Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial

Identifying Patients at Risk for Alcohol-Exposed Pregnancies: The Importance of Addressing Multiple Risk Factors

BACKGROUND

The increasing prevalence of fetal alcohol spectrum disorders is a critical public health issue. Two behaviors, consuming alcohol and using less effective pregnancy prevention, may result in alcohol-exposed pregnancies (AEPs) in individuals who can become pregnant. In the context of alcohol screening and brief intervention (SBI) services, cutoff scores on widely used alcohol risk assessments (eg, Alcohol Use Disorders Identification Test, U.S. version [USAUDIT]) may fail to identify individuals whose relatively low alcohol consumption may still put them at risk for an AEP due to their pregnancy prevention method.

METHODS

To identify this gap in alcohol SBI service delivery, we examined data from 2 reproductive healthcare systems implementing alcohol SBI, to explore the prevalence of individuals who met both of the following risk conditions: reported any alcohol use on the USAUDIT and a pregnancy prevention method less than 88% effective. Electronic health records for individuals aged 18 to 49 presenting for preventive care in 2021 were analyzed.

RESULTS

Of 11 567 screened, 7638 reported some alcohol use, but screened at a lower-risk level and were not flagged to receive an alcohol-focused brief intervention (BI). Of these, 1477 were using a method of pregnancy prevention that was less than 88% effective. In addition, 118 of the 1676 who screened positive on the USAUDIT were using less effective contraception and did not receive a BI. In summary, the number of individuals at risk of an AEP who did not receive an alcohol BI was 1595 (13.8%) of the total patients screened for at-risk alcohol use.

CONCLUSIONS

There is a need for system modifications to assess multiple behaviors simultaneously and alert providers when a combination of behaviors increases a specific health risk, such as an AEP. Tailored alcohol BIs that include the risks/benefits of various pregnancy prevention methods to reduce AEPs provide opportunities to enhance the reach of standard alcohol SBI services.

Revolutionizing decision support: a systematic literature review of contextual implementation models for electronic health records systems

PURPOSE

This study aims to assess previously developed Electronic Health Records System (EHRS) implementation models and identify successful models for decision support.

DESIGN/METHODOLOGY/APPROACH

A systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The data sources used were Scopus, PubMed and Google Scholar. The review identified peer-reviewed papers published in the English Language from January 2010 to April 2023, targeting well-defined implementation of EHRS with decision-support capabilities in healthcare. To comprehensively address the research question, we ensured that all potential sources of evidence were considered, and quantitative and qualitative studies reporting primary data and systematic review studies that directly addressed the research question were included in the review. By including these studies in our analysis, we aimed to provide a more thorough and reliable evaluation of the available evidence.

FINDINGS

The findings suggest that the success of EHRS implementation is determined by organizational and human factors rather than technical factors alone. Successful implementation is dependent on a suitable implementation framework and management of EHRS. The review identified the capabilities of Clinical Decision Support (CDS) tools as essential in the effectiveness of EHRS in supporting decision-making.

ORIGINALITY/VALUE

This study contributes to the existing literature on EHRS implementation models and identifies successful models for decision support. The findings can inform future implementations and guide decision-making in healthcare facilities.

Development of a website for wound assessment

INTRODUCTION

The assessment and treatment of wounds are nurses' and their teams' responsibilities, as it is up to the nurses to outline a therapeutic plan for tissue repair. For the evaluation process, the nurse must be scientifically trained and use reliable instruments.

OBJECTIVE

Website development for wound assessment.

MATERIALS AND METHODS

This is a methodological study that developed a website to evaluate wounds based on an assessment questionnaire called Expected Results of the Evaluation of Chronic Wound Healing (RESVECH 2.0), which consists of an adapted and validated instrument.

RESULTS

The website construction followed the basic flowchart of elaboration. To use it, the professionals create their login and subsequently register their patients. Then, they answer six questionnaires that form the evaluation process according to RESVECH 2.0. The website allows nurses to monitor the patient's evolution through graphs and previous assessments that are filed in a database. For the evaluation process, the professional needs to have a technological internet-accessed device, such as a tablet or cell phone, in order to make wound care assistance more practical and efficient.

CONCLUSION

the findings demonstrate the importance of adding technology to assistance in the treatment of wounds and may provide more qualified service and more resolutive treatment.

Examining clinician choice to follow-up (or not) on automated notifications of medication non-adherence by clinical decision support systems

BACKGROUND

Maintaining medication adherence can be challenging for people living with mental ill-health. Clinical decision support systems (CDSS) based on automated detection of problematic patterns in Electronic Health Records (EHRs) have the potential to enable early intervention into non-adherence events ("flags") through suggesting evidence-based courses of action. However, extant literature shows multiple barriers-perceived lack of benefit in following up low-risk cases, veracity of data, human-centric design concerns, etc.-to clinician follow-up in real-world settings. This study examined patterns in clinician decision making behaviour related to follow-up of non-adherence prompts within a community mental health clinic.

METHODS

The prompts for follow-up, and the recording of clinician responses, were enabled by CDSS software (AI²). De-identified clinician notes recorded after reviewing a prompt were analysed using a thematic synthesis approach-starting with descriptions of clinician comments, then sorting into analytical themes related to design and, in parallel, a priori categories describing follow-up behaviours. Hypotheses derived from the literature about the follow-up categories' relationships with client and medication-subtype characteristics were tested.

RESULTS

The majority of clients were Not Followed-up (n = 260; 78%; Followed-up: n = 71; 22%). The analytical themes emerging from the decision notes suggested contextual factors-the clients' environment, their clinical relationships, and medical needs-mediated how clinicians interacted with the CDSS flags. Significant differences were found between medication subtypes and follow-up, with Anti-depressants less likely to be followed up than Anti-Psychotics and Anxiolytics (χ² = 35.196, 44.825; p < 0.001; v = 0.389, 0.499); and between the time taken to action Followed-up₀ and Not-followed up₁ flags (M₀ = 31.78; M₁ = 45.55; U = 12,119; p < 0.001; η² = .05).

CONCLUSION

These analyses encourage actively incorporating the input of consumers and carers, non-EHR data streams, and better incorporation of data from parallel health systems and other clinicians into CDSS designs to encourage follow-up.

Clinical Research Integration Within the Electronic Health Record: A Literature Review

Clinical trials have become commonplace as a treatment option. As clinical trial participants are integrated into all healthcare delivery settings, organizations are tasked with sustaining specific care regimens with appropriate documentation and maintenance of participant protections within electronic health records. Our aim was to identify the common elements necessary for electronic health record integration of clinical research for optimal trial conduct and participant management. Review of literature was conducted utilizing PubMed and CINAHL to identify relevant publications that described use of the electronic health record to directly support trial conduct, with a total of 15 publications ultimately meeting inclusion criteria. Three thematic groupings emerged that categorized common aspects of clinical research integration: functional, structural, and procedural components. These components include technological requirements (platform/system), regulatory and legal compliance, and stakeholder involvement with clinical trial procedures (recruitment of participants). Without a centralized means of providing clinicians with current treatment and adverse event management information, participant injury or likelihood of withdrawal will increase. Further research is required to develop an optimal model of research-related integration within commercial electronic health records.

Electronic clinical decision support to facilitate a change in clinical practice: Small details can make or break success

BACKGROUND

The use of electronic clinical decision support (CDS) is becoming common to change historically common clinical practices considered outdated by current guidelines. Preimplementation design of CDS tools is key to their success in changing clinical behaviors. Unfortunately, there are no established protocols for CDS tool development, and CDS failure can result from even small design flaws. This paper describes an example of a design oversight and how correction resulted in CDS success.

STUDY DESIGN AND METHODS

We performed a retrospective review of compliance with a CDS tool to encourage the use of prothrombin complex concentrate over plasma transfusion for the emergent reversal of warfarin. We identified a potential design flaw, made the necessary modifications, and repeated the compliance review.

RESULTS

After CDS, plasma orders declined by 150 units/mo; however, 48% of orders placed for non-warfarin coagulopathy were still for warfarin reversal. Hospital-wide, this noncompliance was 36% and was 80% in the emergency department. By simply relocating the qualifier "NOT on warfarin" from the end to the beginning of the order, noncompliance for warfarin reversal was reduced to 5% (P < .0001 by chi-square).

CONCLUSIONS

The successful use of electronic clinical decision support in the electronic medical record can depend on optimal design. Missing even small design elements such as the positioning of key terms within the tool can result in an ineffective CDS. Important design strategies to avoid poor performance are discussed as they relate to the CDS tool we describe.

Twenty-five years after the introduction of Evidence-based Medicine: knowledge, use, attitudes and barriers among physiotherapists in Italy - a cross-sectional study

OBJECTIVES

To explore the knowledge, use, attitudes towards Evidence-based Medicine, also known as Evidence-based Practice (EBP), and perceived barriers to its dissemination among physiotherapists.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

Members of the Italian Association of Physiotherapists (n=2000) were invited to participate in an online survey about EBP knowledge and use.

PRIMARY OUTCOME MEASURES

The survey questionnaire comprised four sections: (1) respondent characteristics; (2) knowledge of EBP principles; (3) attitude, use and perceived effectiveness of EBP; (4) perceived barriers to implementing EBP in clinical practice.

RESULTS

Out of 2000 physiotherapists, 1289 participated in the survey (64.5% response rate). Overall, 90% perceived EBP as useful and necessary for their clinical practice. More than 85% stated that they were familiar with the principles of EBP, 75% reported that they were able to search online databases for relevant information and 60% reported that they were able to understand statistical analyses. However, 56% believed that patient preferences and 39% that clinical expertise are not part of the EBP model. Half stated that they understood and could explain the term 'meta-analysis' but only 17% knew what a forest plot is and just 20% correctly judged the finding of a given meta-analysis. Lack of time was reported as the main barrier to EBP.

CONCLUSION

The majority of Italian physiotherapists overrated their knowledge about EBP, demonstrating a gap between perceived and actual knowledge of EBP in this population.

Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study

BACKGROUND

Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs.

METHODS

A mixed-method combining the Delphi technique and Analytic Hierarchy Process was used. Potentially important items were collected after a thorough search of the literature and from interviews with key contact experts (n = 19). Opinions and views of the 76 panelists on the use of EHRs were also explored. Iterative Delphi rounds were conducted to achieve consensus on 122 potentially important items by a panel of 76 participants. Items on which consensus was achieved were ranked in the order of their importance using the Analytic Hierarchy Process.

RESULTS

Of the 122 potentially important items presented to the panelists in the Delphi rounds, consensus was achieved on 110 (90.2%) items. Of these, 16 (14.5%) items were related to the demographic characteristics of the patient, 16 (14.5%) were related to prescribing medications, 16 (14.5%) were related to checking prescriptions and alerts, 14 (12.7%) items were related to the patient's identity, 13 (11.8%) items were related to patient assessment, 12 (10.9%) items were related to the quality of alerts, 11 (10%) items were related to admission and discharge of the patient, 9 (8.2%) items were general features, and 3 (2.7%) items were related to diseases and making diagnosis.

CONCLUSIONS

In this study, merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs were explored. Considering items on which consensus was achieved might promote congruence and safe use of EHRs. Further studies are still needed to determine if these recommendations can improve patient safety and outcomes in Palestinian hospitals.

Sustainable Change Management through Employee Readiness: Decision Support System Adoption in Technology-Intensive British E-Businesses

Technology brings green sustainable management practices to the workplace. It is important to ascertain the factors that enable or inhibit employees’ perceptions towards technology adoption. Corporate sustainability and sustainable management practices partially depend on employees for the successful implementation of technological changes in the workplace. This study aims at applying the technology acceptance model (TAM) from an employees’ user-perspective. It addresses those factors that form employee readiness for e-business and enable their intention to use e-business technologies such as decision support systems (DSS). It focuses on technology intensive firms while combining Davis’ technology acceptance model and Lai and Ong’s employee readiness for e-business (EREB) model. A survey questionnaire was used to collect the data for this cross-sectional study from 331 employees of 28 well-established small and medium-sized e-businesses located in the United Kingdom. The outcomes show that the four dimensions of EREB explain the 58.2% of variance in perceived ease of use and the 50.2% of variance in perceived usefulness. Together, perceived usefulness and perceived ease of use explain the 51.8% of variance in intention to use while fully mediating the relationship between higher order EREB construct and intention to use DSS.

Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System

BACKGROUND

Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014.

METHODS

Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year.

RESULTS

The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003).

DISCUSSION AND CONCLUSIONS

The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation

BACKGROUND

Advanced Computerized Decision Support Systems (CDSSs) assist clinicians in their decision-making process, generating recommendations based on up-to-date scientific evidence. Although this technology has the potential to improve the quality of patient care, its mere provision does not guarantee uptake: even where CDSSs are available, clinicians often fail to adopt their recommendations. This study examines the barriers and facilitators to the uptake of an evidence-based CDSS as perceived by diverse health professionals in hospitals at different stages of CDSS adoption.

METHODS

Qualitative study conducted as part of a series of randomized controlled trials of CDSSs. The sample includes two hospitals using a CDSS and two hospitals that aim to adopt a CDSS in the future. We interviewed physicians, nurses, information technology staff, and members of the boards of directors (n = 30). We used a constant comparative approach to develop a framework for guiding implementation.

RESULTS

We identified six clusters of experiences of, and attitudes towards CDSSs, which we label as "positions." The six positions represent a gradient of acquisition of control over CDSSs (from low to high) and are characterized by different types of barriers to CDSS uptake. The most severe barriers (prevalent in the first positions) include clinicians' perception that the CDSSs may reduce their professional autonomy or may be used against them in the event of medical-legal controversies. Moving towards the last positions, these barriers are substituted by technical and usability problems related to the technology interface. When all barriers are overcome, CDSSs are perceived as a working tool at the service of its users, integrating clinicians' reasoning and fostering organizational learning.

CONCLUSIONS

Barriers and facilitators to the use of CDSSs are dynamic and may exist prior to their introduction in clinical contexts; providing a static list of obstacles and facilitators, irrespective of the specific implementation phase and context, may not be sufficient or useful to facilitate uptake. Factors such as clinicians' attitudes towards scientific evidences and guidelines, the quality of inter-disciplinary relationships, and an organizational ethos of transparency and accountability need to be considered when exploring the readiness of a hospital to adopt CDSSs.

COMBAT study - Computer based assessment and treatment - A clinical trial evaluating impact of a computerized clinical decision support tool on pain in cancer patients

BACKGROUND AND AIMS

The prevalence of pain in cancer patients are relatively high and indicate inadequate pain management strategies. Therefore, it is necessary to develop new methods and to improve implementation of guidelines to assess and treat pain. The vast improvement in information technology facilitated development of a computerized symptom assessment and decision support system (CCDS) - the Combat system - which was implemented in an outpatient cancer clinic to evaluate improvement in pain management.

METHODS

We conducted a controlled before-and-after study between patient cohorts in two consecutive study periods: before (n=80) and after (n=134) implementation of the Combat system. Patients in the first cohort completed questionnaires with the paper-and-pencil method and this data was not shown to physicians. Patients in the latter cohort completed an electronic questionnaire by using an iPad and the data were automatically transferred and presented to physicians at point of care. Additionally, the system provided computerized decision support at point of care for the physician based on the electronic questionnaires completed by the patients, an electronic CRF completed by physicians and clinical guidelines.

RESULTS

The Combat system did not improve pain intensity and there were no significant alterations in the prescribed dose of opiates compared to the cohort of patients managed without the Combat system.

CONCLUSION

The Combat system did not improve pain management. This may be explained by several factors, however, we consider lack of proper implementation of the CCDS in the clinic to be the most important factor. As a result, we did not manage to change the behaviour of the physicians in the clinic.

IMPLICATIONS

There is a need to conduct larger prospective studies to evaluate the efficacy of modern information technology to improve pain management in cancer patients. Before introducing new information technology in the clinics, it is important to have a well thought out implementation strategy. The trial is registered at Clinialtrials.gov, number NCT01795157.

Comprehensible knowledge model creation for cancer treatment decision making

BACKGROUND

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making.

MATERIALS AND METHODS

An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support.

RESULTS

Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules.

CONCLUSION

Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education.