Dataset Information

Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.

ABSTRACT: OBJECTIVE To determine whether a computerized clinical decision support system providing patient-specific recommendations in real-time improves the quality of prescribing for long-term care residents with renal insufficiency. DESIGN Randomized trial within the long-stay units of a large long-term care facility. Randomization was within blocks by unit type. Alerts related to medication prescribing for residents with renal insufficiency were displayed to prescribers in the intervention units and hidden but tracked in control units. Measurement The proportions of final drug orders that were appropriate were compared between intervention and control units within alert categories: (1) recommended medication doses; (2) recommended administration frequencies; (3) recommendations to avoid the drug; (4) warnings of missing information. RESULTS The rates of alerts were nearly equal in the intervention and control units: 2.5 per 1,000 resident days in the intervention units and 2.4 in the control units. The proportions of dose alerts for which the final drug orders were appropriate were similar between the intervention and control units (relative risk 0.95, 95% confidence interval 0.83, 1.1) for the remaining alert categories significantly higher proportions of final drug orders were appropriate in the intervention units: relative risk 2.4 for maximum frequency (1.4, 4.4); 2.6 for drugs that should be avoided (1.4, 5.0); and 1.8 for alerts to acquire missing information (1.1, 3.4). Overall, final drug orders were appropriate significantly more often in the intervention units-relative risk 1.2 (1.0, 1.4). CONCLUSIONS Clinical decision support for physicians prescribing medications for long-term care residents with renal insufficiency can improve the quality of prescribing decisions.http://clinicaltrials.gov Identifier: NCT00599209.

SUBMITTER: Field TS

PROVIDER: S-EPMC2705250 | biostudies-literature | 2009 Jul-Aug

REPOSITORIES: biostudies-literature

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Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.

Field Terry S TS Rochon Paula P Lee Monica M Gavendo Linda L Baril Joann L JL Gurwitz Jerry H JH

Journal of the American Medical Informatics Association : JAMIA 20090423 4

<h4>Unlabelled</h4>OBJECTIVE To determine whether a computerized clinical decision support system providing patient-specific recommendations in real-time improves the quality of prescribing for long-term care residents with renal insufficiency. DESIGN Randomized trial within the long-stay units of a large long-term care facility. Randomization was within blocks by unit type. Alerts related to medication prescribing for residents with renal insufficiency were displayed to prescribers in the inter ...[more]

PMID: 19390107

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Project description:Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners.We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes.Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (p = 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported.Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such as system design, user interface, local context, implementation strategy, and evaluate impact on user satisfaction and workflow, costs, and unintended consequences.

Project description:BackgroundAs dementia progresses, symptoms and concerns increase, causing considerable distress for the person and their caregiver. The integration of care between care homes and health care services is vital to meet increasing care needs and maintain quality of life. However, care home access to high-quality health care is inequitable. eHealth can facilitate this by supporting remote specialist input on care processes, such as clinical assessment and decision-making, and streamlining care on site. How to best implement eHealth in the care home setting is unclear.ObjectiveThe aim of this review was to identify the key factors that influence the implementation of eHealth for people living with dementia in long-term care.MethodsA systematic search of Embase, PsycINFO, MEDLINE, and CINAHL was conducted to identify studies published between 2000 and 2020. Studies were eligible if they focused on eHealth interventions to improve treatment and care assessment or decision-making for residents with dementia in care homes. Data were thematically analyzed and deductively mapped onto the 6 constructs of the adapted Consolidated Framework for Implementation Research (CFIR). The results are presented as a narrative synthesis.ResultsA total of 29 studies were included, focusing on a variety of eHealth interventions, including remote video consultations and clinical decision support tools. Key factors that influenced eHealth implementation were identified across all 6 constructs of the CFIR. Most concerned the inner setting construct on requirements for implementation in the care home, such as providing a conducive learning climate, engaged leadership, and sufficient training and resources. A total of 4 novel subconstructs were identified to inform the implementation requirements to meet resident needs and engage end users.ConclusionsImplementing eHealth in care homes for people with dementia is multifactorial and complex, involving interaction between residents, staff, and organizations. It requires an emphasis on the needs of residents and the engagement of end users in the implementation process. A novel conceptual model of the key factors was developed and translated into 18 practical recommendations on the implementation of eHealth in long-term care to guide implementers or innovators in care homes. Successful implementation of eHealth is required to maximize uptake and drive improvements in integrated health and social care.

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Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.

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Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.

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