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The American Journal of Managed Care January 2018
Measuring Overuse With Electronic Health Records Data
Thomas Isaac, MD, MBA, MPH; Meredith B. Rosenthal, PhD; Carrie H. Colla, PhD; Nancy E. Morden, MD, MPH; Alexander J. Mainor, JD, MPH; Zhonghe Li, MS; Kevin H. Nguyen, MS; Elizabeth A. Kinsella, BA; and Thomas D. Sequist, MD, MPH
The Health Information Technology Special Issue: Has IT Become a Mandatory Part of Health and Healthcare?
Jacob Reider, MD
Bridging the Digital Divide: Mobile Access to Personal Health Records Among Patients With Diabetes
Ilana Graetz, PhD; Jie Huang, PhD; Richard J. Brand, PhD; John Hsu, MD, MBA, MSCE; Cyrus K. Yamin, MD; and Mary E. Reed, DrPH
Electronic Health Record "Super-Users" and "Under-Users" in Ambulatory Care Practices
Juliet Rumball-Smith, MBChB, PhD; Paul Shekelle, MD, PhD; and Cheryl L. Damberg, PhD
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Electronic Sharing of Diagnostic Information and Patient Outcomes
Darwyyn Deyo, PhD; Amir Khaliq, PhD; David Mitchell, PhD; and Danny R. Hughes, PhD
A Cost-Effectiveness Analysis of Cardiology eConsults for Medicaid Patients
Daren Anderson, MD; Victor Villagra, MD; Emil N. Coman, PhD; Ianita Zlateva, MPH; Alex Hutchinson, MBA; Jose Villagra, BS; and J. Nwando Olayiwola, MD, MPH
Electronic Health Record Problem Lists: Accurate Enough for Risk Adjustment?
Timothy J. Daskivich, MD, MSHPM; Garen Abedi, MD, MS; Sherrie H. Kaplan, PhD, MPH; Douglas Skarecky, BS; Thomas Ahlering, MD; Brennan Spiegel, MD, MSHS; Mark S. Litwin, MD, MPH; and Sheldon Greenfield, MD
Racial/Ethnic Variation in Devices Used to Access Patient Portals
Eva Chang, PhD, MPH; Katherine Blondon, MD, PhD; Courtney R. Lyles, PhD; Luesa Jordan, BA; and James D. Ralston, MD, MPH
Hospitalized Patients' and Family Members' Preferences for Real-Time, Transparent Access to Their Hospital Records
Michael J. Waxman, MD, MPH; Kurt Lozier, MBA; Lana Vasiljevic, MS; Kira Novakofski, PhD; James Desemone, MD; John O'Kane, RRT-NPS, MBA; Elizabeth M. Dufort, MD; David Wood, MBA; Ashar Ata, MBBS, PhD; Louis Filhour, PhD, RN; & Richard J. Blinkhorn Jr, MD

Electronic Sharing of Diagnostic Information and Patient Outcomes

Darwyyn Deyo, PhD; Amir Khaliq, PhD; David Mitchell, PhD; and Danny R. Hughes, PhD
A study evaluating the association between hospital sharing of electronic health record diagnostic information and hospital quality using Hospital Compare scores.

Objectives: Hospital sharing of electronic health record (EHR) diagnostic data has the potential to improve communication across providers and improve patient outcomes. However, implementing EHR systems can be difficult for hospitals. This study uses Hospital Compare (HC) and American Hospital Association (AHA) Annual Information Technology Survey data to estimate the association between sharing EHR data and patient outcomes.

Study Design: Descriptive and multivariate linear regression analyses.

Methods: This study links 2 years of HC data on 30-day patient mortality and readmissions for heart failure (HF) and pneumonia with 2 years of AHA data. The sample was restricted to hospitals included in both years in both sets of data. We estimated the associations between sharing EHR diagnostic data and patient outcomes with a multivariate linear regression analysis. Results were adjusted by hospital characteristics from the AHA annual survey.

Results: Hospitals’ sharing of radiology report data with hospitals within their system was associated with significantly lower mortality scores for pneumonia (–0.22; P <.01). Conversely, hospital sharing of radiology report data with hospitals outside their system was associated with significantly higher HF mortality scores (0.26; P <.01). We found qualitatively similar results with sharing laboratory results through EHRs. 

Conclusions: Hospital sharing of EHR data with providers within their system is associated with better patient mortality, whereas sharing data with providers outside their system is associated with worsened patient mortality. Improving communication between hospitals using different EHR systems may be more crucial than simply expanding data sharing.

Am J Manag Care. 2018;24(1):32-37
Takeaway Points

Hospitals that share diagnostic data through their electronic health records (EHRs) with other providers in their system are associated with better patient outcomes. 
  • Sharing diagnostic data through the EHRs within their system was associated with significantly lower 30-day patient mortality scores. 
  • Sharing diagnostic data through the EHRs outside their system was associated with significantly higher 30-day patient mortality scores.
  • Sharing diagnostic data through EHRs with physicians was significantly associated with lower heart failure readmissions overall.
Accurate communication of diagnostic data among medical providers is important for successful patient hand-offs and ensuring high-quality follow-up care.1 One specific avenue of communication, the sharing of electronic health records (EHRs), has emerged as a means to quickly communicate diagnostic data among hospitals and providers and has the potential to significantly reduce patient mortality and readmissions.2-4 Despite the prospective benefits of sharing EHR diagnostic data in terms of improved patient outcomes, the lack of common standards for EHR systems across hospitals and other providers can increase the risk of communication errors that may negatively impact patients.5-8

Further compounding this issue, the benefits of sharing EHR data can be hard to assess given the difficulties in measuring patient outcomes. Previous studies have used the rate of medical errors,9 simulation tools,10 and primary data11 from hospitals. In some cases, however, these studies consider unique institutions and the results may not be generalizable. Conflicting results among studies also may make it difficult to produce general conclusions about EHR data. Moreover, how hospitals pool study data may generate different results.12 Thus, although EHR systems have the potential to improve communication among hospitals and physicians, providers face careful calculations when balancing infrastructure costs, the sharing of EHR system data, and patient outcomes.3,13

By exploiting CMS Hospital Compare (HC) data and the American Hospital Association (AHA) Annual Information Technology (IT) supplement database, we sought to examine the effects on different groups of providers and hospitals within and outside of the hospital system. The CMS HC database contains useful metrics for comparing hospitals, including patient outcomes such as 30-day mortality and readmission for heart failure (HF) and pneumonia. These publicly reported quality measures have already been used to examine patient mortality and readmissions in several studies.14-16 We employed these data in a multivariate regression analysis to consider whether there are associations among hospital sharing of EHR diagnostic data and differences in patient mortality and readmissions. 



We obtained data on the sharing of hospital EHR diagnostic data from the AHA Annual IT Supplement Database for 2012 and 2013. The AHA conducts this annual survey, which gathers information on hospital sharing of EHR patient data, including diagnostic data from radiology reports and laboratory results. The AHA survey data have also been used with private healthcare claims to estimate the impact of EHR use on patient outcomes, including patient mortality and readmissions.10 Question 3 of the AHA IT Supplement asks, “Which of the following patient data does your hospital electronically exchange/share with 1 or more of the provider types listed below?” The AHA survey defines the electronic exchange of EHR data as the “exchanging of data through nonmanual means, such as EHRs and/or portals, and excludes fax/paper.”

Separate responses to this question are collected for radiology reports and laboratory results. Within each response category, the survey lists 4 provider sharing types that a respondent may select, as well as a “Do Not Know” option. The provider sharing types are: 1) “With hospitals inside of your system,” 2) “With hospitals outside of your system,” 3) “With ambulatory providers inside of your system,” and 4) “With ambulatory providers outside of your system.” We assumed “ambulatory providers” to refer to physicians for the purposes of this study. The sample sizes varied slightly for each question category because some hospitals reported blank responses for some of the categories and because responses of “Do Not Know” for any category were removed from the analysis.

We also collected additional hospital-specific data from the full AHA Annual Survey Database for 2012 and 2013 to adjust for factors that may influence the HC scores: 1) the number of licensed beds for each hospital, 2) the number of full-time equivalent (FTE) employees for each hospital, 3) whether or not the hospital is located in a rural area, 4) whether or not the hospital is part of a network, 5) whether or not the hospital is a teaching hospital, and 6) the level of expenditures in millions for each hospital.17 The AHA determines whether a hospital is part of a network, located in a rural area, or a teaching hospital. We also included the CMS hospital case mix index and a year indicator to adjust for any unobservable trends over time that could influence patient outcomes. 

The AHA survey data can be linked with the HC scores using a 1-year time lag due to a delay in data collection and reporting. CMS HC scores provide useful metrics for comparing patient outcomes among hospitals. CMS quality measures have been used to measure the relationships among hospital quality and patient mortality and readmissions.2,18,19 Although the scores themselves have generated some controversy, they remain a useful measure for comparing quality differences among hospitals. HC scores are measured at the hospital level and provide a relative comparison of patient outcomes in different hospitals across the United States. As HC includes most US hospitals, the scores also permit a more representative sample of hospitals and more generalizable results.

As our measures of patient outcomes, we used 2013 and 2014 HC scores for: 1) 30-day patient mortality from HF, 2) 30-day patient mortality from pneumonia, 3) 30-day readmissions from HF, and 4) 30-day readmissions from pneumonia. Each score represents the risk-adjusted ratio of predicted mortality or readmissions compared with expected mortality or readmissions for a hospital multiplied by the national mortality or readmission score. CMS estimates the scores using a hierarchical logistic regression model that accounts for the variance in patient outcomes within and between hospitals and adjusts for the individual hospital’s case mix index of patients.20,21

Statistical Analysis

Hospital scores from the 2013 and 2014 HC scores were linked with the corresponding hospital data collected from the 2012 and 2013 AHA Annual Survey Database and the AHA IT Supplement. Descriptive statistics were calculated for all hospital data collected.

We used multivariate linear regression to examine the associations among the 4 HC outcomes scores and the responses reported on the AHA IT Supplement for Question 3. The responses were reported separately for sharing radiology reports and sharing laboratory results by each of the 4 provider sharing types. Hospitals reporting “Do Not Know” were removed from the analysis. 

The multivariate regression results report the adjusted estimates for sharing radiology reports and laboratory results through hospital EHRs to different provider types on the HC scores for 30-day mortality and readmissions for patients with HF and pneumonia. The results were adjusted by the numbers of hospital beds and FTE employees, rural hospital, network hospital, teaching hospital, total expenditures, hospital case mix index, and a time trend.

Analyses were performed using SAS version 9.4 (SAS Institute; Cary, North Carolina). Two-sided P values <.05 were used to assess statistical significance. 


Between 2012 and 2013, the AHA IT Supplement surveyed 4093 hospitals, which resulted in 6575 observations. Linking these data to each hospital’s HC scores and the additional data from the AHA Annual Survey produced a final sample of 3113 distinct hospitals with 5088 total observations. The total observations varied for each multivariate regression analysis based on which hospitals answered each survey question and on data for each adjustment variable. There were 7.5% to 8.3% of values missing in the responses to IT Supplement Question 3 depending on the specific question component. Of the responding hospitals, less than 4% indicated “Do Not Know” as a response.

Descriptive Statistics

Table 1 reports summary statistics for the other variables in the study. For patients with HF, the average hospital score for 30-day patient mortality was 11.86 (SD = 1.47), and for 30-day readmissions, 22.33 (SD = 1.66). For patients with pneumonia, the average hospital score for 30-day patient mortality was 11.78 (SD = 1.78), and for 30-day readmissions, 17.13 (SD = 1.24). On average, hospitals had 230.7 licensed beds and 1190.6 FTE employees. Twenty-three percent of hospitals in our sample were rural, 48% were in a network, and 8% were teaching hospitals. On average, hospitals had about $196.3 million in expenditures, including bad debt. The average hospital case mix index was 1.46.

Table 2 reports summary statistics for hospital reponses to the AHA survey. Most hospitals in the study shared EHR diagnostic data with hospitals (72% shared radiology reports; 71% shared laboratory results) and physicians (80% shared radiology reports; 81% shared laboratory results) in their system. However, fewer hospitals shared EHR diagnostic data with hospitals or physicians that were outside their system. Only 36% shared radiology reports and 37% shared laboratory results through their EHR with hospitals outside their system. External physicians fared slightly better, with 55% of hospitals sharing radiology reports with physicians outside their system and 57% sharing laboratory results with this group. Hospital responses were also cross-tabulated by whether the hospital was part of a network (Table 2). The proportion of networked hospitals that shared EHR diagnostic data was similar to the proportion of non-networked hospitals that shared these data.

Multivariate Regression Results

Table 3 reports the estimates for sharing hospital EHR diagnostic data with HC 30-day patient mortality and readmission scores.

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