Clostridioides difficile dynamic electronic order panel, an effective automated intervention to reduce inappropriate inpatient ordering.

BACKGROUND: Ordering Clostridioides difficile diagnostics without appropriate clinical indications can result in inappropriate antibiotic prescribing and misdiagnosis of hospital onset C. difficile infection. Manual processes such as provider review of order appropriateness may detract from other infection control or antibiotic stewardship activities. METHODS: We developed an evidence-based clinical algorithm that defined appropriateness criteria for testing for C. difficile infection. We then implemented an electronic medical record-based order-entry tool that utilized discrete branches within the clinical algorithm including history of prior C. difficile test results, laxative or stool-softener administration, and documentation of unformed bowel movements. Testing guidance was then dynamically displayed with supporting patient data. We compared the rate of completed C. difficile tests after implementation of this intervention at 5 hospitals to a historic baseline in which a best-practice advisory was used. RESULTS: Using mixed-effects Poisson regression, we found that the intervention was associated with a reduction in the incidence rate of both C. difficile ordering (incidence rate ratio [IRR], 0.74; 95% confidence interval [CI], 0.63-0.88; P = .001) and C. difficile-positive tests (IRR, 0.83; 95% CI, 0.76-0.91; P < .001). On segmented regression analysis, we identified a sustained reduction in orders over time among academic hospitals and a new reduction in orders over time among community hospitals. CONCLUSIONS: An evidence-based dynamic order panel, integrated within the electronic medical record, was associated with a reduction in both C. difficile ordering and positive tests in comparison to a best practice advisory, although the impact varied between academic and community facilities.

Translating an evidence-based clinical pathway into shareable CDS: developing a systematic process using publicly available tools.

OBJECTIVE: To develop a process for translating semi-structured clinical decision support (CDS) into shareable, computer-readable CDS. MATERIALS AND METHODS: We developed a systematic and transparent process using publicly available tools (eGLIA, GEM Cutter, VSAC, and the CDS Authoring Tool) to translate an evidence-based clinical pathway (CP) into a Clinical Quality Language (CQL)-encoded CDS artifact. RESULTS: We produced a 4-phase process for translating a CP into a CQL-based CDS artifact. CP content was extracted using GEM into discrete clinical concepts, encoded using standard terminologies into value sets on VSAC, evaluated against workflows using a wireframe, and finally structured as a computer readable CDS artifact using CQL. This process included a quality control step and intermediate products to support transparency and reuse by other CDS developers. DISCUSSION: Translating a CP into a shareable, computer-readable CDS artifact was accomplished through a systematic process. Our process identified areas of ambiguity and gaps in the CP, which generated improvements in the CP. Collaboration with clinical subject experts and the CP development team was essential for translation. Publicly available tools were sufficient to support most translation steps, but expression of certain complex concepts required manual encoding. CONCLUSION: Standardized development of CDS from a CP is feasible using a systematic 4-phase process. CPs represent a potential reservoir for developers of evidence-based CDS. Aspects of CP development simplified portions of the CDS translation process. Publicly available tools can facilitate CDS development; however, enhanced tool features are needed to model complex CDS statements.

AHRQ EPC Series on Improving Translation of Evidence: Use of a Clinical Pathway for C. Difficile Treatment to Facilitate the Translation of Research Findings into Practice.

BACKGROUND: In 2018 the Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) Program issued a call for strategies to disseminate AHRQ EPC systematic reviews. In this pilot, findings from the 2016 AHRQ EPC report on Clostridioides difficile infection were translated into a treatment pathway and disseminated via a cloud-based platform and electronic health record (EHR). METHODS: An existing 10-step framework was used for developing and disseminating evidence-based clinical pathways. The development of the EHR intervention was informed by the Five Rights model for clinical decision support and human-computer interaction design heuristics. The researchers used observations and time measurements to describe the impact of the EPC report on pathway development and examined provider adoption using counts of pathway views. RESULTS: Two main themes emerged: (1) discrepancies between the EPC report and existing guidelines prompted critical discussions about available treatments, and (2) lack of guideline and pathway syntheses in the EPC report necessitated a rapid literature review. Pathway development required 340 hours: 205 for the rapid literature review, 63 for pathway development and EHR intervention design, and 5 for technical implementation of the intervention. Pathways were viewed 1,069 times through the cloud-based platform and 47 times through a hyperlink embedded in key EHR ordering screens. CONCLUSION: Pathways can be an approach for disseminating AHRQ EPC report findings within health care systems; however, reports should include guideline and pathway syntheses to meet their full potential. Embedding hyperlinks to pathway content within the EHR may be a viable and low-effort solution for promoting awareness of evidence-based resources.

Next Steps in Improving Healthcare Value: AHRQ Evidence-based Practice Center Program-Applying the Knowledge to Practice to Data Cycle to Strengthen the Value of Patient Care.

For more than 20 years, the Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) Program has been identifying and synthesizing evidence to inform evidence-based healthcare. Recognizing that many healthcare settings continue to face challenges in disseminating and implementing evidence into practice, AHRQ's EPC program has also embarked on initiatives to facilitate the translation of evidence into practice and to measure and monitor how practice changes impact health outcomes. The program has structured its efforts around the three phases of the Learning Healthcare System cycle: knowledge, practice, and data. Here, we use a topic relevant to the field of hospital medicine-Clostridium difficile colitis prevention and treatment-as an exemplar of how the EPC program has used this framework to move evidence into practice and develop systems to facilitate continuous learning in healthcare systems.

Using a 10-step framework to support the implementation of an evidence-based clinical pathways programme.

BACKGROUND: Integration of evidence into practice is suboptimal. Clinical pathways, defined as multidisciplinary care plans, are a method for translating evidence into local settings and have been shown to improve the value of patient care. OBJECTIVE: To describe the development of a clinical pathways programme across a large academic healthcare system. METHODS: We use a 10-step framework (grounded in the Knowledge-to-Action framework and ADAPTE Collaboration methodology for guideline adaptation) to support pathway development and dissemination, including facilitating clinical owner and stakeholder engagement, developing pathway prototypes based on rapid reviews of the existing literature, developing tools for dissemination and impact assessment. We use a cloud-based technology platform (Dorsata, Washington, DC) to assist with development and dissemination across our geographically distributed care settings and providers. Content is viewable through desktop and mobile applications. We measured programme adoption and penetration by examining number of pathways developed as well as mobile application use and pathway views. RESULTS: From 1 February 2016 to 30 April 2018, a total of 202 pathways were disseminated. The three most common clinical domains represented were oncology (46.5%, n=94), pulmonary/critical care (8.9%, n=18) and cardiovascular medicine (7.4%, n=15). Users opting to register for a personal account totalled 1279; the three largest groups were physicians (45.1%, n=504), advanced practice providers (19.5%, n=245) and nurses (19.1%, n=240). Pathway views reached an average of 2150 monthly views during the last 3 months of the period. The majority of pathways reference at least one evidence-based source (93.6%, n=180). CONCLUSIONS: A healthcare system can successfully use a framework and technology platform to support the development and dissemination of pathways across a multisite institution.

Nurse Generated EHR Data Supports Post-Acute Care Referral Decision Making: Development and Validation of a Two-step Algorithm.

Objective: Build and validate a clinical decision support (CDS) algorithm for discharge decisions regarding referral for post-acute care (PAC) and to what site of care. Materials and Methods: Case studies derived from EHR data were judged by 171 interdisciplinary experts and prediction models were generated. Results: A two-step algorithm emerged with area under the curve (AUC) in validation of 91.5% (yes/no refer) and AUC 89.7% (where to refer). Discussion: CDS for discharge planning (DP) decisions may remove subjectivity, and variation in decision-making. CDS could automate the assessment process and alert clinicians of high need patients earlier in the hospital stay. Conclusion: Our team successfully built and validated a two-step algorithm to support discharge referral decision-making from EHR data. Getting patients the care and support they need may decrease readmissions and other adverse events. Further work is underway to test the effects of the CDS on patient outcomes in two hospitals.

Why older adults may decline offers of post-acute care services: A qualitative descriptive study.

The most common post-acute care (PAC) services available to patients after hospital discharge include home care, skilled nursing facilities, nursing homes, inpatient rehabilitation, and hospice. Patients who need PAC and receive services have better outcomes, however almost one-third of those offered services decline. Little research exists on PAC decision-making and why patients may decline services. This qualitative descriptive study explored the responses of thirty older adults to the question: "Can you, from the patient point of view, tell me why someone would not want post hospital care?" Three themes emerged. Participants may decline due to 1) previous negative experiences with PAC, or 2) a preference to be home. Some participants stated, "I'd be there" and would not decline services. Participants also discussed 3) why other patients might decline PAC which included patients' past experiences, lack of understanding/preconceived ideas, and preferences. Clinical implications include assessing patients' knowledge and experience before providing recommendations.

Patient Preferences for Information on Post-Acute Care Services.

The purpose of the current study was to explore what hospitalized patients would like to know about post-acute care (PAC) services to ultimately help them make an informed decision when offered PAC options. Thirty hospitalized adults 55 and older in a Northeastern U.S. academic medical center participated in a qualitative descriptive study with conventional content analysis as the analytical technique. Three themes emerged: (a) receiving practical information about the services, (b) understanding "how it relates to me," and (c) having opportunities to understand PAC options. Study findings inform clinicians what information should be included when discussing PAC options with older adults. Improving the quality of discharge planning discussions may better inform patient decision making and, as a result, increase the numbers of patients who accept a plan of care that supports recovery, meets their needs, and results in improved quality of life and fewer readmissions. [Res Gerontol Nurs. 2016; 9(4):175-182.].