Dataset Information

Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.

ABSTRACT:

Background

Clinical practice patterns greatly diverge from evidence-based recommendations to manage knee osteoarthritis conservatively before resorting to surgery.

Objective

This study aimed to tailor a guideline-based computerized decision support (CDS) intervention that facilitates the conservative management of knee osteoarthritis.

Methods

Experts with backgrounds in clinical medicine, research, implementation, or health informatics suggested the most important recommendations for implementation, how to develop an implementation strategy, and how to form the CDS algorithms. In 6 focus group sessions, 8 general practitioners and 22 patients from Norway, Belgium, and Finland discussed the suggested CDS intervention and identified factors that would be most critical for the success of the intervention. The focus group moderators used the GUideline Implementation with DEcision Support checklist, which we developed to support consideration of CDS success factors.

Results

The experts prioritized 9 out of 22 recommendations for implementation. We formed the concept for 6 CDS algorithms to support implementation of these recommendations. The focus group suggested 59 unique factors that could affect the success of the presented CDS intervention. Five factors (out of the 59) were prioritized by focus group participants in every country, including the perceived potential to address the information needs of both patients and general practitioners; the credibility of CDS information; the timing of CDS for patients; and the need for personal dialogue about CDS between the general practitioner and the patient.

Conclusions

The focus group participants supported the CDS intervention as a tool to improve the quality of care for patients with knee osteoarthritis through shared, evidence-based decision making. We aim to develop and implement the CDS based on these study results. Future research should address optimal ways to (1) provide patient-directed CDS, (2) enable more patient-specific CDS within the context of patient complexity, and (3) maintain user engagement with CDS over time.

SUBMITTER: Van de Velde S

PROVIDER: S-EPMC6018233 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.

Van de Velde Stijn S Kortteisto Tiina T Spitaels David D Jamtvedt Gro G Roshanov Pavel P Kunnamo Ilkka I Aertgeerts Bert B Vandvik Per Olav PO Flottorp Signe S

JMIR research protocols 20180611 6

<h4>Background</h4>Clinical practice patterns greatly diverge from evidence-based recommendations to manage knee osteoarthritis conservatively before resorting to surgery.<h4>Objective</h4>This study aimed to tailor a guideline-based computerized decision support (CDS) intervention that facilitates the conservative management of knee osteoarthritis.<h4>Methods</h4>Experts with backgrounds in clinical medicine, research, implementation, or health informatics suggested the most important recommend ...[more]

PMID: 29891466

Similar Datasets

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:BackgroundTrials evaluating the effects of interventions usually provide little insight into the factors responsible for (lack of) changes in desired outcomes. A process evaluation alongside a trial can shed light on the mechanisms responsible for the outcomes of a trial. The aim of this study was to investigate exposure to and experiences with a computerized decision support system (CDSS) intervention, in order to gain insight into the intervention's impact and to provide suggestions for improvement.MethodsA process evaluation was conducted as part of a large-scale cluster-randomized controlled trial investigating the effects of the CDSS NHGDoc on quality of care. Data on exposure to and experiences with the intervention were collected during the trial period among participants in both the intervention and control group - whenever applicable - by means of the NHGDoc server and an electronic questionnaire. Multiple data were analyzed using descriptive statistics.ResultsNinety-nine percent (n = 229) of the included practices generated data for the NHGDoc server and 50 % (n = 116) responded to the questionnaire: both general practitioners (GPs; n = 112; 49 %) and practice nurses (PNs; n = 52; 37 %) participated. The actual exposure to the NHGDoc system and specific heart failure module was limited with 52 % of the GPs and 42 % of the PNs reporting to either never or rarely use the system. Overall, users had a positive attitude towards CDSSs. The most perceived barriers to using NHGDoc were a lack of learning capacity of the system, the additional time and work it requires to use the CDSS, irrelevant alerts, too high intensity of alerts and insufficient knowledge regarding the system.ConclusionsSeveral types of barriers may have negatively affected the impact of the intervention. Although users are generally positive about CDSSs, a large share of them is insufficiently aware of the functions of NHGDoc and, finds the decision support not always useful or relevant and difficult to integrate into daily practice. In designing CDSS interventions we suggest to more intensely involve the end-users and increase the system's flexibility and learning capacity. To improve implementation a proper introduction of a CDSS among its target group including adequate training is advocated.Trial registrationClinical trials NCT01773057 .

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.

Dataset Information

Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.

Background

Objective

Methods

Results

Conclusions

Publications

Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets