Dataset Information

Decision support systems for incurable non-small cell lung cancer: a systematic review.

ABSTRACT:

Background

Individually tailored cancer treatment is essential to ensure optimal treatment and resource use. Treatments for incurable metastatic non-small cell lung cancer (NSCLC) are evolving rapidly, and decision support systems (DSS) for this patient population have been developed to balance benefits and harms for decision-making. The aim of this systematic review was to inventory DSS for stage IIIB/IV NSCLC patients.

Methods

A systematic literature search was performed in Pubmed, Embase and the Cochrane Library. DSS were described extensively, including their predictors, model performances (i.e., discriminative ability and calibration), levels of validation and user friendliness.

Results

The systematic search yielded 3531 articles. In total, 67 articles were included after additional reference tracking. The 39 identified DSS aim to predict overall survival and/or progression-free survival, but give no information about toxicity or cost-effectiveness. Various predictors were incorporated, such as performance status, serum and inflammatory markers, and patient and tumor characteristics. Some DSS were developed for the entire incurable NSCLC population, whereas others were specifically for patients with brain or spinal metastases. Few DSS had been validated externally using recent clinical data, and the discrimination and calibration were often poor.

Conclusions

Many DSS have been developed for incurable NSCLC patients, but DSS are still lacking that are up-to-date with a good model performance, while covering the entire treatment spectrum. Future DSS should incorporate genetic and biological markers based on state-of-the-art evidence, and compare multiple treatment options to estimate survival, toxicity and cost-effectiveness.

SUBMITTER: Revesz D

PROVIDER: S-EPMC5625762 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

Decision support systems for incurable non-small cell lung cancer: a systematic review.

Révész D D Engelhardt E G EG Tamminga J J JJ Schramel F M N H FMNH Onwuteaka-Philipsen B D BD van de Garde E M W EMW Steyerberg E W EW Jansma E P EP De Vet H C W HCW Coupé V M H VMH

BMC medical informatics and decision making 20171002 1

<h4>Background</h4>Individually tailored cancer treatment is essential to ensure optimal treatment and resource use. Treatments for incurable metastatic non-small cell lung cancer (NSCLC) are evolving rapidly, and decision support systems (DSS) for this patient population have been developed to balance benefits and harms for decision-making. The aim of this systematic review was to inventory DSS for stage IIIB/IV NSCLC patients.<h4>Methods</h4>A systematic literature search was performed in Pubm ...[more]

PMID: 28969629

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Project description:BackgroundWorldwide, the burden of allergies-in particular, drug allergies-is growing. In the process of prescribing, dispensing, or administering a drug, a medication error may occur and can have adverse consequences; for example, a drug may be given to a patient with a documented allergy to that particular drug. Computerized physician order entry (CPOE) systems with built-in clinical decision support systems (CDSS) have the potential to prevent such medication errors and adverse events.ObjectiveThe aim of this review is to provide a comprehensive overview regarding all aspects of CDSS for drug allergy, including documenting, coding, rule bases, alerts and alert fatigue, and outcome evaluation.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed as much as possible and searches were conducted in 5 databases using CPOE, CDSS, alerts, and allergic or allergy as keywords. Bias could not be evaluated according to PRISMA guidelines due to the heterogeneity of study types included in the review.ResultsOf the 3160 articles considered, 60 met the inclusion criteria. A further 9 articles were added based on expert opinion, resulting in a total of 69 articles. An interrater agreement of 90.9% with a reliability ?=.787 (95% CI 0.686-0.888) was reached. Large heterogeneity across study objectives, study designs, study populations, and reported results was found. Several key findings were identified. Evidence of the usefulness of clinical decision support for drug allergies has been documented. Nevertheless, there are some important problems associated with their use. Accurate and structured documenting of information on drug allergies in electronic health records (EHRs) is difficult, as it is often not clear to healthcare providers how and where to document drug allergies. Besides the underreporting of drug allergies, outdated or inaccurate drug allergy information in EHRs poses an important problem. Research on the use of coding terminologies for documenting drug allergies is sparse. There is no generally accepted standard terminology for structured documentation of allergy information. The final key finding is the consistently reported low specificity of drug allergy alerts. Current systems have high alert override rates of up to 90%, leading to alert fatigue. Important challenges remain for increasing the specificity of drug allergy alerts. We found only one study specifically reporting outcomes related to CDSS for drug allergies. It showed that adverse drug events resulting from overridden drug allergy alerts do not occur frequently.ConclusionsAccurate and comprehensive recording of drug allergies is required for good use of CDSS for drug allergy screening. We found considerable variation in the way drug allergy are recorded in EHRs. It remains difficult to reduce drug allergy alert overload while maintaining patient safety as the highest priority. Future research should focus on improving alert specificity, thereby reducing override rates and alert fatigue. Also, the effect on patient outcomes and cost-effectiveness should be evaluated.

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:PurposePalliative radiation therapy (RT) can improve quality of life but also incurs time and financial costs. The aim of this study was to evaluate factors associated with use and intensity of palliative RT for incurable non-small cell lung cancer (NSCLC).Methods and materialsThis was a retrospective analysis of Medicare's Surveillance, Epidemiology and End Results data. We identified patients who were diagnosed with incurable (American Joint Committee on Cancer 6th edition stage IIIB with malignant effusion or stage IV) NSCLC between 2004 and 2011. Univariable and multivariable logistic regressions were used to identify factors associated with the receipt of palliative RT and the use of >10 fractions during the first course of radiation. Among patients who were treated with radiation, freestanding versus hospital-based center information was collected on the basis of the location of the RT delivery claim.ResultsAmong 55,258 patients with incurable NSCLC, 38% (21,053 patients) received palliative RT during the first year after diagnosis. Among patients who received RT, 56% (11,717 patients) received >10 fractions. On multivariable analysis, factors associated with greater RT use included younger age group (overall P < .01), lower modified Charlson comorbidity score (overall P < .01), female sex (odds ratio [OR]: 1.1; P < .01), marital status (OR: 1.1; P < .01), and chemotherapy use (OR: 3.6; P < .01). Predictors for >10 fractions were chemotherapy use (OR: 1.7; P < .01) and treatment at a freestanding versus hospital-based facility (58% vs 43%; OR: 1.7; P < .01).ConclusionsMore than a third of patients diagnosed with incurable lung cancer receive palliative RT and 56% received >10 fractions. The use of RT varied by region and patient characteristics, and patients treated at freestanding RT centers were more likely to receive >10 fractions. Further research into factors that influence treatment decisions including potential financial incentives may contribute to the high value and strategic utilization of palliative RT.

Project description:BackgroundComputerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake.MethodsMedline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression.ResultsAmong 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake: (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS.Conclusions and relevanceSystem uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects.RegistrationPre-registered on PROSPERO, CRD42018092337.

Project description:BackgroundThe use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations).MethodsWe conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes.ResultsOf 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported.ConclusionsA small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

Dataset Information

Decision support systems for incurable non-small cell lung cancer: a systematic review.

Background

Methods

Results

Conclusions

Publications

Decision support systems for incurable non-small cell lung cancer: a systematic review.

Similar Datasets

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