Outcomes From Health Information Exchange Systematic Review and Future Research Needs
JMIR Med Inform. 2015 Oct-Dec; 3(4): e39.
Outcomes From Health Information Exchange: Systematic Review and Future Research Needs
Monitoring Editor: Gunther Eysenbach
William R Hersh, MD, 
i Annette Thou Totten, PhD,ane Karen B Eden, PhD,1 Beth Devine, MBA, PhD, PharmD,2 Paul Gorman, MD,1 Steven Z Kassakian, Physician,1 Susan S Woods, MD,3 Monica Daeges, BS,1 Miranda Pappas, MA,1 and Marian S McDonagh, PharmD1
anePacific Northwest Evidence-Based Do Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, U.s.a.
2Centers for Comparative and Wellness System Effectiveness, University of Washington, Seattle, WA, United States
3Veteran's Affairs Maine Healthcare System, Augusta, ME, Us
William R Hersh, Pacific Northwest Evidence-Based Exercise Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Wellness & Science University, 3181 SW Sam Jackson Park Rd., BICC, Portland, OR, , Usa, Phone: 1 503 494 4563, Fax: 1 503 494 4551, Email: ude.usho@hsreh.
William R Hersh
1Pacific Northwest Evidence-Based Practice Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Wellness & Science University, Portland, OR, United States
Annette 1000 Totten
anePacific Northwest Evidence-Based Practice Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Wellness & Science University, Portland, OR, United states of america
Karen B Eden
iPacific Northwest Evidence-Based Exercise Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Wellness & Science University, Portland, OR, United states of america
Beth Devine
2Centers for Comparative and Health System Effectiveness, Academy of Washington, Seattle, WA, United States
Paul Gorman
anePacific Northwest Evidence-Based Practice Eye, Department of Medical Computer science & Clinical Epidemiology, Oregon Health & Scientific discipline University, Portland, OR, Us
Steven Z Kassakian
iPacific Northwest Evidence-Based Practise Center, Section of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, Usa
Susan S Forest
3Veteran'south Affairs Maine Healthcare System, Augusta, ME, U.s.
Monica Daeges
1Pacific Northwest Evidence-Based Do Heart, Section of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, United states
Miranda Pappas
1Pacific Northwest Evidence-Based Practice Center, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, United States
Marian S McDonagh
iPacific Northwest Evidence-Based Practice Eye, Section of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, United states of america
Received 2015 October 8; Revisions requested 2015 Nov vi; Revised 2015 Nov 10; Accustomed 2015 Nov 11.
Abstruse
Groundwork
Health information exchange (HIE), the electronic sharing of clinical information across the boundaries of health care organizations, has been promoted to improve the efficiency, cost-effectiveness, quality, and rubber of health care delivery.
Objective
To systematically review the available inquiry on HIE outcomes and analyze future enquiry needs.
Methods
Data sources included citations from selected databases from January 1990 to February 2015. Nosotros included English-language studies of HIE in clinical or public health settings in whatever country. Information were extracted using dual review with adjudication of disagreements.
Results
Nosotros identified 34 studies on outcomes of HIE. No studies reported on clinical outcomes (eg, bloodshed and morbidity) or identified harms. Low-quality show generally finds that HIE reduces duplicative laboratory and radiology testing, emergency section costs, hospital admissions (less then for readmissions), and improves public health reporting, convalescent quality of intendance, and disability claims processing. Most clinicians attributed positive changes in care coordination, communication, and knowledge about patients to HIE.
Conclusions
Although the evidence supports benefits of HIE in reducing the use of specific resource and improving the quality of care, the total touch on of HIE on clinical outcomes and potential harms are inadequately studied. Future studies must accost comprehensive questions, utilize more rigorous designs, and employ a standard for describing types of HIE.
Trial Registration
PROSPERO Registry No CRD42014013285; http://world wide web.crd.york.air conditioning.u.k./PROSPERO/ display_record.asp?ID=CRD42014013285 (Archived by WebCite at http://www.webcitation.org/6dZhqDM8t).
Keywords: diagnostic tests, health information exchange, outcome assessment (health care), patient readmission, routine, systematic review
Introduction
In recent years, there has been substantial growth in the adoption of the electronic health record (EHR) in convalescent and hospital settings across the United states of america, fueled largely by incentive funding provided by the Health Information Engineering science for Economic and Clinical Health (HITECH) Act. Following HITECH, 94% of nonfederal hospitals [1], 78% of infirmary-based physicians [2], 84% of emergency departments (EDs), and 73% of infirmary outpatient departments in the United States have adopted EHRs [3]. The motivation to increase the adoption of EHRs is grounded in evidence that health information technology (HIT) can meliorate the quality, condom, efficiency, and satisfaction with care, as has been reported in a series of systematic reviews [four-7].
One key challenge to effective use of HIT, however, is that most patients in the United States, especially those with multiple conditions, receive care across a number of settings [8,nine]. To enable data to follow patients wherever they receive care, attention has recently focused on health information substitution (HIE), defined as the reliable and interoperable electronic sharing of clinical information among physicians, nurses, pharmacists, other health intendance providers, and patients across the boundaries of health care institutions, health data repositories, laboratories, public health agencies, and other entities that are not within a unmarried arrangement or amongst affiliated providers [10].
The Office of the National Coordinator for Health Information Technology (ONC) has divers the following forms of HIE [eleven]:
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Directed exchange: Sending and receiving secure information electronically between intendance providers.
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Query-based exchange: Provider-initiated requests for information on a patient from other providers.
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Consumer-mediated exchange: Patients accumulation and controlling the use of their wellness information among care providers.
ONC also uses the words "push" to describe directed exchange and "pull" to describe query-based exchange [12]. ONC leadership has also advocated that HIE be thought of as a verb and not every bit a noun, with more than focus on the action of exchange and what is achieved with the information than on the technological and organizational structures required [13]. This is not meant to imply that the structures are not necessary, rather it is designed to shift the focus when evaluating HIE from documenting what has been created to the touch on HIE has on health and health care.
The HITECH Act recognized that EHR adoption alone was insufficient to realize the full promise of Hitting, allocating The states $563 1000000 for states or state-designated entities to establish HIE capability among health care providers and hospitals [xi]. As a result of HITECH funding, HIE adoption has grown in a parallel though somewhat smaller fashion. Past 2014, 76% of United states of america hospitals had engaged in some form of HIE [14]. An almanac survey of organizations engaged in HIE constitute 135 in the United States in 2014 [fifteen].
Evaluating the effectiveness of HIE (and Striking generally) has been challenging [16]. HIE systems are intermediate to improving care delivery, allowing clinicians and others improved access to patient data to inform decisions, and facilitate advisable use of testing and treatment. HIE is not specific to whatsoever wellness event or diagnosis. HIE implementations have often been supported past ane-time starting time-up funding, without long-term support to sustain the programs long enough for evaluation.
There are 3 previously published systematic reviews that focus exclusively on HIE [17-19]. One of these reviews was conducted a half-decade ago [17], another focused only on The states-based and clinical-merely (ie, not public health) activities [18], and a 3rd assessed mainly the associations between study characteristics and the frequency of positive outcomes [19]. We expanded upon these reviews to non only perform a systematic review of HIE but besides determine needs for time to come research that reflect our assessment of the benefits and limitations of HIE.
Methods
Key questions guiding this review were adult by the review team with input from a group of stakeholders and the Agency for Healthcare Research and Quality (AHRQ). A standard protocol was developed using input from key informants and a technical expert panel, registered in PROSPERO [xx], and posted on an AHRQ public website. A technical report farther describes the methods and includes search strategies and additional information [21]. A research librarian conducted electronic database searches identifying relevant articles published between Jan 1990 and February 2015 in MEDLINE (Ovid), PsycINFO, CINAHL, and the Cochrane Library databases. Searches were peer reviewed past some other librarian and supplemented by references identified from additional sources, including reference lists, table of contents of journals not indexed in databases searched, gray literature sources, and experts. English-language studies of HIE that reported on clinical, economic, population, and intermediate (eg, patient or provider perceptions, availability or accurateness of information, or time saved) outcomes were included. We included comparative studies of effectiveness, and other designs for more than qualitative outcomes. We excluded studies that investigated benefits of HIE other than in clinical or public health settings (eg, to heighten clinical inquiry). Ii investigators independently evaluated each study to determine inclusion eligibility. Disagreement was resolved by consensus with a third investigator making the final determination as needed.
Details of included studies were extracted by one investigator and reviewed for accurateness and completeness by a second investigator. 2 investigators independently assessed gamble of bias for all effectiveness studies. Differences were resolved past discussion and consensus and reviewed by the squad of investigators. Individual studies were rated equally "depression," "moderate," or "loftier" risk of bias. Investigators and then assessed the force of the trunk of prove. Both the risk of bias and forcefulness of prove ratings were conducted using the criteria and procedures described in the AHRQ Methods Guide for Effectiveness and Comparative Effectiveness Reviews [22].
The forcefulness of bear witness consisted of the following four major categories: high, moderate, depression, or insufficient, based on the methodological limitations of studies; consistency across studies; precision of estimates; and directness of effect. Ratings were reviewed by a 2d investigator, and disagreements were resolved past consensus or involvement of a third investigator if necessary. Data could non be combined in a quantitative meta-analysis because of heterogeneity in the interventions, the outcomes measured, and the way information were reported. Therefore, we combined studies qualitatively based on the similarity of the type of HIE, the implementation of the HIE, outcomes measured, and results reported. Where studies were non similar in these areas, nosotros provided the results of the individual studies without grouping them.
Results
Of the 5211 potentially relevant citations identified in our literature searches, 849 articles were selected for full-text review and 34 studies were ultimately deemed to address outcomes. Study characteristics, results, and gamble of bias assessments are presented in Multimedia Appendices i and two. Of the studies included in this report, 2 were randomized controlled trials (RCTs) described in 3 papers and 32 were observational and survey studies. Almost were conducted in the United States, although 8 were from Europe, Canada, State of israel, and Republic of korea. These studies reported clinical or public health process, economic, or population outcomes; nonetheless, none of the studies explicitly stated that they assessed for harms of HIE or reported whatsoever negative unintended consequences. The bulk were assessed to be of low risk of bias (ie, proficient internal validity) but also contained by and large retrospective observational evidence.
Of 34 studies, 26 reported clinical, economic, or population outcomes (meet Multimedia Appendix 1), whereas the other 8 were found to report on perceptions of outcomes (see Multimedia Appendix 2). None of the studies evaluated primary clinical outcomes from HIE (eg, bloodshed and morbidity) nor explicitly measured or reported harms. We list the written report designs and geographic locations in Tabular array 1.
Table 1
Written report designs and locations.
| | Study designs and locations | References | |
| Designs (number) | | | |
| | Retrospective cohort (18) | [23-40] | |
| | Survey (viii) | [41-48] | |
| | Randomized controlled trial (2 reported in iii papers) | [49-51] | |
| | Cantankerous sectional (2) | [52,53] | |
| | Case series (2) | [54,55] | |
| Location (number) | | | |
| | Republic of austria (1) | [47] | |
| | Canada (2) | [49,51] | |
| | Finland (2) | [23,46] | |
| | State of israel (two) | [29,56] | |
| | South Korea (1) | [48] | |
| | All of United States (ii) | [41,53] | |
| | California and Florida | [52] | |
| | Colorado (1) | [24] | |
| | Indiana (3) | [35,36,44] | |
| | Louisiana (ane) | [34] | |
| | Massachusetts (one) | [45] | |
| | Minnesota (1) | [55] | |
| | Northward Carolina (i) | [50] | |
| | New York (6) | [32,33,37,40,42,43] | |
| | Oklahoma (1) | [38] | |
| | South Carolina (1) | [54] | |
| | Tennessee (3) | [25,27,28] | |
| | Texas (i) | [31] | |
| | Virginia (1) | [39] | |
| | Wisconsin (2) | [26,xxx] | |
The nearly mutual report design for assessing outcomes was retrospective accomplice, typically with HIE use associated with a specific outcome (Tabular array one). The next most common design was survey, which was usually focused on perception of effectiveness and perceived outcomes: ii studies were RCTs—1 RCT assessed a item directed information commutation (two published papers, i on clinical outcomes, and 1 on perceptions) and the other evaluated a clinical decision support intervention using data from an HIE implementation. Two studies used cross-exclusive analyses of large databases to compare health care organizations having access to HIE with those without access. 2 other studies used a case series methodology, 1 of which involved asking clinicians if HIE access avoided undesirable resource use, and then computing the costs saved and the other that retrospectively analyzed data to decide duplicative testing averted.
The identified studies were performed more often than not in the The states, but nosotros identified 8 studies from 5 other countries. Of the 26 studies in the United States, 2 assessed multiple HIE implementations across the unabridged The states, ane assessed multiple HIE implementations in 2 states (California and Florida), and the remaining 23 studies were conducted in 13 states. Most studies used retrospective designs, usually with an approach examining the association of HIE use with 1 or more clinical variables. All of these studies focused on the direct result of HIE, unremarkably reporting reduction in resource utilize or costs, without determining its larger touch on (eg, overall full or proportion of spending in an ED vs the full dollars that HIE appeared to save). None of the studies analyzed individual episodes of care to determine clinical appropriateness of possible changes brought almost by HIE use.
The prospective studies as well had limitations. The ii RCTs (reported in 3 papers) were focused on highly specific uses of HIE, namely, directed exchange of ED reports in one and pharmacotherapy clinical decision support in some other. Of notation, however, was that neither report showed benefit of HIE. The other prospective study was a case serial that was limited past its methodology relying on physician cocky-reports of resources not utilized when HIE was used, with no follow-upward or validation of their decisions, or analysis of more holistic views of clinical outcomes or costs.
Most of these studies had reasonable but not stiff internal validity. As the intervention (HIE) was only one of many potential influences on clinical result (ie, many more factors go into clinical outcomes than the conclusion to consult an HIE on a patient), there was possible confounding. Because no confounders were explicitly identified and incorporated into the analyses, well-nigh studies with advisable retrospective methods were rated as having low or moderate risk of bias.
Because of the type of study designs used, reporting limitations, and the lack of ability to combine results, the force of this body of evidence was rated equally low, meaning that future studies accept the potential to modify these findings in magnitude or direction. In addition, the number of studies and their locations in the United states of america represent a small fraction of functioning HIE systems. A larger number are reported to exist operational, sustainable, or innovating according to the eHealth Initiative Annual Data Commutation Survey, which reported a total of 84 such HIE implementations in 2013 [57] and 106 in 2014 [15]. In other words, while a substantial number of HIE implementations exist in the Usa, merely a small number have been subject to evaluation. This depression number of studies relative to HIE efforts also makes it hard to generalize well-nigh what aspects of HIE, such every bit location, type, and setting, are associated with the results reported in inquiry.
Improving Resource Use
About of the studies of HIE effectiveness focused on resource utilize. We categorized these as follows (Table 2): laboratory testing, radiology testing, infirmary admissions, hospital readmissions, referrals and consultations, ED costs, public heath reporting, quality of care, and other aspects of HIE. Although the chance of bias in nigh studies was low to moderate, the resulting prove from them was generally of low strength due to retrospective designs. This low-forcefulness evidence mostly favored the value of HIE in reducing resource utilize and costs, peculiarly in the ED, but used a very narrow cost perspective and did not business relationship for how HIE was used and its impact on the overall intendance of the patient beyond the firsthand setting where it was used.
Table 2
Study results by categories.
| Category (number) | Results |
| Laboratory testing (half dozen) | A total of half dozen studies showed do good for health data exchange (HIE) in reducing overall testing, although estimates of impact on price were mixed [23-26,54,55]: 4 studies took place in the emergency section (ED) setting, all showing some corporeality of reduced testing and toll savings [25,26,54,55], whereas 2 studies were conducted in convalescent settings, with 1 showing an increase [23] and the other showing a reduction in the increased overall rate of testing [24]. |
| Radiology testing (ix) | A total of seven studies carried out in the ED setting showing reduced testing [25-28,52,54,55]; 2 studies were conducted in ambulatory settings, with 1 showing a decrease [23] and the other showing no alter in the rate of testing [24]. |
| Hospital admissions (8) | A total of ii studies institute a reduction in hospital admissions and lower costs [25,54]; 3 other studies also measured some benefit for HIE use in reducing hospital admissions [29,32,56], although 3 boosted studies found no such reduction [30,31,49]. |
| Hospital readmissions (ii) | Whereas 1 report showed do good for HIE in reducing hospital readmissions [33], the other did not [53]. |
| Referrals and consultations (two) | A total of ii studies assessed HIE for reducing referrals and/or consultations, with conflicting results [23,54]. |
| ED costs (ii) | A total of two studies found reduced overall ED costs per patient when HIE was available [25,26]. Neither written report reported overall ED expenditures, making it unknown what proportion of overall ED spending was impacted by HIE. |
| Public heath reporting (three) | A total of 3 studies assessed HIE in public wellness settings, all of which were conducted in the Us and reported improved automatic laboratory reporting [36], improved completeness of reporting for notifiable diseases [35], and improved identification of HIV patients for follow-up care [34]. |
| Quality of care in convalescent settings (3) | A total of 2 retrospective studies found HIE associated with improved quality of care [37,38], whereas a randomized controlled trial focused on medication reconciliation plant increased ability to discover medication adherence bug, the results did not show improvement in adherence after it was identified and addressed by providers [50]. |
| Other aspects of HIE (three) | A total of 3 studies assessed other aspects of HIE, including reduction in time for processing of Social Security Disability claims [39], increased ability to identify frequent ED users [40], and associated HIE implementation with improved patient satisfaction scores in hospitals [41]. |
Perceptions
A number of studies evaluated clinician or patient perceptions of outcomes of HIE (see Multimedia Appendix 2), with all reporting perceptions that HIE leads to some do good including improved outcomes. Clinician perceptions of the value of HIE, where studied, were by and large positive. However, how such perceptions translate into improved care is unknown. This body of evidence was considered low strength.
Factors Associated With Outcomes
To decide whether effectiveness of HIE varied by study type, health care setting, location, or HIE type, we examined whether HIE was constitute to have some beneficial effect or non across characteristics. Every bit presented in Table 1, the preponderance of studies reported that HIE use for different functions, in various settings, and of varying types produced generally positive outcomes. Although the number of positive versus negative studies was not an indicator of the overall management of the show, we did annotation that for each "negative" written report, there was at least i "positive" one. For type of HIE, there was no articulate pattern of findings to suggest that i blazon was clearly better than some other, even indirectly. The 2 RCTs reported no benefit for their selected outcomes from HIE intervention [49,50], although a perceptions written report from 1 of them reported impressions of improved patient outcomes and management [51]. These were in contrast to the observational study designs where almost all found beneficial furnishings of HIE. For the HIE setting, only ambulatory and ED had enough studies to evaluate patterns, with outpatient settings less likely to find beneficial results compared with studies in ED settings. The sparseness of studies across geographic settings did not let for identification of patterns, although across most studies in the United states, the findings were positive.
Give-and-take
A drove of low-quality evidence supports the value of HIE for reducing duplicative laboratory and radiology test ordering, lowering ED costs, reducing hospital admissions (less so for readmissions), improving public wellness reporting, increasing convalescent quality of care, and improving disability claims processing. The evidence is low quality because of the retrospective nature of the studies and the limited questions that they ask. Information technology is unlikely that additional studies of the kind included in this review will advance the field and strengthen our agreement when HIE tin reduce laboratory and imaging tests associated with episodes of care without broadening their scope and using more rigorous designs. Although the preponderance of testify reports positive effects of HIE in reducing resource utilize and improving quality of intendance, it is entirely possible that focused studies with stronger written report designs and more comprehensive assessment of utilization or clinical outcomes might reach a dissimilar conclusion.
Nosotros found no studies explicitly addressing patient-specific clinical outcomes such equally morbidity, mortality, or functional status, and therefore the body of evidence is insufficient to determine whether HIE has an impact on patient outcomes. We also did not place any studies that used systematic and comprehensive economic analysis. Although some of the studies we included projected or estimated price savings based on measured changes in utilization or perceptions of clinicians, in that location were no studies that explicitly measured costs and assessed economical bear upon in a comprehensive fashion. Information technology is fair to say, then, that there was bereft evidence to reach conclusions on the economic impact of HIE.
Applicability
How likely are the furnishings reported in this review to be observed when applied under diverse conditions in health systems, hospitals, and clinics in the The states? The greatest conviction in the applicability of these findings comes from the latitude of settings—geographic, organizational, and technical—from which they are derived. By dissimilarity, there are limitations to the applicability of the findings (beyond limitations to the internal validity already mentioned) having to do with these main concerns: (1) concentration of prove from a relatively small number of HIE systems; (ii) utilise of internally developed and refined health IT systems compared with local instances of commercial systems; and (3) the exceptionally wide variety of systems, contexts, and purposes of HIE reported in the studies included in this review.
Showtime, the concern that the majority of the bear witness about health IT bear on arises out of a relatively modest number of centers has been raised before [four]. These centers take been referred to as "health IT leaders," which are typically large academic medical centers with internally developed health IT systems, implemented incrementally, and refined over a long flow. The nature of the health Information technology systems is in each example unique (being locally developed), and more than importantly it is hard to split the effects of the health It from the confounding influences of the health system itself. However, whether findings from these systems tin be generalized to the very different context of wellness system and hospital implementations of commercially developed systems over shorter periods with less internal development and implementation infrastructure has been called into question [4]. This "health IT leader" effect appears to be reduced in more than recent updates to the 2006 systematic review by Chaudhry et al [four] but the consequence remains important [5,seven]. In this review of HIE, the concentration of evidence phenomenon is also nowadays, with big numbers of published studies emanating from relatively few areas, this fourth dimension regional implementation programs rather than bookish health centers, such as Texas, New York, and the MidSouth e-Wellness Alliance.
Second, separate from the "health IT leader" business organization, which has to exercise with the organizational chapters, resources, and mission of these centers, is the issue of internally developed systems compared with commercially developed systems. Although few of the studies we included described whether their software used was commercial or locally developed, the overall model of health IT purchase and installation of nonhealth Information technology leaders are usually quite different from that of the incremental internal development, implementation, and refinement that are seen in systems such as the Department of Veterans Affairs or the same "health IT leader" systems. Related to this concern is a finding from other aspects of health IT [58], namely, clinical decision back up, where systems evaluated by their developers tend to achieve more positive outcomes from their evaluation than external evaluators. This miracle must be assessed with HIE equally well.
3rd, and most important, in terms of limiting the applicability of these findings about HIE to real-globe use is the exceptionally broad variety of systems, purposes, and contexts of use. To predict whether specific implementations of HIE in specific health care contexts volition have favorable impacts on specific desired outcomes is non possible from this review and in nigh cases would not be possible from comparison with individual studies because (one) it is unlikely that studies with low risk of bias have been published for nigh such specific questions, and (two) in almost all cases these are circuitous interventions that are incompletely specified, with insufficient item to depict potent meaningful inferences [59].
Limitations of the Evidence Base
The pregnant limitations of the evidence base, that is, the individual studies included in this review, accept been raised in previous systematic reviews of health IT [iv,v,7] and of HIE [18]. In that location are four principal concerns virtually the limitations of the bachelor evidence on the impact of HIE (and wellness Information technology in general): (one) suitability of study design; (ii) execution of the studies; (3) complexity of the interventions with implications for interpretation and for generalizability; and (4) changes in the engineering or policy governing its use.
Showtime, the bear witness in this expanse addresses a wide variety of questions covering diverse domains beyond medical science from computer science, human factors, sociology, organization and management, and other disciplines. This broad array of questions calls for an equally diverse range of study designs. Studies of usability and use crave usability engineering methods, studies of individual behavior call for methods from anthropology and behavioral sciences, studies of organizational change warrant methods drawn from management and systems science, whereas studies of population furnishings phone call for the methods of epidemiologists. A significant limitation of this literature, with its breadth of inquiry questions, is the express toolbox oft fatigued upon to answer them.
The second limitation is in execution of the studies. Even when potent written report designs are used, their execution may be defective, whether in sampling strategies, measurement methods, or analytic approaches. The unit of measurement of analysis problem is only one example. Interventions carried out at the level of the health system, hospital, or dispensary may exist analyzed at the level of the patient or episode, without controlling for variation at these multiple levels. Incomplete measurement is some other: for example, where ED examination ordering is measured in isolation, ignoring the possibility that the same test might subsequently be ordered in another setting such as urgent care, primary care, or in hospital.
The 3rd limitation has to practise with the complexity of interventions, where the HIE or other health IT system itself is necessarily only part of a more than circuitous intervention. The complication of interventions to alter the behavior of clinicians or others in the wellness systems studied requires more thorough specification, to both adjust for confounders and make sense out of how to apply interventions elsewhere. Others have documented the inadequacy of specification of the details of circuitous interventions and called for a more than systematic and thorough reporting [59,lx].
Finally, the literature does not comprehensively encompass changes in engineering or policies governing its employ. For instance, whereas nearly studies come up from the locally developed systems of HIE leaders as noted earlier, there has been a more than contempo growth in the commercial market for HIE. In addition, the widespread adoption of EHRs under the HITECH Act in the US means that a more diverse array of health intendance organizations volition exist participating in HIE implementations. Every bit an example of policy changes governing HIE development, equally noted in Table 1, most studies have been of query-based systems whereas more recent meaningful apply criteria for incentive funding telephone call for implementation of directed substitution.
Future Enquiry Needs
Given the limited conclusions that tin can exist reached later review of the big volume of published literature on HIE, what are the implications for future enquiry? Recognizing that HIE, like health IT in general, will almost certainly undergo increasingly widespread implementation in the future, the first aim of researchers should be to shift the emphasis from whether HIE systems should exist implemented to specifically how they should exist implemented. The question to be answered is not "Does HIE have positive effects?" merely rather "How can HIE be implemented in lodge to effect in the greatest benefit for patients, clinicians, and health systems with the to the lowest degree cost and harm?"
A second aim of research on HIE should be to develop greater focus and clarity about the level at which interventions are operating and the types and levels at which outcomes are measured. The outcomes of interest and the factors influencing them may be quite dissimilar at different levels of analysis, from specific systems or functionalities of HIE to private patients, providers, or episodes of care; to wellness intendance units such every bit the ED, chief intendance practise, or hospital ward; to institutions such as hospitals; to aggregates such as health systems; or to broader regional multiorganization entities or regions. Combining or confusing these levels of intervention and levels of assay just increases the challenges for those who conduct the enquiry and for those who wish to interpret and apply information technology.
To assist achieve an improved focus and clarity, a more formal analytic framework and a more descriptive taxonomy are needed. An case of such a framework that could exist usefully applied in this area is Rasmussen's sociotechnical hierarchy, which specifies the multiple levels of a complex sociotechnical system that must be considered together to empathize system beliefs alter [61]. Examples of its awarding include Vicente'south assay of the forces interim at multiple levels to reduce hazards arising from patient-controlled analgesia devices [62] and Leveson'south Systems—Theoretic Accident Modeling and Processes model for agreement system functioning and safety [63].
Similarly, a formal taxonomy for implementation of complex interventions has been proposed that would enable more than complete and useful specification of interventions to let improve analysis, interpretation, and awarding [59,64]. This taxonomy should be extended specific to HIE to include clinical, technical, and organizational details of the HIE implementation as outlined by Vest [65]. The clinical taxonomy should focus not only on patient outcomes, but also on issues such as health disparities related to HIE and health system issues that may meliorate or undermine use of HIE. The technical taxonomy should include aspects of organisation architecture, messaging and terminology standards, and other details. It should also address the financial aspects of implementations, such equally whether locally adult or commercial software is used and whether the HIE organisation is public or private. The HIE inquiry community should consider a standardized reporting instrument for HIE evaluation comparable to the Consolidated Standards of Reporting Trials statement for RCTs [66].
The third step researchers can accept to improve the evidence base of operations for implementation of HIE is to broaden the methodologic toolbox applied to these questions. As indicated before, the report approach and architecture must exist suited to the question beingness asked, employing methods from usability engineering, behavioral sciences, systems engineering, and organizational sciences, depending on the question being addressed. These would include methods used in engineering and quality improvement, as well as in the study of circuitous adaptive systems.
What types of studies should be performed? RCTs are impractical for technologies with wide-ranging purposes similar HIE. Yet, retrospective studies associating HIE versus nonuse for outcomes such equally exam ordering and hospital admissions are very limited in conclusions that can be drawn. Inquiry is besides challenging considering many of the of import clinical outcomes that could be positively affected by HIE take many other potential contributing and confounding factors relating to the patient, his or her clinicians, the quality of care delivered, the EHR, other wellness IT used, the nature of the health intendance commitment system, and the regulatory environment. Given the growing evidence based on robust evaluations in other areas of health IT, equally noted in systematic reviews [seven], methodological insights can be gleaned from other topic areas.
Future studies should be prospective, carried out in mature HIE settings, specify a priori what patients and/or use cases are likely to benefit from HIE, and compare appropriate outcomes for the use or nonuse of HIE. The prospective collection of data from diverse settings where HIE is used, classified by the taxonomy advocated earlier, could allow for prospective accomplice studies that could identify aspects of HIE associated with beneficial outcomes. This will probable require an effort comparable in scope to national information collection efforts, such every bit the Patient-Centered Outcomes Research Institute Clinical Data Enquiry Network initiative [67]. Ideally, such an undertaking could exist synergistic with these other large-calibration efforts.
Evaluation should be a requirement for all HIE implementations, certainly those funded by grants or other external funding. The claiming of evaluating health IT projects, specially in community settings, is well-known [16], merely all funders must need this requirement to grow the evidence base. By the same token, funders must provide adequate resource for such evaluations. In add-on, evaluations should be performed by researchers external to the project to reduce potential bias from system developers evaluating their own implementations [58].
Conclusions
The full impact of HIE on clinical outcomes and potential harms is comparatively studied, although prove provides some support for benefit in reducing use of some specific resources and achieving improvements in quality of care measures. To accelerate our understanding of HIE, future studies demand to accost comprehensive questions, use more rigorous designs, and exist part of a coordinated, systematic approach to studying HIE. Going frontward, HIE will become a more integrated part of health care delivery, and its evaluation needs to be focused on maximizing the improvements that HIE usage brings to overall clinical care.
Acknowledgments
The authors gratefully acknowledge the following individuals for their contributions to this project: Andrew Hamilton, MLS, MS, for conducting literature searches and Spencer Dandy, BS, for assistance with preparing this manuscript (both are located at the Oregon Health & Scientific discipline University); and Jon White, Dr., Task Social club Officer at the Agency for Healthcare Enquiry and Quality (AHRQ). The primary funding source was The Agency for Healthcare Research and Quality (Contract Number 290-2012-00014-I, Task Social club 11), Rockville, Maryland. SZK was also supported by a grant from the National Library of Medicine Grooming (Grant No T15LM007088). The findings and conclusions in this document are those of the authors, who are responsible for its content, and exercise not necessarily represent the views of AHRQ or the National Library of Medicine. No argument in this report should be construed as an official position of AHRQ or the The states Department of Wellness and Human Services.
Abbreviations
| AHRQ | Agency for Healthcare Inquiry and Quality |
| ED | emergency department |
| EHR | electronic health record |
| HIE | health information exchange |
| Striking | health information technology |
| HITECH | Health It for Economical and Clinical Health |
| It | information technology |
| ONC | Office of the National Coordinator for Wellness Information technology |
| RCT | randomized controlled trial |
Multimedia Appendix 1
Studies of health information exchange included for assessing outcomes.
Multimedia Appendix ii
Patient and clinician survey perceptions of health data exchange.
Footnotes
Conflicts of Interest: None declared.
References
2. Hsiao C, Hing E. NCHS Information Brief Number 143. 2014. [2015-ten-07]. webcite Use and characteristics of electronic wellness record systems among office-based md practices: Usa, 2001-2013 http://www.cdc.gov/nchs/data/databriefs/db143.htm.
3. Eric J, Esther H. NCHS Information Brief Number 187. 2015. [2015-x-07]. webcite Progress with electronic wellness record adoption amid emergency and outpatient departments: United States, 2006-2011 http://www.cdc.gov/nchs/data/databriefs/db187.htm.
4. Chaudhry B, Wang J, Wu Due south, Maglione Yard, Mojica W, Roth East, Morton SC, Shekelle PG. Systematic review: Impact of health data technology on quality, efficiency, and costs of medical intendance. Ann Intern Med. 2006 May 16;144(10):742–752. [PubMed] [Google Scholar]
7. Jones SS, Rudin RS, Perry T, Shekelle PG. Health information technology: An updated systematic review with a focus on meaningful use. Ann Intern Med. 2014 Jan 7;160(i):48–54. doi: 10.7326/M13-1531. [PubMed] [CrossRef] [Google Scholar]
eight. Conservative FC, Olson KL, Mandl KD. Patients treated at multiple acute wellness intendance facilities: Quantifying data fragmentation. Arch Intern Med. 2010 Dec 13;170(22):1989–1995. doi: 10.1001/archinternmed.2010.439. [PubMed] [CrossRef] [Google Scholar]
12. Dullabh P, Ubri P, Loganathan Southward, Latterner 1000. Evaluation of the Country Wellness Information Commutation Cooperative Agreement Program: State Approaches to Enabling HIE: Typology Cursory. Washington, DC: Office of the National Coordinator for Health It; 2014. [2015-x-07]. webcite https://www.healthit.gov/sites/default/files/statehietypologybrief.pdf. [Google Scholar]
18. Rudin RS, Motala A, Goldzweig CL, Shekelle PG. Usage and issue of health information exchange: A systematic review. Ann Intern Med. 2014 December 2;161(11):803–811. doi: 10.7326/M14-0877. [PubMed] [CrossRef] [Google Scholar]
19. Rahurkar S, Belong JR, Menachemi Northward. Despite the spread of health information exchange, there is little prove of its bear on on cost, use, and quality of intendance. Wellness Aff (Millwood) 2015 Mar;34(3):477–483. doi: 10.1377/hlthaff.2014.0729. [PubMed] [CrossRef] [Google Scholar]
21. Hersh W, Totten A, Eden K, Devine B, Gorman P, Kassakian S, Forest S, Daeges K, Pappas K, McDonagh G. Health Information Commutation. Rockville, MD: Bureau for Healthcare Research and Quality; 2015. [Google Scholar]
22. Bureau for Healthcare Research and Quality . Methods Guide for Effectiveness and Comparative Effectiveness Reviews: AHRQ Publication Number 10(fourteen)-EHC062-EF. Rockville, Md: Agency for Healthcare Research and Quality; 2014. [Google Scholar]
23. Mäenpää T, Asikainen P, Gissler M, Siponen K, Maass Thousand, Saranto Yard, Suominen T. Outcomes assessment of the regional wellness information exchange: A five-year follow-up study. Methods Inf Med. 2011;50(4):308–318. doi: ten.3414/ME10-01-0048. [PubMed] [CrossRef] [Google Scholar]
26. Tzeel A, Lawnicki Five, Pemble KR. The business case for payer support of a community-based health information exchange: A humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care. Am Health Drug Benefits. 2011 Jul;iv(4):207–216. http://europepmc.org/abstruse/MED/25126351. [PMC free article] [PubMed] [Google Scholar]
27. Bailey JE, Wan JY, Mabry LM, Landy SH, Pope RA, Waters TM, Frisse ME. Does health data exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department? J Gen Intern Med. 2013 Feb;28(2):176–183. doi: ten.1007/s11606-012-2092-vii. http://europepmc.org/abstract/MED/22648609. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
28. Bailey JE, Pope RA, Elliott EC, Wan JY, Waters TM, Frisse ME. Health data exchange reduces repeated diagnostic imaging for dorsum pain. Ann Emerg Med. 2013 Jul;62(ane):16–24. doi: x.1016/j.annemergmed.2013.01.006. [PubMed] [CrossRef] [Google Scholar]
31. Vest JR. Wellness information substitution and healthcare utilization. J Med Syst. 2009 Jun;33(3):223–231. [PubMed] [Google Scholar]
33. Vest JR, Kern LM, Silver MD, Kaushal R. The potential for customs-based health information commutation systems to reduce hospital readmissions. J Am Med Inform Assoc. 2015 Mar;22(ii):435–442. doi: x.1136/amiajnl-2014-002760. [PubMed] [CrossRef] [Google Scholar]
34. Magnus M, Herwehe J, Gruber D, Wilbright Westward, Shepard East, Abrams A, Foxhood J, Smith L, Xiao Yard, DeYoung K, Kaiser G. Improved HIV-related outcomes associated with implementation of a novel public health information commutation. Int J Med Inform. 2012 Oct;81(10):e30–e38. doi: ten.1016/j.ijmedinf.2012.06.005. [PubMed] [CrossRef] [Google Scholar]
36. Overhage JM, Grannis S, McDonald CJ. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. Am J Public Health. 2008 Feb;98(2):344–350. doi: ten.2105/AJPH.2006.092700. [PMC complimentary article] [PubMed] [CrossRef] [Google Scholar]
38. Nagykaldi Zsolt J, Yeaman Brian, Jones Marking, Mold James W, Scheid Dewey C. HIE-i-health information exchange with intelligence. J Ambul Care Manage. 2014;37(1):20–31. doi: ten.1097/JAC.0000000000000002. [PubMed] [CrossRef] [Google Scholar]
39. Feldman SS, Horan TA. Collaboration in electronic medical evidence evolution: A case study of the Social Security Assistants'southward MEGAHIT System. Int J Med Inform. 2011 Aug;lxxx(8):e127–e140. doi: 10.1016/j.ijmedinf.2011.01.012. [PubMed] [CrossRef] [Google Scholar]
xl. Shapiro JS, Johnson SA, Angiollilo J, Fleischman Due west, Onyile A, Kuperman 1000. Health information substitution improves identification of frequent emergency section users. Health Aff (Millwood) 2013 Dec;32(12):2193–2198. doi: 10.1377/hlthaff.2013.0167. [PubMed] [CrossRef] [Google Scholar]
42. Altman R, Shapiro JS, Moore T, Kuperman GJ. Notifications of infirmary events to outpatient clinicians using wellness information exchange: A postal service-implementation survey. Inform Prim Care. 2012;xx(4):249–255. [PubMed] [Google Scholar]
45. Kaushal R, Dhopeshwarkar R, Gottlieb 50, Jordan H. User experiences with chemist's benefit manager information at the betoken of intendance. J Eval Clin Pract. 2010 Dec;xvi(6):1076–1080. doi: x.1111/j.1365-2753.2009.01255.10. [PubMed] [CrossRef] [Google Scholar]
46. Maass MC, Asikainen P, Mäenpää T, Wanne O, Suominen T. Usefulness of a regional wellness care information system in primary intendance: A case study. Comput Methods Programs Biomed. 2008 Aug;91(2):175–181. doi: 10.1016/j.cmpb.2008.04.005. [PubMed] [CrossRef] [Google Scholar]
47. Machan C, Ammenwerth Due east, Schabetsberger T. Evaluation of the electronic transmission of medical findings from hospitals to practitioners by triangulation. Methods Inf Med. 2006;45(2):225–233. doi: 10.1267/METH06020225. [PubMed] [CrossRef] [Google Scholar]
48. Park H, Lee S, Kim Y, Heo E, Lee J, Park JH, Ha 1000. Patients' perceptions of a health information exchange: A airplane pilot program in Southward Korea. Int J Med Inform. 2013 Feb;82(2):98–107. doi: 10.1016/j.ijmedinf.2012.05.001. [PubMed] [CrossRef] [Google Scholar]
l. Willis JM, Edwards R, Anstrom KJ, Johnson FS, Del Fiol G, Kawamoto One thousand, Lapointe NM, Eisenstein EL, Lobach DF. Conclusion support for show-based pharmacotherapy detects adherence problems but does not bear on medication use. Stud Health Technol Inform. 2013;183:116–125. [PubMed] [Google Scholar]
51. Afilalo Marc, Lang Eddy, Léger Ruth, Xue Xiaoqing, Colacone Antoinette, Soucy Nathalie, Vandal Alain, Boivin Jean-François, Unger Bernard. Bear on of a standardized communication organisation on continuity of care between family unit physicians and the emergency section. CJEM. 2007 Mar;9(two):79–86. [PubMed] [Google Scholar]
52. Lammers EJ, Adler-Milstein J, Kocher KE. Does health information exchange reduce redundant imaging? Evidence from emergency departments. Med Care. 2014 Mar;52(3):227–234. doi: 10.1097/MLR.0000000000000067. [PubMed] [CrossRef] [Google Scholar]
54. Carr CM, Gilman CS, Krywko DM, Moore HE, Walker BJ, Saef SH. Observational study and judge of cost savings from use of a health data exchange in an academic emergency section. J Emerg Med. 2014 Feb;46(2):250–256. doi: 10.1016/j.jemermed.2013.05.068. [PubMed] [CrossRef] [Google Scholar]
56. Ben-Assuli O, Shabtai I, Leshno M. Using electronic health record systems to optimize access decisions: The Creatinine case study. Wellness Computer science J. 2015 Mar;21(1):73–88. doi: 10.1177/1460458213503646. [PubMed] [CrossRef] [Google Scholar]
58. Roshanov PS, Fernandes N, Wilczynski JM, Hemens BJ, You lot JJ, Handler SM, Nieuwlaat R, Souza NM, Beyene J, Van Spall Harriette G C. Garg AX, Haynes RB. Features of effective computerised clinical determination support systems: Meta-regression of 162 randomised trials. BMJ. 2013;346:f657. http://world wide web.bmj.com/cgi/pmidlookup?view=long&pmid=23412440. [PubMed] [Google Scholar]
61. Rasmussen J. Risk management in a dynamic social club: A modelling problem. Saf Sci. 1997 November;27(2-3):183–213. doi: x.1016/S0925-7535(97)00052-0. [CrossRef] [Google Scholar]
62. Vicente Kim J. What does it accept? A case study of radical alter toward patient safety. Jt Comm J Qual Saf. 2003 November;29(11):598–609. [PubMed] [Google Scholar]
64. Michie S, Richardson Grand, Johnston M, Abraham C, Francis J, Hardeman West, Eccles MP, Cane J, Wood CE. The behavior modify technique taxonomy (v1) of 93 hierarchically clustered techniques: Edifice an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013 Aug;46(1):81–95. doi: 10.1007/s12160-013-9486-six. [PubMed] [CrossRef] [Google Scholar]
65. Vest JR. More merely a question of technology: Factors related to hospitals' adoption and implementation of health information exchange. Int J Med Inform. 2010 Dec;79(12):797–806. doi: 10.1016/j.ijmedinf.2010.09.003. [PubMed] [CrossRef] [Google Scholar]
66. Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: Updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010 Jun 1;152(11):726–732. doi: 10.7326/0003-4819-152-eleven-201006010-00232. [PubMed] [CrossRef] [Google Scholar]
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