Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age

Chow, Angela; Lye, David C.; Arah, Onyebuchi A.

doi:10.1038/srep17346

Cited by 24 publications

(32 citation statements)

References 37 publications

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“…Telemedicine and software programs were the next most frequently identified interventions, occurring 7 of 38 occurrences (18%) [ 16 - 18 , 21 , 32 , 40 , 46 ] and 6 of 38 occurrences (16%) [ 25 , 27 , 28 , 30 , 36 , 50 ], respectively. Clinical decision support systems were analyzed at a frequency of 5 of 38 occurrences (13%) [ 22 , 24 , 33 , 35 , 48 ]. mHealth occurred 3 of 38 occurrences (8%) [ 20 , 42 , 45 ].…”

Section: Resultsmentioning

confidence: 99%

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Kruse¹,

Beane²

2018

J Med Internet Res

154

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BackgroundHealth information technology (HIT) has been introduced into the health care industry since the 1960s when mainframes assisted with financial transactions, but questions remained about HIT’s contribution to medical outcomes. Several systematic reviews since the 1990s have focused on this relationship. This review updates the literature.ObjectiveThe purpose of this review was to analyze the current literature for the impact of HIT on medical outcomes. We hypothesized that there is a positive association between the adoption of HIT and medical outcomes.MethodsWe queried the Cumulative Index of Nursing and Allied Health Literature (CINAHL) and Medical Literature Analysis and Retrieval System Online (MEDLINE) by PubMed databases for peer-reviewed publications in the last 5 years that defined an HIT intervention and an effect on medical outcomes in terms of efficiency or effectiveness. We structured the review from the Primary Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), and we conducted the review in accordance with the Assessment for Multiple Systematic Reviews (AMSTAR).ResultsWe narrowed our search from 3636 papers to 37 for final analysis. At least one improved medical outcome as a result of HIT adoption was identified in 81% (25/37) of research studies that met inclusion criteria, thus strongly supporting our hypothesis. No statistical difference in outcomes was identified as a result of HIT in 19% of included studies. Twelve categories of HIT and three categories of outcomes occurred 38 and 65 times, respectively.ConclusionsA strong majority of the literature shows positive effects of HIT on the effectiveness of medical outcomes, which positively supports efforts that prepare for stage 3 of meaningful use. This aligns with previous reviews in other time frames.

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Section: Resultsmentioning

confidence: 99%

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Kruse¹,

Beane²

2018

J Med Internet Res

154

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“…[5][6][7][8][9][10] Evidence for the benefits of AMS functionality within e-prescribing systems comes from published research studies demonstrating positive impact on outcomes including increased guideline adherence 11,12 and effective initial therapy 13 or reductions in antimicrobial prescribing, 14,15 resistance, 16,17 dosing errors, 8 length of hospital or ICU stay 14,18 and mortality. 12,13,19 However, many of these information systems were created on a small scale in individual hospitals or groups of institutions and few reports cover the full potential range of software features that enable AMS.…”

mentioning

confidence: 99%

Electronic prescribing system design priorities for antimicrobial stewardship: a cross-sectional survey of 142 UK infection specialists

Hand

Cumming

Hopkins

et al. 2016

J. Antimicrob. Chemother.

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SynopsisThe implementation of electronic prescribing and medication administration systems (EPMAs) is a priority for hospitals and a potential component of antimicrobial stewardship (AMS). ObjectivesThis study aimed to identify software features within EPMAs that could potentially facilitate AMS and to survey practising UK infection specialist healthcare professionals in order to assign priority to these software features. MethodsA questionnaire was developed using nominal group technique and transmitted via email links through professional networks. The questionnaire collected demographic data, information on priority areas and anticipated impact of EPMA. Responses from different respondent groups were compared using the Mann Whitney U test. ResultsResponses were received from 164 individuals (142 analysable). Respondents were predominantly specialist infection pharmacists (48%) or medical microbiologists (37%). 59% of pharmacists had experience of EPMA in their hospitals compared to 35% of microbiologists. Pharmacists assigned higher priority to: indication prompt (p<0.001), allergy checker (p=0.003) treatment protocols (p=0.003), drug-indication mismatch alerts (p=0.031) and prolonged course alerts (p=0.041); and lower priority to a dose checker for adults (p=0.02) and an interaction checker (p<0.05), than microbiologists. A "soft stop" functionality was rated essential or a high priority by 89% of respondents. Potential EPMA software features were expected to have the greatest impact on stewardship, treatment efficacy and patient safety outcomes with lowest impact on Clostridium difficile infection (CDI), antimicrobial resistance and drug expenditure. ConclusionsThe survey demonstrates key differences in health professionals' opinions of different healthcare benefits of EPMA but a consensus of anticipated positive impact on patient safety and antimicrobial stewardship.

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“…As illustrated, 14 of 27 (52%) of articles analyzed identified ten unique positive indicators of practitioner performance (15,18,19,23,25,28,29,31,35,36,38,39,40,41). Practitioner performance was reported as more accurate prescribing, improved screening of patients, improved overall performance, increased awareness of patients' conditions, improved follow-up due to better communication with patients, improved accuracy of diagnosis, improved documentation, improved benchmarking, improved care plans, and improved buy-in of CDSS.…”

Section: Table 2: Summary Of Themes Identified For Practitioner Perfomentioning

confidence: 96%

“…Of those that reported a difference, 88% reported positive effect. Two articles (7%) reported no statistical difference between control and intervention groups (27,29). Ten articles (37%) did not discuss patient medical outcomes (15)(16)(17)19,20,21,23,27,31,33,40).…”

Section: Table 3: Summary Of Themes Identified For Patient Medical Oumentioning

confidence: 99%

What are the Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes

Kruse¹,

Ehrbar²

2019

Preprint

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Background Computerized decision support systems (CDSS) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSS, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes. The purpose of this review was to analyze the relationship between CDSS, practitioner performance, and patient medical outcomes. PubMed, CINAHL, and Cochrane databases were queried.Methods 27 articles were chosen based on year published (last ten years), high quality source, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet to collect information on the relationship between CDSS and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, and outcomes (PICO) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse Protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting.Results Fourteen articles (52%) discussed positive practitioner performance, three articles (11%) found no difference in practitioner performance, ten articles (37%) did not discuss practitioner performance. Zero articles reported negative practitioner performance. Fifteen articles (56%) discussed positive patient medical outcomes, two articles (7%) found no statistically significant difference in medical outcomes between intervention and control groups, and ten articles (37%) did not discuss medical outcomes. Zero articles found negative patient medical outcomes.Conclusions Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found significant positive reporting of a positive effect on patient medical outcomes. Our findings support adoption of decision support systems.

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Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age

Cited by 24 publications

References 37 publications

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Electronic prescribing system design priorities for antimicrobial stewardship: a cross-sectional survey of 142 UK infection specialists

What are the Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes

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