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Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis

      Abstract

      Introduction

      Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization.

      Methods

      Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004-2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models.

      Results

      A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = –0.17; 95% confidence interval [CI] = [–0.25, –0.09]; P < .001). However, image sharing technology was associated with a significant increase in any imaging utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias.

      Conclusions

      Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings.

      Key Words

      Introduction

      Patients often seek care from multiple providers, which spreads information, including imaging studies and reports, across various health care organizations. Clinicians want access to these studies and results, for accurate interpretation and diagnoses [
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      ], but often, they are difficult to obtain in a timely manner [
      • Sandberg J.C.
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      Insight into the sharing of medical images: physician, other health care providers, and staff experience in a variety of medical settings.
      ]. This lack of access may result in additional imaging [
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      Outside CT imaging among emergency department transfer patients.
      ], thereby increasing radiation exposure of the patient [
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      ACR white paper on radiation dose in medicine.
      ] and creating avoidable costs [
      • Jones A.C.
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      Repeated computed tomographic scans in transferred trauma patients: indications, costs, and radiation exposure.
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      ]. In addition, searching for studies from other sources wastes provider time [
      • Bagg S.A.
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      Handling of outside trauma studies: a survey of program directors.
      ,

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      ,
      • Robinson J.
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      Transfer patient imaging: a survey of members of the American Society of Emergency Radiology.
      ,
      • Yeager D.
      Swamped with CDs.
      ] and delays treatment [
      • Emick D.M.
      • Carey T.S.
      • Charles A.G.
      • Shapiro M.L.
      Repeat imaging in trauma transfers: a retrospective analysis of computed tomography scans repeated upon arrival to a Level I trauma center.
      ]. Finally, imaging has high utility in the diagnosis and treatment of disease, but inaccessible studies cannot support clinical decision making [
      • Robinson J.
      • McNeeley M.
      Transfer patient imaging: a survey of members of the American Society of Emergency Radiology.
      ,
      • Lu M.T.
      • Tellis W.M.
      • Fidelman N.
      • Qayyum A.
      • Avrin D.E.
      Reducing the rate of repeat imaging: import of outside images to PACS.
      ].
      Image sharing technologies are a potential intervention to improve access to imaging studies and reports [
      • Hendee W.R.
      • Becker G.J.
      • Borgstede J.P.
      • et al.
      Addressing overutilization in medical imaging.
      ]. Various technologies allow providers to electronically access patients’ external imaging information (ie, outside the organization), such as that contained in a health information exchange (HIE), regional PACS, regional image exchange networks, interoperable electronic health records (EHRs), and tools for importing physical media (eg, CDs) [
      • Sandberg J.C.
      • Ge Y.
      • Nguyen H.T.
      • et al.
      Insight into the sharing of medical images: physician, other health care providers, and staff experience in a variety of medical settings.
      ,
      • Mendelson D.S.
      • Bak P.R.
      • Menschik E.
      • Siegel E.
      Image exchange: IHE and the evolution of image sharing.
      ,
      • Mendelson D.S.
      • Erickson B.J.
      • Choy G.
      Image sharing: evolving solutions in the age of interoperability.
      ]. Reports and qualitative studies suggest that these technologies improve provider access to patients’ imaging information [
      • Sandberg J.C.
      • Ge Y.
      • Nguyen H.T.
      • et al.
      Insight into the sharing of medical images: physician, other health care providers, and staff experience in a variety of medical settings.
      ,
      • Lee J.
      Share ware.
      ,
      • Landro L.
      Health & wellness—the informed patient: image sharing seeks to reduce repeat scans.
      ,

      Morey D. Image sharing moves up a level. Orlando Medical News 2010. Available at: http://orlando.medicalnewsinc.com/image-sharing-moves-up-a-level-cms-1098. Accessed January 2, 2015.

      ,
      • Kierkegaard P.
      • Kaushal R.
      • Vest J.
      Patient information retrieval in multiple care settings: examining methods of exchange in emergency departments, primary care practices, and public health clinics?.
      ].
      Whether these technologies will result in changes to imaging utilization is less well understood. Several quantitative evaluations indicate that use of image sharing technologies reduces imaging utilization, particularly that for repeat and unnecessary imaging [
      • Lu M.T.
      • Tellis W.M.
      • Fidelman N.
      • Qayyum A.
      • Avrin D.E.
      Reducing the rate of repeat imaging: import of outside images to PACS.
      ,
      • Ip I.K.
      • Mortele K.J.
      • Prevedello L.M.
      • Khorasani R.
      Repeat abdominal imaging examinations in a tertiary care hospital.
      ,
      • Sodickson A.
      • Opraseuth J.
      • Ledbetter S.
      Outside imaging in emergency department transfer patients: CD import reduces rates of subsequent imaging utilization.
      ,
      • Bailey J.E.
      • Wan J.Y.
      • Mabry L.M.
      • et al.
      Does health information exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department?.
      ,
      • Bailey J.E.
      • Pope R.A.
      • Elliott E.C.
      • Wan J.Y.
      • Waters T.M.
      • Frisse M.E.
      Health information exchange reduces repeated diagnostic imaging for back pain.
      ]. However, other studies show inconsistent results, or no effect at all [
      • McCormick D.
      • Bor D.H.
      • Woolhandler S.
      • Himmelstein D.U.
      Giving office-based physicians electronic access to patients' prior imaging and lab results did not deter ordering of tests.
      ,
      • Ross S.E.
      • Radcliff T.A.
      • LeBlanc W.G.
      • Dickinson L.M.
      • Libby A.M.
      • Nease Jr., D.E.
      Effects of health information exchange adoption on ambulatory testing rates.
      ,
      • You J.J.
      • Yun L.
      • Tu J.V.
      Impact of PACS on rates of duplicate imaging: a before-after study.
      ].
      Identification of effective interventions to improve access to images and reports is critical [
      • Reiner B.I.
      Medical imaging data reconciliation, part 3: reconciliation of historical and current radiology report data.
      ,
      • Robinson J.
      • McNeeley M.
      Transfer patient imaging: a survey of members of the American Society of Emergency Radiology.
      ] for several reasons: utilization of imaging is on the rise [
      • Smith-Bindman R.
      • Miglioretti D.
      • Larson E.
      Rising use of diagnostic medical imaging in a large integrated health system.
      ,

      Medicare Payment Advisory Commission. Report to the Congress: Medicare payment policy. Washington, DC: 2014. http://www.medpac.gov/documents/reports/mar14_entirereport.pdf?sfvrsn=0.

      ]; repeat imaging is common [
      • Hendee W.R.
      • Becker G.J.
      • Borgstede J.P.
      • et al.
      Addressing overutilization in medical imaging.
      ]; and costs are increasingly drawing the attention of payers and policymakers. In this systematic review and meta-analysis, we sought to summarize the impact of image sharing technologies on imaging utilization, particularly repeat imaging.

      Methods

       Searching

      Relevant studies were identified, with adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [
      • Moher D.
      • Liberati A.
      • Tetzlaff J.
      • Altman D.G.
      • The P.G.
      Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.
      ], summarized in Figure 1.
      Figure thumbnail gr1
      Fig 1Article identification strategy with inclusion and exclusion criteria.
      We reviewed the English-language medicine and health services research literature from the past decade (2004-2014) for original quantitative research and evaluation studies of the impact of image sharing technology on utilization. Radiology search terms were combined with keywords for image sharing technologies (Appendix 1), in Medline, ISI, CINAHL, EMBASE, Open Grey (grey literature archive), and the National Technical Reports Library (government reports). We manually reviewed citations, and the citing articles, from several recent image sharing evaluations, to identify additional articles. The initial search yielded 1,189 unduplicated records.

       Selection

      Based on abstracts, we excluded the following types of publications: editorials, practice guidelines, reviews, and those that had no indication that the topic was the impact of image sharing technology. Our primary search and screening process resulted in identification of 55 articles for a full-text review (kappa [κ] = 0.65).
      Articles were retained if they met the following criteria after full-text review: (1) reported on original research; (2) provided a quantitative measure of the effect of image sharing technology on utilization of imaging; and (3) technology involved allowed for access to external images or reports (eg, image sharing was interorganizational and not intraorganizational). In addition, we reassessed all full-text articles according to our previous exclusion criteria. We did not restrict inclusion on the basis of study design. Qualitative investigations, and surveys measuring perceptions and/or attitudes, were not included. Three of the investigators independently read each article and determined its inclusion status. Agreement on inclusion was high (κ = 0.97). Remaining differences were resolved by consensus. A total of 17 articles met the inclusion criteria [
      • Lu M.T.
      • Tellis W.M.
      • Fidelman N.
      • Qayyum A.
      • Avrin D.E.
      Reducing the rate of repeat imaging: import of outside images to PACS.
      ,
      • Sodickson A.
      • Opraseuth J.
      • Ledbetter S.
      Outside imaging in emergency department transfer patients: CD import reduces rates of subsequent imaging utilization.
      ,
      • Bailey J.E.
      • Wan J.Y.
      • Mabry L.M.
      • et al.
      Does health information exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department?.
      ,
      • Bailey J.E.
      • Pope R.A.
      • Elliott E.C.
      • Wan J.Y.
      • Waters T.M.
      • Frisse M.E.
      Health information exchange reduces repeated diagnostic imaging for back pain.
      ,
      • McCormick D.
      • Bor D.H.
      • Woolhandler S.
      • Himmelstein D.U.
      Giving office-based physicians electronic access to patients' prior imaging and lab results did not deter ordering of tests.
      ,
      • Ross S.E.
      • Radcliff T.A.
      • LeBlanc W.G.
      • Dickinson L.M.
      • Libby A.M.
      • Nease Jr., D.E.
      Effects of health information exchange adoption on ambulatory testing rates.
      ,
      • You J.J.
      • Yun L.
      • Tu J.V.
      Impact of PACS on rates of duplicate imaging: a before-after study.
      ,
      • Cheponis J.
      • Weathers A.
      • Amin D.
      • Sims S.
      • Ouyang B.
      Does the ability to incorporate images from external radiology studies into an electronic health record (EHR) change the ordering practices of academic neurologists and neurosurgeons?.
      ,
      • Flanagan P.T.
      • Relyea-Chew A.
      • Gross J.A.
      • Gunn M.L.
      Using the Internet for image transfer in a regional trauma network: effect on CT repeat rate, cost, and radiation exposure.
      ,
      • Frisse M.E.
      • Johnson K.B.
      • Nian H.
      • et al.
      The financial impact of health information exchange on emergency department care.
      ,
      • Lammers E.J.
      • Adler-Milstein J.
      • Kocher K.E.
      Does health information exchange reduce redundant imaging? Evidence from emergency departments.
      ,
      • Mäenpää T.
      • Asikainen P.
      • Gissler M.
      • et al.
      Outcomes assessment of the regional health information exchange: a five-year follow-up study.
      ,
      • Psoter K.J.
      • Roudsari B.S.
      • Vaughn M.
      • Fine G.C.
      • Jarvik J.G.
      • Gunn M.L.
      Effect of an image-sharing network on CT utilization for transferred trauma patients: a 5-year experience at a level I trauma center.
      ,
      • Tzeel A.
      • Lawnicki V.
      • Pemble K.R.
      The business case for payer support of community-based health information exchange: a humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care.
      ,
      • Vest J.
      • Kaushal R.
      • Silver M.
      • Hentel K.
      • Kern L.
      for the HITEC investigators
      Health information exchange and the frequency of repeat medical imaging.
      ,
      • Whiteman C.
      • Kiefer C.
      • D'Angelo J.
      • Davidov D.
      • Larrabee H.
      • Davis S.
      The use of technology to reduce radiation exposure in trauma patients transferred to a level I trauma center.
      ,
      • Winden T.J.
      • Boland L.L.
      • Frey N.G.
      • Satterlee P.A.
      • Hokanson J.S.
      Care everywhere, a point-to-point HIE tool.
      ].

       Abstraction

      From each included article, we abstracted the following information: study design; patient population; setting; modality (specific, multiple, basic, or advanced); outcome; sample size; effect size (with variances); and technology type. Given the small sample, we grouped HIEs and EHRs into a single category, because they are both information systems that contain (and can share) a broad range of clinical, demographic, and administrative data. We grouped PACS and physical media importation systems into a single category, because these are radiology-specific systems, and in the PACS studies, authors often mentioned that physical media importation was still an available option.
      For five articles [
      • Sodickson A.
      • Opraseuth J.
      • Ledbetter S.
      Outside imaging in emergency department transfer patients: CD import reduces rates of subsequent imaging utilization.
      ,
      • You J.J.
      • Yun L.
      • Tu J.V.
      Impact of PACS on rates of duplicate imaging: a before-after study.
      ,
      • Cheponis J.
      • Weathers A.
      • Amin D.
      • Sims S.
      • Ouyang B.
      Does the ability to incorporate images from external radiology studies into an electronic health record (EHR) change the ordering practices of academic neurologists and neurosurgeons?.
      ,
      • Tzeel A.
      • Lawnicki V.
      • Pemble K.R.
      The business case for payer support of community-based health information exchange: a humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care.
      ,
      • Whiteman C.
      • Kiefer C.
      • D'Angelo J.
      • Davidov D.
      • Larrabee H.
      • Davis S.
      The use of technology to reduce radiation exposure in trauma patients transferred to a level I trauma center.
      ], we reanalyzed reported frequencies or means, to determine the effect sizes, using Student’s t tests, and correlations, with standard formulas to derive missing information if necessary [
      • Hozo S.
      • Djulbegovic B.
      • Hozo I.
      Estimating the mean and variance from the median, range, and the size of a sample.
      ,
      • Altman D.G.
      • Bland J.M.
      How to obtain the P value from a confidence interval.
      ,
      • Lakens D.
      Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs.
      ]. Effect sizes could not be determined for four of the articles [
      • Flanagan P.T.
      • Relyea-Chew A.
      • Gross J.A.
      • Gunn M.L.
      Using the Internet for image transfer in a regional trauma network: effect on CT repeat rate, cost, and radiation exposure.
      ,
      • Mäenpää T.
      • Asikainen P.
      • Gissler M.
      • et al.
      Outcomes assessment of the regional health information exchange: a five-year follow-up study.
      ,
      • Psoter K.J.
      • Roudsari B.S.
      • Vaughn M.
      • Fine G.C.
      • Jarvik J.G.
      • Gunn M.L.
      Effect of an image-sharing network on CT utilization for transferred trauma patients: a 5-year experience at a level I trauma center.
      ,
      • Winden T.J.
      • Boland L.L.
      • Frey N.G.
      • Satterlee P.A.
      • Hokanson J.S.
      Care everywhere, a point-to-point HIE tool.
      ], either because of the study design or because the article did not contain sufficient statistical information for analysis. We included the characteristics of these articles in our overall descriptions of the literature, but they did not contribute to the meta-analysis. We converted all reported results to standard effect sizes and 95% confidence intervals (CIs) [

      Wilson DB. Practical meta-analysis effect size calculator. Available at: http://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator-Home.php. Accessed February 10, 2015.

      ].
      Some of the articles in the final set (n = 13) contained multiple research findings (ie, more than one “study” within a single article). Individual studies were defined as follows: stratified samples (eg, imaging utilization reported separately for primary versus specialty care settings); independent assessments of different modalities (eg, CTs and radiographs measured separately); and/or different outcomes. We selected the best-fitting models, or the adjusted effect sizes if multiple regression estimates or sensitivity analyses on the same outcomes were reported.
      To describe the possibility of bias, we noted the presence, versus absence, of the following safeguards to internal validity: adjustment for potential confounding; inclusion of an appropriate comparison group; inclusion of preintervention observations; measurement of technology usage (not just adoption); adjustment for repeated or clustered measures; and robustness checks (eg, formal tests or stratified analyses). We characterized studies involving multiple institutions or settings as being more generalizable (ie, a safeguard against bias) than single-institution studies. The number of indicators present, from these seven, was used as a measure of potential risk of bias: studies with only three or fewer indicators were at moderate or high risk for bias; those with four or more indicators were at lower risk.

       Statistical Analysis

      We characterized the articles by type of technology, using frequencies and Fisher’s exact test. We summarized the research on the impact of image sharing technologies with a random-effects model meta-analysis [
      • Ringquist E.J.
      Meta-analysis for public management & policy.
      ,
      • Lipsey M.W.
      • Wilson D.B.
      Practical meta-analysis.
      ]. Pooled estimates of effect size, and forest plots, for all findings were obtained using Stata (StataCorp LP version 13.1, College Station, Texas) with the I2 statistic, to describe the extent of statistical heterogeneity of the findings [
      • Harris R.
      • Bradburn M.
      • Deeks J.
      • Harbord R.
      • Altman D.
      • Sterne J.
      Metan: fixed- and random-effects meta-analysis.
      ]. In addition, we stratified the pooled effect sizes by use outcome (unnecessary imaging was combined with repeat imaging, owing to small sample size).
      To explore the relationship between study characteristics and observed effects on utilization, we performed a meta-regression using the individual study findings as the units of analysis (with inverse variance weights) and robust SEs to account for multiple study findings per article. Finally, we assessed risk of bias, by limiting the pooled analyses to those studies that were found to have the lowest risk for bias, and by examining the full sample of studies, using funnel plots (Appendix 1, Fig A1) and Egger’s test for publication bias [
      • Harbord R.M.
      • Harris R.J.
      • Sterne J.A.C.
      Updated tests for small-study effects in meta-analyses.
      ].

      Results

       Characteristics of Included Articles and Studies

      A total of 17 articles described the quantitative effects of image sharing technologies on utilization, with nine focusing on repeat imaging, and eight using any imaging as the outcome (Table 1; Appendix 1, Table A1). Most articles evaluated HIEs or EHRs (58.8%), were set in emergency departments (EDs; 58.8%), included the general patient population (52.9%), and considered both advanced and basic modalities (70.6%). Articles did vary significantly by the type of image sharing technology used in the study. With PACS, the sharing was more likely to be of actual images, and the focus on patients with a specific condition. The risk of bias tended to be lower in studies that evaluated HIEs and/or EHRs. All the studies focusing on PACS had a moderate or high risk of bias. The 13 articles that had sufficient information to contribute to the meta-analysis included 42 different studies.
      Table 1Characteristics of articles on the quantitative effect of image sharing technologies on utilization
      TotalHIE or EHRPACS or Physical Mediap value
      Articles17107
      Outcome
       Repeat imaging
      Includes “unnecessary” or “avoidable” imaging.
      9 (52.9)5 (50.0)3 (42.9).581
       Any imaging8 (47.1)5 (50.0)4 (57.1)
      Imaging modality
       Advanced only5 (29.4)1 (10.0)4 (57.1).060
       Advanced and basic12 (70.6)9 (90.0)3 (42.9)
      Information content
       Images
      Also gave access to reports.
      9 (52.9)2 (20.0)7 (100.0).003
       Reports6 (35.3)6 (60.0)0 (0.0)
       Not specified2 (11.8)2 (20.0)0 (0.0)
      Setting
       Emergency department10 (58.8)6 (60.0)4 (57.1).767
       Inpatient1 (5.9)0 (0.0)1 (14.3)
       Office-based2 (11.8)1 (10.0)1 (14.3)
       Community-wide4 (23.5)3 (30.0)1 (14.3)
      Patient population
       General9 (52.9)8 (80.0)1 (14.3).008
       Specific condition4 (23.5)0 (0.0)4 (57.1)
       Transfer/trauma4 (23.5)2 (20.0)2 (28.6)
      Study design
       Cohort7 (41.2)4 (40.0)3 (42.9).091
       Quasi-experimental2 (11.8)2 (20.0)0 (0.0)
       Cross-sectional2 (11.8)1 (10.0)1 (14.3)
       Pretest–posttest3 (17.6)0 (0.0)3 (42.9)
       Posttest only/case series3 (17.6)3 (30.0)0 (0.0)
      Risk of bias
       Low7 (41.2)7 (70.0)0 (0.0).010
       Moderate or high10 (58.8)3 (30.0)7 (100.0)
      Insufficient information for inclusion
      Excluded from the meta-analysis.
      4 (23.5)2 (20.0)2 (28.6)
      Total number of findings abstracted422715
      EHR = electronic health record; HIE = health information exchange.
      Includes “unnecessary” or “avoidable” imaging.
      Also gave access to reports.
      Excluded from the meta-analysis.

       Estimated Effect of Image Sharing Technology on Imaging Utilization

      A total of 57% of all studies found some reduction in imaging utilization when image sharing technology was available. However, in the overall pooled analysis (Fig 2), image sharing technologies were not associated with reductions in imaging utilization (effect size (ES) = 0.00; 95% CI [–0.07, 0.07]; P = .991 Substantial heterogeneity was found in the results of the studies (I2 = 98%).
      Figure thumbnail gr2
      Fig 2Association (standard effect size) between image sharing technologies and any imaging, repeat imaging, and all outcomes: systematic review and meta-analysis, 2004 to 2014.
      HIE = health information exchange; EHR = electronic health records.
      The effect of image sharing technology did differ significantly depending on the outcome studied (Fig 2). If the outcome was any imaging, image sharing technology was associated with a significant increase in utilization (pooled ES = 0.20; 95% CI [0.07, 0.32]; P = .002). In contrast, image sharing technology was associated with a significant decrease in repeat imaging (pooled ES = –0.17; 95% CI [–0.25, –0.09]; P < .001).

       Study Characteristics and Observed Effects on Imaging Utilization

      Negative coefficients in the adjusted meta-regression model (Table 2) indicate that the study characteristic was associated with reductions in utilization. Studies in the ED setting were more likely to indicate reductions in utilization (β = –0.34; 95% CI [–0.66, –0.01]), as were studies that looked at the occurrence of repeat (including unnecessary) imaging as an outcome (β = –0.58; 95% CI [–0.84, –0.33]). Given the highly variable effect sizes and the small sample size, we were more interested in the direction of the estimated associations than in the point estimates. Due to collinearity, not all of the abstracted information could be included in the model.
      Table 2Adjusted associations between study characteristics and effect sizes of image sharing technology on imaging utilization: systematic review and meta-analysis, 2004-2014
      Characteristicβ (95% Confidence interval)P Value
      Outcome
       Repeat imaging versus any imaging–0.58 (–0.84, –0.33)<.001
      Technology
       Health information exchange and/or electronic health record versus PACS and/or CD importation–1.08 (–2.48, 0.32).125
      Setting
       Emergency department versus all other settings–0.34 (–0.66, –0.01).043
      Patient population
       General patients versus all other patient populations–0.32 (–1.16, 0.52).451
      Evidence quality score0.31 (–0.19, 0.82).213
      Note: Estimates with inverse variance weights and robust SEs.
      The type of image sharing technology was not statistically associated with effect size; however, studies examining HIE and/or EHRs did reveal more negative effect estimates than did studies of PACS. For example, HIE was negatively associated with the occurrence of repeat (or unnecessary) imaging in all of the included studies [
      • Bailey J.E.
      • Wan J.Y.
      • Mabry L.M.
      • et al.
      Does health information exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department?.
      ,
      • Bailey J.E.
      • Pope R.A.
      • Elliott E.C.
      • Wan J.Y.
      • Waters T.M.
      • Frisse M.E.
      Health information exchange reduces repeated diagnostic imaging for back pain.
      ,
      • Lammers E.J.
      • Adler-Milstein J.
      • Kocher K.E.
      Does health information exchange reduce redundant imaging? Evidence from emergency departments.
      ,
      • Vest J.
      • Kaushal R.
      • Silver M.
      • Hentel K.
      • Kern L.
      for the HITEC investigators
      Health information exchange and the frequency of repeat medical imaging.
      ] (Appendix 1, Table A1). The effect of HIE on any utilization was more ambiguous: eight studies found reductions, but five found increases in imaging [
      • Ross S.E.
      • Radcliff T.A.
      • LeBlanc W.G.
      • Dickinson L.M.
      • Libby A.M.
      • Nease Jr., D.E.
      Effects of health information exchange adoption on ambulatory testing rates.
      ,
      • Frisse M.E.
      • Johnson K.B.
      • Nian H.
      • et al.
      The financial impact of health information exchange on emergency department care.
      ,
      • Tzeel A.
      • Lawnicki V.
      • Pemble K.R.
      The business case for payer support of community-based health information exchange: a humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care.
      ]. Additionally, those studies that did not meet the meta-analysis inclusion requirements suggested reductions in utilization [
      • Mäenpää T.
      • Asikainen P.
      • Gissler M.
      • et al.
      Outcomes assessment of the regional health information exchange: a five-year follow-up study.
      ,
      • Winden T.J.
      • Boland L.L.
      • Frey N.G.
      • Satterlee P.A.
      • Hokanson J.S.
      Care everywhere, a point-to-point HIE tool.
      ]. Additionally, the occurrence of repeat imaging was lower in one study that used a shared PACS system [
      • You J.J.
      • Yun L.
      • Tu J.V.
      Impact of PACS on rates of duplicate imaging: a before-after study.
      ], and in two that examined physical media importation [
      • Lu M.T.
      • Tellis W.M.
      • Fidelman N.
      • Qayyum A.
      • Avrin D.E.
      Reducing the rate of repeat imaging: import of outside images to PACS.
      ,
      • Whiteman C.
      • Kiefer C.
      • D'Angelo J.
      • Davidov D.
      • Larrabee H.
      • Davis S.
      The use of technology to reduce radiation exposure in trauma patients transferred to a level I trauma center.
      ].

       Risk of Bias

      Most studies used a cohort or cross-sectional design, without true before and after measurements; this factor was the most common for risk of bias (Appendix 1, Table A1). These design choices were further weakened by the frequent lack of a comparison group. The lack of a definable comparison group was a problem only among the PACS and/or importation technology articles; all HIE and/or EHR articles had a comparison group. Generally, the HIE and/or EHR articles included features that better guarded against bias, such as study designs with stronger internal validity, adjustment for confounding, adjustment for repeated measures, and findings from multiple institutions. Analysis of only those studies that had the lowest risk of bias produced results that did not vary substantially from the main findings. Image sharing technology was not associated with reductions in overall imaging utilization or in utilization of any imaging, but it was associated with reductions in repeat utilization (Appendix 1, Table A1).
      The potential for publication bias cannot be ruled out. Visual examination of the funnel plots of effect sizes, for all studies and by outcome (Appendix 1, Fig A1), did not suggest any overt publication bias, but the small sample size complicates interpretation. In addition, Egger’s test did not suggest publication bias, but the test has a high type 1 error rate (ie, it is susceptible to false positives).

      Discussion

      Image sharing technology utilization was associated with reductions in repeat and unnecessary imaging, in the overall literature and in the most rigorous studies. Not all repeated imaging is avoidable, but repeating imaging solely because an earlier image is inaccessible at the time of care is likely avoidable [
      • Rao V.M.
      • Levin D.C.
      The overuse of diagnostic imaging and the Choosing Wisely initiative.
      ]. When providers have sufficient access to relevant imaging, they are more likely to forego repeat imaging [
      • Winden T.J.
      • Boland L.L.
      • Frey N.G.
      • Satterlee P.A.
      • Hokanson J.S.
      Care everywhere, a point-to-point HIE tool.
      ,
      • Carr C.M.
      • Gilman C.S.
      • Krywko D.M.
      • Moore H.E.
      • Walker B.J.
      • Saef S.H.
      Observational study and estimate of cost savings from use of a health information exchange in an academic emergency department.
      ].
      Image sharing technologies were designed to address this issue [
      • Hendee W.R.
      • Becker G.J.
      • Borgstede J.P.
      • et al.
      Addressing overutilization in medical imaging.
      ]. Although payers (including Medicare) often do not reimburse providers for reviewing an external study, image sharing technologies can make the process of accessing earlier studies easier for physicians. Additionally, repeat imaging and unnecessary imaging are clearly important to target for cost-saving efforts that can simultaneously improve care and the patient experience [
      • Hendee W.R.
      • Becker G.J.
      • Borgstede J.P.
      • et al.
      Addressing overutilization in medical imaging.
      ,
      • Rao V.M.
      • Levin D.C.
      The overuse of diagnostic imaging and the Choosing Wisely initiative.
      ]. The potential impact on repeat imaging is particularly promising in the context of fee-for-service reimbursement, the dominant payment model used in the United States, which does not penalize providers for inappropriate utilization. However, even integrated delivery systems (in which incentives are theoretically aligned) are not immune from inappropriate imaging, so image sharing technologies could play a role in quality strategies in those settings, or for any organization preparing for value-based payments [
      • Burwell S.M.
      Setting value-based payment goals—HHS efforts to improve U.S. health care.
      ].
      In contrast, image sharing technology was not effective in reducing any (eg, overall) imaging utilization. For many studies, once image sharing technology was introduced into a setting or used by health care professionals, imaging utilization increased. Unlike the case of repeat and/or unnecessary imaging, no clear link was found between reductions in overall imaging and utilization of image sharing technology. Many instances of imaging may be unavoidable, or should be expected as appropriate diagnostic procedures, treatment regimens, or in light of changes to patients’ condition [
      • Cascade P.N.
      The ACR. ACR APPROPRIATENESS CRITERIA® project. Radiology.
      ]. In these cases, access to prior imaging could improve the accuracy of diagnoses, monitor disease progression, or aid in decision making, but it would have little role in utilization.
      Alternatively, the actual increase in imaging utilization may be a product of technology that, although it increases access to existing images, simultaneously makes it easier for providers to order imaging studies [
      • McCormick D.
      • Bor D.H.
      • Woolhandler S.
      • Himmelstein D.U.
      Giving office-based physicians electronic access to patients' prior imaging and lab results did not deter ordering of tests.
      ], particularly for EHRs, which have viewing and ordering within the same application [
      • DesRoches C.M.
      • Campbell E.G.
      • Rao S.R.
      • et al.
      Electronic health records in ambulatory care—a national survey of physicians.
      ]. The same might be true for PACS, if a system were introduced at the same time, or interfaced tightly with the radiology information system in which the image ordering takes place [
      • Paré G.
      • Trudel M.-C.
      Knowledge barriers to PACS adoption and implementation in hospitals.
      ]. Another possibility is that the increase in imaging is attributable to increases in work efficiency that result from PACS adoption [
      • Reiner B.I.
      • Siegel E.L.
      • Hooper F.J.
      • Pomerantz S.
      • Dahlke A.
      • Rallis D.
      Radiologists' productivity in the interpretation of CT scans.
      ].
      The opportunities to use image sharing technology are growing, through projects such as the RSNA’s Image Share [

      RSNA. RSNA image share. Available at: https://www.rsna.org/Image_Share.aspx. Accessed March 23, 2015.

      ], and federal policies that encourage technology adoption, such as the Medicare and Medicaid Electronic Health Records (EHR) Incentive Programs, commonly called Meaningful Use [
      • Heisey-Grove D.
      • Patel V.
      Physician motivations for adoption of electronic health records.
      ]. The expectation that these technologies will be used will grow, as public recognition of the potential value of access to images increases [
      • Landro L.
      Image sharing seeks to reduce repeat scans.
      ,
      • Yeager D.
      Sharing images—a hospital and a radiology group tell how they utilize VNA to meet different needs.
      ]. Nonetheless, the evidence demonstrating effectiveness of image sharing technologies is limited. This meta-analysis supports the hypothesis that image sharing technologies can be useful, but given the small number of quantitative studies, and the frequent risk of bias, many important questions remain unanswered.
      A critical limitation on acquiring such evidence is that effects reported in the literature cannot be stratified by modality, patient characteristics, or conditions. Imaging rates vary according to patient populations, and the ability to easily access prior studies reportedly varies by modality [
      • Kalia V.
      • Carrino J.A.
      • Macura K.J.
      Policies and procedures for reviewing medical images from portable media: survey of radiology departments.
      ]. We do not have any conclusive insights into the relative effectiveness of various image sharing technologies. For example, comparing PACS to HIEs would provide insights as to whether access to imaging information alone is sufficient to change subsequent utilization, or if access to imaging information in conjunction with broader patient information is more useful.
      The current study suggests that HIE was the technology most likely to reduce utilization, but the sample size and risk of bias in the other image sharing technology studies prevented further investigation. Lastly, the available quantitative research does not sufficiently capture the differences in provider workflows and information needs. For example, a primary care provider may prefer access to a report that has accompanying clinical information, whereas a subspecialty physician, such as a neurosurgeon, may prioritize access to the image.
      The evidence base can be improved in several ways. Stronger research designs are required, to allow causal inferences to be drawn and better control of confounding. Opportunities are available to select and use better designs. For example, interrupted time series designs fit well with technology implementations. Implementation planning takes time, including the collection of baseline data.
      In addition, as part of the implementation plan, institutions may roll out or stagger implementation dates across various sites, allowing for natural comparison groups. Alternatively, the system vendors could assist in identifying other customers going through the process of implementation, to both add as comparisons and increase the generalizability of findings. Additionally, multidisciplinary research teams could help strengthen studies: Health services researchers could provide expertise to address the issues of selection and confounding present in many studies, informaticists understand the actual usage of systems, and clinicians provide the conceptual linkage between imaging information and clinical care.
      In general, health IT research and evaluation needs to be strengthened and made more generalizable [
      • Chaudhry B.
      • Wang J.
      • Wu S.
      • et al.
      Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.
      ,
      • Rahurkar S.
      • Vest J.R.
      • Menachemi N.
      Despite the spread of health information exchange, there is little evidence of its impact on cost, use, and quality of care.
      ,
      • Rudin R.S.
      • Motala A.
      • Goldzweig C.L.
      • Shekelle P.G.
      Usage and effect of health information exchange: a systematic review.
      ]. For example, evaluations outside of ED settings are a clear gap in the literature. Available methods and designs could improve the quality of research; but those who fund research (ie, government agencies, health systems, or vendors) must be willing to invest the necessary resources and time to make higher-quality research possible.

       Limitations

      First, this analysis does not address all the potential effects of image sharing technology, such as efficiency gains, satisfaction, or cost [
      • Rahurkar S.
      • Vest J.R.
      • Menachemi N.
      Despite the spread of health information exchange, there is little evidence of its impact on cost, use, and quality of care.
      ,
      • Rudin R.S.
      • Motala A.
      • Goldzweig C.L.
      • Shekelle P.G.
      Usage and effect of health information exchange: a systematic review.
      ]. Second, we did not explore barriers that prevent organizations from adopting these technologies into their clinical workflow. Even when such technologies are available, it may always just be “easier” to order the image. Third, this review is not about clinical decision support. Evidence suggests that this too may be a technology-enabled approach to improving utilization [
      • Sistrom C.L.
      • Dang P.A.
      • Weilburg J.B.
      • Dreyer K.J.
      • Rosenthal D.I.
      • Thrall J.H.
      Effect of computerized order entry with integrated decision support on the growth of outpatient procedure volumes: seven-year time series analysis.
      ]. Fourth, generalizability may be limited, because many of the included articles analyzed data that were from only one organization or a single technology. Given the variation among vendor products, and differences in the levels of adoption and integration among organizations, these findings may not translate to all settings. Lastly, even though our search strategy included multiple databases, and the gray literature, we may be missing studies, and our overall findings may be limited by publication bias.

      Conclusions

      Image sharing technologies have the potential to improve provider access to existing imaging studies and reports. Usage of image sharing technology was associated with reductions in repeat and unnecessary imaging utilization in both the overall literature and in the most-rigorous studies. Stronger evidence is needed to identify the role of specific technologies and the potential impact on various modalities, patient populations, and settings.

      Take-Home Points

      • Image sharing technologies (health information exchange, PACS, EHRs, and media import) are a potential intervention to improve access to previous imaging studies and reports.
      • Across multiple technologies, and in the most-rigorous studies, image sharing was associated with a modest, but statistically significant, decrease in repeat imaging.
      • The literature on the impact of image sharing technology is small, so that no specific conclusions can be drawn about the effects of a specific modality, technology, or patient population.
      • The literature would benefit from stronger research designs and better control of confounding. Those funding the research must be willing to invest the necessary resources and time needed to make higher-quality research possible.

      Acknowledgements

      This work was funded under a grant by the Harvey L. Neiman Health Policy Institute (to J.R.V. and H-Y.J.). We thank the many investigators and authors who supplied us with additional information about their work.

      Appendix 1

      Table A1List of articles and studies
      Article (Year) [Reference Number]OutcomeTechnologySettingPatient PopulationIn Meta-analysis?StudiesDescriptionRisk of Bias ScoreComparison GroupPre-postMeasured UsageAdjust for ConfoundingAdjusted for CorrelationRobustness Check>1 Institution
      Bailey (2013)
      • Bailey J.E.
      • Wan J.Y.
      • Mabry L.M.
      • et al.
      Does health information exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department?.
      UnnecessaryHIEEDHeadacheY1Unnecessary neuroimaging5YNYYYNY
      Bailey (2013)
      • Bailey J.E.
      • Pope R.A.
      • Elliott E.C.
      • Wan J.Y.
      • Waters T.M.
      • Frisse M.E.
      Health information exchange reduces repeated diagnostic imaging for back pain.
      RepeatHIEEDBack painY1Duplicative imaging for back pain5YNYYYNY
      Cheponis (2013)
      • Cheponis J.
      • Weathers A.
      • Amin D.
      • Sims S.
      • Ouyang B.
      Does the ability to incorporate images from external radiology studies into an electronic health record (EHR) change the ordering practices of academic neurologists and neurosurgeons?.
      Any imagingPhysical media importOffice-basedNeurologyY4Monthly CT and MRI rates overall and for repeat patients2NYNNNYN
      Flanagan (2012)
      • Flanagan P.T.
      • Relyea-Chew A.
      • Gross J.A.
      • Gunn M.L.
      Using the Internet for image transfer in a regional trauma network: effect on CT repeat rate, cost, and radiation exposure.
      RepeatShared PACSEDTransferNRepeat imaging among transfer patients1NYNNNNN
      Frisse (2012)
      • Frisse M.E.
      • Johnson K.B.
      • Nian H.
      • et al.
      The financial impact of health information exchange on emergency department care.
      Any imagingHIEEDGeneralY8Radiograph and CT utilization at different sites6YNYYYYY
      Lammers (2014)
      • Lammers E.J.
      • Adler-Milstein J.
      • Kocher K.E.
      Does health information exchange reduce redundant imaging? Evidence from emergency departments.
      RepeatHIEEDGeneralY3Repeat CT, ultrasound and radiograph6YYNYYYY
      Lu (2012)
      • Lu M.T.
      • Tellis W.M.
      • Fidelman N.
      • Qayyum A.
      • Avrin D.E.
      Reducing the rate of repeat imaging: import of outside images to PACS.
      RepeatPhysical media importInpatientCancerY1CT or MRI at transfer3YNYYNNN
      Mäenpää (2011)
      • Mäenpää T.
      • Asikainen P.
      • Gissler M.
      • et al.
      Outcomes assessment of the regional health information exchange: a five-year follow-up study.
      Any imagingHIECommunity-wideGeneralNPopulation study of regional HIE1NNNNNNY
      McCormick (2012)
      • McCormick D.
      • Bor D.H.
      • Woolhandler S.
      • Himmelstein D.U.
      Giving office-based physicians electronic access to patients' prior imaging and lab results did not deter ordering of tests.
      Any imagingEHRCommunity-wideGeneralY4Any and advanced imaging based on results or image sharing5YNNYYYY
      Psoter (2014)
      • Psoter K.J.
      • Roudsari B.S.
      • Vaughn M.
      • Fine G.C.
      • Jarvik J.G.
      • Gunn M.L.
      Effect of an image-sharing network on CT utilization for transferred trauma patients: a 5-year experience at a level I trauma center.
      Any imagingShared PACSEDTransferNAny imaging among transfer patients2NYNYNNN
      Ross (2013)
      • Ross S.E.
      • Radcliff T.A.
      • LeBlanc W.G.
      • Dickinson L.M.
      • Libby A.M.
      • Nease Jr., D.E.
      Effects of health information exchange adoption on ambulatory testing rates.
      Any imagingHIEOffice-basedGeneralY4Primary and specialty care; any and advanced imaging rates6YYNYYYY
      Sodickson (2011)
      • Sodickson A.
      • Opraseuth J.
      • Ledbetter S.
      Outside imaging in emergency department transfer patients: CD import reduces rates of subsequent imaging utilization.
      Any imagingPhysical media importEDTransferY2Importation of CT only, or all images2YNYNNNN
      Tzeel (2011)
      • Tzeel A.
      • Lawnicki V.
      • Pemble K.R.
      The business case for payer support of community-based health information exchange: a humana pilot evaluating its effectiveness in cost control for plan members seeking emergency department care.
      Any imagingHIEEDGeneralY2CT or diagnostic imaging utilization3YNNYNNY
      Vest (2014)
      • Vest J.
      • Kaushal R.
      • Silver M.
      • Hentel K.
      • Kern L.
      for the HITEC investigators
      Health information exchange and the frequency of repeat medical imaging.
      RepeatHIECommunity-wideGeneralY4Repeat of any, CT, ultrasound, or radiograph at 90 days6YNYYYYY
      Whiteman (2014)
      • Whiteman C.
      • Kiefer C.
      • D'Angelo J.
      • Davidov D.
      • Larrabee H.
      • Davis S.
      The use of technology to reduce radiation exposure in trauma patients transferred to a level I trauma center.
      RepeatPhysical media importEDTraumaY1CT utilization1NYNNNNN
      Winden (2014)
      • Winden T.J.
      • Boland L.L.
      • Frey N.G.
      • Satterlee P.A.
      • Hokanson J.S.
      Care everywhere, a point-to-point HIE tool.
      AvoidedHIEEDGeneralNAvoided imaging from HIE1NNYNNNN
      You (2008)
      • You J.J.
      • Yun L.
      • Tu J.V.
      Impact of PACS on rates of duplicate imaging: a before-after study.
      RepeatShared PACSCommunity-wideGeneralY7Repeat of CT and radiograph at 30 days, by body location
      Also reported 7-day and 60-day repeat rates, but not abstracted.
      3NYNNNYY
      ED = emergency department; EHR = electronic health record; HIE = health information exchange; N = no; Y = yes.
      Also reported 7-day and 60-day repeat rates, but not abstracted.
      Figure thumbnail fx1
      Fig A1Funnel plot of effect sizes from image sharing technology systematic review and meta-analysis, 2004-2014.

       Example Search Strategy

      MEDLINE
      • 1. All-field search of “image sharing technology”
      • 2. All-field search of “Picture Archiving and Communications Systems”
      • 3. All-field search of “electronic health record”
      • 4. All-field search of “image exchange network”
      • 5. All-field search of “physical media”
      • 6. All-field search of “health information exchange”
      • 7. MESH term “Radiology Information Systems”
      • 8. #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7
      • 9. MESH term “Radiography/utilization”
      • 10. All-field search of imaging
      • 11. All-field search of “repeat imaging”
      • 12. All-field search of “imaging cost”
      • 13. All-field search of “radiology cost”
      • 14. All-field search of “unnecessary imaging”
      • 15. #9 OR #10 OR #11 OR #12 OR #13 OR #14
      • 16. Limits: English. Year 2005/1/1 – 2014/12/31. Abstract. Humans.
      • 17. Not orthodontics. Not dental.
      • 18. Number retrieved = 746
      MESH = medical subject heading.

       Secondary Analysis to Assess Risk of Bias

      To examine the risk of bias in the pooled analyses, we restricted the sample to those studies (n = 25) with the lowest risk of bias (with ≥4 of the 7 possible quality indicators). Overall, no statistical association between image sharing technology and utilization was found (pooled ES = –0.01; 95% CI [–0.09, 0.09]; P < .963). For studies with any imaging utilization as the outcome, image sharing technology was associated with an increase in utilization (pooled ES = 0.17; 95% CI [0.04, 0.30]; P = .012). Again, image sharing technology was associated with a reduction in repeat imaging (pooled ES = –0.27; 95% CI [–0.33, –0.21]; P < .001).

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