1) We are living in the data mining age. Provide an example on how data mining can turn a large collection of data into knowledge that can help meet a current global challenge in order to improve heal
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1) We are living in the data mining age. Provide an example on how data mining can turn a large collection of data into knowledge that can help meet a current global challenge in order to improve healthcare outcomes.
APA Style: 150 words minimum. One reference minimum within a 5 year span.
2) Topic: Healthcare Informatics Research and Innovation:
Include intro, a currently emerging healthcare technology system, goals for the product, data supporting the product, healthcare settings (including education), conclusion.
-You should carry out investigation about one of the technologies used in Health Informatics, for example EHR, CPOE, EMR, COSS, eMAR, or electronics devices used in Health Care
-APA formatted papper
– 3 References within 5 years (1 must be course textbook)
the 3 references are provided including a 4th one
1) We are living in the data mining age. Provide an example on how data mining can turn a large collection of data into knowledge that can help meet a current global challenge in order to improve heal
© 2011 Menachemi and Collum, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. Risk Management and Healthcare Policy 2011:4 47–55 Risk Management and Healthcare PolicyDovepress submit your manuscript | www.dovepress.com Dovepress 47 Review open access to scientific and medical research Open Access Full Text Article DOI: 10.2147/RMHP.S12985 Benefits and drawbacks of electronic health record systems Nir Menachemi 1 Taleah H Collum 2 1Depar tment of Health Care Organization and Policy, University of Alabama at Birmingham, Birmingham, AL, USA; 2Depar tment of Health Services Administration, University of Alabama at Birmingham, Birmingham, AL, USA Correspondence: Nir Menachemi UAB School of Public Health, 1530 3rd Ave, S Birmingham, AL 35294, USA Tel +1 205 934 7192 Fax +1 205 934 3347 email [email protected] u Abstract: The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 that was signed into law as part of the “stimulus package” represents the largest US initiative to date that is designed to encourage widespread use of electronic health records (EHRs). In light of the changes anticipated from this policy initiative, the purpose of this paper is to review and summarize the literature on the benefits and drawbacks of EHR systems. Much of the literature has focused on key EHR functionalities, including clinical decision sup- port systems, computerized order entry systems, and health information exchange. Our paper describes the potential benefits of EHRs that include clinical outcomes (eg, improved quality, reduced medical errors), organizational outcomes (eg, financial and operational benefits), and societal outcomes (eg, improved ability to conduct research, improved population health, reduced costs). Despite these benefits, studies in the literature highlight drawbacks associated with EHRs, which include the high upfront acquisition costs, ongoing maintenance costs, and disruptions to workflows that contribute to temporary losses in productivity that are the result of learning a new system. Moreover, EHRs are associated with potential perceived privacy concerns among patients, which are further addressed legislatively in the HITECH Act. Overall, experts and policymakers believe that significant benefits to patients and society can be realized when EHRs are widely adopted and used in a “meaningful” way. Keywords: EHR, health information technology, HITECH, computerized order entry, health information exchange Introduction Over the past decade, virtually every major industry invested heavily in computerization. Relative to a decade ago, today more Americans buy airline tickets and check in to flights online, purchase goods on the Web, and even earn degrees online in such disci- plines as nursing, 1 l aw, 2 and business, 3 among others. Yet, despite these advances in our society, the majority of patients are given handwritten medication prescriptions, and very few patients are able to email their physician 4 or even schedule an appointment to see a provider without speaking to a live receptionist. 5 Electronic health record (EHR) systems have the potential to transform the health care system from a mostly paper-based industry to one that utilizes clinical and other pieces of information to assist providers in delivering higher quality of care to their patients. The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, which is part of the American Recovery and Reinvestment Act (ARRA) (aka “stimulus package”), was signed into law with an explicit purpose of incentivizing providers (eg, hospitals and physicians) to adopt EHR systems. Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 48 Menachemi and Collum However, given that a bare-bone EHR system provides only partial benefits to patients and society, 6 the HITECH Act requires that providers adopt EHRs and utilize them in a “meaningful” way, which includes using certain EHR functionalities associated with error reduction and cost containment. How exactly do EHRs improve care? And what is the current evidence that certain EHR “meaningful use” functionalities will translate into benefits? Answering these questions is the purpose of this paper. Stated explicitly, the purpose of this study is to review the literature on the impacts of EHR. Impacts include both benefits and drawbacks, and, as such, we discuss the advantages and disadvantages that have been identified by researchers and other experts. Overall, we expect that any reader interested in understanding the current state of the knowledge base with regard to EHR benefits will find this paper useful. Why we need EHRs EHRs are defined as “a longitudinal electronic record of patient health information generated by one or more encoun- ters in any care delivery setting. Included in this informa- tion are patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports”. 7 Some of the basic benefits associated with EHRs include being able to easily access computerized records and the elimination of poor penmanship, which has historically plagued the medical chart. 8,9 EHR systems can include many potential capabili- ties, but three particular functionalities hold great promise in improving the quality of care and reducing costs at the health care system level: clinical decision support (CDS) tools, computerized physician order entry (CPOE) systems, and health information exchange (HIE). These and other EHR capabilities are requirements of the “meaningful use” criteria set forth in the HITECH Act of 2009. 10 A CDS system is one that assists the provider in making decisions with regard to patient care. Some functionalities of a CDS system include providing the latest information about a drug, cross-referencing a patient allergy to a medication, and alerts for drug interactions and other potential patient issues that are flagged by the computer. With the continuous growth of medical knowledge, each of these functionalities provides a means for care to be delivered in a much safer and more effi- cient manner. As more and more CDS systems are used, one can expect certain medical errors to be averted and that, overall, the patient will receive more efficient and safe care. 11 CPOE systems allow providers to enter orders (eg, for drugs, laboratory tests, radiology, physical therapy) into a computer rather than doing so on paper. Computerization of this process eliminates potentially dangerous medical errors caused by poor penmanship of physicians. It also makes the ordering process more efficient because nursing and phar – macy staffs do not need to seek clarification or to solicit miss- ing information from illegible or incomplete orders. Previous studies suggest that serious medication errors can be reduced by as much as 55% when a CPOE system is used alone, 12 and by 83% when coupled with a CDS system that creates alerts based on what the physician orders. 13 Using a CPOE system, especially when it is linked to a CDS, can result in improved efficiency and effectiveness of care. Once health data are available electronically to providers, EHRs facilitate the sharing of patient information through HIE. HIE is the process of sharing patient-level electronic health information between different organizations 14 and can create many efficiencies in the delivery of health care. 15 By allowing for the secure and potentially real-time sharing of patient information, HIE can reduce costly redundant tests that are ordered because one provider does not have access to the clinical information stored at another provider’s location. Patients typically have data stored in a variety of locations where they receive care. This can include their primary care physician’s office, as well as other physician specialists, one or more pharmacies, and other locations, such as hospitals and emergency departments. Over a lifetime, much data accumulates at a variety of different places, all of which are stored in silos. Historically, providers rely on faxing or mailing each other pertinent information, which makes it difficult to access in “real time” when and where it is needed. HIE facilitates the exchange of this information via EHRs, which can result in much more cost-effective and higher-quality care. In the following section, we describe the literature that has examined the effect of EHRs on various clinical and orga- nizational outcomes. A large proportion of the literature has focused on one or more computerized capabilities of EHRs, including CDS, CPOE, and HIE. Many of these studies have been discussed in previously published literature reviews, 16–20 so we further summarize them here. Advantages of EHRs Researchers have examined the benefits of EHRs by con- sidering clinical, organizational, and societal outcomes. Clinical outcomes include improvements in the quality of care, a reduction in medical errors, and other improvements in patient-level measures that describe the appropriateness of care. Organizational outcomes, on the other hand, have Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 49 Benefits and drawbacks of EHRs included such items as financial and operational performance, as well as satisfaction among patients and clinicians who use EHRs. Lastly, societal outcomes include being better able to conduct research and achieving improved population health. eHRs and clinical outcomes Many clinical outcomes that have been a focus of EHR studies relate to quality of care and patient safety. Quality of care has been defined as “doing the right thing at the right time in the right way to the right person and having the best possible results”, 21 and patient safety has been defined as “avoiding injuries to patients from the care that is intended to help them”. 11 Quality of care includes six dimensions, 11 but most EHR research has focused on the following three: patient safety, effectiveness, and efficiency. In the following paragraphs we summarize some of the studies that examine how EHRs or various related components impact these three quality dimensions. More research is needed on the other three components: patient centeredness, timeliness, and equitable access. EHRs, especially those with CDS tools, have been empirically linked to an increased adherence to evidence- based clinical guidelines and effective care. Despite the best intention of providers, various factors may result in patient encounters that do not adhere to best practice guidelines. Some reasons for this nonadherence include i) clinicians not knowing the guidelines, ii) clinicians not realizing that a guideline applies to a given patient, and iii) lack of time during the patient visit. EHR systems try to overcome these issues, and researchers have focused on preventive services, including vaccine administration, to examine how EHRs can improve adherence rates. For example, researchers found that computerized physician reminders increased the use of influenza and pneumococcal vaccinations from practically 0% to 35% and 50%, respectively, for hospitalized patients. 22 A similar study, but in the outpatient setting, found that computerized reminders were associated with improved influenza and pneumococcal vaccination rates among rheu- matology patients taking immunosuppressant medications. 23 Specifically, influenza vaccinations increased from 47% to 65% of patients, and pneumococcal vaccinations increased from 19% to 41% of patients. Other studies on vaccination rates found comparable results that computerized reminders can improve adherence to immunization guidelines. 24,25 From the societal public health perspective, adhering to these guidelines keeps individuals healthy and lowers the risk of disease outbreaks in communities. Researchers have also focused on other preventive services and on how EHRs can improve various outcomes and make care more effective. Kucher et al 26 hypothesized that computerized alerts, as part of a CPOE system with CDS, directed at physicians may increase the use of prophylactic care for hospitalized patients at high risk for deep vein thrombosis. They found a 19% increase in the use of anticoagulation prophylaxis when using computer alerts, and this translated into a 41% reduced risk of deep vein thrombosis or pulmonary embolism at 90 days after discharge. Willson et al 27 found a significant association between computerized reminders and pressure ulcer preven- tion in hospitalized patients. They found a 5% decrease in the development of pressure ulcers 6 months after the imple- mentation of computerized reminders that targeted hospital nurses. Other similar studies found comparable results. Rossi and Every, 28 for example, found that computerized reminders as part of a CDS have been linked to an 11.3% increase in appropriate hypertension treatment in a primary care setting. Other studies in the outpatient setting have also found that an EHR and its components significantly increase adherence to protocol-based or recommended care. 29,30 Although researchers have found CDS tools to be ben- eficial in most situations, many medical conditions do not have scientifically based guidelines for providers to follow, thus reducing the usefulness and effectiveness of these tools in many clinical situations. More scientific-based guidelines need to be developed in order to maximize the benefits associ- ated with CDS. Similar to a focus on adherence to guidelines, researchers have also found an association between EHRs and efficiency in health care delivery. Efficiency refers to the avoidance of wasting resources, including supplies, equip- ment, ideas, and energy. 11 One such form of waste involves redundant diagnostic testing. Performing redundant tests is costly and may lead to more false-positive results, which will then lead to even more costs. 31 Evidence indicates that there is a significant negative (eg, desirable) association between redundant diagnostic testing and the use of an EHR and/or its components. For example, Nies et al 32 examined the affects of a CDS on the redundancy of blood tests in a cardiovas- cular surgery department. They found that point-of-care computerized reminders of previous blood tests significantly reduced the proportion of unnecessarily repeated tests. In the outpatient setting, Tierney et al 33 found a 14.3% decrease in the number of diagnostic tests ordered per visit and a 12.9% decrease in diagnostic test costs per visit when using an EHR with CDS and CPOE components. Other, unrelated studies found an 18% decrease in tests ordered for medical visits in the emergency department, 34 a 27% decrease in Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 50 Menachemi and Collum redundant laboratory tests of antiepileptic medication levels in hospitalized patients, 35 and a 24% reduction in redundant laboratory tests in a hospital. 36 Studies focusing on patient safety have frequently exam- ined the effect of EHR components on medical or medication errors. In a widely cited study, experts found that a CPOE system was associated with a 55% reduction in serious medication errors in the hospital setting. 12 A follow-up study by the same team found that by adding a CDS system to a CPOE system, medication errors can be reduced by as much as 86%. 13 A similar, more recent study in the outpa- tient setting found that computerization resulted in an error rate reduction from 18.2% to 8.2%. 37 Other studies have concluded that the number of appropriate medication orders involving dosing levels or dosing frequency can be increased with the use of a computerized system. 38 Specifically, in one study, the use of a CDS yielded a 32% decrease in the number of days that antibiotics were prescribed outside the recommended dosage range and a 59% decrease in the need for pharmacist intervention to correct a drug dose. 39 On the other hand, a few studies have found an association between the use of CPOE and increased medical errors. These increases generally occur due to poorly designed system interfaces, lack of end-user training, 40 or lack of sys – tems integration. 41 Factors such as dense pull-down menus and text entries in inappropriate areas of an EHR can have negative consequences for patients. 40 Specifically, one study found that the use of a CPOE was associated with 22 types of medication error risks. 41 Many of the studies described have focused on clini- cal outcomes at the patient level. Such studies have been conducted in a clinical setting, frequently by employing a randomized trial research design. An additional body of lit- erature has examined, observationally, whether hospitals that have adopted EHR or other computerized capabilities per – form better than their counterparts that have not. For example, Menachemi et al 42 found that Florida hospitals with greater investments in EHR technologies had more desirable rates on a variety of commonly used quality indicators. In a simi- lar study of hospitals, researchers found that computerized records and order entry were associated with lower mortality rates, and CDS was associated with fewer complications. 43 Additionally, the same study found that computerized test results, order entry, and CDS were all associated with lower costs. However, despite the results discussed here, other researchers have found only small positive effects from EHR adoption 44,45 or mixed results. 46 eHRs and organizational and societal outcomes Organizational outcomes Studies examining organizational outcomes have focused on EHR use in both the inpatient and outpatient settings. Such outcomes have frequently included increased revenue, averted costs, and other benefits that are less tangible, such as improved legal and regulatory compliance, improved ability to conduct research, and increased job/career satisfaction among physicians. Increased revenue comes from multiple sources, including improved charge capture/decrease in billing errors, improved cash flow, and enhanced revenue. Several authors have asserted that EHRs assist providers in accurately capturing patient charges in a timely manner. 47,48 With an EHR system, many billing errors or inaccurate coding may be eliminated, which will potentially increase a provider’s cash flow and enhance revenue. 18,49,50 Reductions to outstanding days in accounts receivable and lost or disal- lowable charges can potentially lead to improved cash flow. 50 In addition, EHR reminders to providers and patients about routine health visits can increase patient visits and therefore enhance revenue. 49 Many averted costs associated with EHRs are the result of efficiencies created by having patient information electroni- cally available. Some of these include increased utilization of tests, reduced staff resources devoted to patient management, reduced costs relating to supplies needed to maintain paper files, decreased transcription costs, and the costs relating to chart pulls. The use of EHRs can reduce the redundant use of tests or the need to mail hard copies of test results to different providers. 35,51 By making patient information more readily available, EHRs reduce costs related to chart pulls 52 as well as supplies needed to maintain paper charts. 53 Studies have also shown that having an EHR as opposed to a paper file can result in reduced transcription costs through point- of-care documentation and other structured documentation procedures. 50 One author found a significant decrease in staff resources dedicated to anemia management for hemodialysis patients when a CDS was used for medication dosing. 54 Other, less tangible benefits have been associated with EHR use. In a study conducted by Bhattacherjee et al, 55 Florida hospitals with a greater adoption of health informa- tion technology had higher operational performance, as measured by outcomes of Joint Commission on Accreditation of Healthcare Organizations (JCAHO) site visits. It has also been pointed out that EHRs can facilitate improved legal and regulatory compliance in terms of increased security of Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 51 Benefits and drawbacks of EHRs data and enhanced patient confidentiality through controlled and auditable provider access. 50 In addition, researchers in Massachusetts have found that physicians using an EHR had fewer paid malpractice claims. 56 Specifically, they found that 6.1% of physicians with an EHR had a history of paid malpractice claims compared with 10.8% of physicians with- out EHRs. This reduction is potentially the result of increased communication among caregivers, increased legibility and completeness of patient records, and increased adherence to clinical guidelines. Societal benefits Another less tangible benefit associated with EHRs is an improved ability to conduct research. Having patient data stored electronically increases the availability of data, which may lead to more quantitative analyses to identify evidence- based best practices more easily. 57 Moreover, public health researchers are actively using electronic clinical data that are aggregated across populations to produce research that is beneficial to society. The availability of clinical data is limited, but as providers continue to implement EHRs, this pool of data will grow. By combining aggregated clinical data with other sources, such as over-the-counter medica- tion purchases and school absenteeism rates, public health organizations and researchers will be able to better monitor disease outbreaks and improve surveillance of potential biological threats. 58 Researchers have also found an association between EHR use and physician satisfaction with their current practice, 59 as well as their career satisfaction. 60 According to many stud- ies, physician satisfaction should be a priority in health care organizations, because it is associated with better quality of care, better prescribing behaviors, and increased retention in medical practices, particularly those in underserved areas. 61,62 To balance the generally positive findings of the afore- mentioned studies, Chaudhry et al 16 noted that a large pro- portion of the studies that found benefits from EHR were conducted in a select number of academic medical centers. This raises the question about whether or not many of the benefits identified can be generalized to other settings of care that do not have similar financial and human resources nor a decades-long commitment to health information technology. More research on the varying types and degrees of benefits associated with EHR is warranted, especially in community settings such as physician practices and nonacademic hospital settings. Potential disadvantages of EHRs Despite the growing literature on benefits of various EHR functionalities, some authors have identified potential dis- advantages associated with this technology. These include financial issues, changes in workflow, temporary loss of pro – ductivity associated with EHR adoption, privacy and security concerns, and several unintended consequences. Financial issues, including adoption and implementation costs, ongoing maintenance costs, loss of revenue associated with temporary loss of productivity, and declines in revenue, present a disincentive for hospitals and physicians to adopt and implement an EHR. EHR adoption and implementation costs include purchasing and installing hardware and soft- ware, converting paper charts to electronic ones, and training end-users. Many studies have documented these costs in both the inpatient and outpatient settings. 47,50 In a 2002 study con- ducted in a 280-bed acute care hospital, the projected total cost for a 7-year-long EHR installation project was approximately US$19 million. 47 In the outpatient setting, early researchers estimated an average initial cost of US$50,000–US$70,000 per physician for a three-physician office. 50 However, as EHR technologies have become more commonplace over the past decade, the initial cost of systems has come down dramatically. One industry group estimated hardware, software, services, and telecommunications cost of approximately US$14,000 per physician in the initial year of implementation for a six- physician practice and US$19,000 per physician with three or fewer physicians. 63 Similarly, a recent study estimates initial costs of software, training, and installation of US$22,038 and hardware costs of US$13,000 per full-time-equivalent (FTE) provider in a solo or small-group primary care practice. 64 Lastly, another study estimated costs during the first 60 days of launch of US$162,047 (or US$32,409 per physician) for a five-physician practice to implement an EHR system. 65 The maintenance cost of an EHR can also be costly. Hardware must be replaced and software must be upgraded on a regular basis. In addition, providers must have ongoing training and support for the end-users of an EHR. According to one study conducted on 14 solo or small-group primary care practices, estimated ongoing EHR maintenance costs averaged US$8412 per FTE provider per year. A total of 91% of this cost was related to hardware replacement, vendor software maintenance and support fees, and payments for information systems staff or external contractors. 64 Other estimates of ongoing maintenance costs for the first year after implementation were about US$17,100 per physician in a medical group of five. 65 Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 52 Menachemi and Collum The costs of EHR adoption, implementation, and ongoing maintenance are compounded by the fact that many financial benefits of an EHR generally do not accrue to the provider (who is required to make the upfront investment) but rather to the third-party payers in the form of errors averted and improved efficiencies, which translate into reduced claims payments. This misalignment of incentives for health care organizations, along with the high upfront costs, creates a bar – rier to adoption and implementation of an EHR, especially for smaller practices. In fact, physicians frequently cite upfront costs and ongoing maintenance costs as the largest barriers to adoption and implementation of an EHR. 66 Another disadvantage of an EHR is disruption of work- flows for medical staff and providers, which result in tem- porary losses in productivity. This loss of productivity stems from end-users learning the new system and may potentially lead to losses in revenue. One study involving several internal medicine clinics estimated a productivity loss of 20% in the first month, 10% in the second month, and 5% in the third month, with productivity subsequently returning to its origi- nal levels. 52 In that study, the loss in productivity resulted in lost revenue of US$11,200 per provider in the first year. In a study of solo and small-group primary care practices of one to six FTE providers, revenue losses from reduced visits during the initial stages of an EHR averaged approximately US$7500 per FTE provider. This depended on whether physicians worked longer hours during this stage or reduced patient visits. 64 Lastly, researchers have estimated that EHR end-users spent 134.2 hours on implementation activities associated with getting and learning a new system. These hours spent on nonclinical responsibilities had an estimated cost of US$10,325 per physician. 65 Other declines in revenue are possible following EHR implementation. Because EHRs are often associated with fewer redundancies, fewer errors, and shorter lengths of stay, it is conceivable that a given provider may avert certain bill- able transactions that, although superfluous, may have gener – ated reimbursements from third-party payers, especially in a fee-for-service payment system. Although reimbursement rates may differ for each organization, these declines could be offset by increased revenue that is generated as a result of efficiencies achieved with the help of an EHR system. 64 Another potential drawback of EHRs is the risk of patient privacy violations, which is an increasing concern for patients due to the increasing amount of health informa- tion exchanged electronically. 67,68 To relieve some of these concerns, policymakers have taken measures to ensure safety and privacy of patient data. For example, recent legislation has imposed regulations specifically relating to the electronic exchange of health information that strengthen existing Health Insurance Portability and Accountability Act privacy and security policies. 69 Although few electronic data are 100% secure, the rigorous requirements set forth by the new legislation make it much more difficult for electronic data to be accessed inappropriately. For example, all EHR systems are required to have an audit function that allows system operators to identify each individual who accessed every aspect of a given medical record. Many hospitals and physicians are implementing strict, no tolerance penalties for employees who access files inappropriately. For example, a hospital in Arizona terminated several employees after they inappropriately accessed the records of victims who were hospitalized after the January 2011 shooting involving a US Congresswoman. 70 Although privacy will likely continue to be a concern for patients, many steps are being taken by policymakers and individual organizations to ensure that EHRs comply with the strict laws and regulations intended to ensure the privacy of clinical information. EHRs may cause several unintended consequences, such as increased medical errors, negative emotions, changes in power structure, and overdependence on technology. 40 As mentioned previously, researchers have found an asso- ciation between the use of CPOE and increased medical errors due to poorly designed system interfaces or lack of end-user training. Additionally, end-users of an EHR may experience strong emotional responses as they struggle to adapt to new technology and disruptions in their workflow. Changes in the power structure of an organization may also occur due to the implementation of an EHR. For example, a physician may lose his or her autonomy in making patient decisions because an EHR blocks the ordering of certain tests or medications. Overdependence on technology may also become an issue for providers as they become more reliant upon it. Organizations should ensure that basic medi- cal care can still be provided in the absence of technology, especially in times when the downtime of the system may be critical. Although there are many unintended consequences of EHRs, when balancing the advantages and disadvan- tages of these systems, they are beneficial, especially at the society level. Conclusion In this paper we discussed several advantages and disad- vantages associated with an EHR adoption. Many of the benefits accrue to patients and society overall. For these benefits to be realized, the US Government has embarked Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.com Dovepress Dovepress 53 Benefits and drawbacks of EHRs on an ambitious journey to transition a maximum number of providers toward EHR adoption and “meaningful use”. Without ubiquitous use of EHR technologies, experts believe that many efficiencies in the US health care system cannot be realized. 15 The financial incentives built into the HITECH Act are designed to defray some of the costs associated with EHR adoption, especially for smaller organizations where these expenses serve as a major barrier. The financial incentives in HITECH, which are made available through the Medicare and Medicaid programs, are also an attempt to correct some of the misalignment of incentives associated with EHR as discussed previously, especially because the US Government, through the Medicare and Medicaid programs, is the largest insurer in the country. I n c e n t ive s m a d e ava i l a bl e t o p hy s i c i a n s t h r o u g h the HITECH Act differ among Medicaid and Medicare physicians. 71 Medicaid offers more generous incentives than Medicare and has less stringent requirements for the first year. Physicians with more than 30% of their patients paying with Medicaid are eligible for up to US$63,750 in incentives over a 6-year period. They can begin earning these incentives as they adopt, implement, or upgrade an EHR. The last year to begin participation in the Medicaid incentive program is 2016, and physicians do not need to begin prov- ing “meaningful use” until the second year of their program participation. On the other hand, physicians accepting more Medicare patients are eligible for up to US$44,000 over a 5-year period as long as they can meet the “meaningful use” criteria starting the first year. Physicians not meeting the “meaningful use” criteria by 2015 will be assessed for penalties in the form of reduced Medicare reimbursements. Physicians are allowed to participate in either the Medicaid or Medicare incentive program, but not both. Those who are eligible are expected to participate in the Medicaid program, because its benefits are more generous. Hospitals are also eligible for incentives under the HITECH Act. The amount of the incentives they receive depends on a number of fac- tors, but the base amount to each hospital that complies with the meaningful use criteria will be more than US$2 million. Both physician and hospital incentives are structured so that those immediately achieving meaningful use of an EHR will receive larger payments. Providers are also expected to face technological and logistical obstacles on their quest to achieve meaningful use of EHRs. 72 To help combat the technological problems faced by providers, the federal government, through the HITECH Act, has committed approximately US$650 mil- lion for the establishment of a network of up to 70 regional health information technology extension centers. The primary purpose of these organizations is to offer advice to physi- cians on which information technology systems they should purchase and assistance on how to become meaningful users of EHRs. To address some of the logistical problems associated with EHRs, the federal government has entrusted US$560 million under the HITECH Act to state govern- ments for the development of infrastructure to facilitate the exchange of health information. Nationwide implementation of EHRs is a necessary, although not sufficient, part in transforming the US health care system for the better. EHR adoption must be consid- ered one of many approaches that diversify our focus on quality improvement and cost reduction. The current major legislative and political support for EHRs represents the greatest investment in health information technologies in US history. Over time, providers and researchers will be eager to quantify the returns that are expected from these investments. Disclosure The authors report no conflicts of interest in this work. References 1. Mancuso-Murphy J. 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Development and impact of a computerized pediatric antiinfective decision support program. Pediatrics. 2001;108(4):E75. 40. Campbell EM, Sittig DF, Ash JS, et al. Types of unintended conse- quences related to computerized provider order entry. J Am Med Inform Assoc. 2006;13(5):547–556. 41. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA. 2005; 293(10):1197–1203. 42. Menachemi N, Chukmaitov A, Saunders C, Brooks R. Hospital quality of care: does information technology matter? The relationship between information technology adoption and quality of care. Health Care Manage Rev. 2008;33(1):51–59. 43. Amarasingham R, Plantinga L, Diener-West M, et al. Clinical informa – tion technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108–114. 44. DesRoches CM, Campbell EG, Vogeli C, et al. Electronic health records’ limited successes suggest more targeted uses. 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Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA. 1993;269(3):379–383. 52. Wang SJ, Middleton B, Prosser LA, et al. A cost-benefit analysis of electro – nic medical records in primary care. Am J Med. 2003;114(5):397–403. 53. Ewing T, Cusick D. Knowing what to measure. Healthcare Financial Management. 2004;58(6):60–63. 54. Miskulin DC, Weiner DE, Tighiouart H, et al. Computerized decision support for EPO dosing in hemodialysis patients. Am J Kidney Dis. 2009;54(6):1081–1088. 55. Bhattacherjee A, Hikmet N, Menachemi N, et al. The differential performance effects of healthcare information technology adoption. Information Systems Management. 2007;24(1):5–14. 56. Virapongse A, Bates DW, Shi P, et al. Electronic health records and malpractice claims in office practice. Arch Intern Med. 2008;168(21): 2362–2367. 57. Aspden P. Patient Safety Achieving a New Standard for Care . Washington, D.C.: National Academies Press; 2004. 58. Kukafka R, Ancker JS, Chan C, et al. Redesigning electronic health record systems to support public health. J Biomed Inform. 2007;40(4): 398–409. Risk Management and Healthcare Policy Publish your work in this journal Submit your manuscript here: http://www.dovepress.com/risk-management-and-healthcare-policy-journal Risk Management and Healthcare Policy is an international, peer- reviewed, open access journal focusing on all aspects of public health, policy, and preventative measures to promote good health and improve morbidity and mortality in the population. The journal welcomes submit- ted papers covering original research, basic science, clinical & epidemio-logical studies, reviews and evaluations, guidelines, expert opinion and commentary, case reports and extended reports. The manuscript manage- ment system is completely online and includes a very quick and fair peer- review system, which is all easy to use. Visit http://www.dovepress.com/ testimonials.php to read real quotes from published authors. Risk Management and Healthcare Policy 2011:4 submit your manuscript | www.dovepress.co m Dovepress Dovepress Dovepress 55 Benefits and drawbacks of EHRs 59. Menachemi N, Powers TL, Brooks RG. The role of information technology usage in physician practice satisfaction. Health Care Manage Rev. 2009;34(4):364–371. 60. Elder KT, Wiltshire JC, Rooks RN, et al. Health information technol- ogy and physician career satisfaction. Perspect Health Inf Manag. 2010;7:1d. 61. Linzer M, Konrad TR, Douglas J, et al. Managed care, time pressure, and physician job satisfaction: results from the physician worklife study. J Gen Intern Med. 2000;15(7):441–450. 62. Pathman DE, Williams ES, Konrad TR. Rural physician satisfaction: its sources and relationship to retention. J Rural Health. 1996;12(5): 366–377. 63. CDW. CDW Healthcare Physician Practice EHR Price Tag. Vernon Hills, IL; 2010. 64. Miller RH, West C, Brown TM, et al. The value of electronic health records in solo or small group practices. Health Aff (Millwood). 2005; 24(5):1127–1137. 65. Fleming NS, Culler SD, McCorkle R, et al. The financial and nonfi- nancial costs of implementing electronic health records in primary care practices. Health Aff (Millwood). 2011;30(3):481–489. 66. Menachemi N. Bar riers to ambulatory EHR: who are ‘imminent adopters’ and how do they differ from other physicians? Inform Prim Care. 2006;14(2):101–108. 67. Zurita L, Nohr C. Patient opinion: EHR assessment from the users perspective. Stud Health Technol Inform. 2004;107(2):1333–1336. 68. Westin AF. Public attitudes toward electronic health records. Privacy and American Business. 2005;12(2):1–6. 69. Parver C. How the American Recovery and Reinvestment Act of 2009 Changed HIPAA’s privacy requirements. CCH Health Care Compliance Letter. July 28, 2009:4–7. 70. Innes S. 3 UMC workers fired for invading records. Arizona Daily Star. January 13, 2011. 71. Bruen BK, Ku L, Burke MF, Buntin MB. More than four in five office- based physicians could qualify for federal electronic health record incentives. Health Aff (Millwood). 30(3):472–480. 72. Blumenthal D. Stimulating the adoption of health infor mation technology. N Engl J Med. 2009;360(15):1477–1479.
1) We are living in the data mining age. Provide an example on how data mining can turn a large collection of data into knowledge that can help meet a current global challenge in order to improve heal
ORIGINAL INVESTIGATION Electronic Health Records and Malpractice Claims in Office Practice Anunta Virapongse, MD, MPH; David W. Bates, MD, MSc; Ping Shi, MA; Chelsea A. Jenter, MPH; Lynn A. Volk, MHS; Ken Kleinman, ScD; Luke Sato, MD; Steven R. Simon, MD, MPH Background: Electronic health records (EHRs) may im- prove patient safety and health care quality, but the re- lationship between EHR adoption and settled malprac- tice claims is unknown. Methods: Between June 1, 2005, and November 30, 2005, we surveyed a random sample of 1884 physicians in Mas- sachusetts to assess availability and use of EHR func- tions, predictors of use, and perceptions of medical prac- tice. Information on paid malpractice claims was accessed on the Massachusetts Board of Registration in Medicine (BRM) Web site in April 2007. We used logistic regres- sion to assess the relationship between the adoption and use of EHRs and paid malpractice claims. Results: The survey response rate was 71.4% (1345 of 1884). Among 1140 respondents with data on the pres- ence of EHR and available BRM records, 379 (33.2%) had EHRs. A total of 6.1% of physicians with an EHR had ahistory of a paid malpractice claim compared with 10.8% of physicians without EHRs (unadjusted odds ratio, 0.54; 95% confidence interval, 0.33-0.86;P= .01). In logistic re- gression analysis controlling for sex, race, year of medical school graduation, specialty, and practice size, the rela- tionship between EHR adoption and paid malpractice settle- ments was of smaller magnitude and no longer statisti- cally significant (adjusted odds ratio, 0.69; 95% confidence interval, 0.40-1.20;P= .18). Among EHR adopters, 5.7% of physicians identified as “high users” of EHR had paid malpractice claims compared with 12.1% of “low users” (P= .14). Conclusions: Although the results of this study are in- conclusive, physicians with EHRs appear less likely to have paid malpractice claims. Confirmatory studies are needed before these results can have policy implications. Arch Intern Med. 2008;168(21):2362-2367 I N THE PAST 10 YEARS ,HEALTH IN – formation technology (HIT) has emerged as an essential compo- nent of a transformed health care system that focuses on safety, qual- ity, and efficiency. 1,2 Although results of some studies have been equivocal, 3,4the po- tential impact of HIT on the safe practice of medicine seems increasingly compel- ling: if used actively by caregivers, studies indicate that HIT can reduce adverse drug events and improve physician perfor- mance in areas such as diagnosis, preven- tive care, disease management, drug dos- ing, and drug management. 5,6 One component of HIT in particular, elec- tronic health records (EHRs), has been tar- geted by policymakers as an essential tool for ensuring the secure availability of pa- tient health records across health care en- tities and for reducing health care spend- ing. 7Many clinicians have also recognized the benefits of implementing an EHR de- spite the large initial capital expenditure. Research indicates that EHRs can improvedocumentation, enhance the efficiency of clinic visits, 8minimize medication errors, and enable clinicians to perform popula- tion surveillance and monitoring. 2,9As a re- sult, EHRs are being increasingly adopted by caregivers seeking to improve the qual- ity of patient care. 10 The potential for EHRs to prevent ad- verse events and reduce health care costs has also created interest in whether use of EHRs reduces the risk of malpractice law- suits. The Joint Commission on Accredi- tation of Healthcare Organizations has sug- gested that HIT can address factors that have proved to be risk points for error and subsequent malpractice suits by patients, such as communication among care- givers, availability of patient informa- tion, medication prescribing, and adher- ence to clinical guidelines. 11One study 12 that involved 307 closed malpractice cases claiming medical negligence found that more than half of the cases were due to di- agnostic errors that harmed patients. Most of these errors occurred because of fail- Author Affiliations:Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital (Drs Virapongse, Bates, and Sato and Ms Jenter), Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care (Ms Shi and Drs Kleinman and Simon), Boston, Partners Health Care, Wellesley (Dr Bates and Ms Volk), Harvard Risk Management Foundation, Cambridge (Dr Sato), Massachusetts. (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2362 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020 ure to order diagnostic tests or lack of a follow-up plan. Because EHRs and HIT seem to mitigate reliance on cog- nitive factors through clinical decision support and avoid- ance of errors of omission, diagnostic errors may in turn decrease with implementation of such systems. Further- more, electronic documentation tends to be superior to the paper record in legibility and completeness. Since many lawsuits hinge on the presentation of proper docu- mentation to the court, a thorough and accurate medi- cal record would likely make lawsuits easier to defend for physicians. 13Many malpractice claims also base their allegations on the failure to adhere to the standard of care. With the inclusion of decision support into an EHR, phy- sicians can be presented with the relevant guidelines from the onset of ordering treatment and may be more likely to adhere to them. In addition, malpractice claims due to medical errors constitute the bulk of malpractice claim payouts and ad- ministrative costs. 14Of all malpractice claims, 83% show no evidence of negligence, and most of these claims with- out injury are uncompensated or account for a small frac- tion of overall malpractice costs. 14,15 Thus, if medical er- rors were minimized through HIT, significant health care savings would occur through a reduction in tort- associated costs. Conversely, some studies 16,17 have shown that HIT has the potential to increase adverse events at- tributable to information errors and human-machine in- terface flaws. Although these reports primarily focus on computerized physician order entry systems in hospital settings, the fact remains that adoption of any HIT is not without risk, and unintended consequences may create a new realm of litigation issues. Despite a considerable body of evidence indicating that HIT can prevent medical errors, little is known about the relationship between EHR adoption in the office prac- tice setting and medical malpractice claims. Few data are available to evaluate the association between use level of EHR functions and the prevalence of malpractice claims. In the inpatient setting, use of computerized physician order entry was correlated with a lower frequency of medi- cation-related malpractice claims, 18but the frequency of these claims is low enough to make such analyses diffi- cult. To assess whether EHR use was associated with fewer paid malpractice claims, we linked survey data about EHR adoption and use to physician profile data from the Mas- sachusetts Board of Registration in Medicine (BRM). METHODS The sampling methods, survey questionnaire development, and survey administration have been published elsewhere 19,20 and are described briefly herein. SAMPLE Using a database from a private vendor (Folio Associates, Hy- annis, Massachusetts) and information from the BRM, 21we iden- tified the population of practicing physicians in Massachu- setts in 2005. After excluding physicians who were residents in training, retired, or without direct patient-care responsibili- ties, the total population of physicians was 20 227. These phy- sicians practiced in 6174 unique practice sites in Massachu-setts. Of these practices, a stratified random sample of 1921 practices was obtained, and 1 physician from each practice was randomly selected for the survey. After excluding practices that had closed, the final sample size was 1884 physicians. SURVEY We administered a survey by mail between June 1, 2005, and November 30, 2005, to physicians in office practice in Massa- chusetts. The 8-page questionnaire was based on a systematic review of the literature regarding barriers to EHR adoption and ascertained physician and practice characteristics, adoption of EHRs and other HIT, and use of EHR functions. Initially, the sur- vey was sent via express mail with a $20 cash honorarium. Two subsequent mailings to nonresponders were sent without remu- neration. Between mailings, multiple telephone contacts were at- tempted to remind physicians to complete the survey. The survey ascertained physicians’ personal demographic and practice characteristics and their use of HIT, including EHRs. Physicians reported their age; race, which we dichotomized as white vs other; year of medical school graduation; and num- ber of physicians in their practice. We determined each phy- sician’s specialty from the database from which we drew the survey sample. MALPRACTICE CLAIMS DATA COLLECTION In April 2007, available identifying data (name, date of gradu- ation, and zip code) were used to access each survey respon- dent’s physician profile on the BRM Web site (http://profiles .massmedboard.org/MA-Physician-Profile-Find-Doctor.asp). The BRM Web site contains information only for the previous 10 years of the physician’s practice. Two trained data extractors (including A.V.), blinded to the physicians’ responses to the survey questionnaire and the specialties of the physicians, in- dependently determined the presence or absence of a paid mal- practice claim for each study physician from the BRM Web site. If a paid malpractice claim was present, then number of claims and year of the settlement payment was noted. Data collection sheets from the 2 data extractors were com- pared for accuracy, and any discrepancies were adjudicated using the BRM Web site. After a master data extraction form was com- piled, the names and addresses of the respondents were re- moved and pertinent measures from the survey were merged. The study protocol was approved by the Partners HealthCare Human Research Committee. STATISTICAL ANALYSIS Statistical analysis was performed using commercially avail- able software programs (Stata Intercooled 9; StataCorp, Col- lege Station, Texas; and SAS statistical software, version 9.1; SAS Institute Inc, Cary, North Carolina). Baseline character- istics between respondents who were EHR adopters and non- adopters, as well as between physicians with and without paid malpractice claims, were compared using the Pearson 2test, the Wilcoxon rank sum test, and the unpaired, 2-tailedttest. The primary outcome, the presence or absence of paid mal- practice claims among physicians using EHRs and those not using EHRs, was assessed using the Pearson 2and Fisher ex- act test, as appropriate, and calculating unadjusted odds ratios (ORs) with 95% confidence intervals (CIs). We used logistic regression to adjust for the potential in- fluence of physician characteristics on the relationship be- tween EHR and malpractice claims. The model was run first with all covariates and then with inclusion only of those vari- ables found to be statistically significantly associated (P .05) (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2363 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020 with paid malpractice claims in bivariate analysis. Because age and graduation year were highly correlated, only graduation year (a proxy for years in practice) was used in the logistic re- gression models. In an exploratory analysis to address the po- tential temporal relationship between EHR adoption and the prevention of malpractice settlements, we excluded any phy- sicians who had paid malpractice claims the date of which pre- ceded the date of EHR adoption. In this analysis, we also ex- cluded any physicians who had adopted EHRs after 2001 based on the assumption that it would take a minimum of 5 years for a malpractice event to result in a paid settlement. A subsequent analysis limited to EHR adopters examined the relationship between use of EHR functions and paid mal- practice claims. Physicians with EHRs were asked to docu- ment the availability and degree of use of 10 key functions in their EHR. Those who used half or more of their available func- tions all or most of the time were considered “high EHR us- ers,” whereas the remaining physicians were classified as “low users.” 20The rate of paid malpractice claims among high and low users was compared using the 2test. To determine whether the relationship between EHR adop- tion and paid malpractice claims was similar among physicians in specialties considered high risk vs low risk for malpractice claims, we first determined the percentage of physicians with paid malpractice claims in each specialty within our data set. The per- centages ranged from 0% (dermatology) to 34.6% (general sur- gery). We dichotomized the sample at the median (10.5%) to create a variable that indicated whether each physician prac- ticed in a low-risk or high-risk specialty. For example, internal medicine (7.1%) and family medicine (10.5%) were considered in the low-risk group, whereas obstetrics and gynecology (24.2%) and urology (30.8%) were in the high-risk group. We then ex- amined the relationship between the presence of EHR and paid malpractice settlements within each stratum. RESULTS As reported previously, 19,20 1345 physicians completed the survey (response rate, 71.4%). We excluded 157 phy- sicians who indicated that they did not see outpatientsand 41 physicians who did not have physician profiles on the BRM Web site ( Figure ). Seven physicians did not answer survey questions regarding use of EHRs. This re- sulted in 1140 respondents eligible for analysis. EHR ADOPTION Overall, 33.2% of the sample (379 of 1140) used EHRs in their practices ( Table 1 ). Physicians who used EHRs were younger than those who did not use EHRs (mean age, 49.1 vs 52.8 years;P .001) and had completed medi- cal school more recently (median graduation year, 1987 vs 1983;P .001). The EHR adopters were less likely to be in solo practice (14.2% vs 35.9%;P .001). Among physicians who used EHRs, 71.8% reported implement- ing their systems within the 10 years preceding the sur- vey. Duration of EHR use ranged from less than 1 year to 18 years among survey respondents who used EHRs in their practice. PAID MALPRACTICE CLAIMS A total of 105 of the 1140 survey respondents (9.2%) had a history of 1 or more malpractice payments within the past 10 years ( Table 2 ). Paid malpractice claims were more common among male physicians (11.1%) than fe- male physicians (5.6%) (P= .003). Paid malpractice claims were more common among physicians who had been in practice longer. For example, 15.2% of physicians who graduated from medical school more than 20 years ago had paid malpractice claims in the past 10 years com- pared with 5.8% of physicians who had graduated within the past 20 years (P .001) (data not shown). Practice size was also correlated with malpractice claims. Paid mal- practice claims were more common among physicians in solo practice (43.7%) and among those in small group practices of 2 to 4 people (29.1%) and 5 to 9 people (19.4%) than among physicians who practiced in groups of 10 or more physicians (7.8%). Respondents for matching on BRM Web site 1188 Physicians were sent initial survey 1884 Did not answer EHR questions on survey 7 Excluded because of no BRM physician profile 41 Excluded because they reported not seeing outpatients 157 Physicians did not respond 539 Respondents remaining 1147 Survey respondents 1345 Respondents remaining for analysis 1140 Figure.Flow diagram of included and excluded survey respondents. BRM indicates Board of Registration in Medicine; EHR, electronic health record. Table 1. Characteristics of EHR Adopters and Nonadopters a CharacteristicEHR Adopters (n = 379)EHR Nonadopters (n = 761)PValue Age, mean (SD), y 49.1 (9.6) 52.8 (10.7) .001 Women 133 (35.7) 224 (29.9) .05 White race 308 (84.9) 619 (84.9) .98 Median year of medical school graduation (IQR)1987 (1980-1993) 1983 (1974-1991) .001 Practice size .001 Solo practice 53 (14.2) 268 (35.9) 2-4 Physicians 71 (19.0) 268 (35.9) 5-9 Physicians 110 (29.5) 131 (17.5) 10 Physicians 139 (36.3) 80 (10.7) Primary care b 149 (40.2) 297 (39.5) .83 Abbreviations: EHR, electronic health record; IQR, interquartile range. aData are presented as number (percentage) of study participants unless otherwise indicated. Categories do not sum to 1140 because of participant nonresponse; denominators vary for the same reason. bPrimary care included family practice, general internal medicine, general pediatrics, combined medicine and pediatrics, and geriatrics. (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2364 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020 Among physicians who used EHRs, 6.1% had a rec- ord of paid malpractice claims compared with 10.8% of physicians who did not use EHRs (unadjusted OR, 0.54; 95% CI, 0.33-0.86;P= .01) (Table 2). In logistic regres- sion analysis controlling for physician sex, race, year of medical school graduation, specialty, and practice size, the relationship between EHR adoption and paid mal- practice settlements was of smaller magnitude and no longer statistically significant (adjusted OR, 0.69; 95% CI, 0.40-1.20;P= .18) ( Table 3 ). A more parsimonious model that adjusted only for variables found to be asso- ciated with the outcome variable demonstrated a rela- tionship between EHR adoption and paid malpractice claims (OR, 0.68; 95% CI, 0.40-1.16;P= .16) that did not materially differ from the fully adjusted model. In the exploratory analysis that excluded physicians who had adopted EHRs after 2001 and those with paid malpractice settlements the date of which preceded the EHR adoption date, the resultant sample was limited to 117 EHR adopters, of whom 2 (1.7%) had paid malprac- tice settlements. In logistic regression analysis, control- ling for physician sex, year of medical school gradua- tion, and practice size, a significant association was found, indicating that physicians with EHRs were less likely to have paid malpractice claims (adjusted OR, 0.19; 95% CI, 0.05-0.78). The power for this analysis was ex- tremely small because of the small number of outcomes in EHR adopters, and excluding subjects from this group in a nonrandom manner may have led to a more biased result. Within the physician group that used EHRs, 299 phy- sicians were characterized as high users and 33 as low users. Seventeen of the high users (5.7%) had paid mal- practice claims compared with 4 of the low users (12.1%) (P= .14). Among the 105 physicians with any paid mal- practice claims, 16 had multiple paid claims during the observation period, 3 of whom had EHRs. This preva- lence of EHR adoption among physicians with multiple claims (3 of 16 physicians [18.8%]) was similar to that among those with only 1 paid claim (20 of 89 [22.5%]) (P= .74). In stratified analyses, the relationship between the presence of EHR and paid malpractice claims was simi- lar among physicians practicing in high-risk specialties (OR, 0.55; 95% CI, 0.27-1.12;P= .10) and those in low- risk specialties (0.51; 0.26-1.00;P= .05). COMMENT In this cross-sectional study, we found that physicians who used EHRs were less likely to have paid malprac- tice claims compared with physicians who did not use EHRs. Although this relationship is partially con- founded by physician sex, year of medical school gradu- ation, and practice size, the presence of EHR appears to be associated with a lower malpractice risk. This impres- sion is further strengthened by the observed trend among physicians with EHRs that suggests lower rates of paid malpractice claims among more avid users of their EHR systems. Few previous studies have directly examined the re- lationship between EHR adoption and malpractice claims.Although 1 study 18found that computerized physician order entry was associated with a lower rate of malprac- tice claims in the hospital, studies of HIT and malprac- tice claims in the ambulatory setting have been lacking. The results of this study support the hypothesis that EHR adoption and use lead to improved quality of care and patient safety, resulting in fewer adverse events and fewer paid malpractice claims. A number of mechanisms could be responsible for a lower frequency of malpractice claims. For example, use of EHRs may lead to fewer diagnostic errors, improved follow-up of abnormal test results, bet- ter guideline adherence, and fewer adverse clinical events. Alternatively, EHRs may be facilitating more extensive Table 2. Characteristics of Physicians With Malpractice Settlements a CharacteristicPhysicians With Malpractice Settlements (n = 105)Physicians Without Malpractice Settlements (n = 1035)PValue Age, mean (SD), y 49.5 (10.7) 54.1 (8.7) .001 Median year of medical school graduation (IQR)1977 (1971-1985) 1986 (1977-1992) .001 Graduated medical school before 198062 (59.0) 346 (33.4) .001 Women 20 (19.0) 337 (33.1) .003 White race 88 (86.3) 839 (84.7) .77 Practice size .001 Solo practice 45 (43.7) 276 (27.1) 2-4 Physicians 30 (29.1) 309 (30.4) 5-9 Physicians 20 (19.4) 221 (21.7) 10 Physicians 8 (7.8) 211 (20.8) Primary care b 39 (37.5) 407 (39.9) .67 EHR adoption 23 (21.9) 356 (34.4) .009 Abbreviations: EHR, electronic health record; IQR, interquartile range. aData are presented as number (percentage) of study participants unless otherwise indicated. Data were missing for sex (n = 18), race (n = 48), practice size (n = 20), specialty (n = 17), and any component of EHRs in practice (n = 1). Denominators vary because of missing data. bPrimary care included family practice, general internal medicine, general pediatrics, combined medicine and pediatrics, and geriatrics. Table 3. Correlates of Paid Malpractice Claims From a Logistic Regression Model a CharacteristicAdjusted OR (95% CI)PValue EHR adoption 0.69 (0.40-1.20) .18 Medical school graduation year0.96 (0.95-0.98) .001 Women 0.59 (0.34-1.02) .06 White race 0.92 (0.49-1.71) .78 Practice size Solo practice 2.39 (1.03-5.53) .04 2-4 Physicians 2.20 (0.95-5.10) .07 5-9 Physicians 2.30 (0.97-5.47) .06 10 Physicians 1 [Reference] Primary care 1.00 (0.64-1.56) .99 Abbreviations: CI, confidence interval; EHR, electronic health record; OR, odds ratio. aModel adjusted for EHR adoption status, year of medical school graduation, sex, race, practice size, and specialty. (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2365 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020 and more legible documentation of medical practice, re- sulting in stronger legal defenses when malpractice suits are filed. In addition, EHRs may be enhancing patient- physician communication, an important determinant of malpractice claims. 22 If confirmed in future studies, the observed relation- ship between EHR adoption and paid malpractice claims could have implications for physicians and malpractice insurers. First, for practices struggling to reconcile the expense of investing in HIT, 19the potential benefit of fewer malpractice claims may tip the scale toward EHR adop- tion. Second, if EHRs are proved to be an effective tool in minimizing tort claims and improving patient safety, insurance companies may lower malpractice premiums for practices with EHRs. Currently, most liability insur- ers adjust physicians’ premiums by specialty, location, and past malpractice experience. 23,24 We are familiar with 1 carrier that has instituted a premium credit for physi- cians and practices with EHRs. 25If other carriers follow, lower malpractice premiums could provide an addi- tional incentive for clinicians considering the purchase of an EHR system for an office practice. The relationship between EHR adopters and malprac- tice claims also has potential health care policy implica- tions. If confirmed in future studies, our results may give the federal government and other payers further incen- tive to fund subsidies for EHR adoption because of the additional reduction in health care costs through a de- crease in medical liability and associated costs. A strength of this study is its use of verified paid mal- practice claims rather than claims filed. Because most closed malpractice claims have proved negligence, 14by identifying only claims that had been paid out rather than those filed, we were able to exclude lawsuits whose out- come was still in doubt, as well as so-called frivolous law- suits. In addition, our survey enabled us to examine not only EHR adoption but also use of key EHR functions as they relate to paid malpractice claims. This study has several important limitations. Al- though provocative, our findings are inconclusive. They should not be interpreted as establishing a causal link be- tween EHR adoption and the prevention of malpractice claims. It is possible that unmeasured confounding ac- counts for the fact that physicians who use EHRs may be less likely to be subjects of successful malpractice liti- gation. For instance, use of EHR may be an intermedi- ate marker for preestablished physician behaviors or prac- tice variations that may lead to a reduction in malpractice claims. Another limitation is our data source for malpractice claims, the BRM Web site, which indicates only paid mal- practice settlements; malpractice suits that were dis- missed or still in process are not included. Further- more, detailed information regarding the nature of the claim is not available. Relying on paid malpractice settle- ments created a 5-year or longer time lag between the time when the putative error and adverse event oc- curred and the time when the claim was settled and paid. Moreover, because the BRM posts data on physicians only for the preceding 10 years, additional malpractice claims for physicians in practice earlier than this period may not have been captured.To compensate for these cross-sectional limitations, future studies would ideally include a longitudinal data source that would record the physician’s date of EHR implementation and use, along with the date of the li- able incident, filing date, and its outcome. Such studies would require an observation period of many years to ac- count for the time lag between the malpractice-related event and the consequent settlement process. We con- ducted an exploratory analysis to isolate the temporal re- lationship between EHR adoption and paid malpractice settlements that yielded results consistent with the pri- mary analyses; however, this exploratory analysis must be interpreted with caution because of the small num- ber of outcomes observed and the resulting imprecision of the effect estimate. An additional limitation is that this study was con- ducted among physicians licensed in Massachusetts, and the results may not be applicable to the remainder of the nation. On the basis of a previous analysis, 19Massachu- setts EHR adoption rates (23% of practices and 45% of physicians) are considerably higher than rates observed nationwide. The percentage of Massachusetts physi- cians with malpractice claims may also be different from the national average. The Kaiser Family Foundation re- ported that, in 2007, Massachusetts had 8 claims per 1000 nonfederal physicians, half of the national average. 26No- tably, this rate is consistent with a 2004 BRM report27that reviewed malpractice data from 1994 to 2003. Whether the relationship between EHRs and malpractice claims differs across states remains to be studied. In conclusion, the results of this study should be con- sidered preliminary. The findings suggest that physi- cians with EHRs may have a lower prevalence of paid mal- practice claims than physicians without EHRs. Further study is needed to clarify this relationship and the mecha- nisms that may underlie it. Accepted for Publication:June 2, 2008. Correspondence:Steven R. Simon, MD, MPH, Depart- ment of Ambulatory Care and Prevention, Harvard Medi- cal School and Harvard Pilgrim Health Care, 133 Brook- line Ave, Sixth Floor, Boston, MA 02215 (steven_simon @hphc.org). Author Contributions:Drs Virapongse and Simon had full access to all of the data in the study and take respon- sibility for the integrity of the data and the accuracy of the data analysis.Study concept and design:Virapongse and Simon.Acquisition of data:Virapongse, Bates, Jenter, Volk, and Simon.Analysis and interpretation of data:Vi- rapongse, Simon, Volk, and Shi.Drafting of the manu- script:Virapongse and Simon.Critical revision of the manu- script for important intellectual content: Virapongse, Bates, Shi, Jenter, Volk, Kleinman, Sato, and Simon.Statistical analysis: Virapongse, Shi, and Kleinman.Administra- tive, technical, or material support:Jenter and Volk. Financial Disclosure:Dr Virapongse reports that dur- ing the writing of the manuscript she was a fellow at Blue Cross, Blue Shield of Massachusetts. Funding/Support:This study was funded in part by the Agency for Healthcare Research and Quality coopera- tive agreement 1UC1HS015397-01 and the Massachu- setts e-Health Collaborative. (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2366 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020 Role of the Sponsors:The Agency for Healthcare Re- search and Quality and the Massachusetts e-Health Col- laborative had no role in the design and conduct of the study; collection, management, analysis, and interpreta- tion of the data; and preparation, review, or approval of the manuscript. Disclaimer:The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality, or of the Massachusetts e-Health Collaborative. Additional Contributions:Hannah Pham performed the duplicate malpractice review, Christina Kara provided ad- ministrative support and assistance with manuscript preparation, and Gheorghe Doros, PhD, provided ad- vice on the statistical analysis. REFERENCES 1. Committee on Quality of Health Care in America, Institute of Medicine.Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC: National Academies Press; 2001. 2. Hillestad R, Bigelow J, Bower A, et al. Can electronic medical record systems transform health care? potential health benefits, savings, and costs.Health Aff (Millwood). 2005;24(5):1103-1117. 3. Linder JA, Ma J, Bates DW, Middleton B, Stafford RS. Electronic health record use and the quality of ambulatory care in the United States.Arch Intern Med. 2007;167(13):1400-1405. 4. Welch WP, Bazarko D, Ritten K, Burgess Y, Harmon R, Sandy LG. 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Systematic review: impact of health informa- tion technology on quality, efficiency, and costs of medical care.Ann Intern Med. 2006;144(10):742-752.10. Hing ES, Burt CW, Woodwell DA. Electronic medical record use by office-based physicians and their practices: United States, 2006.Adv Data. 2007;(393):1-7. 11. Joint Commission on Accreditation of Healthcare Organizations.Health Care at the Crossroads: Strategies for Improving the Medical Liability System and Pre- venting Patient Injury.Oakbrook Terrace, IL: JCAHO; 2005. 12. Gandhi TK, Kachalia A, Thomas EJ, et al. Missed and delayed diagnoses in the ambulatory setting: a study of closed malpractice claims.Ann Intern Med. 2006; 145(7):488-496. 13. Davenport J. Documenting high-risk cases to avoid malpractice liability.Fam Pract Manag. 2000;7(9):33-36. 14. Studdert DM, Mello MM, Gawande AA, et al. Claims, errors, and compensation payments in medical malpractice litigation.N Engl J Med. 2006;354(19):2024- 2033. 15. 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Kaiser Family Foundation. Number of paid medical malpractice claims, 2007. http: //www.statehealthfacts.org/comparetable.jsp?ind=436&cat=8. Accessed Sep- tember 20, 2007. 27. Commonwealth of Massachusetts Board of Registration in Medicine. Medical mal- practice analysis, November 2004. http://www.massmedboard.org/public/pdf /announcements/Med_Mal_2004.pdf. Accessed May 5, 2008. (REPRINTED) ARCH INTERN MED/ VOL 168 (NO. 21), NOV 24, 2008 WWW. ARCHINTERNMED.COM 2367 ©2008 American Medical Association. All rights reserved.Downloaded From: https://jamanetwork.com/ on 05/30/2020
1) We are living in the data mining age. Provide an example on how data mining can turn a large collection of data into knowledge that can help meet a current global challenge in order to improve heal
The Use of Health Information Technology to Improve Care and Outcomes for Older Adults Kathryn H. Bowles, PhD, FAAN, FACMI , van Ameringen Professor in Nursing Excellence, Director of the Center for Integrative Science in Aging, University of Pennsylvania School of Nursing, Philadelphia, PA Patricia Dykes, PhD, FAAN, FACMI , and Senior Nurse Scientist, Director of the Center for Patient Safety Research and Practice; Director of the Center for Nursing Excellence, Brigham and Women’s Hospital, Boston, MA George Demiris, PhD, FACMI Alumni Endowed Professor in Nursing; Professor in Biomedical and Health Informatics, School of Medicine; Director, Clinical Informatics and Patient Centered Technologies; Graduate Program Director, Biomedical and Health Informatics University of Washington, Seattle, Washington Introduction Using health information technology (HIT) to improve care and outcomes for older adults is a growing program of research propelled by recent transformative policies such as the Health Information Technology for Economic and Clinical Health (HITECH) Act ( Blumenthal, 2010 ; Institute of Medicine, 2011 ) and the Institute of Medicine report, “The Future of Nursing: Leading Change, Advancing Health.” ( Institute of Medicine, 2010 ). Both documents call for the implementation of electronic health records (EHR) and HIT solutions to improve the safety, quality and efficiency of care. Several nurse scientists are at the forefront of advancing this work, particularly using electronic health records, decision support and telehealth. This commentary highlights examples of recent research (2010– 2014) led by nurse scientists using HIT to improve patient safety, and the quality and efficiency of patient care. We also discuss future opportunities for Gerontological nurse scientists interested in blending the care of older adults and HIT and suggest strategies to increase our capacity to engage in such innovative research. Using the EHR to improve outcomes for older adults Recent incentives provided by the HITECH Act have resulted in rapid growth in the development and implementation of the EHR. Nurse led studies are beginning to demonstrate that effective use of the EHR can improve outcomes of relevance to older adults such as pressure ulcers and falls. Dowding and colleagues evaluated the impact of an integrated EHR in 29 Kaiser Permanente hospitals on process and outcome indicators for patient falls and hospital acquired pressure ulcers ( Dowding, Turley, & Garrido, 2012 ). They found that the EHR system was associated with improved documentation of both fall and pressure ulcer risk assessments and statistically significant improvements for pressure ulcer risk assessment documentation. They demonstrated that improved documentation using the EHR was associated with a 13% decrease in hospital acquired pressure ulcer rates. HHS Public Access Author manuscript Res Gerontol Nurs . Author manuscript; available in PMC 2015 May 14. Published in final edited form as: Res Gerontol Nurs . 2015 ; 8(1): 5–10. doi:10.3928/19404921-20121222-01. Author Manuscript Author Manuscript Author Manuscript Author Manuscript The patient fall rates remained unchanged after EHR implementation. The authors reported variation in these outcomes across hospitals and care regions. They noted that in addition to EHR implementation, organizational factors such as collaboration, teamwork, and supportive leadership are needed to achieve sustained improvements in quality and safety outcomes. This highlights a role for Gerontological nurses as they can promote improvements in nursing sensitive measures such as patient falls and hospital acquired pressure ulcer rates by modeling adoption and use of the EHR and by leading quality improvement efforts that engage both senior leadership and front line nursing staff ( McFadden, Stock, & Gowen, 2014 ; Rosen et al., 2010 ). Leading geriatric care improvement programs within a healthcare organization such as NICHE (Nurses Improving Care for Healthsystem Elders) is an example of how Gerontological nurses can partner with nursing leadership and frontline staff to improve the care of older adults. This type of program, coupled with an integrated EHR that captures data in a structured, coded format and provides clinical decision support can ensure that all older adults receive evidence- based, personalized care and that nursing documentation is reused to build evidence for future practice. Gerontological nurse experts can efficiently influence important outcomes and standardize the way we assess and treat older adults by providing input into which evidence-based assessment and decision support tools are embedded into the EHR. For example, in a study in long-term care, the number of malnourished residents decreased significantly after embedding evidence-based assessment tools into the EHR that prompted nutritional and pressure ulcer risk assessments and documentation ( Fossum, Alexander, Ehnfors, & Ehrenberg, 2011 ). Using such tools prompts the caregivers to assess these important parameters, and, over time, the data generated during standardized assessments and documentation will enable research and knowledge generation using large datasets across settings and time. The IOM called for a “learning health system” where we use EHR data to apply what is known about a patient to generate or apply knowledge resulting in evidence- based, personalized care in the form of decision support ( Friedman, Wong, & Blumenthal, 2010 ). An integrated EHR with structured, coded data capture provides the data infrastructure for the learning healthcare system that will transform the way Gerontological nurses generate and apply knowledge. Data recorded at the individual patient level during an encounter can be used to personalize care for that patient and can be simultaneously applied to spur discovery and innovation for future care delivery for older adults ( Greene et al., 2009 ). Gerontological nurses play an important role in guiding the development of our “learning health system.” Providing decision support interventions Using the EHR as a tool to achieve a learning health system affords the opportunity to build decision support within the workflow of nurses caring for older adults. Decision support can take the form of alerts, reminders, or algorithms that guide evidence-based care. Bowles and colleagues implemented the expert discharge decision support system (D2S2) within the hospital nursing admission assessment to identify older adults in need of post-acute care such as skilled home care or skilled nursing facility care. Based on how patients answer a series of questions, an algorithm generates a daily report sent to discharge planners alerting Bowles et al. Page 2 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript them of patients at risk for poor discharge outcomes and therefore in need of a post-acute referral. Use of the decision support achieved a 26% relative reduction in 30 and 60-day readmissions in one study ( Bowles, Hanlon, Holland, Potashnik, & Topaz, 2014 ) and 33%, 30-day and 37%, 60-day relative reductions in readmissions in a subsequent study (under revised review at RINAH). Study findings suggest that using decision support to early identify at risk patients and arranging appropriate follow-up care is associated with improved post-acute care outcomes. Symptom management during cancer treatment is another complex care challenge for many older adults and their caregivers. A nurse led team created a computable algorithm that adapts research evidence for use in a clinical decision support system providing individualized symptom management recommendations to clinicians at the point of care ( Cooley et al., 2013 ). This complex challenge required mixed methods that involved two large clinical sites, multiple panels of experts, a seven-step process, and two years to complete. These rigorously developed algorithms are available for testing. HIT can also provide decision support for sensitive topics like advanced care planning. Hickman and colleagues created a multimedia decision support intervention that delivers education about advanced directives to patients recovering from critical illness ( Hickman, Lipson, Pinto, & Pignatiello, 2013 ). Brought to the bedside via laptop computer, this intervention increased the intent to sign an advanced directive by 25 times compared to the commonly used advanced directive educational brochure, “Putting it in writing”. Clinical decision support in the EHR can also facilitate guideline adherence. Beeckman and colleagues evaluated whether a decision support system for pressure ulcer prevention improves guideline adherence with pressure ulcer prevention recommendations in a nursing home setting ( Beeckman et al., 2013 ). They found that nurses who used the EHR system with the pressure ulcer prevention decision support were more likely to provide guideline- based pressure ulcer prevention interventions than nurses in the control group who received a paper copy of the practice guidelines. The successful work of Dykes and colleagues clearly illustrates the value of integrating fall risk assessment and clinical decision support into the EHR ( Dykes et al., 2010 ). Based on qualitative research with professional and paraprofessional providers ( Dykes, Carroll, Hurley, Benoit, & Middleton, 2009 ), patients and family ( Carroll, Dykes, & Hurley, 2010 ), Dykes and team learned that patient falls were a communication problem. Nurses routinely conduct fall risk assessment on hospitalized patients but the degree to which the results of that assessment and the associated plan are communicated to other care team members, the patient and family was variable. In a randomized control trial of over 10,000 patients, they found that by using HIT to integrate fall risk assessment and clinical decision support for tailored fall prevention plans into the workflow ( Carroll, Dykes, & Hurley, 2012 ), older patients were more likely to have personalized fall prevention plans and were less likely to fall during an acute hospitalization ( Dykes et al., 2010 ). Bowles et al. Page 3 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Remote monitoring of older adults Telehealth, defined as the use of video and biometric devices to monitor and provide care at a distance is a rapidly growing intervention studied by nurses. The body of literature in the domain of telehealth specifically for older adults is growing in more recent years, and numerous studies highlight the leading role of nursing in designing, implementing and evaluating such systems. Published reports range from pilot feasibility studies to large multi- site randomized clinical trials. One such recent trial is by Takahashi et al examining telemonitoring in older adults with multiple chronic conditions (Tele-ERA-Elder Risk Assessment) as a tool to reduce hospitalizations and emergency department visits when compared with usual care ( Takahashi et al., 2010 ). The telehealth device used was a commercially available one that has video monitoring allowing real-time, face-to-face interaction with the provider team. Peripheral devices were attached to measure blood pressure and pulse, oxygen saturation, glucose level, and weight. The elderly study patients found home telemonitoring to be acceptable, providing a sense of safety in their home ( Pecina et al., 2011 ). However, home telemonitoring in older adults with multiple comorbidities did not significantly improve self-perception of mental well-being and may worsen self-perception of physical health. While a report on the effectiveness for reducing hospitalizations has not been published yet, findings from this trial have already highlighted the role of a registered nurse as overseeing all processes and assessing any changes in patient status as assessed by videoconferencing and telemonitoring. A nurse led study examining the effectiveness of home based individual telehealth intervention for stroke caregivers was conducted in South Korea ( Kim et al., 2012 ). This study employed a quasi-experimental design with a repeated-measures analysis to explore if caregiver burden will be lower for families that receive a telecare intervention in addition to standard care, when compared to the control group. Seventy-three patients from five hospitals participate in the study. There was a statistically significant decrease of family caregiver burden in the experimental group and the intervention was found to be cost- effective. Emme and colleagues explored the role of home telehealth in facilitating self-efficacy in patients with chronic obstructive pulmonary disease. She conducted this study within a larger initiative called the Virtual Hospital ( Emme et al., 2014 ). The Virtual Hospital included patients admitted to the emergency department due to chronic obstructive pulmonary disease (COPD) exacerbation. Within 24 hours after admission, participants were randomly assigned to receive standard treatment using telehealth equipment with an integrated organizational support in their own home or standard treatment in the hospital. The results of the study suggest that there may be no difference between self-efficacy in COPD patients undergoing virtual admission, compared with conventional hospital admission. Keeping-Burke et al conducted a randomized clinical trial to determine whether coronary artery bypass graft surgery patients and their caregivers who received telehealth follow-up had greater improvements in anxiety levels from pre-surgery to three weeks after discharge, than those who received standard care ( Keeping-Burke et al., 2013 ). No group differences Bowles et al. Page 4 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript were noted in changes in patients’ anxiety and depressive symptoms, but patients in the telehealth group had fewer physician contacts. Furthermore, caregivers in the telehealth group experienced a greater decrease in depressive symptoms than those in the standard care group and female caregivers in the telehealth group had greater decreases in anxiety than those in standard care. A single-center randomized controlled clinical trial conducted by Wakefield and colleagues compared two remote telehealth monitoring intensity levels (low and high) and usual care in patients with type 2 diabetes and hypertension being treated in primary care ( Wakefield et al., 2012 ). No significant differences were found across the groups in self-efficacy, adherence, or patient perceptions of the intervention mode. The study indicated that home telehealth can enhance detection of key clinical symptoms that occur between regular physician visits but called for further investigation of the mechanism of the effect of the telehealth intervention. In the studies described above, patients and/or their family members have to operate specific hardware and software applications as part of the telehealth intervention. This often raises the question of feasibility for older adults who may live alone and be very frail or inexperienced with technology or are experiencing cognitive or functional limitations. As technology advances, there are opportunities to utilize systems that do not require a user to operate them but instead the systems enable passive and ongoing monitoring of older adults’ well-being. An extensive program of research led by Rantz and colleagues ( Rantz et al., 2012 ) conducted in senior housing facilities demonstrates the power of telehealth to predict adverse events and support seniors to age in place. In these studies, sensor networks were deployed that included stove temperature, bed, chair and motion sensors, and Microfost Kinect sensors in order to assess behavioral and physiological patterns over time and identify abnormalities or emergencies. Findings so far suggest that the sensor data can serve as tools for early illness detection. There are other initiatives underway exploring this concept of a “smart home,” namely a residential setting with technology embedded in the residential infrastructure to enable passive monitoring of residents with the goal to assess overall patterns of activity, quality of life and well-being. As part of the HEALTH-E (Home based Environmental and Assisted Living Technologies for Healthy Elders) initiative in the School of Nursing at the University of Washington, researchers have installed various sensor technologies in apartments of older adults who live in retirement communities in Seattle. The sensor technologies include motion sensors to detect how one moves inside the home, as well as infrastructure mediated sensing, namely an electricity sensor that can detect electricity consumption by electricity source, and a water sensor that detects water consumption by each water source. These features allow the detection of activities such as meal preparation or bathroom visit with a level of granularity that motion sensors alone cannot provide. Advanced data analysis and pattern recognition techniques allow not only the detection of activities but also potential changes over time, for example, if data indicate a more sedentary behavior over time, or an irregular pattern of activities calling for timely interventions to prevent an adverse event ( Reeder, Chung et al., 2013 ). Findings so far indicate that older adults accept these technologies if they see a purpose and perceived usefulness does ameliorate privacy concerns ( Chung et al., 2014 ) Case studies showcase the potential of technology to identify health related trends. However, the concept of smart Bowles et al. Page 5 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript homes is still an emerging one and we are lacking large longitudinal studies and clinical trials that will examine the effectiveness of such technologies and their impact on clinical or other outcomes ( Reeder, Meyer et al., 2013 ) What is in the nursing research pipeline? A search of the National Institute of Health REPORTER database informed us about what nurse-led HIT studies, funded by the National Institute of Nursing, are in the pipeline. We can look forward to hearing the results of several innovative studies that address the needs of and improve outcomes for Alzheimer’s patients and their caregivers. At least four studies address dementia, two are RO1s, one R21 and one R15. RO1NR014737 (Williams, Principal Investigator) will test the effects of technology that connects dementia caregivers to experts for guidance in managing disruptive behaviors and supporting care at home. Experts will analyze video recordings of the triggers and precursors of the disruptive behaviors along with its features and give prevention and management advice to the caregivers. The second RO1NR011042 (Fick, Principal Investigator) proposes the use of the EHR to deliver an Early Nurse Detection of Delirium Superimposed on Dementia intervention. The EHR will provide decision support through standardized delirium assessment and management screens. The R21NR 013471 (Mahoney, Principal Investigator) will develop an innovative bureau dresser retrofitted with sensors and an IPAD that offers visual cues and verbal prompting to help persons with dementia dress. The team hopes to advance the technology from prototype proof of concept to ready it for large-scale intervention trials. Finally, the R21NR013569 (Hickman, Principal Investigator) uses gaming technology to create an interactive, avatar-based tailored electronic program that will engage and prepare family members for the role of surrogate decision maker when caring for persons with impaired judgment. Beyond the study of dementia, the value of large dataset analysis is evident to meet the aims of RO1NR010822 (Larson, Principal Investigator). In this study, investigators are using data within a clinical data warehouse to conduct three comparative effectiveness studies about hospital-acquired infections and various contributing or preventive factors. The study will also produce policies and procedures regarding future use of these large datasets to make them more widely available for future research. An RO3NR012802 (Kim, Principal Investigator) takes advantage of EHR data documented during the longitudinal care of older adults as they transitioned across multiple care settings including their homes. The focus of the study is care coordination and the aims are to identify interventions used in care coordination, identify relationships among patients’ characteristics and care coordination interventions and outcomes. These exciting and innovative examples give us a snapshot of what new knowledge we have to look forward to and provide excellent examples of our learning health system and the use of HIT to improve care for older adults. How Gerontological Nurses Can Get Involved The HIT research completed to date provides a beginning foundation for evidence-based nursing care of older adults and a learning health system. Gerontological nurses can Bowles et al. Page 6 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript contribute to the learning health system in several ways. First, nurses can adopt standardized, evidence-based risk assessments in practice and work with their information technology departments or vendors to make sure that these assessments, corresponding interventions and patient outcomes are represented in a structured coded fashion in the EHR. Linking evidence-based interventions to assessment data in the EHR will ensure that all patients receive evidence-based care during each encounter. In addition, submission of risk assessment and outcome data to a national nursing outcomes database such as the National Database for Nursing Quality Indicators (NDNQI), the Collaborative Alliance for Nursing Outcomes (CALNOC), the Veterans Administration Nursing Outcomes Database (VANOD), or Military Nursing Outcomes Database (MilNOD) provides a means to contribute the types of data needed for local quality benchmarking while contributing to a learning health system that will improve the care of older adults nationally. Challenges and New Directions As noted throughout this commentary, nurses are leading research related to the use of EHRs, clinical decision support, and telehealth. Many of these efforts have resulted in improved care and interventions for older adults. However, this work is not without challenges. One challenge of EHR research is often the inability to conduct randomized clinical trials. Most EHR studies are quasi-experimental because the EHR is delivered to all patients therefore negating the ability to have a simultaneous control group. When considering the quality of EHR research we must take note whether confounding factors were considered and adequate controls were instituted to compensate for the lack of randomization. In addition, many of these studies have multiple components. For example, in telehealth studies, the type of equipment used, the number of times a patient uses the equipment, or the quality of team communication could all affect the study outcomes making it difficult to know which component is responsible for the impact. For decision support, it is important to monitor the fidelity of the intervention to understand the amount of exposure to the advice and to monitor any other interventions occurring simultaneously that could affect the outcomes. In addition, it is important to recognize that these interventions are “decision support”. They are not one size fits all and we must never lose sight of individual patient needs and instances where the decision support is not applicable. To advance the science of HIT research, we suggest more research to: • understand how nurses use HIT systems in practice, the factors associated with adoption, and the effect of EHR systems on nursing practice; • identify the organizational factors that lead to improved quality and safety outcomes after implementation of an EHR; • determine how patient reported data can be captured and used to provide clinical decision support that is aligned with patient preferences; • develop HIT interventions that will facilitate the engagement of older adults in their recovery plan within hospital, homecare, and long-term care settings and in maximizing self-management, wellness, and independence as they age at home Bowles et al. Page 7 Res Gerontol Nurs. Author manuscript; available in PMC 2015 May 14. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Finally, we need to expand the settings in which HIT research occurs. 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