Nursing current advancement

By Larry Wolf, Jennie Harvell, and Ashish K. Jha

Hospitals Ineligible For Federal Meaningful-Use Incentives Have Dismally Low Rates Of Adoption Of Electronic Health Records

ABSTRACT The US government has dedicated substantial resources to help certain providers, such as short-term acute care hospitals and physicians, adopt and meaningfully use electronic health record (EHR) systems. We used national data to determine adoption rates of EHR systems among all types of inpatient providers that were ineligible for these same federal meaningful-use incentives: long-term acute care hospitals, rehabilitation hospitals, and psychiatric hospitals. Adoption rates for these institutions were dismally low: less than half of the rate among short-term acute care hospitals. Specifically, 12 percent of short-term acute care hospitals have at least a basic EHR system, compared with 6 percent of long-term acute care hospitals, 4 percent of rehabilitation hospitals, and 2 percent of psychiatric hospitals. To advance the creation of a nationwide health information technology infrastructure, federal and state policy makers should consider additional measures, such as adopting health information technology standards and EHR system certification criteria appropriate for these ineligible hospitals; including such hospitals in state health information exchange programs; and establishing low- interest loan programs for the acquisition and use of certified EHR systems by ineligible providers.

T he Health Information Technology for Economic and Clinical Health (HITECH) provisions of the Ameri- can Recovery and Reinvestment Act were enacted into law in 2009 to

develop a nationwide health information tech- nology (IT) infrastructure. The legislation pro- motes the electronic exchange of clinical data through the widespread use of certified elec- tronic health records (EHRs) as a means of fos- tering health care quality and efficiency. This foundation is critical to broader health care re- form efforts, such as patient-centered medical homes and accountable care organizations as articulated in the Affordable Care Act of 2010. The HITECH provisions make Medicare and

Medicaid incentives available to certain types of

providers, such as short-term acute care hospi- tals and physicians able to meet specific “mean- ingful use” criteria. However, the law leaves im- portant health care providers out of the incentive program, including nursing homes, home health agencies, long-term acute care hospitals, inpatient rehabilitation hospitals, and inpatient psychiatric hospitals. These providers were ex- cluded from the incentive program primarily be- cause of funding constraints and uncertainty about their readiness to adopt EHR systems.1

Excluding key providers—such as hospitals that care for patients with complex medical con- ditions who are often chronically ill and func- tionally impaired—from broad national efforts to promote the adoption of EHR systems and exchange of clinical data has important implica-

doi: 10.1377/hlthaff.2011.0351 HEALTH AFFAIRS 31, NO. 3 (2012): 505–513 ©2012 Project HOPE— The People-to-People Health Foundation, Inc.

Larry Wolf is a health information technology strategist at Kindred Healthcare, in Louisville, Kentucky.

Jennie Harvell is a senior policy analyst in the Office of the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services, in Washington, D.C.

Ashish K. Jha is an associate professor of health policy at the Harvard School of Public Health and an associate professor of medicine at Harvard Medical School, in Boston, Massachusetts.

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tions. Assuming that these ineligible hospital providers adopt EHR systems at a slower rate as a consequence of their exclusion from finan- cial incentives, the patients who receive care at these hospitals will be less likely to benefit from the improved care associated with access to an EHR. There will be spillover effects as well: If large segments of the health care system remain paper based, then investments to support EHR adoption and use by eligible hospitals and physi- cians might not produce the expected quality and efficiency gains. Nearly one-third of all Medicare patients dis-

charged from short-term acute care hospitals are discharged to postacute care settings such as rehabilitation hospitals.2,3 This proportion of pa- tients is likely to increase over time. As a result, it is critical to ensure the flow of clinical data among providers to reduce waste and promote high-quality care. Case studies of some postacute care providers have identified benefits of imple- menting EHR systems similar to those reported for acute care hospitals and physicians.4,5 It is generally believed that the use of EHR systems would produce the same quality and efficiency gains for the ineligible hospitals as are antici- pated for eligible, short-term acute care hospi- tals. Adoption rates for EHR systems have been previously examined, using national data, for nursing homes, home health, and hospice providers.6,7

This study isthefirst to use nationallyavailable hospital data to provide a baseline of EHR system adoptionrates for hospitals thatareineligiblefor federal incentives. It compares the use of this technology at ineligible hospitals with that at short-term acute care hospitals. We examined data for all ineligible hospital providers: long- term acute care hospitals, rehabilitation hospi- tals, and psychiatric hospitals. First, we deter- mined EHR system adoption rates and compared these rates to those at eligible short-term acute care hospitals to assess whether a gap already exists. Second, we examined how engaged these ineligiblehospitals areinelectronically exchang- ing clinical data. Finally, we assessed whether ineligible hospitals could meet the meaningful- use criteria incorporated in stage 1 of existing federal regulations. These stage 1 criteria spell out EHR data capture and information-sharing requirements that hospitals must meet to qualify for federal incentives. Information from this analysis will provide

critical insights for policy makers about how these providers are faring on adopting EHR tech- nology and what the implications are for efforts to develop a nationwide health IT infrastructure to improve the quality and efficiency of the health care system.

Study Data And Methods Data On The Hospital Survey We used data from the 2009 health IT supplement to the American Hospital Association survey. We fo- cused on responses from the three types of ineli- gible hospitals (long-term acute care, rehabilita- tion, and psychiatric) and compared their responses to those from short-term acute care hospitals, which have been previously pub- lished.8 The 2009 survey was conducted from March through September 2009, and its ap- proach has been described elsewhere.9 The health ITsupplement was developed by an expert panel under the auspices of the Office of the National Coordinator for Health Information Technology. The survey was sent by the Ameri- can Hospital Association to each hospital’s CEO. Each hospital reported on the presence or ab-

sence of thirty-two clinical functions of an EHR system and on whether these had been fully implemented in every unit of the hospital, fully implemented in at least one unit of the hospital, partly implemented, or not yet begun to be implemented.9 The survey results also identify key hospital characteristics, including hospital type, size, ownership, location, and available services (such as a coronary care unit). Defining EHR Systems And Meaningful-Use

Requirements The functions included in basic and comprehensive EHR systems were derived by the expert panel described above and have been used in previous reports of the adoption and use of EHR systems.8,9 A hospital was des- ignated as having a basic EHR system if it had ten specific electronic clinical functions deployed in at least one hospital unit. A hospital was catego- rized as having a comprehensive EHR system if it had a set of twenty-four electronic clinical func- tions deployed in all clinical units of the hospi- tal.9 The functions required to meet the defini- tion of a basic or comprehensive EHR system are included in Appendix Exhibit 1.10

We identified questions from the American Hospital Association survey that had clear ana- logues to the stage 1 meaningful-use criteria. The ones meeting this test were nine of the fourteen core objectives and three of the ten menu objec- tives in the final rule for the Medicare and Medic- aid Electronic Health Record Incentive Program (Appendix Exhibit 2).8,10,11

Analysis We used a series of statistical tests (chi-square tests for categorical variables and t tests for continuous variables) to compare respondents and nonrespondents to the survey and found modest but significant differences. To adjust for nonresponse bias, we used a logistic regression model to estimate the likelihood of a hospital’s responding to the survey based on characteristics such as size, location, and teach-

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ing status.We then weighted all responses by the inverse of that hospital’s likelihood of response. This technique allowed us to create national es- timates while accounting for the observable com- ponents that might produce nonresponse bias. We computed the number of hospitals in each

of our three ineligible hospital types and eligible acute care hospitals that were able to meet the definitions for basic and comprehensive EHR systems explained above.9 We also calculated, using the weighting technique described above, the adoption rates of individual functions, such as computerized physician order entry for med- ications and the ability to exchange clinical data electronically. We used chi-square tests (for cat- egorical variables) and analyses of variance (for continuous variables) to compare adoption rates of basic and comprehensive EHR systems as well as the twenty-four individual functions across the four groups of hospitals. We also considered multivariable models in

which we combined all four groups of hospitals and modeled the likelihood of having a basic or comprehensive EHR system across these groups, adjusting for key hospital characteristics such as size and teaching status. The results were quali- tatively similar. However, given that the finan- cial incentives under the HITECH provisions do not “adjust” or give credit for key hospital char- acteristics, we believe that the most policy-rel- evant comparison was one that was unadjusted. Finally, we used questions identified in the

American Hospital Association survey with ana- logues to the stage 1 meaningful-use criteria and calculated the number of hospitals in each insti- tutional type that would be able to meet certain stage 1 meaningful-use hospital criteria, regard- less of actual eligibility for incentives.11 We used the same statistical approaches defined above, starting with bivariate models (using an analysis of variance) and then building multivariable models (where the results were qualitatively very similar). Again, we present only the bivariate analyses because those are the most relevant for the policy discussion.

Limitations There are several limitations to this study. First, although the survey attained a nearly 70 percent response rate for short-term acute care hospitals, response rates for the ineli- gible hospitals were decidedly lower. We at- tempted to statistically correct for potential non- response bias through weighting; however, these techniques are inherently imperfect. Non- response was associated with characteristics of hospitals that are less likely to have EHR sys- tems. Therefore, we may have overestimated the degree to which these ineligible hospitals have adopted EHR systems. Second, we used self-reported data from

health IT leaders in these institutions. Thus, the data were not independently verified. Third, the definitions of basic EHR system, com-

prehensive EHR system, and meaningful use were largely designed for acute care hospitals. They may not comprise the optimal set of functions to facilitate high-quality, efficient care at ineligible hospitals. Fourth, we focused on whether hospitals had

adopted EHR systems rather than on how hos- pitals used the systems. As a result, this report may overestimate how much clinical care EHR systems support. Finally, we did not ask directly about the mean-

ingful-use objectives. Instead, we mapped our survey responses to the objectives and measures outlined by the Department of Health and Hu- man Services. Our approach represents the cur- rent best estimate of how many of these hospitals might be able to meet meaningful-use criteria. However, it is conservative for the majority of individual criteria and thus may overestimate the number of hospitals that could have met these criteria at the time of the survey. We may have understated the number of hos-

pitals that met the meaningful-use criterion of being able to exchange clinical data electroni- cally with other providers. The meaningful-use rule requires only that hospitals demonstrate the ability to engage in information exchange, whereas our survey asked if hospitals were ac- tively exchanging data with other providers. As a result, we also report our findings without the health information exchange requirement.

Study Results Survey Size And Response Rate The American Hospital Association survey of all nonfederal hospitals included 4,629 general short-term acute care hospitals, 401 long-term acute care hospitals, 237 rehabilitation hospitals, and 466 psychiatric hospitals. The response rates varied by hospital type: 36 percent for long-term acute care hospitals; 46 percent for rehabilita- tion hospitals; 52 percent for psychiatric hospi- tals; and 68 percent for short-term acute care hospitals. Characteristics Of The Ineligible Hospi-

tals There were important differences in the characteristics of hospitals based on their type (Exhibit 1). For example, approximately half of the acute care and psychiatric hospitals were small; by comparison, more than 80 percent of rehabilitation and long-term acute care hospitals were small. There were modest differences among hospital types with respect to the region where they were located and their membership in a provider system. There were large

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differences in terms of their ownership, teaching status, and urban versus rural location. For ex- ample, although only 16 percent of the short- term acute care hospitals were for profit, 67 per- cent of rehabilitation hospitals and 75 percent of long-term acute care hospitals were. Overall Adoption We found a wide range in

the rates of EHR system adoption by hospital type: Although 6 percent of long-term acute care

hospitals had adopted any EHR system (basic or comprehensive), only 4 percent of rehabilitation hospitals and just 2 percent of psychiatric hos- pitals had any system (Exhibit 2). In contrast, 12 percent of short-term acute care hospitals had any system in 2009.When we examined rates of adoption of a comprehensive EHR system (func- tions needed for the system to have a robust impact on quality and efficiency), we found that no psychiatric or rehabilitation hospitals met these criteria and that just 2 percent of long-term acute care hospitals had such systems. As re- ported, 3 percent of short-term acute care hos- pitals met these criteria.9

Selected EHR Capabilities Overall, the adop- tion of specific EHR system functions also varied greatly by hospital type. However, we found one consistent pattern: Compared to short-term acute care hospitals, ineligible hospitals had lower rates of adoption for each of the twenty- four individual functions that make up a com- prehensive or basic EHR (Exhibit 3). For exam- ple, 30 percent of short-term acute care hospitals reported having computerized provider order entry for medications in at least one clinical unit. However, the numbers for the ineligible hospi- tals ranged from 19 percent to 23 percent (for difference across the four hospital subtypes, p ¼ 0:004). Electronic discharge summaries—a key function of sharing data among providers— were available in 62 percent of short-term acute care hospitals but in just 29–36 percent of ineli-

Exhibit 1

Hospital Characteristics Among Responders To The Health Information Technology Survey, 2009

Characteristic

Long-term acute care (n = 144)

Rehabilitation (n = 108)

Psychiatric (n = 240)

Short-term acute care (n = 3,161)

AHA member 70% 83% 82% 98%

Size

Small (< 100 beds) 87 82 53 49 Medium (100–399 beds) 11 18 39 41 Large (≥ 400 beds) 2 0 8 10 Location

Northeast 9 18 20 13 Midwest 22 13 22 30 South 57 57 43 38 West 12 12 15 19 Urban hospital 93 92 84 56

Ownership

For-profit 75 67 37 16 Private, nonprofit 20 26 17 60 Public 5 7 46 24 Teaching hospital 4 15 21 23 Member of provider system 78 68 47 54

SOURCE Authors’ analyses of data from the 2009 American Hospital Association (AHA) annual survey and Health Information Technology Supplement of Acute Care Hospitals in the United States.

Exhibit 2

Electronic Health Record (EHR) System Adoption Rate Among Hospitals, By Type Of Hospital And EHR System Capability, 2009

P er

ce nt

Long-term acute care Rehabilitation Psychiatric Short-term acute care

Comprehensive Basic Any

SOURCE Authors’ analyses of data from the 2009 American Hospital Association annual survey and Health Information Technology Supplement of Acute Care Hospitals in the United States. NOTE For sample sizes, see Exhibit 1.

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gible hospitals. For nearly every function exam- ined, psychiatric hospitals appeared to have the lowest rates of adoption. Finally, ineligible hospitals were also much

more likely than eligible hospitals to report not having plans to implement clinical decision support and computerized provider order entry functions, which have great potential to improve quality and patient safety.12,13

Information Exchange The rate of health information exchange with unaffiliated hospi- tals and physicians was also much lower for ineligible hospitals than eligible hospitals (Exhibit 4). Although 17 percent of short-term acute care hospitals reported that they were ac- tively exchanging health information with other providers, the comparable rates were just 11 per- cent for long-term acute care hospitals, 5 percent for rehabilitation hospitals, and 9 percent for psychiatric hospitals.

Meaningful Use When we mapped our survey questions to meaningful-use criteria, we found that very few hospitals would be able to meet meaningful-use requirements (Exhibit 5). None of the psychiatric or rehabilitation hospitals had all nine core and all three menu objectives re- quired to meet meaningful-use criteria, and only 0.6 percent of long-term acute care hospitals and 2.1 percent of short-term acute care hospitals could meet them. When we eliminated the need to electronically exchange clinical data, there were still no psychiatric or rehabilitation hospi- tals that could meet the criteria, although the rates among long-term acute careand short-term hospitals increased to 3.5 percent and 3.3 per- cent, respectively. Few psychiatric and rehabili- tation hospitals were able to meet even the min- imal core requirements.

Discussion We found very low EHR system adoption rates among hospitals ineligible for the incentives in the HITECH provisions. These rates were less than half of the rate among short-term acute care hospitals. Low EHR system adoption rates among short-term acute care (eligible) hospitals have received much attention from policy mak- ers. The 2–6 percent adoption rates among ineli- gible providers suggest major challenges ahead. The federal meaningful-use incentives will al- most surely widen this gap. We posit several important reasons why EHR

Exhibit 3

Hospitals In Which Electronic Health Record Capabilities Have Been Implemented In At Least One Unit, 2009

Ineligible hospitals (%)a Eligible hospitals (%)b

Capability Long-term acute care Rehabilitation Psychiatric

Short-term acute care

Medication list 48 49 33 65 Computerized provider order entry 23 22 19 30

Drug allergy alerts 47 39 35 62 Radiology images 61 29 7 83 Lab reports 62 46 32 83

Advance directives 17 15 12 48 Discharge summary 33 36 29 62

SOURCE Authors’ analyses of data from the 2009 American Hospital Association Health Information Technology Supplement of Acute Care Hospitals in the United States. NOTE For sample sizes, see Exhibit 1. aIneligible hospitals do not meet meaningful-use criteria and therefore are not eligible to receive financial incentives under the Health Information Technology for Economic and Clinical Health provisions of the American Recovery and Reinvestment Act of 2009. bEligible hospitals meet the necessary meaningful-use criteria and therefore may receive financial incentives. p < 0:01 for differences among the four hospital types.

Exhibit 4

Percentage Of Hospitals That Actively Exchange Data Electronically, By Type Of Hospital, 2009

P er

ce nt

Long-term acute care Rehabilitation Psychiatric Short-term acute care

SOURCE Authors’ analyses of data from the 2009 American Hospital Association annual survey and the Health Information Technology Supplement of Acute Care Hospitals in the United States. NOTES For sample sizes, see Exhibit 1. Hospitals are included that responded: “Participate, we actively ex- change data” when asked, “Does your hospital participate in any regional arrangements to share elec- tronic patient level clinical data through an electronic health information exchange, such as an RHIO (Regional Health Information Organization)?”

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system adoption rates are so much lower among ineligible hospitals. First, the hospitals might not perceive the contribution that EHR systems could make to improving the care they provide, because data on the benefits of inpatient EHR systems come mostly from short-term acute care hospitals. Second, it is likely that providers and vendors alike are uncertain about what type of EHR system functionality these ineligible hospi- tals need and would find appropriate. Third, most vendors of EHR systems for hos-

pitals are focused on meeting the demands of short-term acute care hospitals for products that will enable them to meet meaningful-use crite- ria. It is unlikely that the vendors will devote substantial resources, at least in the short run, to developing EHR systems for ineligible hos- pitals. The lower levels of engagement in health in-

formation exchange among ineligible hospitals have important consequences. Electronically exchanging health information has the ability to enhance care coordination as patients move among care settings. The full use of information exchange depends on the electronic capabilities of providers to both send and receive data. The low levels of health information exchange among ineligible providers probably reflects

both their lower levels of electronic capabilities, such as fewer EHR systems, and their lack of engagement in these efforts. Given that health information exchange is a

clearly stated priority of the federal incentives— and is one of the three components of meaning- ful use highlighted in the HITECH provisions— we expect that the rate of information exchange among short-term acute care hospitals will rise substantially over time. In the final rule for the Medicare and Medicaid Electronic Health Rec- ord Incentive Program, the Centers for Medicare and Medicaid Services states that “stage two meaningful use requirements will include rigor- ous expectations for health information ex- change.”11(p44321) It is unlikely that the ineligible hospitals will catch up. Policy Implications Our findings have im-

portant policy implications. High and rising health care costs, coupled with uneven quality, represent one of the biggest domestic policy challenges facing the nation. The HITECH pro- visions seek to provide some of the necessary infrastructure to advance the electronic use and exchange of health information. The use of EHR systems within a care setting

will be essential to the continued ability of ineli- gible hospitals to provide high-quality and effi-

Exhibit 5

Hospitals’ Ability To Meet Meaningful-Use Criteria

Ineligible hospitals (%)a Eligible hospitals (%)b

Criterion Long-term acute care Rehabilitation Psychiatric

Short-term acute care p value

Meaningful-use core functions

Use computerized provider order entry 23 22 19 30 < 0:04 Implement drug-drug and drug-allergy alerts 17 12 13 14 0.55 Maintain up-to-date problem list 23 18 22 46 < 0:001 Maintain active medication list 48 49 33 66 < 0:001 Key demographics 56 70 60 86 < 0:001 Discharge summary 33 36 29 62 < 0:001 Report hospital quality measures 14 16 12 26 < 0:001 Implement one clinical decision support 38 28 25 60 < 0:001 Information exchange 5 1 2 11 < 0:001 Total core functions 0.6 1.4 0.0 2.1 0.19 Total core functions except information exchange 5.5 2.8 0.0 4.2 0.78

Meaningful-use menu functions

Lab results 62 46 32 84 < 0:001 Medication reconciliation 30 33 22 53 < 0:001 Advance directives 17 15 12 49 < 0:001 Total menu functions 11.1 7.1 6.6 33.1 < 0:001

Totals

Total core and menu functions 0.6 0.0 0.0 1.6 0.30 Total functions except information exchange 3.5 0.0 0.0 3.3 0.60

SOURCE Authors’ analyses of data from the 2009 American Hospital Association annual survey and the Health Information Technology Supplement of Acute Care Hospitals in the United States. NOTE For sample sizes, see Exhibit 1. aIneligible hospitals do not meet meaningful-use criteria and therefore are not eligible to receive financial incentives under the Health Information Technology for Economic and Clinical Health provisions of the American Recovery and Reinvestment Act of 2009. bEligible hospitals meet the necessary meaningful-use criteria and therefore may receive financial incentives.

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cient care. EHR systems help reduce medication errors, promote compliance withevidence-based treatments, and avoid duplication and ineffi- ciency in receipt of services. As adoption of EHR systems grows among the eligible hospi- tals, there may be increasing pressure for the ineligible hospitals to become meaningful users of fully functional EHR systems. A major cause of inefficiency in our health care

system is fragmentation and lack of coordination across care settings.2 The Affordable Care Act makes some efforts to address these challenges by requiring the Centers for Medicare and Medicaid Services to experiment with new deliv- ery and payment models, such as bundled pay- ments and accountable care organizations. Fun- damental to the success of any of these programs is the ability to share clinical data across prov- iders. These emerging payment models—along with the needs of postacute care providers to maintain relationships with acute care hospi- tals—may force ineligible hospitals to adopt EHR systems and use electronic health informa- tion exchange, although they will be at a finan- cial disadvantage because of their lack of HI- TECH incentive payments. By law, the HITECH incentive program for

EHR systems applies to only certain “eligible hospitals” (acute care hospitals) and “eligible professionals” (primarily physicians). Expand- ing this program to include ineligible providers might not be a viable option because of the costs of making incentive payments to them. The HITECH incentive programs managed by

the Office of the National Coordinator for Health Information Technology are not restricted to those health care providers who could be eligible for theEHRsystemincentiveprogram. However, initial federal efforts—such as technical assis- tance through the regional extension centers— were primarily directed to the eligible providers. The Office of the National Coordinator awarded more than half a billion dollars in grants to states and state-designated entities to facilitate health information exchange, primarily among eligible hospitals and professionals. At the same time, the Office of the National

Coordinator recognized the importance of advancing the exchange of health information on behalf of patients who receive services from postacute and long-term care providers, as well as by other providers ineligible for EHR system incentives. As a result, in January 2011 the office provided $7 million in challenge grants to four states to focus on health information exchange for transitions in care that involve nursing homes and home health agencies.14 In addition, a few of the Beacon Community Programs, which are health IT pilots, include postacute care, long-

term care, and behavioral health care provid- ers.15 The Office of the National Coordinator de- scribes a broader set of its activities for ineligible providers on its website.16

The Centers for Medicare and Medicaid Ser- vices anticipates potentially offering assistance to Medicare providers that are ineligible for fi- nancial incentives, through a future contract with Quality Improvement Organizations. These organizations contract with Medicare to help providers improve quality, but they may also be able to function as entities that help provide technical assistance to ineligible providers as they adopt and use EHR systems. Federal and state policy makers could consider

other ways to further advance and accelerate the use of EHR systems by all health care providers. Policy makers could adopt health IT standards and EHR system certification criteria appropri- ate for the ineligible providers. This would pro- vide important guidance to ineligible providers and health IT vendors. In addition, establishing rigorous health information exchange require- ments for eligible providers should increase the value of health information exchange for all providers, which will then be able to send and receive important clinical data. State health information exchange programs

could expand their focus to include ineligible providers. In addition, establishing low-interest loan programs for the acquisition and use of certified EHR systems by ineligible providers could accelerate the acquisition and use of these systems. These actions may encourage ineligible providers to adopt and use EHR systems. Whether investments in the health IT infra-

structure will be sufficient to enable all health care providers to become meaningful users of health IT is an area requiring study. The Office of the National Coordinator uses data from the National Ambulatory Medical Care Survey to track changes in physicians’ adoption rates of EHR systems and data from the American Hos- pital Association annual survey to track EHR system adoption rates by acute care hospitals. As this study has shown, the hospital data can also be used to analyze adoption rates among ineligible hospitals. The National Home Health and Hospice Care

Survey includes questions on the use of EHR systems by home health and hospice care prov- iders. The National Nursing Home Survey cre- ates opportunities to assess trends in EHR sys- tem adoption rates by nursing homes. The nursing home survey includes a question on the use of electronic information systems. How- ever, this question should be refined to provide reliable, valid, and national data on the adoption of EHR systems in nursing homes.17,18

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Including questions in national surveys re- garding the meaningful use of EHR systems would enable comparisons of meaningful use across provider types as well as analyses of mean- ingful use appropriate for each provider type. Fielding questions concerning the adoption of EHR systems by nursing homes and home health care providers would fill an important informa- tion gap and facilitate analyses of trends in EHR adoption by these providers. Conclusion We examined rates of adoption of

EHR systems and engagement in health infor- mation exchange among inpatient providers ineligible for financial incentives and found dis- mally low rates. Given the central importance of

the availability of electronic data in our national efforts to reform the delivery system, these find- ings have important implications: By leaving out ineligible providers, the nation risks building a new digital divide in which key providers, which already have low levels of electronic clinical data, may fall further behind. To develop a nationwide health IT infrastruc-

ture that provides timely and complete informa- tion at the time and place of care, electronic clinical data will need to be available across all sites of care. Consideration should be given to measuring and advancing the use of EHR sys- tems and health information exchange by prov- iders ineligible for federal EHR incentives. ▪

The authors are grateful for the access to the survey data provided by the American Hospital Association.

NOTES

1 Leonard K. Excluded groups want in on health information technology funding . iWatch News [serial on the Internet], 2011 May 23 [cited 2012 Feb 10]. Available from: http:// www.iwatchnews.org/2011/05/23/ 4697/excluded-groups-want-health- information-technology-funding

2 Bogasky S. Examining relationships in an integrated hospital system. Waltham (MA): RTI International; 2008.

3 Kahn JM, Benson NM, Appleby D, Carson SS, Iwashyna TJ. Long-term acute care hospital utilization after critical illness. JAMA. 2010;303(22): 2253–9.

4 Bennett RE, Tuttle M, May K, Harvell J, Coleman EA (University of Colorado Health Sciences Center, Denver, CO). Health information exchange in post-acute and long- term care case study findings: final report. Washington (DC): Depart- ment of Health and Human Services, Office of Disability, Aging and Long- Term Care Policy; 2007 Sep. (Con- tract No. HHS-100-03-0028).

5 Kramer A, Bennett R, Fish R, Lin CT, Floersch N, Conway K, et al. Case studies of electronic health records in post-acute and long-term care. Washington (DC): Department of Health and Human Services; 2004 Aug. (Contract No. HHS-100- 03-0028).

6 Resnick HE, Alwan M. Use of health information technology in home health and hospice agencies: United States, 2007. J Am Med Inform As- soc. 2010;17(4):389–95.

7 Resnick HE, Manard BB, Stone RI, Alwan M. Use of electronic infor- mation systems in nursing homes:

United States, 2004. J Am Med In- form Assoc. 2009;16(2):179–86.

8 Jha AK, DesRoches CM, Kralovec PD, Joshi MS. A progress report on electronic health records in U.S. hospitals. Health Aff (Millwood). 2010;29(10):1951–7.

9 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG, et al. Use of electronic health records in U.S. hospitals. N Engl J Med. 2009;360(16):1628–38.

10 To access the Appendix, click on the Appendix link in the box to the right of the article online.

11 Centers for Medicare and Medicaid Services. Medicare and Medicaid programs; Electronic Health Record Incentive Program; final rule. Fed Regist. 2010;75(144):44314–584.

12 Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch In- tern Med. 2003;163(12):1409–16.

13 Eslami S, de Keizer NF, Abu-Hanna A. The impact of computerized physician medication order entry in hospitalized patients—a systematic review. Int J Med Inform. 2008; 77(6):365–76.

14 Office of the National Coordinator for Health Information Technology. Health Information Exchange Chal- lenge Grant Program [Internet]. Washington (DC): Department of Health and Human Services; [last updated 2011 Feb 23; cited 2012 Feb 10]. Available from: http:// healthit.hhs.gov/portal/server.pt? open=512&mode=2&objID=3378

15 Office of the National Coordinator for Health Information Technology.

Beacon Community Program [Inter- net]. Washington (DC): Department of Health and Human Services; [last updated 2011 May 19; cited 2012 Feb 10]. Available from: http:// healthit.hhs.gov/portal/server.pt/ community/healthit_hhs_gov__ onc_beacon_community_ program__improving_health_ through_health_it/1805

16 Hogin E, Daniel JG. The many meaningful uses of health informa- tion technology. Health IT Buzz [blog on the Internet]. Washington (DC): Department of Health and Human Services, Office of the Na- tional Coordinator; 2011 May 18 [cited 2012 Feb 10]. Available from: http://www.healthit.gov/buzz-blog/ meaningful-use/meaningful-health- information-technology/ #axzz1VOENsSB3

17 Richard A, Kaehny M, May K, Kramer A (University of Colorado, Denver, CO). Literature review and synthesis: existing surveys on health information technology, including surveys on health information tech- nology in nursing homes and home health. Washington (DC): Depart- ment of Health and Human Services, Office of Disability, Aging, and Long- Term Care Policy; 2009 Feb. (Con- tract No. HHS-100-03-0028).

18 Kramer A, Kaehny M, Richard A, May K (University of Colorado, Denver, CO). Survey questions for EHR adoption and use in nursing homes: final report. Washington (DC): Department of Health and Human Services, Office of Disability, Aging, and Long-Term Care Policy; 2010 Jan. (Contract No. HHS-100- 03-0028).

Electronic Health Records

512 Health Affairs March 2012 31:3

by Rachel McCartney on March 5, 2012Health Affairs by content.healthaffairs.orgDownloaded from

ABOUT THE AUTHORS: LARRY WOLF, JENNIE HARVELL & ASHISH K. JHA

Larry Wolf is a health information technology strategist at Kindred Healthcare.

In this month’s Health Affairs, Larry Wolf and coauthors examine the use of electronic health records by inpatient providers that are ineligible for the federal incentives made available to others. The authors found that the rate of adoption among those ineligible providers, which includes long- term acute hospitals and psychiatric hospitals, was “dismally low.” They recommend additional measures that state and federal policy makers should consider to boost adoption by these providers.

Wolf is a health information technology (IT) strategist at Kindred Healthcare who focuses on clinical systems across the spectrum of care. He is also the chair of the Federation of American Hospitals’ Health IT Task Force, cochair of the Healthcare Information and Management Systems Society’s Interoperability Showcase Planning Committee, a member of the American Health Care Association’s Health IT Task

Force, and a member of the American Health Information Management Association’s Emerging Issues Practice Council. Wolf has a master’s degree in computer and information sciences from the University of Massachusetts.

Jennie Harvell is a senior policy analyst at the Department of Health and Human Services.

Jennie Harvell is a senior policy analyst at the Department of Health and Human Services’ Office of the Assistant Secretary for Planning and Evaluation. Her responsibilities include leading the department’s efforts to integrate health IT standards into Medicare and Medicaid postacute care and long-term care programs. She holds a master’s degree in educational administration, supervision, and curriculum from the University of Maryland.

Ashish K. Jha is an associate professor of health policy at the Harvard School of Public Health.

Ashish Jha is both an associate professor of health policy at the Harvard School of Public Health and an associate professor of medicine at Harvard Medical School. His research interest is in the quality of care provided by health care systems, focusing on health care disparities as a marker of poor quality of care and health IT as a potential solution for improving care. Jha also is an associate physician

at Brigham and Women’s Hospital and a staff physician in the Veterans Affairs Boston Healthcare System. Additionally, he is a special assistant to the secretary of the Department of Veterans Affairs. He was awarded the 2009 Young Investigator of the Year award by the Society of General Internal Medicine. Jha earned his medical degree

from Harvard Medical School and a master’s degree in public health from the Harvard School of Public Health.

March 2012 31:3 Health Affairs 513

by Rachel McCartney on March 5, 2012Health Affairs by content.healthaffairs.orgDownloaded from

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