scholarly journals Sinusitis Treatment Guideline Adherence in the e-visit Setting

2016 ◽  
Vol 07 (02) ◽  
pp. 299-307
Author(s):  
Dang Tran ◽  
Bonnie Westra ◽  
Kevin Smith
Keyword(s):  
Quality Improvement ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Guideline Adherence ◽  
Clinical Guideline ◽  
Clinical Decision ◽  
Care Providers ◽  
Post Intervention ◽  
Improvement Project ◽  
Time Period

SummaryStudies demonstrate poor guideline adherence by health care providers for the treatment of upper respiratory infections, particularly acute bacterial rhinosinusitis (ABRS), in the appropriate prescribing of antibiotic medications.The purpose of this quality improvement project was to evaluate the effect of implementing interventions for improving adherence to a clinical practice guideline for the management of ABRS for patients treated in the e-visit setting. Interventions included: providing a report to providers of their adherence to the ABRS clinical guideline prior to the intervention, providing updated education on the ABRS guideline, and implementing a clinical decision support system reminder.A pre and post intervention evaluation design was used. Data were obtained from a retrospective electronic health record (EHR) data extract of all 316 diagnoses for ABRS in the preintervention 2-month time period and all 368 diagnoses of ABRS in the post-intervention 2-month time period. A review of the structured clinical data elements was performed to determine whether the provider adhered to the clinical guideline, meaning that only patients meeting the criteria for ABRS were to receive an antibiotic prescription.The interventions resulted in a 3.3% improvement in adherence to the ABRS clinical guideline from 95.25% adherence pre-intervention to 98.4% post-intervention. These results demonstrated that the use of an educational intervention and clinical decision support resulted in improved adherence to the ABRS clinical guideline in the e-visit setting. The implications for practice could be significant in that these quality improvement interventions improve guideline adherence and reduce unnecessary prescribing of antibiotics.

scholarly journals A multifaceted clinical decision support intervention to improve adherence to thromboprophylaxis guidelines

2021 ◽  
Author(s):  
Tessa Jaspers ◽  
Marjolijn Duisenberg-van Essenberg ◽  
Barbara Maat ◽  
Marc Durian ◽  
Roy van den Berg ◽  
...  
Keyword(s):  
Decision Support ◽  
Venous Thromboembolism ◽  
Clinical Decision Support ◽  
Guideline Adherence ◽  
Intervention Group ◽  
Clinical Decision ◽  
Multifaceted Intervention ◽  
Annual Number ◽  
Post Intervention ◽  
Mobile Phone Application

AbstractBackground Venous thromboembolism is a potentially fatal complication of hospitalisation, affecting approximately 3% of non-surgical patients. Administration of low molecular weight heparins to the appropriate patients adequately decreases venous thromboembolism incidence, but guideline adherence is notoriously low. Objective To determine the effect of a multifaceted intervention on thromboprophylaxis guideline adherence. The secondary objective was to study the effect on guideline adherence specifically in patients with a high venous thromboembolism risk. As an exploratory objective, we determined how many venous thromboembolisms may be prevented. Setting A Dutch general teaching hospital. Method A prospective study with a pre- and post-intervention measurement was conducted. A multifaceted intervention, consisting of Clinical Decision Support software, a mobile phone application, monitoring of duplicate anticoagulants and training, was implemented. Guideline adherence was assessed by calculating the Padua prediction and Improve bleeding score for each patient. The number of preventable venous thromboembolisms was calculated using the incidences of venous thromboembolism in patients with and without adequate thromboprophylaxis and extrapolated to the annual number of admitted patients. Main outcome measure Adherence to thromboprophylaxis guidelines in pre- and post-intervention measurements. Results 170 patients were included: 85 in both control and intervention group. The intervention significantly increased guideline adherence from 49.4 to 82.4% (OR 4.78; 95%CI 2.37–9.63). Guideline adherence in the patient group with a high venous thromboembolism risk also increased significantly from 54.5 to 84.3% (OR 2.46; 95%CI 1.31–4.62), resulting in the potential prevention of ± 261 venous thromboembolisms per year. Conclusions Our multifaceted intervention significantly increased thromboprophylaxis guideline adherence.

scholarly journals Reach, Adoption and Sustainability of a Mobile Clinical Decision Support Tool Paired with a National Quality Improvement Project Targeting Emergency Department Febrile Infant Management

2020 ◽  
Author(s):  
Ellen K Kerns ◽  
Russell McCulloh ◽  
Hongying Dai
Keyword(s):  
Quality Improvement ◽  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Confounding Factors ◽  
Children's Hospitals ◽  
Improvement Project ◽  
Children’S Hospitals ◽  
National Quality

Abstract Background: Electronic clinical decision support (ECDS) tools are often developed within quality improvement (QI) projects to increase adherence with the latest clinical practice guidelines (CPGs).However, scalability and sustainability of ECDS beyond the time and location of their associated project are very limited. Deploying ECDS using a mobile app (mECDS) has shown the potential to be a viable method of overcoming these limitations. However, it is unclear what pattern the spread of uptake and use of such a tool might follow.Methods: In 2016, our team released a freely available mECDS as part of a national multi-site project entitled Reducing Variation in Infant Sepsis Evaluation (REVISE). For this study, we evaluated trends in weekly mECDS usage measures defined as 1) REVISE metric related screen views (MetricHits), 2) unique designated market areas (DMA) where the mECDS was used (Unique DMAs), 3) density of use or MetricHits/Unique DMAs (HitsPerDMA). Linear regressions were performed to examine the app usage trends measures across three time periods (during REVISE, 1-year post, 2-year post). Separate regression analyses were performed among DMAs that contained a REVISE site and those that did not. The number of REVISE sites in the DMA, the number of children’s hospitals in the DMA, DMA population, and season were also evaluated as confounding factors.Results: Strong growth in the number of unique DMAs and MetricHits occurred during the period of 1-year post the REVISE project. The overall usage continued to be relatively stable during the period of 2-years post. HitsPerDMA had stronger growth in DMAs with a REVISE site than those without. MetricHits were higher in DMAs with a larger population, more REVISE sites, and more children’s hospitals. There were also more MetricHits in the summer than in the winter months. Conclusions: Both temporal and spatial increases in mECDS app usage were found as evidence of a contagion method of spread. Other confounding factors may also play a role in app reach, adoption, and sustainability. Further research is needed to determine the factors driving passive diffusion and its impact on clinical practice and patient outcomes.

scholarly journals A Multifaceted Clinical Decision Support Intervention to Improve Adherence to Thromboprophylaxis Guidelines 

2021 ◽  
Author(s):  
Tessa Jaspers ◽  
Marjolijn Duisenberg-van Essenberg ◽  
Barbara Maat ◽  
Marc Durian ◽  
Roy van den Berg ◽  
...  
Keyword(s):  
Decision Support ◽  
Venous Thromboembolism ◽  
Clinical Decision Support ◽  
Guideline Adherence ◽  
Intervention Group ◽  
Clinical Decision ◽  
Multifaceted Intervention ◽  
Annual Number ◽  
Post Intervention ◽  
Mobile Phone Application

Abstract Background: Venous thromboembolism is a potentially fatal complication of hospitalisation, affecting approximately 3% of non-surgical patients. Administration of low molecular weight heparins to the appropriate patients adequately decreases venous thromboembolism incidence, but guideline adherence is notoriously low.Objective: To determine the effect of a multifaceted intervention on thromboprophylaxis guideline adherence. The secondary objective was to study the effect on guideline adherence specifically in patients with a high venous thromboembolism risk. As an exploratory objective, we determined how many venous thromboembolisms may be prevented.Setting: A Dutch general teaching hospital.Method: A prospective study with a pre- and post-intervention measurement was conducted. A multifaceted intervention, consisting of Clinical Decision Support software, a mobile phone application, monitoring of duplicate anticoagulants and training, was implemented. Guideline adherence was assessed by calculating the Padua prediction and Improve bleeding score for each patient. The number of preventable venous thromboembolisms was calculated using the incidences of venous thromboembolism in patients with and without adequate thromboprophylaxis and extrapolated to the annual number of admitted patients.Main outcome measure: Adherence to thromboprophylaxis guidelines in pre- and post-intervention measurements.Results: 170 patients were included: 85 in both control and intervention group. The intervention significantly increased guideline adherence from 49.4% to 82.4% (OR 4.78; 95%CI 2.37-9.63). Guideline adherence in the patient group with a high venous thromboembolism risk also increased significantly from 54.5% to 84.3% (OR 2.46; 95%CI 1.31-4.62), resulting in the potential prevention of ±261 venous thromboembolisms per year.Conclusions: Our multifaceted intervention significantly increased thromboprophylaxis guideline adherence.

scholarly journals Reach, Adoption and Sustainability of a Mobile Clinical Decision Support Tool Paired With a National Quality Improvement Project Targeting Emergency Department Febrile Infant Management

2020 ◽  
Author(s):  
Ellen K Kerns ◽  
Russell McCulloh ◽  
Hongying Dai
Keyword(s):  
Quality Improvement ◽  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Confounding Factors ◽  
Children's Hospitals ◽  
Improvement Project ◽  
Children’S Hospitals ◽  
National Quality

Abstract Background: Electronic clinical decision support (ECDS) tools are often developed within quality improvement (QI) projects to increase adherence with the latest clinical practice guidelines (CPGs).However, scalability and sustainability of ECDS beyond the time and location of their associated project are very limited. Deploying ECDS using a mobile app (mECDS) has shown the potential to be a viable method of overcoming these limitations. However, it is unclear what pattern the spread of uptake and use of such a tool might follow.Methods: In 2016, our team released a freely available mECDS as part of a national multi-site project entitled Reducing Variation in Infant Sepsis Evaluation (REVISE). For this study, we evaluated trends in weekly mECDS usage measures defined as 1) REVISE metric related screen views (MetricHits), 2) unique designated market areas (DMA) where the mECDS was used (Unique DMAs), 3) density of use or MetricHits/Unique DMAs (HitsPerDMA). Linear regressions were performed to examine the app usage trends measures across three time periods (during REVISE, 1-year post, 2-year post). Separate regression analyses were performed among DMAs that contained a REVISE site and those that did not. The number of REVISE sites in the DMA, the number of children’s hospitals in the DMA, DMA population, and season were also evaluated as confounding factors.Results: Strong growth in the number of unique DMAs and MetricHits occurred during the period of 1-year post the REVISE project. The overall usage continued to be relatively stable during the period of 2-years post. HitsPerDMA had stronger growth in DMAs with a REVISE site than those without. MetricHits were higher in DMAs with a larger population, more REVISE sites, and more children’s hospitals. There were also more MetricHits in the summer than in the winter months. Conclusions: Both temporal and spatial increases in mECDS app usage were found as evidence of a contagion method of spread. Other confounding factors may also play a role in app reach, adoption, and sustainability. Further research is needed to determine the factors driving passive diffusion and its impact on clinical practice and patient outcomes.

Measuring quality in cancer care: Utilizing a clinical decision support system to assess pathway adherence.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 172-172
Author(s):  
Debra A. Patt ◽  
Josh Howell ◽  
Marcus A. Neubauer ◽  
Bo He ◽  
Jody S. Garey
Keyword(s):  
Quality Improvement ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Cancer Care ◽  
Clinical Decision ◽  
Data Capture ◽  
Post Intervention ◽  
Improvement Programs ◽  
Exception Reporting ◽  
Quality Improvement Programs

172 Background: Quality-based programs depend on clinical data documentation for reporting, treatment planning, and measuring pathways (PW) compliance. Adherence to treatment PW reduces variability and costs of care. Clinical decision support systems (CDSS) are tools embedded in the EHR to capture assessable data: stage, biomarkers, line of therapy, etc. With such data, CDSS can measure and report on clinical quality improvement programs like PW adherence, assessable data and exception reporting. Methods: A retrospective cohort study from Jan 1, 2014 - May 30, 2016 measured the impact of an integrated CDSS assessing compliance to PW and exception reporting across 9 independent oncology practices over a 9 month period. Assessable data, PW adherence, and exception reporting were tracked in 4 month intervals pre and post CDSS intervention by practice and physician. A one month wash out period was included post CDSS implementation. Overall rates of positivity, assessable data, and exception reporting were compared pre and post intervention using the Chi-square test. To account for the effect of time on the intervention, a segmented regression analysis was performed to analyze weekly rates of positivity pre and post intervention. Results: 9 practices, 633 physicians, and 30,666 treatment regimens were included. The weekly adherence rate increased by 7.2% after intervention (p = 0.005) across the group. Assessable data capture significantly improved across the cohort OR 6.79 (5.64-8.16) and individually for most practices. Physicians adherent to PW 75% of the time increased post intervention collectively, OR 1.83 (1.44-2.31), and individually. Exception reporting improved from 29% to 99% (p<0.0001). Conclusions: Across a cohort of community oncology practices rates of assessable data, PW adherence, and exception reporting improved after implementation of an integrated CDSS. Effective CDSSs are a critical component of quality improvement programs and may be used to improve data capture, increase adherence to PW and overall contribute to quality cancer care delivery. [Table: see text]

scholarly journals Using Clinical Decision Support to Improve Evidence Based Testing and Diagnosis of Clostridium difficile Infection

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S396-S396
Author(s):  
Bahnsen Miller ◽  
Catherine O’Neal ◽  
Diana Hamer
Keyword(s):  
Decision Support ◽  
Clostridium Difficile ◽  
Clinical Decision Support ◽  
Clostridium Difficile Infection ◽  
Diagnostic Testing ◽  
Clinical Decision ◽  
Evidence Based ◽  
Post Intervention ◽  
Improvement Project ◽  
Asymptomatic Patients

Abstract Background Diagnosing Clostridium difficile infection (CDI) requires clinical understanding of the disease and knowledge of diagnostic testing limitations. It is important for providers to utilize CDI testing only in patients with suspected disease. Real-time polymerase chain reaction (PCR) assays are sensitive but cannot differentiate between symptomatic and asymptomatic patients. Individual hospitals have reported a 50% to 100% increase in the rate of CDI after substituting toxin tests with molecular tests such as PCR. We conducted a quality improvement project, implementing clinical decision support in ordering diagnostic testing of CDI, while measuring the number of diagnostic tests ordered and positive results. Methods We implemented evidence based clinical decision support into Cerner order entry system on March 1, 2016. The Cepheid Xpert C. difficile molecular test is used for diagnosis of CDI at our facility. The decision support included a message stating Òuse the test with caution in patients who are receiving tube feeds or recent laxative useÓ and prompted ordering providers to select one of three indications for using the test: 3 or more diarrheal stools per 24 hour period, leukocytosis with abdominal pain, or ileus. A control chart was used to monitor the number of tests ordered and positive tests per month (inpatient adults) for a total of 24 months; 14 months pre-intervention and 10 months post-intervention. Results A decrease in the number of tests ordered per month was seen post intervention. Average number of monthly tests ordered was 207 pre-intervention and 163 post-intervention. After controlling for patient-days per month, there was a 13.5% decrease in the number of tests ordered from a mean of 14.29 vs.. 12.37 tests per thousand patient-days per month. This resulted in special cause variation (Figure 1). There was no special cause variation detected with the number of positive PCRs per month, pre and post intervention. Conclusion Implementing decision support into the electronic medical record may assist providers with evidence-based utilization of the C. difficile PCR by decreasing unnecessary testing. This decrease may also have an impact on overall hospital costs, antibiotic utilization, and public reporting related to CDI. Disclosures All authors: No reported disclosures.

scholarly journals Reach, Adoption and Sustainability of a Mobile Clinical Decision Support Tool Paired With a National Quality Improvement Project Targeting Emergency Department Febrile Infant Management

2021 ◽  
Author(s):  
Ellen K Kerns ◽  
Russell McCulloh ◽  
Hongying Dai
Keyword(s):  
Quality Improvement ◽  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Confounding Factors ◽  
Children's Hospitals ◽  
Improvement Project ◽  
Children’S Hospitals ◽  
National Quality

Abstract Background: Electronic clinical decision support (ECDS) tools are often developed within quality improvement (QI) projects to increase adherence with the latest clinical practice guidelines (CPGs).However, scalability and sustainability of ECDS beyond the time and location of their associated project are very limited. Deploying ECDS using a mobile app (mECDS) has shown the potential to be a viable method of overcoming these limitations. However, it is unclear what pattern the spread of uptake and use of such a tool might follow.Methods: In 2016, our team released a freely available mECDS as part of a national multi-site project entitled Reducing Variation in Infant Sepsis Evaluation (REVISE). For this study, we evaluated trends in weekly mECDS usage measures defined as 1) REVISE metric related screen views (MetricHits), 2) unique designated market areas (DMA) where the mECDS was used (Unique DMAs), 3) density of use or MetricHits/Unique DMAs (HitsPerDMA). Linear regressions were performed to examine the app usage trends measures across three time periods (during REVISE, 1-year post, 2-year post). Separate regression analyses were performed among DMAs that contained a REVISE site and those that did not. The number of REVISE sites in the DMA, the number of children’s hospitals in the DMA, DMA population, and season were also evaluated as confounding factors.Results: Strong growth in the number of unique DMAs and MetricHits occurred during the period of 1-year post the REVISE project. The overall usage continued to be relatively stable during the period of 2-years post. HitsPerDMA had stronger growth in DMAs with a REVISE site than those without. MetricHits were higher in DMAs with a larger population, more REVISE sites, and more children’s hospitals. There were also more MetricHits in the summer than in the winter months. Conclusions: Both temporal and spatial increases in mECDS app usage were found as evidence of a contagion method of spread. Other confounding factors may also play a role in app reach, adoption, and sustainability. Further research is needed to determine the factors driving passive diffusion and its impact on clinical practice and patient outcomes.

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

2020 ◽  
Vol 11 (04) ◽  
pp. 635-643
Author(s):  
Joan S. Ash ◽  
Dian Chase ◽  
Sherry Baron ◽  
Margaret S. Filios ◽  
Richard N. Shiffman ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Primary Care Providers ◽  
Care Providers ◽  
Technical Feasibility ◽  
Primary Care Settings ◽  
Worker Health ◽  
Operational Issues

Abstract 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.

scholarly journals Direct and Electronic Health Record Access to the Clinical Decision Support for Immunizations in the Minnesota Immunization Information System

2016 ◽  
Vol 8s2 ◽  
pp. BII.S40208
Author(s):  
Sripriya Rajamani ◽  
Aaron Bieringer ◽  
Stephanie Wallerius ◽  
Daniel Jensen ◽  
Tamara Winden ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Clinical Decision ◽  
Population Based ◽  
Direct Access ◽  
Care Providers ◽  
Study Objective ◽  
Vaccination Rates ◽  
Electronic Health

Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers. IIS hold comprehensive vaccination histories given across providers and over time. An important aspect to IIS is the clinical decision support for immunizations (CDSi), consisting of vaccine forecasting algorithms to determine needed immunizations. The study objective was to analyze the CDSi presentation by IIS in Minnesota (Minnesota Immunization Information Connection [MIIC]) through direct access by IIS interface and by access through electronic health records (EHRs) to outline similarities and differences. The immunization data presented were similar across the three systems examined, but with varying ability to integrate data across MIIC and EHR, which impacts immunization data reconciliation. Study findings will lead to better understanding of immunization data display, clinical decision support, and user functionalities with the ultimate goal of promoting IIS CDSi to improve vaccination rates.

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