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Computerized Clinical Decision Support to Prevent Venous Thromboembolism Among Hospitalized Patients: Proximal Outcomes from a Multiyear Quality Improvement Project

Amland, Robert C.; Dean, Bonnie B.; Yu, HsingTing; Ryan, Hugh; Orsund, Timothy; Hackman, Jeffrey L.; Roberts, Shauna R.

The Journal for Healthcare Quality (JHQ): July/August 2015 - Volume 37 - Issue 4 - p 221–231
doi: 10.1111/jhq.12069
Original Article

Abstract: Despite venous thromboembolism (VTE) policy initiatives, gaps exist between guidelines and practice. In response, hospitals implement clinical decision support (CDS) systems to improve VTE prophylaxis. To assess the impact of a VTE CDS on reducing incidence of VTE, this study used a pretest/posttest, longitudinal, cohort design incorporating electronic health record (EHR) data from one urban tertiary and level 1 trauma center, and one suburban hospital. VTE CDS was embedded into the EHR system. The study included 45,046 admissions; 171,753 patient days; and 110 VTE events. The VTE rate declined from 0.954 per 1,000 patient days to 0.434 comparing baseline to full VTE CDS. Compared to baseline, patients benefitting from VTE CDS were 35% less likely to have a VTE. VTE CDS utilization achieved 78.4% patients assessed within 24 hr from admission, 64.0% patients identified at risk, and 47.7% patients at risk for VTE with an initiated VTE interdisciplinary plan of care. CDS systems with embedded algorithms, alerts, and notification capabilities enable physicians at the point of care to utilize guidelines and make impactful decisions to prevent VTE. This study demonstrates a phased‐in implementation of VTE CDS as an effective approach toward VTE prevention. Implications for future research and quality improvement are discussed as well.

For more information on this article, contact Robert C. Amland at

The authors declare no conflict of interest.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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This study evaluates the impact of implementing a healthcare technology‐driven clinical decision support (CDS) system to prevent venous thromboembolism (VTE) among hospitalized patients.

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Review of the literature

VTE is one of the most frequent multifactorial diseases and manifests clinically by deep vein thrombosis (DVT) and pulmonary embolism (PE). The estimate of the cumulative incidence of diagnosed or fatal VTE is 71 to 171 cases per 100,000 adult population per year (White, 2003). During 2007–2009, an estimated annual average of 547,596 adult hospitalizations with a discharge diagnosis of VTE were recorded in the United States (Centers for Disease Control and Prevention, 2012). The total estimated direct medical cost payment from health plans to providers for inpatient claims submitted with VTE diagnoses ranges from $7,594 to $16,644, depending on VTE being documented as a primary or secondary diagnosis (Spyropoulos & Lin, 2007).

VTE is potentially preventable through proper prophylaxis (Agnelli, Bergqvist, Cohen, Gallus, & Gent, 2005; Bergqvist et al., 2002; Lieberman & Hsu, 2005; Mismetti et al., 2004; Rasmussen et al., 2006). In the last decade, a large number of evidence‐based guidelines have been published to improve the appropriateness of prevention and treatment (Cluzeau, Littlejohns, Grimshaw, Feder, & Moran, 1999; Grilli, Magrini, Penna, Mura, & Liberati, 2000), including the recently published guidelines developed by the American College of Chest Physicians for antithrombotic therapy and prevention of thrombosis (Geerts et al., 2008; Guyatt, Akl, Crowther, Gutterman, & Schuunemann, 2012).

However, a gap exists between treatment recommendations presented in the guidelines and actual treatment. Rothberg et al. reported an evaluation of hospitalized medical patients with a primary diagnosis that made them candidates for VTE prophylaxis (Rothberg, Lahti, Pekow, & Lindenauer, 2010). Only 36% of candidates received prophylaxis by their second day of hospitalization, and rates of prophylaxis varied from 20% in patients with urinary tract infection to 62% for patients with respiratory failure, with other risk factors also influencing the likelihood of receiving prophylaxis. To help close the gap between guideline recommendations and real‐world practice, the Joint Commission includes VTE in their core measures for hospital quality and accreditation, including ordering and delivery of appropriate preventive measures.

Hospitals have implemented a number of initiatives to improve prophylaxis and meet VTE core measures. One such initiative, a CDS system, offers a systematic, standardized application of health‐related knowledge that enables providers to make informed clinical decisions at the point of care. A CDS houses algorithms and scenarios, and analyzes available data to help healthcare providers make clinical decisions, which has been shown can effectively improve patient outcomes. At the enterprise level, a CDS facilitates achievement of performance goals related to patient safety, quality of care, and cost (Osheroff et al., 2007).

To improve compliance with guideline‐appropriate prophylaxis for VTE, a study conducted by Kucher et al. found that a VTE CDS (without computerized provider order entry [CPOE]), which applied an electronic alert with a notification flag that required an acknowledgment by the physician, demonstrated a twofold increase in prophylaxis, from 14.5% to 33.5%, and significantly lowered the VTE rate at 90 days post discharge (e.g., 4.8% intervention vs. 8.2% control group) (Kucher et al., 2005). Bhalla et al. reported that during the 6 months following implementation of CPOE and VTE CDS on medicine services, which also applied a hard stop for prophylaxis, results showed an increase in VTE prophylaxis from 61.9% to 82.1%, and reduced incidence of VTE from 0.65% to 0.42% (Bhalla et al., 2013). Haut et al. reported that CPOE and VTE CDS that applied a mandatory clinical workflow implemented at a level 1 trauma center significantly increased compliance with guideline‐appropriate prophylaxis from 66.2% to 84.4%, and reduced VTE among trauma patients from 1.0% to 0.17% (Haut et al., 2012); moreover, they concluded that utilization of VTE CDS was associated with higher VTE prophylaxis rates versus paper‐based orders among medicine and surgery services (Streiff et al., 2012). This body of evidence suggested that VTE CDS, with CPOE functionality, as well as incorporating some type of mandatory clinical workflow, a required action, or a hard‐stop interruption increased guideline‐appropriate prophylaxis to reach 80% levels and prevent avoidable VTE.

The objective of this study was to evaluate the impact of a computerized VTE CDS implemented broadly across medicine and surgery patient‐care units on reducing incidence of VTE in a large urban teaching hospital system.

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Study Design and Methods

Setting and Intervention

This study was conducted at Truman Medical Center (TMC) in Kansas City, Missouri, which is a 580‐bed two‐hospital nonprofit academic health system. TMC's urban campus is a level 1 trauma center whereas the second campus is a suburban hospital, both with extensive outpatient service capacity. TMC has an electronic health record (EHR) system (Millennium: Cerner Corporation, Kansas City, Missouri), which was rolled out in July 2009. The EHR system was engineered onto a common clinical transaction database platform used by TMC hospitals. In just over 3 years from that EHR rollout, TMC achieved Healthcare Information and Management Systems Society (HIMSS) Analytics Stage 7, which was awarded to them in September 2012 for achieving the highest level of EHR adoption. HIMSS Analytics Stage 7 designates organizations that have a paperless system that supports the sharing and use of patient data that ultimately improve process performance, quality of care, and patient safety.

TMC had a system‐wide VTE prophylaxis policy and risk assessment in place since 2007. However, the only active performance improvement work was focused on all surgical patients to improve the sampled and overall Surgical Care Improvement Project (SCIP) measure cases. By analyzing cases with a surgical procedure code for the encounter, separately from the other cases, TMC wanted to demonstrate the effect of VTE CDS on further improvement over the cases targeted for SCIP, and the effect of the VTE CDS on further improvement for all other cases that the VTE policy might have influenced.

The VTE CDS implemented at TMC included rules, documentation, interdisciplinary plans of care, and a Discern Advisor, which were integrated with nursing and physician workflows. Executable knowledge (i.e., decision support) was based upon guidelines and published evidence for identification of VTE risk, complications, and prevention. At the time of this study, the VTE prevention program was based on the eighth edition (the most currently available) of the American College of Chest Physicians’ Antithrombotic Therapy and Prevention of Thrombosis guidelines (Geerts et al., 2008).

These elements were created to screen at‐risk patients, notify and advise the appropriate clinicians, and monitor for patient‐specific events related to VTE. Physicians were responsible for risk stratification, which included establishing and documenting VTE risk level, documenting contraindications, and receiving an evidence‐based recommendation for prophylactic treatment. A system‐generated flag prompted the physician when the algorithm detected a patient who was either not assessed, or was at increased risk, for VTE. The physician was required to take a subsequent action (i.e., to agree or modify, or knowingly override the alert). Nursing was responsible for initiating the VTE interdisciplinary plan of care (IPOC) among patients at risk for VTE. The VTE IPOC included orders, interventions, documentation, and outcomes designed together to help direct patient care. Other patient‐centered responsibilities included medication administration; monitoring for signs of potential VTE, side effects, and contraindications from prophylactic treatment; activity progression; and patient education.

In July 2009, TMC rolled out their EHR system followed by VTE CDS in early 2010. The VTE CDS implementation occurred over three distinct phases: (A) nursing‐driven workflow with the program's Discern Advisor (i.e., a proprietary CDS application); (B) CPOE with providers conducting risk screening and prophylaxis ordering via the Discern Advisor; and (C) additional flags in the system during the order entry process to alert the physician that the patient's risk level has not been assessed.

VTE CDS began with the go‐live of VTE nursing content in March 2010. In late August 2010, CPOE and VTE Advisor were implemented. By tracking physician adoption of the VTE Advisor for several months, data suggested substantial underutilization. Thus, a VTE Advisor Alert and Notification Flag was developed and implemented in May 2011. Essentially, TMC was in their first year of experiencing an EHR system when the new VTE CDS was being implemented enterprise‐wide. Moreover, the VTE CDS included their first physician‐driven clinical informatics solution integrated into the EHR system; hence, real‐time digital CDS functionality for physicians at the point of care was new to them too.

A reporting system with an ad hoc query tool was used to extract and transform EHR transaction detail‐level data into analytic‐ready encounter‐level datasets. Once validated via clinical review and statistical processes, data were calculated into established metrics and disseminated broadly in management monthly trend reports. These review cycles typically occurred on a quarterly basis with project stakeholders.

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Data Collection

This study used a pretest/posttest, longitudinal, cohort design to evaluate the impact of VTE CDS on incidence of hospital‐acquired VTE (HA‐VTE) among adult inpatients, age 18 years and older. Since the VTE CDS was implemented in three phases, we established independent patient cohorts to represent each phase. The study design, therefore, was depicted as OXOXOXOO (Cook & Campbell, 1979) encompassing a baseline observation; three implementations, each followed by an observation; and a study endpoint observation to identify longer‐term impact or sustainability of outcomes. Within each of the five observation windows, patients were grouped into a respective cohort, based on their date of admission (i.e., admission cohorts). The observation window spanned 6 months for each cohort. The study period included 33 months of patient admissions from September 1, 2009 to May 31, 2012.

EHR data were collected on inpatients. The baseline data were collected retrospectively looking back 6 months (September 2009 through February 2010) prior to implementation go‐live. Data were then prospectively collected each month over the ensuing 27 months (March 2010 through May 2012) following implementation. Five admission cohorts were established commensurate with phases of implementation: Baseline (September 1, 2009 to February 28, 2010); VTE nursing content (March 1, 2010 to August 31, 2010); CPOE and VTE Advisor (September 1, 2010 to February 28, 2011); VTE Advisor Alert and Notification Flag (June 1, 2011 to November 30, 2011); and Study Endpoint (December 1, 2011 to May 31, 2012).

Adult patients, 18 years of age and older, suspected of having a VTE (i.e., DVT or PE) were identified if they received either a venous Doppler ultrasound of the upper or lower extremities or a Computed Tomographic Pulmonary Angiogram. Key clinical documents including the admitting history and physical, daily progress notes, radiology imaging study results, and the discharge summary were reviewed by an investigator to determine whether the identified clot(s) was considered an ongoing chronic condition or an acute new event complication. Confirmed positive VTEs were coded as present on admission (POA‐VTE) if the order for the imaging study was placed within 24 hr from when the patient either arrived at the emergency department or was directly admitted. For inclusion into the study, an HA‐VTE event was defined as (1) HA‐VTE, if the positive DVT or PE was acquired after 24 hr from emergency department arrival or hospitalization, or (2) a readmission encounter with POA‐VTE within 30 days of a previous hospitalization—clean discharge (i.e., absence of any clinically documented VTE condition or complication on that prior hospitalization encounter).

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Measures and Analysis

Data were reported as descriptive and inferential statistics appropriate for the type of data and research question. Reported results included frequencies, proportions, means, standard deviation, medians, interquartile range, and odds ratios with confidence intervals. All analyses were conducted using Statistica software (version 8.0; StatSoft, Inc., Tulsa, OK). Three rate‐based output metrics were reported for each admission cohort: percentage of patients who received a VTE risk assessment within 24 hr from admission, percentage of patients identified at risk for VTE, and the percentage of patients at risk for VTE with an initiated VTE IPOC. The primary outcome measure was defined as “VTE per 1,000 patient days” (refer to equation above). A secondary outcome metric was defined as “percentage of patients with a VTE event.” Both primary and secondary VTE rates were calculated at baseline and for each of the four subsequent admission cohorts. The longer‐term (5 year) future impact of the VTE prevention program was estimated by comparing the primary outcome “VTE per 1,000 patient days” at baseline and study endpoint, applied to total patient days from year 2011. This annualized impact was multiplied by 5 years, extending beyond the study endpoint.

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Institutional Review Board Approval

This quality improvement evaluation was reviewed and categorized as not requiring approval by the University of Missouri, Kansas City Adult Health Sciences Institutional Review Board.

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Patient Characteristics

During the course of the study, 45,046 hospitalizations representing 171,753 patient days were identified (refer to Table 1). The mean age for patients was 45.1 years, and just over half of all patients were White/Other (55.8%) and female (58.6%). By service, medicine patients encompassed 55% of all patients, with obstetrics and gynecology representing 27%, and surgery encompassing an additional 12% of all patients. Overall, 110 patients experienced a VTE event; 67 patients had new onset acute complication (HA‐VTE) and 43 patients had a POA‐VTE within 30 days of a prior hospitalization.

Table 1

Table 1

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VTE CDS Utilization

Three output metrics measured adoption of VTE CDS. Figure 1 illustrates the increase in utilization of VTE CDS (right axis) among physicians and nurses. For this cohort analysis, data were grouped data into 6‐month buckets discussed in the Methods–Data Collection section. Because no measurable utilization of VTE CDS occurred as a result of implementing just VTE nursing content (A), the cohort analysis began with CPOE and VTE Advisor (B). Comparing cohort CPOE and VTE Advisor (B) to the immediate subsequent cohort who experienced the fully implemented VTE CDS (i.e., VTE Advisor Alert and Notification Flag [C]), results indicated that “percentage of patients assessed within 24 hr from admission” increased from 49.7% to 78.4%, “percentage of patients at risk for VTE” increased from 42.8% to 64.0%, and “percentage of patients at risk for VTE with an initiated VTE IPOC” increased from 25.4% to 47.7%.

Relationship Between VTE CDS Utilization and VTE Outcomes

Relationship Between VTE CDS Utilization and VTE Outcomes

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VTE Events

Figure 1 also illustrates the trend on the primary outcome measure VTE per 1,000 patient days (left axis). The cohort analysis similarly grouped data into 6‐month buckets discussed in the Methods–Data Collection section. The baseline VTE rate was 0.954 per 1,000 patient days (refer to Table 2). Subsequently, the VTE rate decreased by 23% to 0.734 VTE per 1,000 patient days for VTE nursing content (A); the VTE rate remained generally flat at 0.790 for CPOE and VTE Advisor (B). Not until the VTE Advisor Alert and Notification Flag (C) did the VTE rate drop by 55% from the baseline to a rate of 0.434 VTE per 1,000 patient days. This VTE rate was sustained, represented by a rate of 0.407 at Study Endpoint.

Table 2

Table 2

Analysis of the secondary outcome measure comparing baseline to full implementation of VTE CDS (i.e., VTE Advisor Alert and Notification Flag [C]), revealed the percentage of patients with a VTE event reduced from 0.36% to 0.17% (OR = 0.65, 0.49–0.87, p = .0039). Patients experiencing the full VTE CDS (i.e., VTE Advisor Alert and Notification Flag [C]) were 35% less likely to have a VTE than patients at baseline (i.e., 100 × (0.65–1) = 35%). This effect was sustained at Study Endpoint (OR = 0.71, 0.55–0.93, p = .014). In contrast, the percentage of patients with a VTE event did not change significantly between baseline and VTE nursing content (A), nor between baseline and CPOE and VTE Advisor (B); 0.36% versus 0.27% (OR = 0.75, 0.44–1.27, p = .28) and 0.36% versus 0.31% (OR = 0.86, 0.50–1.46, p = .58), respectively.

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Several factors influence clinicians’ adherence to guideline‐recommended VTE prophylaxis in real‐world practice (Yu, Dylan, Lin, & Dubois, 2007). Barriers to compliance with guidelines include the inadequate availability of guideline‐based evidence for providers at the point of care (Buchman et al., 2006). Technology that assists providers at the point of care in making treatment decisions and closing the gap between guideline‐driven recommended care and actual care can result in reduced VTE. Different strategies incorporating electronic alerts have been implemented in hospital settings to prevent VTE, with mixed results.

Piazza et al. reported that an alert from a hospital staff member to the attending physician increased VTE prophylaxis use (e.g., 46.0% alerted physicians vs. 20.6% not‐alerted physicians), but the difference in VTE rates was not significant (e.g., 2.7% intervention vs. 3.4% control group) (Piazza et al., 2009). Fiumara et al. reported that a serial multiscreen electronic alert provided additional educational information to physicians, which improved prophylaxis orders for 58.4% of patients whose physicians had previously declined prophylaxis at the initial screen alert; but no difference was observed in the 90‐day VTE rate (e.g., 2.2% three‐screen vs. 2.8% one‐screen group) (Fiumara et al., 2010). Mitchell et al. reported that when a simple electronic reminder was added to admission notes, appropriate prophylaxis improved from 42.8% before implementation to 60.0% after the reminder was added, but they concluded that 60% appropriate prophylaxis rate was unacceptably low, even though the electronic reminder was associated with fewer patients diagnosed with VTE (e.g., 0.34% intervention vs. 1.1% control group) (Mitchell, Collen, Petteys, & Holley, 2012). Lecumberri et al. concluded that the implementation of a computer‐generated alert program helped physicians to assess each patient's thrombotic risk, leading to a better use of thromboprophylaxis, and a 46% relative reduction in VTE among hospitalized patients although the overall risk for VTE was unchanged from baseline (OR = 0.51, 0.24–1.05) (Lecumberri et al., 2008). In stark contrast, two studies that evaluated the effectiveness of VTE CDS with CPOE functionality, and had some form of mandatory workflow or other system requirements, led to an increased guideline‐appropriate VTE prophylaxis (e.g., 80% levels) and improved VTE outcomes (Bhalla et al., 2013; Haut et al., 2012). Results from our study expand this body of research evidence, and contribute new information on the impact of implementing a computerized VTE prevention program.

The EHR system was relatively new at TMC (i.e., first year of roll out), when the VTE CDS was implemented enterprise‐wide across the two hospitals. Utilization of the VTE CDS remained generally flat until an interruptive flag was implemented in the physician workflow, requiring physician attention and action. Thereafter, we found adoption and utilization of VTE CDS increased significantly: 50% versus 78% patients being assessed within 24 hr from admission, 43% versus 64% of patients identified at risk for VTE, and 25% versus 48% patients at risk for VTE with an initiated VTE IPOC. Furthermore, the VTE CDS risk stratification effectively screened in patients at risk for VTE (e.g., CPOE and VTE Advisor “unassigned risk” subgroup who accounted for 9 of 25 VTE versus a combined VTE Advisor Alert and Notification Flag and Study Endpoint “unassigned risk” subgroup who accounted for only 2 of 25 VTE). The early lag in VTE CDS utilization may be due to a time‐varying factor in that physicians began to align treatment more closely with guideline recommendations once they were familiar with CPOE and VTE CDS. But, results point to interruptive technology (i.e., VTE Advisor Alert and Notification Flag), to get the ball rolling in risk assessment and VTE prevention; it was annoying, but worked as intended.

Overall, the impact of VTE CDS improved over time. Our VTE prevention program resulted in a 55% relative risk reduction in VTE events, reflective of a primary outcome of 0.434 VTE per 1,000 patient days, or 0.17%, among patient cohort VTE Advisor Alert and Notification Flag. Compared to baseline, these patients were 35% less likely to acquire a VTE; this effect was sustained at the Study Endpoint.

In the ensuing 27 months following adoption of VTE CDS, estimates suggested 48 VTE incidents were avoided and represented 32 fewer incidents of DVT, 16 fewer PE, 3 fewer patient deaths, and 800 patient days eliminated. This impact was based on one‐in‐three DVT progressing to PE, and one‐in‐five PE resulting in death within a year (White, 2003). In the next 5 years, we can expect to prevent 166 VTE incidents (i.e., ((0.407 – 0.954) × (60,564 days/1,000) × 5 years) = −166 VTE). thereby avoiding 111 DVT, 55 PE, and 11 deaths; and eliminating 2,761 patient days.

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Although this was an evaluation within a single healthcare system made of an urban campus and level 1 trauma center, and a suburban hospital, standardized definitions of VTE were developed and defined prior to assessment, making results more generalizable across healthcare systems. The diagnosis of VTE was based on both clinical assessment and radiology impressions. Some diagnoses can be difficult to rule in—or out—because not all patients present with classic symptoms. Thus, some subjectivity could affect misclassification of VTE cases. Redundant efforts were taken for case review; any misclassification of cases was likely to affect baseline and adoption cohorts equally. Although development of the baseline used a retrospective methodology, and a parallel control group was not incorporated into the study design, the implementation and ongoing trending did apply a rigorous prospective cohort model across multiple, independent observation periods. A suite of components was implemented, so it is difficult to determine which of the individual components had the greatest impact. However, trends continued to improve, suggesting that the components of the program in combination were beneficial.

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Directions for Future Research

Potential areas of future research include a focus on identifying key factors that increase utilization and/or accelerate adoption of VTE CDS, and the initiation of interdisciplinary plans of care, especially on behalf of patients at risk for VTE. We found that nearly 80% patients were assessed for risk within 24 hr from admission, and that two‐thirds of patients either are, or become, at risk for VTE during their hospitalization. This situation can outpace the downstream nurse responsibility to initiate the VTE IPOC. Moreover, we would like to understand the commensurate cost reduction to the healthcare system overall, associated with VTE prevention, including the ambulatory side for integrated health systems. Furthermore, although VTE CDS helps patients avoid unnecessary complications while they are hospitalized, unfortunate patients stricken with VTE do experience loss of productivity because of the illness, or burden of VTE, and have increased risk of chronic conditions from VTE. After all, reducing VTE does not just affect the acute inpatient side, and further research would add depth to our understanding of transition care, the care continuum, and patient health and wellness.

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Implications for Practice

CDS systems with embedded algorithms, alerts, and notification capabilities enable physicians at the point of care to utilize guidelines and make impactful decisions to prevent VTE. Our study focused on electronic alerts, nursing and physician workflows, and prophylaxis ordering. We gained insights into how an interruptive flag when applied to the physician workflow, although annoying to physicians, increased their utilization of VTE CDS. The relationship between VTE CDS and VTE outcomes illustrates that hospitals can save lives, reduce complications, and lower costs by adopting VTE CDS enterprise‐wide across differing hospital settings, even if an EHR system is relatively new. This study demonstrated a phased‐in implementation of VTE CDS as an effective approach toward VTE prevention.

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Authors' Biographies

Robert C. Amland, PhD, MPA, MSSM, is a solution strategist in Cerner's Population Health organization located in Kansas City, Missouri. Dr. Amland was the co‐principal investigator of this study. His responsibilities included establishing the evaluation research design and methodology, collecting data and obtaining agreement on clinical diagnoses, ensuring integrity of clinical data and study results.

Bonnie B. Dean, MPH, PhD, is a director and principal investigator for Cerner Research located in Kansas City, Missouri. As a principal investigator, she is responsible for observational and health outcomes research including the development and implementation of surveys and assessment instruments, burden‐of‐illness studies, program evaluation, and data analyses from primary data collection as well as large patient databases.

Hsing‐Ting Yu, MPH, is a scientist of Cerner Research located in Culver City, California. As a researcher, she is responsible for observational and health outcomes research focusing on data analyses using primary data sources as well as national patient databases such as claims or electronic medical record data. Other types of research include systematic review and health economic modeling.

Hugh Ryan, MD, FACEP, is Director and Chief Medical Officer for Cerner Lighthouse, having responsibility for establishing design strategy and architecting condition‐focused performance improvement programs. In this capacity, Dr. Ryan contributes to the development of solutions that address problems ranging from readmission prevention to sepsis recognition and treatment. Dr. Ryan is also an attending physician and Adjuvant Chief Medical Informatics Officer for North Kansas City Hospital.

Timothy Orsund, MBA, is an Engagement Leader in Cerner's Population Health—Strategic Performance Consulting organization located in Kansas City, Missouri. As a strategic advisor to his clients, Mr. Orsund is responsible for project delivery, postimplementation adoption, and value achievement.

Jeffrey L. Hackman, MD, is the Chief Medical Information Officer for Truman Medical Centers in Kansas City, Missouri, serving as the liaison between the clinicians and Information Technology. His focus is on improving patient safety and quality of care through the use of electronic medical records.

Shauna R. Roberts, MD, is the Medical Director of Quality for Truman Medical Centers. Her focus is on measuring patient care impact through organizational system development and change efforts.


computerized clinical decision support (CDS); electronic health record (EHR); hospital‐acquired VTE; patient safety and prevention venous thromboembolism (VTE)

© 2015 National Association for Healthcare Quality