A review of randomized controlled trials of medical record powered clinical decision support system to improve quality of diabetes care

Ali, Syed Mustafa; Giordano, Richard; Lakhani, Saima; Walker, Dawn‐Marie

doi:10.1016/j.ijmedinf.2015.12.017

Cited by 61 publications

(51 citation statements)

References 19 publications

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“…However, it is also noted that in the developing country context, a prerequisite to the success of mHealth interventions is the consideration of developers and implementers about the field workers' expectations, needs and work settings [29,30]. Moreover, a gap between the work practices and use of the new technologies is attributed by the poor implementation design of the technology-based interventions [31].…”

Section: Discussionmentioning

confidence: 99%

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

Ali¹,

Powers

Beorse

et al. 2016

Future Internet

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Abstract:The present grievous tuberculosis situation can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology, this can be achieved through quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during a testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, the application and 3G-enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to determine the impact of ODK Scan. Additionally, at the end of the study, users' feedback was collected regarding app usability, user interface design and workflow changes. A total of 122 patients' records were retrieved from the server and analysed in terms of quality. It was found that ODK Scan recognized 99.2% of multiple choice fill-in bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, but data verification and form-filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, but they were more concerned about the time-consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

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Section: Discussionmentioning

confidence: 99%

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

Ali¹,

Powers

Beorse

et al. 2016

Future Internet

View full text Add to dashboard Cite

show abstract

“…Moreover, a gap between the work practices and use of the new technologies is attributed by the poor implementation design of the technology-based interventions. [20] In the Public-Private Mix model of the TB control program of Pakistan, despite available direct-to-digital data collection solutions, the ODK Scan paper-to-digital system was chosen because of the current healthcare system requirement. Largely, the healthcare system relies on the paper-based records for recording, reporting, verification, validation and other purposes.…”

Section: Discussionmentioning

confidence: 99%

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in the Tuberculosis Control Program of Pakistan

Ali¹,

Powers²,

Beorse³

et al. 2016

Preprint

Self Cite

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Abstract:The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users' feedback was collected regarding app usability, user interface design and workflow changes. 122 patients' records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

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“…Achieving real-world practice change takes a long time and is often incomplete [35][36][37]. EHR-based CDS has been shown to improve clinical process measures across multiple clinical domains [38][39][40][41][42][43][44][45][46][47][48]. Yet current guidelines can be difficult to implement as point-of-care CDS, to help "make the right thing the easy thing to do" for busy clinicians within their daily work tool, the EHR [49][50][51][52][53].…”

Section: Authoring Practice Guidelines and Ecqms For Streamlined Implmentioning

confidence: 99%

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets (Preprint)

Chu¹,

Kannan²,

Basit³

et al. 2018

Preprint

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Background: Defining clinical phenotypes from EHR-derived data proves crucial for clinical decision support, population health endeavors, and translational research. EHR diagnoses now commonly draw from a finely-grained clinical terminologyeither native SNOMED CT, or a vendor-supplied terminology mapped to SNOMED CT concepts as the standard for EHR interoperability. Accordingly, electronic clinical quality measures (eCQMs) increasingly define clinical phenotypes with SNOMED CT value sets. The work of creating and maintaining list-based value sets proves daunting, as does vetting that their contents accurately represent the clinicallyintended condition. Objective: To compare an intensional (concept hierarchy-based) vs. extensional (list-based) value set approach to defining clinical phenotypes using SNOMED CT encoded data from EHRs, by evaluating value set conciseness, time to create, and completeness. Methods: Starting from published CMS 2018 high-priority eCQMs, we selected ten clinical conditions referenced by those eCQMs. For each, the published SNOMED CT list-based (extensional) value set was downloaded from the Value Set Authority Center (VSAC). Ten corresponding SNOMED CT hierarchy-based intensional value sets for the same conditions were identified within our EHR. From each hierarchybased intensional value set, an exactly equivalent full extensional value set was derived enumerating all included descendant SNOMED CT concepts. Comparisons were then made between (a) (VSAC) downloaded list-based (extensional) value sets, (b) corresponding hierarchy-based intensional value sets for the same conditions, and (c) derived list-based (extensional) value sets exactly equivalent to the hierarchy-based intensional value sets. Value set conciseness was assessed by the number of SNOMED CT concepts needed for definition. Time to construct the value sets for local use was measured. Value set completeness was assessed by comparing contents of the downloaded extensional vs. intensional value sets. Two measures of content completeness were made: for individual SNOMED CT concepts, and for the mapped diagnosis clinical terms available for selection within the EHR by clinicians. Results: The 10 hierarchy-based intensional value sets proved far simpler and faster to construct than exactly equivalent derived extensional value set lists, requiring a median 3 vs. 78 concepts to define, and 5 vs. 37 min to build. The hierarchy-based intensional value sets also proved more complete: in comparison, the 10 downloaded 2018 extensional value sets contained a median of just 35% of the intensional value sets' SNOMED CT concepts and 65% of mapped EHR clinical terms. Conclusions: In the EHR era, defining conditions preferentially should employ SNOMED CT concept hierarchy-based (intensional) value sets, rather than 1 extensional lists. By doing so, clinical guideline and eCQM authors can more readily engage specialists in vetting condition subtypes to include and exclude, and streamline broad EHR implementation of condition-specific ...

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A review of randomized controlled trials of medical record powered clinical decision support system to improve quality of diabetes care

Cited by 61 publications

References 19 publications

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in the Tuberculosis Control Program of Pakistan

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets (Preprint)

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