by advanced/basic CDS than paper prescribers at 1 year than paper prescribers.

The stand-alone electronic prescribing system was equipped with CDS.

Kim, G.R., A.R. Chen, R.J. Arceci, S.H. Mitchell, K.M. Kokoszka, D. Daniel, and C.U. Lehmann. “Error Reduction in Pediatric Chemotherapy: Computerized Order Entry and Failure Modes and Effects Analysis.” Archives of Pediatrics and Adolescent Medicine, vol. 160 (2009): 495-498.

A pre-post study of chemotherapy orders written in a pediatric oncology unit. The study compared 1,259 paper orders written before implementation of the CPOE system (from July 31 to August 1, 2001, and from August 14, 2001, to August 22, 2002) to 1,116 electronic orders written after implementation of the CPOE system (from February 3, 2003, to February 12, 2004).

Whether the orders were submitted before or after the implementation of the CPOE. A paper based survey was used to capture the pre-CPOE data, and the post-CPOE data were captured through the system.

Data on chemotherapy steps of high morbidity/mortality potential if missed, as determined by attending oncologists.

Findings reported by the study included: after CPOE implementation, daily chemotherapy orders (1) were less likely to have improper dosing, incorrect dosing calculations, missing cumulative dose calculations, and incomplete nursing checklists, and (2) had a higher likelihood of not matching medication orders to treatment plans.

Ko, Y., J. Abarca, D.C. Malone, D.C. Dare, D. Geraets, A. Houranieh, W.N. Jones, W.P. Nichol, G.P. Schepers, M. Wilhardt. “Practitioners’ Views on Computerized Drug-Drug Interaction Alerts in the VA System.” Journal of the American Medical Informatics Association, vol. 14, no. 1 (2007): 56-64.

A survey of 258 prescribers and 84 pharmacists from seven VA Medical Centers across the United States. The time period of the survey was between 2004 and 2005.

Survey participants had prescribing authority in a VA Medical Center and an active outpatient practice. In the VA’s computerized patient record system, prescribers enter prescription orders electronically for review and verification by a pharmacist before dispensing.

The survey asked respondent a variety of questions including those related to (1) respondent satisfaction with the combined inpatient and outpatient CPOE system (the computerized patient record system), (2) attitude towards drug–drug interaction alerts, and (3) suggestions for improving drug–drug interaction alerts.

Findings reported in the study included the following: (1) in general, both prescribers and pharmacists indicated that the computerized patient record system had a positive effect on their jobs. Pharmacists revealed more favorable attitudes toward computerized patient record system than prescribers. (2) Sixty-one percent of prescribers felt that drug–drug interaction alerts had increased their potential to prescribe safely. Thirty percent of prescribers felt that drug–drug interaction alerts provided them with exactly what they needed most of the time. (3) Both prescribers and pharmacists agreed that drug–drug interaction alerts should be accompanied by management alternatives (73 percent and 82 percent, respectively) and more detailed information (65 percent and 89 percent, respectively).

Kocakulah, M.C., and J. Upson. “Cost Analysis of Computerized Physician Order Entry Using Value Stream Analysis: A Case Study.” Research in Healthcare Financial Management, vol. 10, no. 1 (2005): 13-25.

A case study of a 400-bed urban hospital, using value-stream mapping to conduct a cost analysis of a CPOE system. The study determined the potential costs and adverse drug reaction reductions related to CPOE implementation in this hospital, which did not have CPOE installed.

This hospital did not have an electronic prescribing or CPOE system.

Using published studies or reports and data from the hospital, this study determined (1) the projected decrease in medication errors, (2) the potential net savings, (3) net present value, and (4) project internal rate of return for a CPOE system based on the severity, average cost, and projected reduction of adverse drug reactions. (1) The percentage of illegible orders is projected to decrease by 78 percent, incomplete orders by 71 percent, incorrect orders by 46 percent, and drug therapy problems by 9 percent. (2) The projected net savings were $155,686 per year. (3) The projected project 5-year net present value was a negative $1,270,112. (4) The projected 5-year internal rate of return was negative 24 percent. Because of these projections, the authors did not recommend the hospital invest in a CPOE system at the current time.

McCullough, J.S., M. Casey, I. Moscovice, and S. Prasad. “The Effect of Health Information Technology on Quality in U.S. Hospitals.” Health Affairs, vol. 29, no. 4 (2010): 647-654.

A comparison study of 3,401 nonfederal acute-care U.S. hospitals from 2004 to 2007.

Whether the hospital had an EHR and a CPOE system, as identified from information from the American Hospital Association’s annual survey and the HIMSS analytics database that describes hospitals’ health information technology adoption decisions.

Performance on six process quality measures in the CMS Hospital Compare database.

For nearly all measures, average quality was higher for hospitals with EHR and CPOE (with larger effects for academic hospitals than when compared to all hospitals). However, the difference was only significant for pneumococcal vaccine administration (2.1 percent increase) and use of the most appropriate antibiotic for pneumonia (1.3 percent increase).

The study defined an EHR as a set of applications including a computerized patient record with a clinical data repository and some CDS capabilities, such as providing treatment recommendations.

McMullin, S.T., T.P. Lonergan, and C.S. Rynearson. “Twelve-Month Drug Cost Savings Related to Use of an Electronic Prescribing System with Integrated Decision Support in Primary Care.” Journal of Managed Care Pharmacy, vol. 11, no. 4 (2005): 322-332.

A comparison study of 38 primary care clinicians (19 electronic prescribing system users; 19 electronic prescribing system nonusers) conducted from June 2002 through May 2003.

Whether or not the physician was using an electronic prescribing system with CDS capabilities as identified through the study design.

Using pharmacy claims, determined (1) if the 6-month savings on new prescriptions were sustained during the 12-months of follow-up, (2) the 12-month cost savings associated with CDS on pharmacy claims, and (3) prescribing behavior of clinicians on eight high-cost therapeutic groups targeted by electronic messages to prescribers. (1) Savings seen in the last 6 months of the 12 month follow-up period were greater than the first 6 months ($748 per-member-per-month at 6 months to $794 at 12 months per-member-per-month). (2) Use of the electronic prescribing system was associated with a sustained decrease in prescription costs. Over the 12 month follow- up period, the average cost per new prescription for the intervention group decreased by $1.00 and increased by $3.75 in the control group. The number of other refilled prescriptions decreased more in the intervention group than in the control group. The number of new prescriptions increased slightly more in the intervention group than the controls. (3) Prescriptions for high-cost target medications overall decreased by 9.1 percent in the intervention group because of CDS and increased in the control group by 8.2 percent. Compared with the control group, the prescription ratio for high- cost drug classes was a relative 17.5 percent lower in the group using the CDS (35.8 percent versus 43.4 percent).

The electronic prescribing system had integrated CDS, formulary, payor, and clinical guideline alert messaging capabilities.

Peterson, J.F., G.J. Kuperman, C. Shek, M. Patel, J. Avorn, and D.W. Bates. “Guided Prescription of Psychotropic Medications for Geriatric Inpatients.” Archives of Internal Medicine, vol. 165, no. 7 (2005): 802-807.

A comparison study at a tertiary care hospital, including 3,718 patients 65 years or older that were prescribed a psychotropic medication targeted in the intervention and admitted for medical, surgical, neurology, or gynecology services from October 8, 2001, to May 16, 2002.

Whether the geriatric decision support system, which included medication dosing and selection guidelines for elderly patients, was activated.

The study measured several outcomes including: (1) The rate at which prescriptions were written in agreement with expert recommendations regarding recommended daily dose for the initial drug order, (2) incidence of dosing at least 10-fold greater than the recommended daily dose, and (3) prescription of nonrecommended drugs.

Findings presented included: (1) The prescriptions for psychotropic medications agreed with the system recommendations for dosing more frequently during the intervention periods when the geriatric decision support application was available. The agreement rate for both control periods was lower than the agreement rate for the intervention periods. (2) During the intervention periods, the incidence of 10-fold dosing decreased from 5.0 percent to 2.8 percent, (3) the prescription of nonrecommended drugs decreased from 10.8 percent to 7.6 percent.

Ross, S.M., D. Papshev, E.L. Murphy, D.J. Sternberg, J. Taylor, and R. Barg. “Effects of Electronic Prescribing on Formulary Compliance and Generic Drug Utilization in the Ambulatory Care Setting: A Retrospective Analysis of Administrative Claims Data.” Journal of Managed Care Pharmacy, vol. 11, no. 5 (2005): 410-415.

A comparison study of 110,975 paid pharmacy claims submitted by two groups—95 providers using predominantly electronic prescribing and a matched sample of 95 providers who did not electronically prescribe—between August 1, 2001, and July 31, 2002.

Whether or not a provider used electronic prescribing during the study period. (1) Formulary compliance, which was assessed using the formulary code field in pharmacy data claims, and (2) generic utilization rates, which was assessed using First DataBank National Drug Data File Plus software to determine the brand or generic status of each drug. (1) Formulary compliance for both groups was similar. The electronic prescribing group was 83.2 percent compliant, compared to 82.8 percent compliance in the group that did not electronically prescribe. (2) Generic utilization rates were also similar, 37.3 percent for those who electronically prescribed and 36.9 percent for those that did not.

The electronic prescribing system provided drug and formulary information during the prescribing process.

Spencer, D.C., A. Leininger, R. Daniels, R. Granko, and R.R. Coeytaux. “Effect of a Computerized Prescriber-Order-Entry System on Reported Medication Errors.” American Journal of Health-System Pharmacy, vol. 62, no. 4 (2005): 416-419.

A pre-post study and comparison of two medicine units at an academic hospital before and after implementation of a CPOE with CDS, compared to units in the hospital that did not implement a CPOE system. Data were collected over a period of 16 months.

Whether the medication error was reported before or after the implementation of the CPOE system in two medicine units of the hospital and whether or not the medication error was reported from the two medicine units of the hospital that implemented CPOE.

Reported medication errors and potential medication errors, as obtained from the hospital’s center for medication safety.

Implementation of the CPOE system in the two units was associated with an increase in reported errors, from 0.068 per discharge preimplementation to 0.088 per discharge after implementation. The units in the hospital that did not implement CPOE systems had a decrease in the number of reported errors from 0.133 per discharge to 0.079 per discharge.

The authors note that while the error rates increased in the units with CPOE, the error rates in the units in the hospital without CPOE decreased. Therefore, the increase in reported medication errors on units with CPOE systems may have been attributable to the direct or indirect consequences of introduction of the CPOE system.

Steele, A.W., S. Eisert, J. Witter, P. Lyons, M.A. Jones, P. Gabow, and E. Ortiz. “The Effect of Automated Alerts on Provider Ordering Behavior in an Outpatient Setting.” PLoS Medicine, vol. 2, no. 9 (2005): 864-870.

A pre-post study of the implementation and effect of alerts generated during medication ordering in primary care clinics. The baseline data were collected from August 1, 2002, to November 29, 2002, and the postintervention data were collected from December 1, 2002, to April 30, 2003.

All provider staff entered medication orders using CPOE. The study design compared baseline ordering behavior (when no alert was triggered) to ordering behavior after alerts were triggered. (1) The number of medication orders not completed in response to an alert, (2) the number of rule-associated laboratory test orders initiated after an alert was displayed, as captured in the electronic prescribing system, and (3) the rates of adverse drug events assessed by completing file reviews on a random sample of medication orders. (1) Before the alerts were implemented, prescribers did not complete medication orders 5.4 percent of the time, compared to 8.3 percent of the time after the alerts were implemented. The authors noted that this was not a significant difference between the groups. When the alert was for an abnormal laboratory value, the percentage of times where the medication order was not completed increased from 5.6 percent at baseline to 10.9 percent during the intervention. (2) Comparing the pre- and postintervention periods for medication orders when no alert was displayed, prescribers ordered associated laboratory tests 17 percent of the time during the preintervention period, compared to 16.2 percent of the time in the postintervention period. The authors state that this finding was not significant and indicates that there was no trend, in general, to increased laboratory test ordering during the study period. (3) The preintervention group had a potential ADE in 10.3 percent of charts compared to in 4.3 percent of the charts in the postintervention group. The authors state that the difference between the groups was not significant and that the study was too small to show for sure whether there was any true effect on adverse drug reactions.

Stone, W.M., B.E. Smith, J.D. Shaft, R.D. Nelson, and S.R. Money. “Impact of a Computerized Physician Order-Entry System.” Journal of the American College of Surgeons, vol. 208, no. 5 (2009): 960-969.

A pre-post study of patient-safety measures before and after CPOE implementation at the Mayo Clinic Hospital in Phoenix, Arizona. The CPOE system was implemented from May 8, 2007, to April 30, 2008.

Whether or not the physicians’ orders were submitted electronically using the CPOE system. (1) Medication errors and (2) order-implementation time. (1) There were no significant differences in the rate of medication errors in any of the study time periods, which were captured through self-reporting. (2) The time from a doctor placing an order, which was recorded or captured electronically, to a nurse receiving that order decreased from 41.2 minutes pre-CPOE to 27 seconds post- CPOE.

Taylor, J.A., L.A. Loan, J. Kamara, S. Blackburn, and D. Whitney. “Medication Administration Variances Before and After Implementation of Computerized Physician Order Entry in a Neonatal Intensive Care Unit.” Pediatrics, vol. 121, no. 1 (2008): 123-128.

A comparison, pre-post study of how the actual medication administration differed from the medication order before and after CPOE implementation. The study was conducted in the 30-bed Neonatal Intensive Care Unit at Madigan Army Medical Center from August 2004 to April 2006 (pre-CPOE: August 2004 to June 2005; post- CPOE: August 2005 to April 2006).

Whether or not the physicians’ medication orders were handwritten or submitted electronically using a CPOE system. (1) Differences between the medication order and how the medication was actually administered. (2) Reasons for variances between the medication order and administration, as noted by the research nurses. (1) The variation between the medication order and how the medication was actually administered was lower post-CPOE than pre-CPOE (11.6 percent and 19.8 percent, respectively). (2) Findings related to rates of variance in medication order and administration in the pre- and post-CPOE included the following: similar variances in both periods were found for administration mistakes, pharmacy problems, and prescribing problems; and variances related to administration of drugs by the wrong route and the wrong time were significantly lower after CPOE implementation.

The CPOE utilized CDS and display formats and defaults configured specifically for use in the Neonatal Intensive Care Unit for ordering prescriptions.

Upperman, J.S., P. Staley, K. Friend, W. Neches, D. Kazimer, J. Benes, and E.S. Wiener. “The Impact of Hospitalwide Computerized Physician Order Entry on Medical Errors in a Pediatric Hospital.” Journal of Pediatric Surgery, vol. 40, no.1 (2005): 57-59.

A pre-post study comparing orders written before the implementation of a CPOE system in a children’s hospital from January 2002 to October 2002 to those written after the implementation of CPOE system in November 2003 (the end point of the study period was not specified).

Whether a prescription was written before or after the implementation of CPOE.

The rate and types of ADEs determined by analyzing data collected at the hospital.

ADE rates pre-CPOE were 0.3 per 1,000 doses, compared to 0.37 per 1,000 doses post-CPOE. The authors note that the study demonstrates a substantial decrease in harmful ADEs, but no significant difference in all ADEs between the pre- and post- CPOE periods. The rate of harmful ADEs pre-CPOE were 0.05 per 1,000 doses, compared to 0.03 per 1,000 doses post-CPOE.

The CPOE had CDS.

Vaidya, V., A.K. Sowan, M.E. Mills, K. Soeken, M. Gaffoor, and E. Hilmas. “Evaluating the Safety and Efficiency of a CPOE System for Continuous Medication Infusions in a Pediatric ICU.” AMIA Symposium Proceedings, 2006.

A comparison study evaluating the safety of a CPOE system compared to a handwritten, hand-calculated method for prescribing continuous drug infusions for pediatric ICU patients. The time period of the study was not specified.

Whether the orders for the drug infusions were generated in the CPOE system or through a handwritten, hand-calculated method.

The (1) occurrence and (2) risk level of errors, as identified through a review of order sheets for errors. (1) The drug infusion orders generated using the CPOE system had fewer errors (4.3 percent) than those that were handwritten (73 percent). (2) Twenty-five percent of the errors in the handwritten group were judged to be “high-risk” compared to 0 percent in the CPOE group. All of the errors in the CPOE group were missing signatures.

The CPOE included decision support.

Varkey, P., P. Aponte, C. Swanton, D. Fischer, S.F. Johnson, and M.D. Brennan. “The Effect of Computerized Physician-Order Entry on Outpatient Prescription Errors.” Managed Care Interface, vol. 20, no. 3 (2007): 53-57.

A retrospective survey of 4,527 prescriptions ordered from March 1996 through March 2002 at Mayo Clinic ambulatory clinics comparing prescriptions ordered through the clinic’s CPOE to handwritten orders.

Whether or not the type of prescription generated was handwritten, computerized, or preprinted.

The (1) prevalence and (2) type of pharmacist-intercepted prescription errors in computerized and handwritten prescriptions. (1) The frequency of intercepted prescription errors were highest in handwritten prescriptions (7.4 percent), followed by computerized prescriptions (4.9 percent), and preprinted prescriptions (1.7 percent). (2) The most commonly intercepted prescriptions involved the dosage form, dispense quantity, medication dosage, and drug allergies. CPOE resulted in lower rates in every type of intercepted prescription error, including form, dosage, quantity, allergy, frequency, drug name, patient name, illegibility, route, and drug–drug interaction, compared to handwritten prescriptions.

The CDS included required fields and duplicate order checking.

Wang, C.J., M.H. Patel, A. Schueth, M. Bradley, S. Wu, J.C. Crosson, P.A. Glassman, and D.S. Bell. “Perceptions of Standards- based Electronic Prescribing Systems as Implemented in Outpatient Primary Care: A Physician Survey.” Journal of the American Medical Informatics Association, vol. 16, no. 4 (2009): 493-502.

Cross-sectional survey of physicians was fielded from October 2006 to December 2006 among physicians enrolled in a Blue Cross Blue Shield electronic prescribing sponsorship program.

Whether or not the physician had installed an electronic prescribing system. (1) Adequacy of available drug formulary and medication history information and (2) perceptions of the electronic prescribing system’s enhancement of job performance. (1) Electronic prescribing users were more likely than nonusers to “agree” or “strongly agree” that the information available about the patient’s medication history helps them to identify clinically important drug–drug interactions and prevent callbacks from pharmacies for safety problems. Electronic prescribing users were slightly more favorable toward statements that electronic prescribing system drug coverage helps patients maintain lower drug costs. (2) Sixty-two percent of electronic prescribers “agreed” or “strongly agreed” that electronic prescribing improves the quality of care they can deliver.

Weingart, S.N., B. Simchowitz, L. Shiman, D. Brouillard, A. Cyrulik, R.B. Davis, T. Isaac, M. Massagli, L. Morway, D.Z. Sands, J. Spencer, and J.S. Weissman. “Clinicians’ Assessments of Electronic Medication Safety Alerts in Ambulatory Care.” Archives of Internal Medicine, vol. 169, no. 17 (2009): 1627-1632.

A survey mailed to 300 clinicians in December 2007 about the value of electronic prescribing.

Whether clinicians adopted a commercial electronic prescribing system with a drug- allergy and interaction alerts drug reference database and used the electronic prescribing system to write at least 100 prescriptions per month between January 1 and June 30, 2006. (1) Clinicians’ satisfaction with electronic prescribing and (2) perceptions of the effects of electronic prescribing and alerts on the safety, efficiency, and cost of care. (1) Forty-seven percent were satisfied or very satisfied with medication safety alerts. Clinicians said electronic prescribing would improve the quality of care delivered (78 percent); prevent medical errors (83 percent); enhance patient satisfaction (71 percent); and improve clinician efficiency (75 percent). (2) Seventy-eight percent said at least one alert had caused them to change their behavior in the past 6 months. Fifty-seven percent said an alert might have prevented at least one error or injury in the average month. Twenty-two percent said an alert had prevented a serious error or injury in their practice. Sixty-three percent of respondents said an alert caused them to take action other than change an alerted prescription (counsel patient, look up information in a drug reference, or change how they monitor a patient). The study also reported participant ratings on potential problems associated with the drug allergy or interaction alerts. For example, 58 percent of respondents reported that alerts were triggered by discontinued medications.

Yu, F.B., N. Menachemi, E.S. Berner, J.J. Allison, N.W. Weissman, and T.K. Houston. “Full Implementation of Computerized Physician Order Entry and Medication Related Quality Outcomes: A Study of 3364 Hospitals.” American Journal of Medical Quality, vol. 24, no. 4 (2009): 278-286.

A comparison study of hospitals—264 that used a CPOE system to enter all orders and 3,100 that did not—over a 1–year period (July 2003 to June 2004).

Whether the hospital reported on the HIMSS analytics survey that it entered all orders through CPOE.

Performance on hospital quality-of-care measures from CMS.

Of the 11 medication-related measures, the mean performance on 6 cardiovascular- related measures was higher among CPOE hospitals than non-CPOE hospitals, and the mean performance on one measure, antibiotics within 4 hours of arrival, was lower among CPOE hospitals than non-CPOE hospitals.

Yu, F., M. Salas, Y. Kim, and N. Menachemi. “The Relationship Between Computerized Physician Order Entry and Pediatric Adverse Drug Events: A Nested Matched Case-Control Study.” Pharmacoepidemiology and Drug Safety, vol. 18, no. 8 (2009): 751-755.

A comparison study between 54 pediatric hospitals that had CPOE systems and 68 pediatric hospitals that did not. Patient data were retrieved between October 1, 2005, and September 30, 2006.

Whether a CPOE system was fully implemented for all orders and clinical domains, as identified through the HIMSS analytics database.

The odds of ADEs, using data from the national association of children’s hospitals and related institutions case-mix comparative data program and HIMSS.

The odds of experiencing an ADE were 42 percent higher for hospitals without CPOE compared to those with CPOE.

Zhan C., R.W. Hicks, C.M. Blanchette, M.A. Keyes, and D.D. Cousins. “Potential Benefits and Problems with Computerized Prescriber Order Entry: Analysis of a Voluntary Medication Error-Reporting Database.” American Journal of Health-System Pharmacy, vol. 63, no. 4. (2006): 353-358.

Comparison study of 120 facilities that reported having a CPOE in all clinical areas to 339 facilities that did not have a CPOE. Facilities included general community hospitals, specialty hospitals, and outpatient clinics. Data analyzed were from 2003.

Whether the facility had CPOE, as determined by Medmarx, a national voluntary medication-error reporting database. (1) The number of errors reported by CPOE versus non-CPOE facilities and (2) the characteristics of errors caused by CPOE, as captured in the Medmarx database.

The authors stated that the different facilities that self-reported data to the Medmarx database appeared to have different levels of underreporting of medication errors, and therefore, these data cannot be used to assess the potential benefits of CPOE or compare rates of medication errors between providers though facilities with CPOE had fewer inpatient errors, more outpatient errors, and smaller numbers of outpatient and inpatient errors that reached or harmed patients compared to facilities without CPOE. The article did not evaluate the sophistication of the CDS employed by the studied CPOE systems.

Appendix III: Scope and Methodology

This appendix provides additional details regarding our scope and methodology for reporting information on the providers who participated in and received incentive payments from the 2009 Electronic Prescribing Program.

To conduct our analyses, we analyzed four Centers for Medicare & Medicaid Services (CMS) files. 2009 Electronic Prescribing Program Participation. We obtained a file from CMS in October 2010 that provided summary information for each provider that participated in the Electronic Prescribing Program in 2009, which CMS also used to make payments to providers for 2009. For each combination of national provider identifier and tax identification number, this file contained the following information: the total number of times each of the three electronic prescribing codes were submitted; the total number of applicable visits; whether CMS determined that the provider would receive an incentive payment; and the amount of the incentive payment. 2009 Electronic Prescribing Program Eligible Providers. We obtained a file from CMS in October 2010 that listed each provider that had at least one applicable visit for the Electronic Prescribing Program in 2009—which we refer to in this appendix as “applicable providers.” Over 597,000 providers had at least one applicable visit for the Electronic Prescribing Program in 2009. This number represents a count of all Medicare providers who had at least one applicable visit in 2009. However, not all of these providers have prescribing authority. Consequently, there may be some individuals included in the count of 597,000 providers that were not eligible for an electronic prescribing incentive payment.

National Plan and Provider Enumeration System (NPPES)

Downloadable File. We downloaded this file from CMS’s Web site (http://nppes.viva-it.com/NPI_Files.html) in October 2010. We used the variable “Provider Business Practice Location Address State Name” to obtain the state for providers.

Provider Enrollment, Chain, and Ownership System (PECOS)

Global Extract File. We obtained this file from CMS in October 2010. In the few cases when we were unable to obtain the state for providers using the NPPES Downloadable File, we attempted to determine the state for providers using either the “Practice Location State” variable or the “Correspondence Address State” variable from the PECOS Global Extract File.

CMS determined which providers met or exceeded the reporting requirement for 2009 using each unique combination of providers’ national provider identifiers and tax identification numbers. However, we analyzed and report information at the national provider identifier level only so that we could present results for unduplicated providers. We were unable to match 1,052 applicable providers (less than 0.2 percent of applicable providers) to either the NPPES Downloadable File or the PECOS Global Extract file.

To determine the percent of Medicare providers who received incentive payments by state and the average incentive payment by state using the state for each provider, we obtained state information for over 99 percent of applicable providers using data from the NPPES Downloadable File and for the remaining applicable providers using data from the PECOS Global Extract File. We excluded the about 0.2 percent of applicable providers mentioned above that we could not match to either the NPPES Downloadable File or the PECOS Global Extract File. In addition, we excluded about another 0.2 percent of applicable providers for whom we were unable to obtain state information, the 0.9 percent of applicable providers who were from U.S. insular areas, and six providers whose state information we deemed unreliable.

Appendix IV: Maximum Electronic Health Record (EHR) Program Incentive Payments, Based on First Year of Payment

Appendix IV: Maximum Electronic Health Record (EHR) Program Incentive Payments, Based on First Year of Payment Maximum EHR incentive payments by year ual to 75 percent of the provider’s total allowed charges for services covered by Medicare Part B for the year, but are subject to the annual limits displayed in this table.

Appendix V: Stage-One Reporting Requirements for the Electronic Health Records (EHR) Program

1. Generate and transmit more than 40 percent of permissible

1. Perform medication reconciliation for more than 50 percent of all transitions of care.

2. Enter medication order into computerized physician order entry (CPOE) system for more than 30 percent of patients with at least one medication in their medication lists.3. Enter medication lists or indicate no current prescriptions for 2. Enable the EHR system’s ability to check a prescription against a formulary and maintain access to at least one internal or external drug formulary for the entire EHR reporting period. 3.

Incorporate as structured data more than 40 percent of all clinical lab tests results ordered. allergies for more than 80 percent of patients.5. Enable the EHR system’s ability to check a prescription for 4. Generate at least one list of patients by a specific condition. 5. Send reminders during the EHR reporting period for potential drug–drug and drug–allergy interactions. 6. Record as structured data demographics for more than preventative or follow-up care to more than 20 percent of patients aged 65 and over or aged 5 and younger. 6. Provide electronic access to health information within 4 7. Record as structured data list of current and active diagnoses business days of being updated in the EHR system to more than 10 percent of patients. or indicate no known problems for more than 80 percent of patients.

7. Provide patient-specific education resources to more than 8. Record as structured data height, weight, and blood pressure 10 percent of all patients. for more than 50 percent of patients aged 2 and over.

8. Provide summary of care record to more than 50 percent of 9. Record as structured data smoking status for more than transitions of care and referrals.

50 percent of patients aged 13 and over.

9. Perform at least one test of certified EHR technology’s 10. Implement one clinical decision support rule relevant to capacity to submit electronic data to immunization registries and follow-up submission if the test is successful.

Medicare & Medicaid Services (CMS) or the states. 12. Provide electronic copy of health information within 3 business capacity to provide electronic syndromic surveillance data to public health agencies and follow-up submission if the test is successful. days to more than 50 percent of all patients who requested that information. 13. Provide clinical summaries to patients within 3 business days for more than 50 percent of all office visits. 14. Perform at least one test of certified EHR technology’s capacity to electronically exchange key clinical information (i.e., problem list, medication list, medication allergies, or diagnostic test results). 15. Protect electronic health information created or maintained by the certified EHR technology by conducting or reviewing a security risk analysis, implementing security updates as necessary, and correcting identified security deficiencies. uirement is electronic prescribing-related. uality measures help uantify health care processes, outcomes, patient perceptions, and organizational structure. To meet this reporting reuirement, providers must report on 6 out of 44 clinical uality measures identified by CMS.

The reuirement is public health–related.

Appendix VI: Comments from the Department of Health and Human Services

Appendix VII: GAO Contact and Staff Acknowledgments

Staff Acknowledgments

In addition to the contact name above, Robert Copeland, Assistant Director; Nick Bartine; George Bogart; Julianne Flowers; Krister Friday; Toni Harrison; Daniel Lee; Shannon Legeer; and Sarah Marshall made key contributions to this report.