Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus

Wei, Igor; Pappas, Yannis; Car, Josip; Sheikh, Aziz; Majeed, Azeem

doi:10.1002/14651858.cd008488.pub2

“…We screened 493 reviews after removal of duplicates. Based on their titles and abstracts, a total of 82 reviews met the inclusion criteria and made up the data set 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 . The 82 relevant CSRs included 1177 RCTs.…”

Section: Resultsmentioning

confidence: 99%

An assessment of randomized controlled trials (RCTs) for non-communicable diseases (NCDs): more and higher quality research is required in less developed countries

Hong

¹

2015

Sci Rep

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Research is crucial to implement evidence-based health interventions for control of non-communicable diseases (NCDs). This study aims to assess main features of randomized controlled trials (RCTs) for control of NCDs, and to identify gaps in clinical research on NCDs between high-income and less developed countries. The study included 1177 RCTs in 82 Cochrane Systematic reviews (CSRs) and evaluated interventions for adults with hypertension, diabetes, stroke, or heart diseases. Multivariate logistic regression analyses were conducted to explore factors associated with risk of bias in included RCTs. We found that 78.2% of RCTs of interventions for major NCDs recruited patients in high-income countries. The number of RCTs included in the CSRs was increasing over time, and the increasing speed was more noticeable for RCTs conducted in middle-income countries. RCTs conducted in less developed countries tended to be more recently published, less likely to be published in English, with smaller sample sizes, and at a higher risk of bias. In conclusion, there is still a lack of research evidence for control of NCDs in less developed countries. To brace for rising NCDs and avoid waste of scarce research resources, not only more but also higher quality clinical trials are required in low-and-middle-income countries.

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“…A purposeful sample of articles was included based on relevance to build the Results and Discussion section. Robust evidence regarding CAHT and DMIA systems and their impact on the medical consultation was limited, as most studies evaluating these systems focused on other aspects, such as acquiring dietary or family history to estimate risk for diabetes, studies evaluating computer-assisted data collection for specific populations or related to screening, studies evaluating the test-retest reliability of computer-based medical histories, or efforts to generally computerize medicine, just to give some examples [ 13 - 18 ]. Relevant insights that were most useful for our purposes came mainly from commentaries, perspectives, and historical pieces [ 2 , 3 , 19 ], some of which analyzed or identified existing CAHT and DMIA software programs [ 1 , 20 , 21 ].…”

Section: Methodsmentioning

confidence: 99%

Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review

Jiménez

¹

,

Tyagi

²

,

Osman

³

et al. 2020

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Background Digital medical interview assistant (DMIA) systems, also known as computer-assisted history taking (CAHT) systems, have the potential to improve the quality of care and the medical consultation by exploring more patient-related aspects without time constraints and, therefore, acquiring more and better-quality information prior to the face-to-face consultation. The consultation in primary care is the broadest in terms of the amount of topics to be covered and, at the same time, the shortest in terms of time spent with the patient. Objective Our aim is to explore how DMIA systems may be used specifically in the context of primary care, to improve the consultations for diabetes and depression, as exemplars of chronic conditions. Methods A narrative review was conducted focusing on (1) the characteristics of the primary care consultation in general, and for diabetes and depression specifically, and (2) the impact of DMIA and CAHT systems on the medical consultation. Through thematic analysis, we identified the characteristics of the primary care consultation that a DMIA system would be able to improve. Based on the identified primary care consultation tasks and the potential benefits of DMIA systems, we developed a sample questionnaire for diabetes and depression to illustrate how such a system may work. Results A DMIA system, prior to the first consultation, could aid in the essential primary care tasks of case finding and screening, diagnosing, and, if needed, timely referral to specialists or urgent care. Similarly, for follow-up consultations, this system could aid with the control and monitoring of these conditions, help check for additional health issues, and update the primary care provider about visits to other providers or further testing. Successfully implementing a DMIA system for these tasks would improve the quality of the data obtained, which means earlier diagnosis and treatment. Such a system would improve the use of face-to-face consultation time, thereby streamlining the interaction and allowing the focus to be the patient's needs, which ultimately would lead to better health outcomes and patient satisfaction. However, for such a system to be successfully incorporated, there are important considerations to be taken into account, such as the language to be used and the challenges for implementing eHealth innovations in primary care and health care in general. Conclusions Given the benefits explored here, we foresee that DMIA systems could have an important impact in the primary care consultation for diabetes and depression and, potentially, for other chronic conditions. Earlier case finding and a more accurate diagnosis, due to more and better-quality data, paired with improved monitoring of disease progress should improve the quality of care and keep the management of chronic conditions at the primary care level. A somewhat simple, easily scalable technology could go a long way to improve the health of the millions of people affected with chronic conditions, especially if working in conjunction with already-established health technologies such as electronic medical records and clinical decision support systems.

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“…A purposeful sample of articles was included based on relevance to build the Results and Discussion section. Robust evidence regarding CAHT and DMIA systems and their impact on the medical consultation was limited, as most studies evaluating these systems focused on other aspects, such as acquiring dietary or family history to estimate risk for diabetes, studies evaluating computer-assisted data collection for specific populations or related to screening, studies evaluating the test-retest reliability of computer-based medical histories, or efforts to generally computerize medicine, just to give some examples [13][14][15][16][17][18].…”

Section: Methodsmentioning

confidence: 99%

Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review (Preprint)

Jiménez¹,

Tyagi²,

Osman³

et al. 2020

Preprint

Self Cite

1

0

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BACKGROUND Digital medical interview assistant (DMIA, also known as computer-assisted history taking (CAHT)) systems have the potential to improve the quality of care and the medical consultation by exploring more patient-related aspects without time constraints, and therefore acquiring more and better quality information, prior to the face-to-face consultation. The consultation in primary care (PC) is the broadest in terms of the amount of topics to be covered and, at the same time, the shortest in term of time spent with the patient. OBJECTIVE To explore how DMIA systems may be used specifically in the context of PC, to improve the consultations for diabetes and depression, as exemplars of chronic conditions. METHODS A narrative review was conducted focusing on (1) the characteristics of the PC consultation in general and for diabetes and depression specifically, and on (2) the impact of DMIA/CAHT systems on the medical consultation. Through thematic analysis, we identified the characteristics of the PC consultation that a DMIA system would be able to improve. Based on the identified PC consultation tasks and the potential benefits of DMIA systems, we developed a sample questionnaire for diabetes and depression to illustrate how such a system may work. RESULTS A DMIA system, prior to the first consultation, could aid in the essential PC tasks of case finding/screening, diagnosing and, if needed, timely referral to specialists or urgent care. Similarly, for follow-up consultations, it could aid with the control/monitoring of these conditions, help check for additional health issues and for updating the PC provider about visits to other providers or further testing. Successfully implementing a DMIA system for these tasks would improve the quality of the data obtained, which means earlier diagnosis and treatment; would improve the use of face-to-face consultation time, streamlining the interaction and allowing the focus to be the patient's needs, which ultimately would lead to better health outcomes and patient satisfaction. However, for such a system to be successfully incorporated, there are important considerations to be taken into account, such as the language to be used and the challenges for implementing eHealth innovations in PC and healthcare in general. CONCLUSIONS Given the benefits explored here, we foresee that DMIA systems could have an important impact in the PC consultation for diabetes and depression and, potentially, for other chronic conditions. Earlier case finding and a more accurate diagnosis, due to more and better-quality data, paired with improved monitoring of disease progress, should improve the quality of care and keep the management of chronic conditions at the primary care level. A somewhat simple, easily scalable technology could go a long way to improve the health of the millions of people affected with chronic conditions, especially if working in conjunction with already established health technologies such as EMRs and CDSS. CLINICALTRIAL

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Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus

Abstract: Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus.

Cited by 9 publications

References 38 publications

An assessment of randomized controlled trials (RCTs) for non-communicable diseases (NCDs): more and higher quality research is required in less developed countries

An assessment of randomized controlled trials (RCTs) for non-communicable diseases (NCDs): more and higher quality research is required in less developed countries

Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review

Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review (Preprint)

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