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An audit of anticoagulant management to assess anticoagulant control using decision support software.

ABSTRACT: To evaluate the effectiveness of a computerised self-adjusting anticoagulant algorithm to predict appropriate warfarin dosing and to assess its use in clinical practice.A 3-year audit of anticoagulant control in patients managed by doctors and pharmacists using computer decision support and an evaluation of the impact of dose adjustments made by the users.3660 patients on oral anticoagulants; one-third of patients managed by doctors and two-thirds by pharmacists.Anticoagulant supervision in primary care and pharmacies at 60 sites in New Zealand.The time in the therapeutic range (TTR), the outcome of adherence to the computer dosing algorithm, the percentage of time the clinicians over-ride the algorithm and the impact of their intervention on anticoagulant control.A TTR of 72.9% was achieved for all patients. The TTR was significantly better in patients managed by pharmacists than doctors (75.1% versus 67.4%, p<0.0001). The computer algorithm provides appropriate dose recommendations for INR results from 1.5 to 4. Users administered a dose that differed from the computer recommendation 23.3% of the time. The doctors adjusted the dose more frequently (28.2% versus 21.1% of tests) and made larger dose changes than the pharmacists.The clinicians predominantly change the dose when the INR is below the therapeutic range. The changes are not necessary to correct for inaccuracies in the algorithm. The most likely explanation is the clinician's belief that their own dose adjustment would achieve better control; however, in practice, their changes tend to underdose patients. The doctors achieved poorer control than the pharmacists; this is in part due to the action of the doctors over-riding the algorithm. Our results imply that clinicians could achieve better anticoagulant control if they more closely followed the computer algorithm.

SUBMITTER: Harper P

PROVIDER: S-EPMC4158218 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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An audit of anticoagulant management to assess anticoagulant control using decision support software.

Harper Paul P Harper Joe J Hill Claire C

BMJ open 20140902 9

<h4>Objective</h4>To evaluate the effectiveness of a computerised self-adjusting anticoagulant algorithm to predict appropriate warfarin dosing and to assess its use in clinical practice.<h4>Design</h4>A 3-year audit of anticoagulant control in patients managed by doctors and pharmacists using computer decision support and an evaluation of the impact of dose adjustments made by the users.<h4>Participants</h4>3660 patients on oral anticoagulants; one-third of patients managed by doctors and two-t ...[more]

PMID: 25183709

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Project description:BackgroundMoving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements."ObjectiveWe aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse).MethodsAcceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite.ResultsWe used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build.ConclusionsAutomated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization.

Project description:BackgroundThe clinical decision-making process in pressure ulcer management is complex, and its quality depends on both the nurse's experience and the availability of scientific knowledge. This process should follow evidence-based practices incorporating health information technologies to assist health care professionals, such as the use of clinical decision support systems. These systems, in addition to increasing the quality of care provided, can reduce errors and costs in health care. However, the widespread use of clinical decision support systems still has limited evidence, indicating the need to identify and evaluate its effects on nursing clinical practice.ObjectiveThe goal of the review was to identify the effects of nurses using clinical decision support systems on clinical decision making for pressure ulcer management.MethodsThe systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. The search was conducted in April 2019 on 5 electronic databases: MEDLINE, SCOPUS, Web of Science, Cochrane, and CINAHL, without publication date or study design restrictions. Articles that addressed the use of computerized clinical decision support systems in pressure ulcer care applied in clinical practice were included. The reference lists of eligible articles were searched manually. The Mixed Methods Appraisal Tool was used to assess the methodological quality of the studies.ResultsThe search strategy resulted in 998 articles, 16 of which were included. The year of publication ranged from 1995 to 2017, with 45% of studies conducted in the United States. Most addressed the use of clinical decision support systems by nurses in pressure ulcers prevention in inpatient units. All studies described knowledge-based systems that assessed the effects on clinical decision making, clinical effects secondary to clinical decision support system use, or factors that influenced the use or intention to use clinical decision support systems by health professionals and the success of their implementation in nursing practice.ConclusionsThe evidence in the available literature about the effects of clinical decision support systems (used by nurses) on decision making for pressure ulcer prevention and treatment is still insufficient. No significant effects were found on nurses' knowledge following the integration of clinical decision support systems into the workflow, with assessments made for a brief period of up to 6 months. Clinical effects, such as outcomes in the incidence and prevalence of pressure ulcers, remain limited in the studies, and most found clinically but nonstatistically significant results in decreasing pressure ulcers. It is necessary to carry out studies that prioritize better adoption and interaction of nurses with clinical decision support systems, as well as studies with a representative sample of health care professionals, randomized study designs, and application of assessment instruments appropriate to the professional and institutional profile. In addition, long-term follow-up is necessary to assess the effects of clinical decision support systems that can demonstrate a more real, measurable, and significant effect on clinical decision making.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42019127663; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=127663.

Project description:BackgroundElectronic health record (EHR)-based clinical decision support tools can improve the use of evidence-based clinical guidelines for preeclampsia management that can reduce maternal mortality and morbidity. No study has investigated the organizational capabilities that enable hospitals to use EHR-based decision support tools to manage preeclampsia.ObjectiveTo examine the association of organizational capabilities and hospital adoption of EHR-based decision support tools for preeclampsia management.MethodsCross-sectional analyses of hospitals providing obstetric care in 2017. In total, 739 hospitals responded to the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS) and were linked to the 2017 American Hospital Association (AHA) Annual Survey Database and the Area Health Resources File (AHRF). A total of 425 hospitals providing obstetric care across 49 states were included in the analysis. The main outcome was whether a hospital adopted EHR-based clinical decision support tools for preeclampsia management. Hospital organizational capabilities assessed as predictors include EHR functions, adoption of evidence-based clinical treatments, use of quality improvement methods, and dissemination processes to share best patient care practices. Logistic regression estimated the association of hospital organizational capabilities and hospital adoption of EHR-based decision support tools to manage preeclampsia, controlling for hospital structural and patient sociodemographic characteristics.ResultsTwo-thirds of the hospitals (68%) adopted EHR-based decision support tools for preeclampsia, and slightly more than half (56%) of hospitals had a single EHR system. Multivariable regression results indicate that hospitals with a single EHR system were more likely to adopt EHR-based decision support tools for preeclampsia (17.4 percentage points; 95% CI, 1.9 to 33.0; P < .05) than hospitals with a mixture of EHR and paper-based systems. Compared with hospitals having multiple EHRs, on average, hospitals having a single EHR were also more likely to adopt the tools by 9.3 percentage points, but the difference was not statistically significant (95% CI, -1.3 to 19.9). Hospitals with more processes to aid dissemination of best patient care practices were also more likely to adopt EHR-based decision-support tools for preeclampsia (0.4 percentage points; 95% CI, 0.1 to 0.6, for every 1-unit increase in dissemination processes; P < .01).ConclusionStandardized EHRs and policies to disseminate evidence are foundational hospital capabilities that can help advance the use of EHR-based decision support tools for preeclampsia management in the approximately one-third of US hospitals that still do not use them.

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An audit of anticoagulant management to assess anticoagulant control using decision support software.

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An audit of anticoagulant management to assess anticoagulant control using decision support software.

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