- Email: [email protected]
Consumer Perceptions of Electronic Health Information Exchange
Consumer Perceptions of Electronic Health Information Exchange Jessica S. Ancker, MPH, PhD, Alison M. Edwards, MStat, Melissa C. Miller, MPH, Rainu Kaushal, MD, MPH Background: Public support will be critical to the success and long-term sustainability of electronic health information exchange (HIE) initiatives currently promoted by federal policy.
Purpose: The goal of this study was to assess consumer perceptions of HIE in a state (New York) with a 6-year history of successful HIE organizations. Methods: The Empire State Poll is a random-digit-dial telephone survey of adult New York State residents conducted annually by the Survey Research Institute at Cornell University. In 2011, it contained 77 items.
Results: The survey was conducted and data were analyzed in 2011. Eight hundred respondents participated (71% response rate). Large majorities supported HIE among healthcare providers (69%); thought it would improve quality of care (68%); and supported “break the glass” access to HIE data without need for consent in emergencies (90%). Support was lower among people who rated large corporations as less trustworthy. Privacy and security concerns were expressed by 68%. Respondents were supportive whether the architecture involved a physician sending data to another physician, a physician sending data to a patient who could send it to other physicians, or a physician accessing data from other institutions. Conclusions: In New York, public support for HIE is strong. Policy and outreach pertaining to this type of exchange may be most effective if it clarifıes the roles and responsibilities of large businesses involved in different aspects of the exchange, and privacy and security controls. Differing architectures received similar levels of support. (Am J Prev Med 2012;43(1):76 – 80) © 2012 American Journal of Preventive Medicine
Introduction
H
ealth information exchange (HIE), the exchange of electronic patient data among healthcare providers and institutions, is being promoted by national policy because of its potential to improve healthcare quality and effıciency, engage consumers, and promote population health. Among the goals of the federal “meaningful use” program, which is providing incentives for the adoption and use of electronic health records (EHRs) to improve the quality of care, is to promote the exchange of electronic data.1 Nevertheless, building sustainable HIE infrastructure is challenging.2– 4
From the Department of Pediatrics (Ancker, Kaushal), the Department of Public Health (Ancker, Edwards, Miller, Kaushal), the Department of Medicine (Kaushal), Weill Cornell Medical College, NewYork-Presbyterian Hospital (Kaushal), New York, and Health Information Technology Evaluation Collaborative (HITEC; Ancker, Edwards, Miller, Kaushal), New York, New York Address correspondence to: Jessica S. Ancker, MPH, PhD, 425 E. 61st St., Suite 301, New York NY 10065. E-mail: [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2012.02.027
76 Am J Prev Med 2012;43(1):76 – 80
Multiple HIE models are being explored nationwide, many supported by the American Reinvestment and Recovery Act of 2009 and the State HIE Cooperative Agreement Program.5–7 The Direct Project model under development by the Offıce of the National Coordinator for Health Information Technology permits a provider to send patient data to a known recipient (directproject.org/); as with a fax, the sender must know the recipient’s identity. Another model is nondirected exchange, in which healthcare organizations feed data to a central organization where it is available for lookup by providers.8 A third model is patient-controlled exchange, in which a provider releases data to the patient to share as needed. Examples are the Microsoft HealthVault personal health record (PHR) and the Veterans Administration’s Blue Button initiative that permits patients to download their electronic data. Nationwide, the continued development and sustainability of HIE projects depend on public support. Efforts in this area depend on trust in privacy and security; some patients are prepared to hide information from doctors if they know the information could be shared electronically.9 Forty percent of HIE organizations relied on grants
© 2012 American Journal of Preventive Medicine • Published by Elsevier Inc.
Ancker et al / Am J Prev Med 2012;43(1):76 – 80 2
in 2007, and public funding subsequently expanded with the American Reinvestment and Recovery Act. For such organizations, voter preferences have the potential to affect funding. In addition, patient consent is a factor in some form for most states.10 In some, consent is required for any data to be exchanged through organizations, whereas in others, consent is required for specifıc situations, senders, recipients, or types of sensitive data.10 Health information exchange has been a priority in New York State since 2006 under the Healthcare Effıciency and Affordability Law for New Yorkers (HEAL-NY), which is investing more than $800 million in health information technology.11 In New York, patient consent is required before providers can obtain a patient’s data through an HIE organization (with exceptions for emergency access, unless patients have explicitly prohibited emergency access).11 About 1.8 million people (in a state with 19.4 million residents)12 have provided consent to one of 12 regional health information organizations (RHIOs).13 Nationally, surveys and qualitative studies have found strong support for HIE for clinical purposes, partnered with signifıcant privacy and security concerns.14 –17 Support is much lower for sharing data for research or with “health insurance plans” and ”companies.”9 Predictors of attitudes have been found to include health-related issues14,15,18 (e.g., having a chronic health condition); SES15,18; Internet use; and beliefs14,15,18 (e.g., that such exchange will improve health care). The objective of this survey was to assess attitudes toward HIE in a state with a relatively advanced public infrastructure for it, using rigorous methodology to obtain a representative statewide sample. In addition, this survey differs from previous surveys by asking about support for the three models described above: directed exchange between providers, nondirected exchange in which providers access data supplied by other providers (with consent, as required in New York), and exchange through a patient-managed PHR.
Methods Survey Development The Empire State Poll is an annual survey of adult New York State residents by the Survey Research Institute of Cornell University. A standard set of questions is repeated annually, covering sociodemographics, political ideology, party affıliation, and attitudes toward statewide political topics, workplace issues, community, government, and social institutions. Researchers may submit small numbers of additional questions each year. In 2011, the survey contained 77 interview questions, including 12 submitted by this research group. Questions were pretested with 25 respondents, resulting in changes to wording for clarity. The study was approved by the Cornell University IRB. July 2012
77
Sampling The sample was drawn from random-digit-dial lists covering cellular and land-line exchanges. Every adult in a sampled household had an equal chance to be included. Census districts with large minority populations were modestly oversampled to ensure suffıcient minority representation in the sample. The sample size of 800 produced a margin of error of 3.5 percentage points.
Statistical Analysis Data were collected in February and March 2011. The primary outcome was support for HIE (Table 1, Question 3). All poll items were reviewed to determine which should be tested for association with HIE support. Questions with little relevance to the research topic were excluded: these included attitudes toward specifıc statewide or community issues (e.g., shale gas hydrofracking); religious attendance; and highly specifıc probe questions (such as number of hours worked, which followed the question about employment). In addition, questions were excluded if they were strongly correlated with others (e.g., party affıliation was excluded because of strong correlation with political ideology). Twenty-four variables were tested, as well as exposure to doctors using electronic health records (Table 1, Question 1) for association with HIE support. Those with bivariate associations at p⬍0.10 were added to a multivariate model, and backward stepwise elimination used to eliminate variables not signifıcant at 0.05. Data were analyzed in 2011 with SAS, version 9.2.
Results With 1120 completed calls to eligible respondents, 800 participated (response rate⫽71%). Average interview length was 22 minutes. Respondents had a mean age of 49.5 years. Fifty-two percent were female, 74% were white, and 11% Hispanic. Forty-eight percent had a college or postgraduate degree, and 61% were employed. Thirty-eight percent had annual incomes of ⬍$50,000, and 26% had annual incomes of ⱖ$100,000. Seventy-four percent reported using the Internet or e-mail at least once a day. Eighty-eight percent indicated that they were in good or excellent health; 15% indicated they were a caregiver for somebody with serious illness. Support for HIE was strong, although privacy concerns were common (Table 1). All three types of HIE were supported by approximately 80% of respondents. In bivariate analyses of demographics and previous exposure to health information technology, 11 variables were associated with support for HIE: gender; children in the household; education; income; use of the Internet or e-mail; perceived trustworthiness of local business, other people, local government, and large corporations; and indicating that people were more likely to lie in person than online. In the multivariate model, four variables remained signifıcant: having at least one child in the household (OR⫽0.57, 95% CI⫽0.40, 0.81, p⬍0.002); income (ⱖ$100,000 compared to ⬍$50,000, OR⫽2.27, 95% CI⫽1.43, 3.61, p⬍0.002); perceived trustworthiness of large corporations (high compared to low trustworthiness, OR⫽1.80, 95% CI⫽1.13, 2.86, p⬍0.03); and indicating
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
78
people are more likely to lie in person (OR⫽ 0.52, 95% CI⫽0.32, 0.85, p⬍0.009). The following variables were not found to be associated with HIE support in the multivariate model: age, gender, race, Hispanic ethnicity, urban residency, marital status, number of household members aged ⱖ65 years, education, employment, use of the Internet, self-rated health, being a caregiver for somebody with a serious illness, political orientation, and perceived trustworthiness of local business, other people, the Internet, local government, labor unions, news media, and state government.
Discussion Support for clinical HIE was strong in New York. Large majorities supported HIE among healthcare providers, believed it would improve their medical care, would consent to such exchange, and supported emergency data access without consent. Support was equally strong for directed exchange between providers, nondirected exchange, and patient-managed exchange. Nevertheless, privacy and security concerns were common. This suggests
Table 1. New York State residents’ perceptions of health information technology and health information exchange Weighted n (%)
Question text and response options STORING MEDICAL INFORMATION ON COMPUTERS 1. Do any of your doctors use a computer to store your personal medical information? Yes
615 (78)
No
104 (13)
Do not know
71 (9)
2. How do you think keeping your personal medical information in a computer could affect the privacy and security of your medical information? Greatly or slightly improve
204 (25)
No effect
256 (32)
Slightly or greatly worsen
321 (41)
Do not know
19 (2)
HEALTH INFORMATION EXCHANGE 3. How would you feel about computers being used to share your medical information electronically between doctors, hospitals, and other places where you receive medical care? Strongly or somewhat support
555 (69)
No opinion
102 (13)
Somewhat or strongly against
141 (18)
4. How do you think that using computers to share your medical information electronically among healthcare providers would affect your medical care? Greatly or slightly improve
544 (68)
No effect
184 (23)
Slightly or greatly worsen
58 (7)
Do not know
13 (2)
5. If your medical information is shared electronically between healthcare providers, how would you feel about the following three methods of sharing? Your doctor would use a computer to send your medical information electronically to another doctor involved in your health care
638 (80)
Your doctor would send your medical information to you electronically (for example, in a personal health record) so that you can share it with other doctors
614 (77)
Your doctor would ask your consent to access your medical information electronically from all other places where you have received care
644 (81)
CONSENT 6. If you had the opportunity, would you sign a consent form that would allow your doctor to use a computer to access your medical information electronically from other places where you receive medical care? Definitely or probably yes
675 (85)
Probably or definitely no
115 (15)
Do not know
10 (1) (continued on next page)
www.ajpmonline.org
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
Table 1. (continued)
79
consent rate of 90% reported by New Weighted York State RHIOs19 Question text and response options n (%) and by the Mas7. When considering whether to sign a consent form to allow doctors to electronically sachusetts eHealth access your medical data from other places, how concerned would you be about the Collaborative.16 privacy and security of your medical information? Increased support Not concerned 257 (32) among higher-income Somewhat or very concerned 540 (68) brackets previously has been reported.15 Do not know 3 (⬍1) However, some other 8. In the case of a medical emergency, where you were not able to give consent (e.g., if fındings are surprisyou were unconscious), would you want doctors caring for you to be able to use computers to access medical information electronically about you from other places ing. Our previous sinwhere you receive medical care? gle-community study Yes 718 (90) found that support was higher among No 70 (9) caregivers,15 a fınding Do not know 13 (2) not corroborated by 9. Have you ever signed a consent form to allow your doctor to access your medical the current study. data electronically from other doctors involved in your care? (An example would be if The lack of relationyou have signed consent form with an organization called a regional health information organization or RHIO.) ship between demographics and support Yes 250 (31) also contrasts with No 518 (65) some previous reDo not know 32 (4) search.14,15,18 Both may be artifacts of the strong HIE support in the current survey, which may have created a that patients may be willing to accept various mechanisms for ceiling effect. It is also possible that New Yorkers’ attiexchangingdata,aslongastheyareconvincedthattheirprivacy tudes have evolved as a result of experience with HIE. is protected. Alternately, previous smaller studies may not generalize Alternatively, differences between the models may not to the state. A counterintuitive fınding was that support have been clear to the respondents, which would support was higher among those who thought lying was more the need for increased education and engagement with all likely to occur online than in-person; these people may stakeholders. The fact that patient-controlled exchange have been expressing a skeptical view of online behavior, was not more popular than provider-managed exchange rather than distrust of electronic communication. suggests that patients do not necessarily prefer hands-on control of the process. Support was somewhat lower among those with children in the household, lower inLimitations come, distrust of large corporations, and a belief that This poll was designed to provide estimates for New people were more likely to lie in person than online. York. Generalizability to national attitudes is not known, The current fınding of a relationship between HIE supand New York’s experience with HIE may have increased port and trust in business is new but appears to be consistent familiarity with this topic. Differences between responwith other research. The California Healthcare Foundation dents and nonrespondents are not known. The survey found stronger interest in PHRs offered by providers than covered complex topics, and despite pretesting, responthose offered by insurers or companies “like Microsoft or dents may have interpreted questions differently from Google.”9 A question in that survey about sharing health what was intended. Specifıcally, the 31% who reported data with “health insurance plans, researchers, companies, consenting to HIE is inconsistent with registries by New 9 found very low support. However, that survey and others” York RHIOs, which indicate that roughly 9% of the popincluded no questions about exchange between healthcare ulation has consented to having data accessed through providers, so it is unclear whether respondents would have RHIOs; respondents may have interpreted the question expressed stronger support for clinical HIE. The 85% supto include other medical data release forms. port for clinical HIE in the current survey is consistent An additional limitation is that many potentially relevant topics, such as health insurance status, presence of with other surveys,14 –17 as well as with the median July 2012
80
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
chronic diseases, experience with healthcare system, and other health questions, were not available in the Empire State Poll. As with all surveys, self-report may bias answers in unknown ways, and cross-sectional associations do not necessarily imply causal relationships.
Conclusion Given the survey fındings, policies promoting HIE for clinical care are likely to continue receiving public support. With support lower among those expressing distrust of large corporations, there may be a need for additional policy or outreach to clarify the responsibilities of businesses involved in different aspects of exchange. Three different architectures were all strongly supported. This suggests that consumers may be willing to accept a variety of models as long as they are confıdent their privacy is respected. It also supports the need for continued engagement in public discussions about HIE to ensure that consumers understand how differences in the architecture might affect them. This study was supported by New York eHealth Collaborative (NYeC). The study sponsors provided feedback on the survey instrument but played no role in study design or data analysis. The investigators thank Darren Hearn and Yasamin Miller of the Cornell Survey Research Institute for contributions to survey design and administration and Rachel Block, Ellen Flink, Steven Smith from the New York State Department of Health Offıce of Health Information Technology Transformation for feedback on the survey instrument. No fınancial disclosures were reported by the authors of this paper.
References 1. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010;363:501– 4. 2. Adler-Milstein J, McAfee AP, Bates DW, Jha AK. The state of regional health information organizations: current activities and fınancing. Health Aff (Millwood) 2008;27(1):w60 –w69. 3. Thornewill J, Dowling AF, Cox BA, Esterhay RJ. Information infrastructure for consumer health: a health information exchange stakeholder study. Am J Prev Med 2011;40(5S2):S123–S133.
4. Shaikh AR, Das IP, Vinson CA, Spring B. Cyber infrastructure for consumer health. Am J Prev Med 2011;40(5S2):S91–S96. 5. Kuperman GJ, Blair JS, Franck RA, Devaraj S, Low AFH, for the NHIN Trial Implementations Core Services Content Working Group. Developing data content specifıcations for the Nationwide Health Information Network Trial Implementations. JAMA. 2010;17(1):6 –12. 6. The Nationwide Health Information Network at the website of the Offıce of the National Coordinator for Health Information Technology. healthit.hhs.gov/portal/server.pt/community/healthit_hhs_ gov__nationwide_health_information_network/1142. 7. State Health Information Exchange Program fact sheet. healthit.hhs. gov/portal/server.pt?open⫽512&mode⫽2&objID⫽1834. 8. Kern LM, Kaushal R. Health information technology and health information exchange in New York State: new initiatives in implementation and evaluation. J Biomed Inform 2007;40(6S):S17–S20. 9. Undem T. Consumers and health information technology: a national survey. Oakland CA: California HealthCare Foundation, 2010. 10. Pritts J, Lewis S, Jacobson R, Lucia K, Kayne K. Privacy and security solutions for interoperable health information exchange. Chicago IL: Agency for Healthcare Research and Quality, Offıce of the National Coordinator for Health IT, 2009. 11. Anonymous. Privacy and security policies and procedures for RHIOs and their participants in New York State, v 2.2. Albany NY: New York eHealth Collaborative and the New York State Department of Health, 2010. nyehealth.org/images/fıles/File_Repository16/pdf/fınal%20pps%20v2.2% 204.1.11.pdf. 12. U.S. Census Bureau. State and country QuickFacts. quickfacts.census. gov/qfd/states/36000.html. 13. Anonymous. NYeC dashboard report on health information exchange users, patients, and volume. New York NY: New York eHealth Collaborative, 2011. 14. Patel VN, Dhopeshwarkar RV, Edward A, Barrón Y, Sparenborg J, Kaushal R. Consumer support for health information exchange and personal health records: a regional health information organization survey. J Med Syst 2010. 15. O’Donnell HC, Patel V, Kern LM, et al. Healthcare consumers’ attitudes toward physician and personal use of health information exchange. J Gen Intern Med 2011;26(9):1019 –26. 16. Tripathi M, Delano D, Lund B, Rudolph L. Engaging patients for health information exchange. Health Aff (Millwood) 2009;28(2):435– 43. 17. Simon SR, Evans JS, Benjamin A, Delano D, Bates DW. Patients’ attitudes toward electronic health information exchange: qualitative study. J Med Internet Res 2009;11(3):e30. 18. Wen K-Y, Kreps G, Zhu F, Miller S. Consumers’ perceptions about and use of the Internet for personal health records and health information exchange: analysis of the 2007 Health Information National Trends Survey. J Med Internet Res 2010;12(4):e73. 19. Campion TR, Kern LM, Kaushal R. Implementation factors associated with adoption of health information technology through communitybased organizations: preliminary fındings report. New York NY: Health Information Technology Evaluation Collaborative (HITEC), Weill Cornell Medical College, 2011.
www.ajpmonline.org
Purpose: The goal of this study was to assess consumer perceptions of HIE in a state (New York) with a 6-year history of successful HIE organizations. Methods: The Empire State Poll is a random-digit-dial telephone survey of adult New York State residents conducted annually by the Survey Research Institute at Cornell University. In 2011, it contained 77 items.
Results: The survey was conducted and data were analyzed in 2011. Eight hundred respondents participated (71% response rate). Large majorities supported HIE among healthcare providers (69%); thought it would improve quality of care (68%); and supported “break the glass” access to HIE data without need for consent in emergencies (90%). Support was lower among people who rated large corporations as less trustworthy. Privacy and security concerns were expressed by 68%. Respondents were supportive whether the architecture involved a physician sending data to another physician, a physician sending data to a patient who could send it to other physicians, or a physician accessing data from other institutions. Conclusions: In New York, public support for HIE is strong. Policy and outreach pertaining to this type of exchange may be most effective if it clarifıes the roles and responsibilities of large businesses involved in different aspects of the exchange, and privacy and security controls. Differing architectures received similar levels of support. (Am J Prev Med 2012;43(1):76 – 80) © 2012 American Journal of Preventive Medicine
Introduction
H
ealth information exchange (HIE), the exchange of electronic patient data among healthcare providers and institutions, is being promoted by national policy because of its potential to improve healthcare quality and effıciency, engage consumers, and promote population health. Among the goals of the federal “meaningful use” program, which is providing incentives for the adoption and use of electronic health records (EHRs) to improve the quality of care, is to promote the exchange of electronic data.1 Nevertheless, building sustainable HIE infrastructure is challenging.2– 4
From the Department of Pediatrics (Ancker, Kaushal), the Department of Public Health (Ancker, Edwards, Miller, Kaushal), the Department of Medicine (Kaushal), Weill Cornell Medical College, NewYork-Presbyterian Hospital (Kaushal), New York, and Health Information Technology Evaluation Collaborative (HITEC; Ancker, Edwards, Miller, Kaushal), New York, New York Address correspondence to: Jessica S. Ancker, MPH, PhD, 425 E. 61st St., Suite 301, New York NY 10065. E-mail: [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2012.02.027
76 Am J Prev Med 2012;43(1):76 – 80
Multiple HIE models are being explored nationwide, many supported by the American Reinvestment and Recovery Act of 2009 and the State HIE Cooperative Agreement Program.5–7 The Direct Project model under development by the Offıce of the National Coordinator for Health Information Technology permits a provider to send patient data to a known recipient (directproject.org/); as with a fax, the sender must know the recipient’s identity. Another model is nondirected exchange, in which healthcare organizations feed data to a central organization where it is available for lookup by providers.8 A third model is patient-controlled exchange, in which a provider releases data to the patient to share as needed. Examples are the Microsoft HealthVault personal health record (PHR) and the Veterans Administration’s Blue Button initiative that permits patients to download their electronic data. Nationwide, the continued development and sustainability of HIE projects depend on public support. Efforts in this area depend on trust in privacy and security; some patients are prepared to hide information from doctors if they know the information could be shared electronically.9 Forty percent of HIE organizations relied on grants
© 2012 American Journal of Preventive Medicine • Published by Elsevier Inc.
Ancker et al / Am J Prev Med 2012;43(1):76 – 80 2
in 2007, and public funding subsequently expanded with the American Reinvestment and Recovery Act. For such organizations, voter preferences have the potential to affect funding. In addition, patient consent is a factor in some form for most states.10 In some, consent is required for any data to be exchanged through organizations, whereas in others, consent is required for specifıc situations, senders, recipients, or types of sensitive data.10 Health information exchange has been a priority in New York State since 2006 under the Healthcare Effıciency and Affordability Law for New Yorkers (HEAL-NY), which is investing more than $800 million in health information technology.11 In New York, patient consent is required before providers can obtain a patient’s data through an HIE organization (with exceptions for emergency access, unless patients have explicitly prohibited emergency access).11 About 1.8 million people (in a state with 19.4 million residents)12 have provided consent to one of 12 regional health information organizations (RHIOs).13 Nationally, surveys and qualitative studies have found strong support for HIE for clinical purposes, partnered with signifıcant privacy and security concerns.14 –17 Support is much lower for sharing data for research or with “health insurance plans” and ”companies.”9 Predictors of attitudes have been found to include health-related issues14,15,18 (e.g., having a chronic health condition); SES15,18; Internet use; and beliefs14,15,18 (e.g., that such exchange will improve health care). The objective of this survey was to assess attitudes toward HIE in a state with a relatively advanced public infrastructure for it, using rigorous methodology to obtain a representative statewide sample. In addition, this survey differs from previous surveys by asking about support for the three models described above: directed exchange between providers, nondirected exchange in which providers access data supplied by other providers (with consent, as required in New York), and exchange through a patient-managed PHR.
Methods Survey Development The Empire State Poll is an annual survey of adult New York State residents by the Survey Research Institute of Cornell University. A standard set of questions is repeated annually, covering sociodemographics, political ideology, party affıliation, and attitudes toward statewide political topics, workplace issues, community, government, and social institutions. Researchers may submit small numbers of additional questions each year. In 2011, the survey contained 77 interview questions, including 12 submitted by this research group. Questions were pretested with 25 respondents, resulting in changes to wording for clarity. The study was approved by the Cornell University IRB. July 2012
77
Sampling The sample was drawn from random-digit-dial lists covering cellular and land-line exchanges. Every adult in a sampled household had an equal chance to be included. Census districts with large minority populations were modestly oversampled to ensure suffıcient minority representation in the sample. The sample size of 800 produced a margin of error of 3.5 percentage points.
Statistical Analysis Data were collected in February and March 2011. The primary outcome was support for HIE (Table 1, Question 3). All poll items were reviewed to determine which should be tested for association with HIE support. Questions with little relevance to the research topic were excluded: these included attitudes toward specifıc statewide or community issues (e.g., shale gas hydrofracking); religious attendance; and highly specifıc probe questions (such as number of hours worked, which followed the question about employment). In addition, questions were excluded if they were strongly correlated with others (e.g., party affıliation was excluded because of strong correlation with political ideology). Twenty-four variables were tested, as well as exposure to doctors using electronic health records (Table 1, Question 1) for association with HIE support. Those with bivariate associations at p⬍0.10 were added to a multivariate model, and backward stepwise elimination used to eliminate variables not signifıcant at 0.05. Data were analyzed in 2011 with SAS, version 9.2.
Results With 1120 completed calls to eligible respondents, 800 participated (response rate⫽71%). Average interview length was 22 minutes. Respondents had a mean age of 49.5 years. Fifty-two percent were female, 74% were white, and 11% Hispanic. Forty-eight percent had a college or postgraduate degree, and 61% were employed. Thirty-eight percent had annual incomes of ⬍$50,000, and 26% had annual incomes of ⱖ$100,000. Seventy-four percent reported using the Internet or e-mail at least once a day. Eighty-eight percent indicated that they were in good or excellent health; 15% indicated they were a caregiver for somebody with serious illness. Support for HIE was strong, although privacy concerns were common (Table 1). All three types of HIE were supported by approximately 80% of respondents. In bivariate analyses of demographics and previous exposure to health information technology, 11 variables were associated with support for HIE: gender; children in the household; education; income; use of the Internet or e-mail; perceived trustworthiness of local business, other people, local government, and large corporations; and indicating that people were more likely to lie in person than online. In the multivariate model, four variables remained signifıcant: having at least one child in the household (OR⫽0.57, 95% CI⫽0.40, 0.81, p⬍0.002); income (ⱖ$100,000 compared to ⬍$50,000, OR⫽2.27, 95% CI⫽1.43, 3.61, p⬍0.002); perceived trustworthiness of large corporations (high compared to low trustworthiness, OR⫽1.80, 95% CI⫽1.13, 2.86, p⬍0.03); and indicating
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
78
people are more likely to lie in person (OR⫽ 0.52, 95% CI⫽0.32, 0.85, p⬍0.009). The following variables were not found to be associated with HIE support in the multivariate model: age, gender, race, Hispanic ethnicity, urban residency, marital status, number of household members aged ⱖ65 years, education, employment, use of the Internet, self-rated health, being a caregiver for somebody with a serious illness, political orientation, and perceived trustworthiness of local business, other people, the Internet, local government, labor unions, news media, and state government.
Discussion Support for clinical HIE was strong in New York. Large majorities supported HIE among healthcare providers, believed it would improve their medical care, would consent to such exchange, and supported emergency data access without consent. Support was equally strong for directed exchange between providers, nondirected exchange, and patient-managed exchange. Nevertheless, privacy and security concerns were common. This suggests
Table 1. New York State residents’ perceptions of health information technology and health information exchange Weighted n (%)
Question text and response options STORING MEDICAL INFORMATION ON COMPUTERS 1. Do any of your doctors use a computer to store your personal medical information? Yes
615 (78)
No
104 (13)
Do not know
71 (9)
2. How do you think keeping your personal medical information in a computer could affect the privacy and security of your medical information? Greatly or slightly improve
204 (25)
No effect
256 (32)
Slightly or greatly worsen
321 (41)
Do not know
19 (2)
HEALTH INFORMATION EXCHANGE 3. How would you feel about computers being used to share your medical information electronically between doctors, hospitals, and other places where you receive medical care? Strongly or somewhat support
555 (69)
No opinion
102 (13)
Somewhat or strongly against
141 (18)
4. How do you think that using computers to share your medical information electronically among healthcare providers would affect your medical care? Greatly or slightly improve
544 (68)
No effect
184 (23)
Slightly or greatly worsen
58 (7)
Do not know
13 (2)
5. If your medical information is shared electronically between healthcare providers, how would you feel about the following three methods of sharing? Your doctor would use a computer to send your medical information electronically to another doctor involved in your health care
638 (80)
Your doctor would send your medical information to you electronically (for example, in a personal health record) so that you can share it with other doctors
614 (77)
Your doctor would ask your consent to access your medical information electronically from all other places where you have received care
644 (81)
CONSENT 6. If you had the opportunity, would you sign a consent form that would allow your doctor to use a computer to access your medical information electronically from other places where you receive medical care? Definitely or probably yes
675 (85)
Probably or definitely no
115 (15)
Do not know
10 (1) (continued on next page)
www.ajpmonline.org
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
Table 1. (continued)
79
consent rate of 90% reported by New Weighted York State RHIOs19 Question text and response options n (%) and by the Mas7. When considering whether to sign a consent form to allow doctors to electronically sachusetts eHealth access your medical data from other places, how concerned would you be about the Collaborative.16 privacy and security of your medical information? Increased support Not concerned 257 (32) among higher-income Somewhat or very concerned 540 (68) brackets previously has been reported.15 Do not know 3 (⬍1) However, some other 8. In the case of a medical emergency, where you were not able to give consent (e.g., if fındings are surprisyou were unconscious), would you want doctors caring for you to be able to use computers to access medical information electronically about you from other places ing. Our previous sinwhere you receive medical care? gle-community study Yes 718 (90) found that support was higher among No 70 (9) caregivers,15 a fınding Do not know 13 (2) not corroborated by 9. Have you ever signed a consent form to allow your doctor to access your medical the current study. data electronically from other doctors involved in your care? (An example would be if The lack of relationyou have signed consent form with an organization called a regional health information organization or RHIO.) ship between demographics and support Yes 250 (31) also contrasts with No 518 (65) some previous reDo not know 32 (4) search.14,15,18 Both may be artifacts of the strong HIE support in the current survey, which may have created a that patients may be willing to accept various mechanisms for ceiling effect. It is also possible that New Yorkers’ attiexchangingdata,aslongastheyareconvincedthattheirprivacy tudes have evolved as a result of experience with HIE. is protected. Alternately, previous smaller studies may not generalize Alternatively, differences between the models may not to the state. A counterintuitive fınding was that support have been clear to the respondents, which would support was higher among those who thought lying was more the need for increased education and engagement with all likely to occur online than in-person; these people may stakeholders. The fact that patient-controlled exchange have been expressing a skeptical view of online behavior, was not more popular than provider-managed exchange rather than distrust of electronic communication. suggests that patients do not necessarily prefer hands-on control of the process. Support was somewhat lower among those with children in the household, lower inLimitations come, distrust of large corporations, and a belief that This poll was designed to provide estimates for New people were more likely to lie in person than online. York. Generalizability to national attitudes is not known, The current fınding of a relationship between HIE supand New York’s experience with HIE may have increased port and trust in business is new but appears to be consistent familiarity with this topic. Differences between responwith other research. The California Healthcare Foundation dents and nonrespondents are not known. The survey found stronger interest in PHRs offered by providers than covered complex topics, and despite pretesting, responthose offered by insurers or companies “like Microsoft or dents may have interpreted questions differently from Google.”9 A question in that survey about sharing health what was intended. Specifıcally, the 31% who reported data with “health insurance plans, researchers, companies, consenting to HIE is inconsistent with registries by New 9 found very low support. However, that survey and others” York RHIOs, which indicate that roughly 9% of the popincluded no questions about exchange between healthcare ulation has consented to having data accessed through providers, so it is unclear whether respondents would have RHIOs; respondents may have interpreted the question expressed stronger support for clinical HIE. The 85% supto include other medical data release forms. port for clinical HIE in the current survey is consistent An additional limitation is that many potentially relevant topics, such as health insurance status, presence of with other surveys,14 –17 as well as with the median July 2012
80
Ancker et al / Am J Prev Med 2012;43(1):76 – 80
chronic diseases, experience with healthcare system, and other health questions, were not available in the Empire State Poll. As with all surveys, self-report may bias answers in unknown ways, and cross-sectional associations do not necessarily imply causal relationships.
Conclusion Given the survey fındings, policies promoting HIE for clinical care are likely to continue receiving public support. With support lower among those expressing distrust of large corporations, there may be a need for additional policy or outreach to clarify the responsibilities of businesses involved in different aspects of exchange. Three different architectures were all strongly supported. This suggests that consumers may be willing to accept a variety of models as long as they are confıdent their privacy is respected. It also supports the need for continued engagement in public discussions about HIE to ensure that consumers understand how differences in the architecture might affect them. This study was supported by New York eHealth Collaborative (NYeC). The study sponsors provided feedback on the survey instrument but played no role in study design or data analysis. The investigators thank Darren Hearn and Yasamin Miller of the Cornell Survey Research Institute for contributions to survey design and administration and Rachel Block, Ellen Flink, Steven Smith from the New York State Department of Health Offıce of Health Information Technology Transformation for feedback on the survey instrument. No fınancial disclosures were reported by the authors of this paper.
References 1. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010;363:501– 4. 2. Adler-Milstein J, McAfee AP, Bates DW, Jha AK. The state of regional health information organizations: current activities and fınancing. Health Aff (Millwood) 2008;27(1):w60 –w69. 3. Thornewill J, Dowling AF, Cox BA, Esterhay RJ. Information infrastructure for consumer health: a health information exchange stakeholder study. Am J Prev Med 2011;40(5S2):S123–S133.
4. Shaikh AR, Das IP, Vinson CA, Spring B. Cyber infrastructure for consumer health. Am J Prev Med 2011;40(5S2):S91–S96. 5. Kuperman GJ, Blair JS, Franck RA, Devaraj S, Low AFH, for the NHIN Trial Implementations Core Services Content Working Group. Developing data content specifıcations for the Nationwide Health Information Network Trial Implementations. JAMA. 2010;17(1):6 –12. 6. The Nationwide Health Information Network at the website of the Offıce of the National Coordinator for Health Information Technology. healthit.hhs.gov/portal/server.pt/community/healthit_hhs_ gov__nationwide_health_information_network/1142. 7. State Health Information Exchange Program fact sheet. healthit.hhs. gov/portal/server.pt?open⫽512&mode⫽2&objID⫽1834. 8. Kern LM, Kaushal R. Health information technology and health information exchange in New York State: new initiatives in implementation and evaluation. J Biomed Inform 2007;40(6S):S17–S20. 9. Undem T. Consumers and health information technology: a national survey. Oakland CA: California HealthCare Foundation, 2010. 10. Pritts J, Lewis S, Jacobson R, Lucia K, Kayne K. Privacy and security solutions for interoperable health information exchange. Chicago IL: Agency for Healthcare Research and Quality, Offıce of the National Coordinator for Health IT, 2009. 11. Anonymous. Privacy and security policies and procedures for RHIOs and their participants in New York State, v 2.2. Albany NY: New York eHealth Collaborative and the New York State Department of Health, 2010. nyehealth.org/images/fıles/File_Repository16/pdf/fınal%20pps%20v2.2% 204.1.11.pdf. 12. U.S. Census Bureau. State and country QuickFacts. quickfacts.census. gov/qfd/states/36000.html. 13. Anonymous. NYeC dashboard report on health information exchange users, patients, and volume. New York NY: New York eHealth Collaborative, 2011. 14. Patel VN, Dhopeshwarkar RV, Edward A, Barrón Y, Sparenborg J, Kaushal R. Consumer support for health information exchange and personal health records: a regional health information organization survey. J Med Syst 2010. 15. O’Donnell HC, Patel V, Kern LM, et al. Healthcare consumers’ attitudes toward physician and personal use of health information exchange. J Gen Intern Med 2011;26(9):1019 –26. 16. Tripathi M, Delano D, Lund B, Rudolph L. Engaging patients for health information exchange. Health Aff (Millwood) 2009;28(2):435– 43. 17. Simon SR, Evans JS, Benjamin A, Delano D, Bates DW. Patients’ attitudes toward electronic health information exchange: qualitative study. J Med Internet Res 2009;11(3):e30. 18. Wen K-Y, Kreps G, Zhu F, Miller S. Consumers’ perceptions about and use of the Internet for personal health records and health information exchange: analysis of the 2007 Health Information National Trends Survey. J Med Internet Res 2010;12(4):e73. 19. Campion TR, Kern LM, Kaushal R. Implementation factors associated with adoption of health information technology through communitybased organizations: preliminary fındings report. New York NY: Health Information Technology Evaluation Collaborative (HITEC), Weill Cornell Medical College, 2011.
www.ajpmonline.org