A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success

Vascular surgeons are positioned to fight healthcare disparities

Comprehensively managing vascular disease in the United States can seem overwhelming. Vascular surgery providers encounter daily stress-inducing challenges, including caring for sick patients who often, because of healthcare barriers, struggle with access to care, socioeconomic challenges, and a complex medical system. These individuals can present with advanced disease and comorbidities, and many have limited treatment options. Subsequently, it could seem as if the vascular surgeon's efforts have little opportunity to make a difference. This review describes a method to counter this sentiment through directed action, hope, and community building. Vascular surgeons are passionate about what they do and are built to fight healthcare disparities. This review also outlines the reasoning for attempting to create change and one approach to begin making a difference.

Exploring medication safety structures and processes in nursing homes: a cross-sectional study

BACKGROUND

Medication safety is important to limit adverse events for nursing home residents. Several factors, such as interprofessional collaboration with pharmacists and medication reviews, have been shown in the literature to influence medication safety processes.

AIM

This study had three main objectives: (1) To assess how facility- and unit-level organization and infrastructure are related to medication use processes; (2) To determine the extent of medication safety-relevant processes; and (3) To explore pharmacies' and pharmacists' involvement in nursing homes' medication-related processes.

METHOD

Cross-sectional multicenter survey data (2018-2019) from a convenience sample of 118 Swiss nursing homes were used. Data were collected on facility and unit characteristics, pharmacy services, as well as medication safety-related structures and processes. Descriptive statistics were used.

RESULTS

Most of the participating nursing homes (93.2%) had electronic resident health record systems that supported medication safety in various ways (e.g., medication lists, interaction checks). Electronic data exchanges with outside partners such as pharmacies or physicians were available for fewer than half (10.2-46.3%, depending on the partner). Pharmacists collaborating with nursing homes were mainly involved in logistical support. Medication reviews were reportedly conducted regularly in two-thirds of facilities.

CONCLUSION

A high proportion of Swiss nursing homes have implemented diverse processes and structures that support medication use and safety for residents; however, their collaboration with pharmacists remains relatively limited.

Barriers and facilitators to implementing a nursing clinical decision support system in a tertiary hospital setting: A qualitative study using the FITT framework

OBJECTIVE

Clinical decision support systems (CDSSs) have been increasingly introduced to health care settings; however, their adoption is far from ideal. Guided by the FITT framework, this study aims to explore barriers and facilitators to the implementation of a CDSS from the perspective of nurses.

METHODS

A qualitative study with 200 h of participatory observation and 21 semi structured interviews was conducted from February to August 2021 in four medical-surgical wards in a 2000-bed tertiary hospital in Shanghai, China. The field notes were typed and the audio-recorded interviews were transcribed to texts verbatim and were coded with a four-step approach. We used the FITT framework to interpret our findings based on the technology, individual and task attributes and the fit between them.

RESULTS

A total of twelve categories were identified, which were integrated into two themes: barriers and facilitators to system implementation. All categories but one can be mapped to the three attributes of the FITT framework: technology, individual and task. We assumed that management has a vital role to play in the following areas: addressing user resistance, improving system usability, setting standards on practice and, finally, building connectivity between nurses and the technical staff to improve the fit between the technology, individual and task attribute and thus promote system implementation.

CONCLUSION

Barriers and facilitators to CDSS implementation include system-related, user-related and organizational factors which can largely be fit io the FITT framework. There is potential to extend the FITT framework to represent management intervention on inter-disciplinary collaboration. Future empirical studies on facilitating strategies from the management to improve user experience and willingness of CDSS adoption are needed.

Applying requisite imagination to safeguard electronic health record transitions

Over the next decade, many health care organizations (HCOs) will transition from one electronic health record (EHR) to another; some forced by hospital acquisition and others by choice in search of better EHRs. Herein, we apply principles of Requisite Imagination, or the ability to imagine key aspects of the future one is planning, to offer 6 recommendations on how to proactively safeguard these transitions. First, HCOs should implement a proactive leadership structure that values communication. Second, HCOs should implement proactive risk assessment and testing processes. Third, HCOs should anticipate and reduce unwarranted variation in their EHR and clinical processes. Fourth, HCOs should establish a culture of conscious inquiry with routine system monitoring. Fifth, HCOs should foresee and reduce information access problems. Sixth, HCOs should support their workforce through difficult EHR transitions. Proactive approaches using Requisite Imagination principles outlined here can help ensure safe, effective, and economically sound EHR transitions.

Immunization calculation engine: An open source immunization evaluation and forecasting system

INTRODUCTION

The immunization calculation engine (ICE) is a free, open-source immunization forecasting evaluation and software system whose default immunization schedule supports all routine childhood, adolescent, and adult immunizations based on the recommendations of the Advisory Committee on Immunization Practices (ACIP). ICE utilizes its immunization rules and patient data to evaluate and return the validity of each immunization in the patient's history along with one or more evaluation reasons. It also returns a recommendation for each vaccine group along with one or more recommendation reasons.

METHODS

In January 2020, ICE was first released as a Docker image along with the traditional zip archive file which had been used up to that point. Docker enables software providers to easily distribute their software so that it can be run "out of the box" in the user's local environment. Software running in Docker containers drastically reduces the complexity of software distribution and set up.

RESULTS

Clinical systems of many types use ICE. The project began within the public health arena as a feature of Immunization Information Systems (IIS), but electronic health records (EHR) and personal health records (PHR) have also deployed ICE. While it is not possible to identify the specific impact of ICE on clinical care without additional research, it should be pointed out that once deployed within an IIS, EHR, or PHR the display of ICE results is performed for every patient viewed by a user and often for every patient appearing on a report. In a typical month, thousands if not millions of evaluations and forecasts are performed by ICE and displayed to the users.

CONCLUSIONS

The ICE Project believes in minimizing the barriers to installing and using ICE anywhere. To that end, there is no registration required to download the source code or runtime code for the ICE service and its default rule. Similarly, the Project created a Docker image of ICE to facilitate easy and seamless implementation.

Safe use of the EHR by medical scribes: a qualitative study

OBJECTIVE

Hiring medical scribes to document in the electronic health record (EHR) on behalf of providers could pose patient safety risks because scribes often have no clinical training. The aim of this study was to investigate the effect of scribes on patient safety. This included identification of best practices to assure that scribe use of the EHR is not a patient safety risk.

MATERIALS AND METHODS

Using a sociotechnical framework and the Rapid Assessment Process, we conducted ethnographic data gathering at 5 purposively selected sites. Data were analyzed using a grounded inductive/hermeneutic approach.

RESULTS

We conducted site visits at 12 clinics and emergency departments within 5 organizations in the US between 2017 and 2019. We did 76 interviews with 81 people and spent 80 person-hours observing scribes working with providers. Interviewees believe and observations indicate that scribes decrease patient safety risks. Analysis of the data yielded 12 themes within a 4-dimension sociotechnical framework. Results about the "technical" dimension indicated that the EHR is not considered overly problematic by either scribes or providers. The "environmental" dimension included the changing scribe industry and need for standards. Within the "personal" dimension, themes included the need for provider diligence and training when using scribes. Finally, the "organizational" dimension highlighted the positive effect scribes have on documentation efficiency, quality, and safety.

CONCLUSION

Participants perceived risks related to the EHR can be less with scribes. If healthcare organizations and scribe companies follow best practices and if providers as well as scribes receive training, safety can actually improve.

Clinical Decision Support for Worker Health: A Five-Site Qualitative Needs Assessment in Primary Care Settings

BACKGROUND

Although patients who work and have related health issues are usually first seen in primary care, providers in these settings do not routinely ask questions about work. Guidelines to help manage such patients are rarely used in primary care. Electronic health record (EHR) systems with worker health clinical decision support (CDS) tools have potential for assisting these practices.

OBJECTIVE

This study aimed to identify the need for, and barriers and facilitators related to, implementation of CDS tools for the clinical management of working patients in a variety of primary care settings.

METHODS

We used a qualitative design that included analysis of interview transcripts and observational field notes from 10 clinics in five organizations.

RESULTS

We interviewed 83 providers, staff members, managers, informatics and information technology experts, and leaders and spent 35 hours observing. We identified eight themes in four categories related to CDS for worker health (operational issues, usefulness of proposed CDS, effort and time-related issues, and topic-specific issues). These categories were classified as facilitators or barriers to the use of the CDS tools. Facilitators related to operational issues include current technical feasibility and new work patterns associated with the coordinated care model. Facilitators concerning usefulness include users' need for awareness and evidence-based tools, appropriateness of the proposed CDS for their patients, and the benefits of population health data. Barriers that are effort-related include additional time this proposed CDS might take, and other pressing organizational priorities. Barriers that are topic-specific include sensitive issues related to health and work and the complexities of information about work.

CONCLUSION

We discovered several themes not previously described that can guide future CDS development: technical feasibility of the proposed CDS within commercial EHRs, the sensitive nature of some CDS content, and the need to assist the entire health care team in managing worker health.

The Impact of an Intraoperative Clinical Decision Support Tool to Optimize Perioperative Glycemic Management

With the transition from Vanderbilt's Perioperative Information Management System (VPIMS) to Epic's Best Practice Advisory (BPA) framework, a replacement intraoperative glucose clinical decision support (CDS) system was designed. We examined changes in the frequency of intraoperative glucose monitoring, hyper- and hypoglycemia rates in the post-anesthesia care unit (PACU), to determine the impact of the changes on glucose management. Data were collected into three phases: 1) VPIMS CDS, 2) No CDS, and 3) BPA CDS. One-way ANOVA was conducted to test the significance of changes in the frequency of glucose monitoring and abnormal glucose across phases. Interrupted time series segmented analysis was performed to assess the autocorrelation and trend over times. A total of 3706 cases were analyzed. The monitoring rate fell from 84.5% in VPIMS CDS to 67.6% in No CDS (p < .001) and increased to 83.1% in BPA CDS (p < .001). The PACU hyperglycemia rate increased from VPIMS CDS to No CDS (5.2% to 10.4%, p < .001) and decreased from No CDS to BPA CDS (10.4% to 7.2%, p = 0.031). The segmented analysis demonstrated immediate changes in the intraoperative monitoring frequency (p < .001) and postoperative hyperglycemia rate (p = 0.002) with the replacement of CDS. The temporary removal of CDS was associated with a significant reduction in intraoperative glucose monitoring and increased hyperglycemia in the PACU. Implementation of the BPA CDS led to a significant improvement in the intraoperative glucose monitoring and glucose management in the PACU.

How can we partner with electronic health record vendors on the complex journey to safer health care?

The Office of the National Coordinator for Health Information Technology released the Safety Assurance Factors for EHR Resilience (SAFER) guides in 2014. Our group developed these guides covering key facets of both electronic health record (EHR) infrastructure (eg, system configuration, contingency planning for downtime, and system-to-system interfaces) and clinical processes (eg, computer-based provider order entry with clinical decision support, test result reporting, patient identification, and clinician-to-clinician communication). The SAFER guides encourage healthy relationships between EHR vendors and users. We conducted a qualitative study over 12 months. We visited 9 health care organizations ranging in size from 1-doctor outpatient clinics to large, multisite, multihospital integrated delivery networks. We interviewed and observed clinicians, IT professionals, and administrators. From the interview transcripts and observation field notes, we identified overarching themes: technical functionality, usability, standards, testing, workflow processes, personnel to support implementation and use, infrastructure, and clinical content. In addition, we identified health care organization-EHR vendor working relationships: marine drill sergeant, mentor, development partner, seller, and parasite. We encourage health care organizations and EHR vendors to develop healthy working relationships to help address the tasks required to design, develop, implement, and maintain EHRs required to achieve safer and higher quality health care.

Digitizing Infectious Disease Clinical Guidelines for Improved Clinician Satisfaction

The purpose of this project was to implement an improved rapid-deployment clinical decision support strategy for the detection and treatment of emerging and reemerging infectious diseases within an electronic health record informed by end-user satisfaction. After a review of the evidence and comprehensive workflow assessments, interdisciplinary focus groups were assembled to determine current infectious disease needs within the electronic health record and what guidance should be provided to clinicians to assist in making the best decisions for both patient care and population health. Education and reeducation issues were handled throughout the implementation process. Using the Plan-Do-Study-Act quality improvement framework for rapid cycle deployment, the design was implemented and monitored. To evaluate efficacy and clinician satisfaction of the implementation, presurvey and postsurvey measurements were employed. The Clinical Information System Implementation Evaluation Scale was used, along with demographic and qualitative textual questions, to evaluate clinician satisfaction. Findings indicate the implementation was successful (P < .05).

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data

IMPORTANCE

Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged.

OBJECTIVE

To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018.

MAIN OUTCOMES AND MEASURES

Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved.

RESULTS

Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results.

CONCLUSIONS AND RELEVANCE

This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.

Availability and usage of clinical decision support systems (CDSSs) in office-based primary care settings in the USA

BACKGROUND

A clinical decision support system (CDSS) covers a broad spectrum of applications, for example, screening reminders, can reduce malpractice, improve preventive services and enable better management of chronic conditions. CDSSs have traditionally been used successfully in large hospitals. The availability (ie, whether the function is provided by the software) and usage (ie, actual use) of a CDSS in office-based primary care settings, however, are less well studied.

OBJECTIVE

To establish a benchmark of CDSS availability and usage in office-based primary care settings, particularly given the large volume of visits in such settings.

METHODS

We used the 2015 Centers for Disease Control and Prevention's National Ambulatory Medical Care Survey to conduct secondary data analysis. We selected preventive services reminders and drug interaction alerts, along with several other variables as examples of a CDSS.

RESULTS

CDSS usage rates ranged from 68.5% to 100% among solo or non-solo primary care practices owned by physicians or physician groups that have electronic medical records (EMRs)/electronic health records (EHRs) and 44.7% to 96.1%, regardless of EMR/EHR status. According to proportion tests, solo practices had significantly lower CDSS usage and availability rates on several measures if the practice is entirely EMR/EHR based and significantly lower (16.3%-28.9%) CDSS usage rates than did non-solo practices on each measure, regardless of EMR/EHR status.

CONCLUSION

In the USA, a CDSS, especially under the categories of basic preventive reminders and drug interaction alerts, is used routinely between 68% and 100% in primary care if a practice is entirely EMR/EHR based. More work is needed, however, to determine the reasons for large usage gaps between solo and non-solo practices and to reduce such gaps.

Challenges with Patient Adoption of Automated Integration of Blood Glucose Meter Data in the Electronic Health Record

Providers often encourage patients with type 1 diabetes (T1D) to contact them with blood glucose (BG) values between visits. However, patients and families find it cumbersome to share their BG values with clinical providers, creating a barrier to communication. Although many phone applications exist to help patients track BG values, most do not integrate with the electronic health record (EHR). Recent advances in technology can integrate the glucose meter (GM) data into the EHR. This pilot and feasibility study aimed to understand how an automated integration system of GM data into the EHR and remote monitoring by health care providers would impact patient-provider communication. Patients or parents of patients with T1D (n = 32, average hemoglobin A1c [HgbA1c]: 8.5%, SD: 1.7, average age: 13.9 years, SD: 3.8) who owned an Apple iPod^® or iPhone^® (5s or higher) participated, and their number of contacts through telephone calls or MyChart™ messages between clinic visits was recorded during each of the three phases: run-in, intervention, and learned. Twenty-eight families completed all phases, and despite guided review of BG trends and automated integration of BG values, the number of patient-initiated calls (P = 0.23) and HgbA1c values (P = 0.08) did not improve, nor was there a clinically significant change in the number of BG checks per day. Barriers to adoption and effectiveness of this technology exist, and patient motivation is still needed.

Essential activities for electronic health record safety: A qualitative study

Electronic health record-caused safety risks are an unintended consequence of the implementation of clinical systems. To identify activities essential to assuring that the electronic health record is managed and used safely, we used the Rapid Assessment Process, a collection of qualitative methods. A multidisciplinary team conducted visits to five healthcare sites to learn about best practices. Although titles and roles were very different across sites, certain tasks considered necessary by our subjects were remarkably similar. We identified 10 groups of activities/tasks in three major areas. Area A, decision-making activities, included overseeing, planning, and reviewing to assure electronic health record safety. Area B, organizational learning activities, involved monitoring, testing, analyzing, and reporting. Finally, Area C, user-related activities, included training, communication, and building clinical decision support. To minimize electronic health record-related patient safety risks, leaders in healthcare organizations should ensure that these essential activities are performed.

Adaptive design of a clinical decision support tool: What the impact on utilization rates means for future CDS research

OBJECTIVE

We employed an agile, user-centered approach to the design of a clinical decision support tool in our prior integrated clinical prediction rule study, which achieved high adoption rates. To understand if applying this user-centered process to adapt clinical decision support tools is effective in improving the use of clinical prediction rules, we examined utilization rates of a clinical decision support tool adapted from the original integrated clinical prediction rule study tool to determine if applying this user-centered process to design yields enhanced utilization rates similar to the integrated clinical prediction rule study.

MATERIALS & METHODS: We conducted pre-deployment usability testing and semi-structured group interviews at 6 months post-deployment with 75 providers at 14 intervention clinics across the two sites to collect user feedback. Qualitative data analysis is bifurcated into immediate and delayed stages; we reported on immediate-stage findings from real-time field notes used to generate a set of rapid, pragmatic recommendations for iterative refinement. Monthly utilization rates were calculated and examined over 12 months.

RESULTS

We hypothesized a well-validated, user-centered clinical decision support tool would lead to relatively high adoption rates. Then 6 months post-deployment, integrated clinical prediction rule study tool utilization rates were substantially lower than anticipated based on the original integrated clinical prediction rule study trial (68%) at 17% (Health System A) and 5% (Health System B). User feedback at 6 months resulted in recommendations for tool refinement, which were incorporated when possible into tool design; however, utilization rates at 12 months post-deployment remained low at 14% and 4% respectively.

DISCUSSION

Although valuable, findings demonstrate the limitations of a user-centered approach given the complexity of clinical decision support.

CONCLUSION

Strategies for addressing persistent external factors impacting clinical decision support adoption should be considered in addition to the user-centered design and implementation of clinical decision support.

The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background

Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed.

Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully.

Methods

We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist.

Results

We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy.

Conclusions

The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed.

Electronic supplementary material

The online version of this article (10.1186/s13012-018-0772-3) contains supplementary material, which is available to authorized users.

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy

Objective

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions.

Materials and Methods

We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions.

Results

We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common.

Discussion

Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS.

Conclusion

CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

The Value of Monitoring Clinical Decision Support Interventions

BACKGROUND

Well-functioning clinical decision support (CDS) can facilitate provider workflow, improve patient care, promote better outcomes, and reduce costs. However, poorly functioning CDS may lead to alert fatigue, cause providers to ignore important CDS interventions, and increase provider dissatisfaction.

OBJECTIVE

The purpose of this article is to describe one institution's experience in implementing a program to create and maintain properly functioning CDS by systematically monitoring CDS firing rates and patterns.

METHODS

Four types of CDS monitoring activities were implemented as part of the CDS lifecycle. One type of monitoring occurs prior to releasing active CDS, while the other types occur at different points after CDS activation.

RESULTS

Two hundred and forty-eight CDS interventions were monitored over a 2-year period. The rate of detecting a malfunction or significant opportunity for improvement was 37% during preactivation and 18% during immediate postactivation monitoring. Monitoring also informed the process of responding to user feedback about alerts. Finally, an automated alert detection tool identified 128 instances of alert pattern change over the same period. A subset of cases was evaluated by knowledge engineers to identify true and false positives, the results of which were used to optimize the tool's pattern detection algorithms.

CONCLUSION

CDS monitoring can identify malfunctions and/or significant improvement opportunities even after careful design and robust testing. CDS monitoring provides information when responding to user feedback. Ongoing, continuous, and automated monitoring can detect malfunctions in real time, before users report problems. Therefore, CDS monitoring should be part of any systematic program of implementing and maintaining CDS.

Rapid Adjustment of Clinical Decision Support in Response to Updated Recommendations for Palivizumab Eligibility

Background: Palivizumab is effective at reducing hospitalizations due to respiratory syncytial virus among high-risk children, but is indicated for a small population. Identification of patients eligible to receive palivizumab is labor-intensive and error-prone. To support patient identification we developed Clinical Decision Support (CDS) based on published recommendations in 2012. This CDS was developed using a systematic process, which directly linked computer code to a recommendation’s narrative text. In 2014, updated recommendations were published, which changed several key criteria used to determine eligible patients.

Objective: Assess the effort required to update CDS in response to new palivizumab recommendations and identify factors that impacted these efforts.

Methods: We reviewed the updated American Academy of Pediatrics (AAP) policy statement from Aug 2014 and identified areas of divergence from the prior publication. We modified the CDS to account for each difference. We recorded time spent on each activity to approximate the total effort required to update the CDS.

Results: Of the 15 recommendations in the initial policy statement, 7 required updating. The CDS update was completed in 11 person-hours. Comparison of old and new recommendations was facilitated by the AAP policy statement structure and required 3 hours. Validation of the revised logic required 2 hours by a clinical domain expert. An informaticist required 3 hours to update and test the CDS. This included adding 24 lines and deleting 37 lines of code. Updating relevant data queries took an additional 3 hours and involved 10 edits.

Conclusion: We quickly adapted CDS in response to changes in recommendations for palivizumab administration. The consistent AAP policy statement structure and the link we developed between these statements and the CDS rules facilitated our efforts. We recommend that CDS implementers establish linkages between published narrative recommendations and their executable rules to facilitate maintenance efforts.

Citation: Michel J, Utidjian LH, Karavite D, Hogan A, Ramos MJ, Miller J, Shiffman RN, Grundmeier RW. Rapid adjustment of clinical decision support in response to updated recommendations for palivizumab eligibility. Appl Clin Inform 2017; 8: 581–592 https://doi.org/10.4338/ACI-2016-10-RA-0173

For which clinical rules do doctors want decision support, and why? A survey of Dutch general practitioners

Despite the promise of decision support for improving care, alerts are often overridden or ignored. We evaluated Dutch general practitioners’ intention to accept decision support in a proposed implementation based on clinical rules regarding care for elderly patients, and their reasons for wanting or not wanting support. We developed a survey based on literature and structured interviews and distributed it to all doctors who would receive support in the proposed implementation (n = 43), of which 65 percent responded. The survey consisted of six questions for each of 20 clinical rules. Despite concerns about interruption, doctors tended to choose more interruptive forms of support. Doctors wanted support when they felt the rule represented minimal care, perceived a need to improve care, and felt responsible for the action and that they might forget to perform the action; doctors declined support due to feeling that it was unnecessary and due to concerns about interruption.

User-centered design to improve clinical decision support in primary care

BACKGROUND

A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations."

OBJECTIVES

(1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support.

METHODS

We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics.

RESULTS

User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance improvement" was the only user-centered design practice significantly associated with perceived utility of clinical decision support, b=.47 (p<.001). This association was present in hospital-based clinics, b=.34 (p<.05), but was stronger at community-based clinics, b=.61 (p<.001).

CONCLUSIONS

Our findings are highly supportive of the practice of analyzing the impact of clinical decision support on performance metrics. This was the most common user-centered design practice in our study, and was the practice associated with higher perceived utility of clinical decision support. This practice may be particularly helpful at community-based clinics, which are typically less connected to VA medical center resources.

New Unintended Adverse Consequences of Electronic Health Records

Although the health information technology industry has made considerable progress in the design, development, implementation, and use of electronic health records (EHRs), the lofty expectations of the early pioneers have not been met. In 2006, the Provider Order Entry Team at Oregon Health & Science University described a set of unintended adverse consequences (UACs), or unpredictable, emergent problems associated with computer-based provider order entry implementation, use, and maintenance. Many of these originally identified UACs have not been completely addressed or alleviated, some have evolved over time, and some new ones have emerged as EHRs became more widely available. The rapid increase in the adoption of EHRs, coupled with the changes in the types and attitudes of clinical users, has led to several new UACs, specifically: complete clinical information unavailable at the point of care; lack of innovations to improve system usability leading to frustrating user experiences; inadvertent disclosure of large amounts of patient-specific information; increased focus on computer-based quality measurement negatively affecting clinical workflows and patient-provider interactions; information overload from marginally useful computer-generated data; and a decline in the development and use of internally-developed EHRs. While each of these new UACs poses significant challenges to EHR developers and users alike, they also offer many opportunities. The challenge for clinical informatics researchers is to continue to refine our current systems while exploring new methods of overcoming these challenges and developing innovations to improve EHR interoperability, usability, security, functionality, clinical quality measurement, and information summarization and display.

Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy

This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors.

Automated integration of continuous glucose monitor data in the electronic health record using consumer technology

The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data communication bridge via a patient’s/parent’s smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits. It is feasible to utilize available consumer technology to assess and triage home diabetes device data within the EHR, and to engage patients/parents and improve healthcare provider workflow.

What is the extent of research on the characteristics, behaviors, and impacts of health information technology champions? A scoping review

Background

Although champions are commonly employed in health information technology (HIT) implementations, the state of empirical literature on HIT champions’ is unclear. The purpose of our review was to synthesize quantitative and qualitative studies to identify the extent of research on the characteristics, behaviors, and impacts of HIT champions. Ultimately, our goal was to identify gaps in the literature and inform implementation science.

Methods

Our review employed a broad search strategy using multiple databases—Embase, Pubmed, Cinahl, PsychInfo, Web of Science, and the Cochrane library. We identified 1728 candidate articles, of which 42 were retained for full-text review.

Results

Of the 42 studies included, fourteen studies employed a multiple-case study design (33 %), 12 additional articles employed a single-case study design (29 %), five used quantitative methods (12 %), two used mixed-methods (5 %), and one used a Delphi methodology (2 %). Our review revealed multiple categories and characteristics of champions as well as influence tactics they used to promote an HIT project. Furthermore, studies have assessed three general types of HIT champion impacts: (1) impacts on the implementation process of a specific HIT; (2) impacts on usage behavior or overall success of a specific HIT; and (3) impacts on general organizational-level innovativeness. However the extent to which HIT projects fail even with a champion and why such failures occur is not clear. Also unclear is whether all organizations require a champion for successful HIT project implementation. In other words, we currently do not know enough about the conditions under which (1) a health IT champion is needed, (2) multiple champions are needed, and (3) an appointed champion—as opposed to an emergent champion—can be successful.

Conclusions

Although champions appear to have contributed to successful implementation of HIT projects, simply measuring the presence or absence of a champion is not sufficient for assessing impacts. Future research should aim for answers to questions about who champions should be, when they should be engaged, what they should do, how management can support their efforts, and what their impact is given the organizational context.

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development

OBJECTIVE

Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems.

METHODS

We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin.

RESULTS

Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules.

CONCLUSION

Significant improvements in the EHR certification and implementation procedures are necessary.

Clinical decision support systems and infection prevention: to know is not enough

Clinical decision support (CDS) systems are an increasingly used form of technology designed to guide health care providers toward established protocols and best practices with the intent of improving patient care. Utilization of CDS for infection prevention is not widespread and is particularly focused on antimicrobial stewardship. This article provides an overview of CDS systems and summarizes key attributes of successfully executed tools. A selection of published reports of CDS for infection prevention and antimicrobial stewardship are described. Finally, an individual organization describes its CDS infrastructure, process of prioritization, design, and development, with selected highlights of CDS tools specifically targeting common infection prevention quality improvement initiatives.

Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations

Background

Computerized clinical decision support (CDS) can help hospitals to improve healthcare. However, CDS can be problematic. The purpose of this study was to discover how the views of clinical stakeholders, CDS content vendors, and EHR vendors are alike or different with respect to challenges in the development, management, and use of CDS.

Methods

We conducted ethnographic fieldwork using a Rapid Assessment Process within ten clinical and five health information technology (HIT) vendor organizations. Using an inductive analytical approach, we generated themes from the clinical, content vendor, and electronic health record vendor perspectives and compared them.

Results

The groups share views on the importance of appropriate manpower, careful knowledge management, CDS that fits user workflow, the need for communication among the groups, and for mutual strategizing about the future of CDS. However, views of usability, training, metrics, interoperability, product use, and legal issues differed. Recommendations for improvement include increased collaboration to address legal, manpower, and CDS sharing issues.

Conclusions

The three groups share thinking about many aspects of CDS, but views differ in a number of important respects as well. Until these three groups can reach a mutual understanding of the views of the other stakeholders, and work together, CDS will not reach its potential.

Computerized provider order entry reduces length of stay in a community hospital

OBJECTIVE

Does computerized provider order entry (CPOE) improve clinical, cost, and efficiency outcomes as quantified in shortened hospital length of stay (LOS)? Most prior studies were done in university settings with home-grown electronic records, and are now 20 years old. This study asked whether CPOE exerts a downward force on LOS in the current era of HITECH incentives, using a vendor product in a community hospital.

METHODS

The methodology retrospectively evaluated correlation between CPOE and LOS on a perpatient, per-visit basis over 22 consecutive quarters, organized by discipline. All orders from all areas were eligible, except verbals, and medication orders in the emergency department which were not available via CPOE. These results were compared with quarterly case mix indices organized by discipline. Correlational and regression analyses were cross-checked to ensure validity of R-square coefficients, and data were smoothed for ease of display. Standard models were used to calculate the inflection point.

RESULTS

Gains in CPOE adoption occurred iteratively house-wide, and in each discipline. LOS decreased in a sigmoid shaped curve. The inflection point shows that once CPOE adoption approaches 60%, further lowering of LOS accelerates. Overall there was a 20.2% reduction in LOS correlated with adoption of CPOE. Case mix index increased during the study period showing that reductions in LOS occurred despite increased patient complexity and resource utilization.

CONCLUSIONS

There was a 20.2% reduction in LOS correlated with rising adoption of CPOE. CPOE contributes to improved clinical, cost, and efficiency outcomes as quantified in reduced LOS, over and above other processes introduced to lower LOS. CPOE enabled a reduction in LOS despite an increase in the case mix index during the time frame of this study.