Clinical Decision Support Systems to Identify Drug-Related Problems in Diabetes Mellitus Patients: A Systematic Review
Keywords:
clinical decision support systems, drug-related problems, diabetes mellitus
Abstract
Clinical Decision Support Systems (CDSSs) has been developed for utilization to provide rational therapy to Diabetes Mellitus (DM) patients including preventing Drug-related Problems (DRPs) such as the effect of drug treatment being not optimal, untreated indications and symptoms, unnecessary therapy, and adverse drug reactions. This study aims to summarize the available evidence on the intervention of CDSSs, key outputs, and impact of the user in DM patients. This study was a systematic review using PubMed, Scopus database, and by manually searching the bibliographies of articles that have been found. We included studies reporting on evaluated CDSSs that had been implemented in medication prescription, reducing medication errors, adverse drug events, drug-allergy checking, drug dosing support, and so on. A total of 8 studies were selected among 855 studies. CDSSs are used in hospitals and primary care settings to identify potential drug interactions, correct therapy regimens, monitor therapy, blood glucose documentation, ensure patients receive medication according to the guideline, provide nutritional advice, and schedule physical activity. The usage of CDSSs improves blood glucose levels, detects possible drug interactions, reduces face-to-face consultations, improves documentation, assists in identifying dose, and promotes prescribing in line with the guideline. The use of CDSSs can help to reduce the risk of errors in management therapy.
References
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Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Plank, J., Neubauer, K. M., Baumgartner, C., & Pieber, T. R. (2016). Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study. International Journal of Medical Informatics, 90, 58–67. https://doi.org/10.1016/j.ijmedinf.2016.03.007
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Kart, Ö., Mevsim, V., Kut, A., Yürek, İ., Altın, A. Ö., & Yılmaz, O. (2017). A Mobile and Web-Based Clinical Decision Support and Monitoring System for Diabetes Mellitus Patients in Primary Care: a study protocol for a randomized controlled trial. BMC Medical Informatics and Decision Making, 17(154). https://doi.org/10.1186/s12911-017-0558-6
Kesavadev, J., Krishnan, G., & Mohan, V. (2021). Digital health and diabetes: experience from India. Therapeutic Advances in Endocrinology and Metabolism, 12, 1–13. https://doi.org/https://doi.org/10.1177/20420188211054676
Kim, B. Y., Sharafoddini, A., Tran, N., Wen, E. Y., & Lee, J. (2018). Consumer Mobile Apps for Potential Drug-Drug Interaction Check: Systematic Review and Content Analysis Using the Mobile App Rating Scale (MARS). JMIR MHealth and UHealth, 6(3). https://doi.org/10.2196/mhealth.8613
Kiyani, S., Abasi, S., Koohjani, Z., & Aslani, A. (2020). Technical Requirement of Clinical Decision Support System for Diabetic Patients. Frontiers in Health Informatics, 9(31). https://doi.org/http://dx.doi.org/10.30699/fhi.v9i1.217
Mazzaglia, G., Piccinni, C., Filippi, A., Sini, G., Lapi, F., Sessa, E., Cricelli, I., Cutroneo, P., Trifirò, G., & Cricelli, C. (2016). Effects of a computerized decision support system in improving pharmacological management in high-risk cardiovascular patients: A cluster-randomized open-label controlled trial. Health Informatics Journal, 22(2), 232–247.
Mazzaglia, G., Piccinni, C., Filippi, A., Sini, G., Lapi, F., Sessa, E., Cricelli, I., Cutroneo, P., Trifirò, G., Cricelli, C., & Caputi, A. P. (2016). Effects of a computerized decision support system in improving pharmacological management in high-risk cardiovascular patients: A cluster-randomized open-label controlled trial. Health Informatics Journal, 22(2), 232–247. https://doi.org/10.1177/1460458214546773
Moghadam, S. T., Sadoughi, F., Velayati, F., Ehsanzadeh, S. J., & Poursharif, S. (2021). The Efects of Clinical Decision Support System for Prescribing Medication on Patient Outcomes and Physician Practice Performance: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making, 21(98). https://doi.org/https://doi.org/10.1186/s12911-020-01376-8
Murphy, M. E., McSharry, J., Byrne, M., Boland, F., Corrigan, D., Gillespie, P., Fahey, T., & Smith, S. M. (2020). Supporting Care for Suboptimally Controlled Type 2 Diabetes Mellitus in General Practice with a Clinical Decision Support System: a mixed methods pilot cluster randomised trial. BMJ Open, 10. https://doi.org/doi. org/10.1136/bmjopen-2019- 032594
Neubauer, K. M., Mader, J. K., Höll, B., Aberer, F., Donsa, K., Augustin, T., Schaupp, L., Spat, S., Beck, P., & Fruhwald, F. M. (2015). Standardized glycemic management with a computerized workflow and decision support system for hospitalized patients with type 2 diabetes on different wards. Diabetes Technology & Therapeutics, 17(10), 685–692. https://pubmed.ncbi.nlm.nih.gov/26355756/
O’Connor, P. J., Sperl-Hillen, J. M., Fazio, C. J., Averbeck, B. M., Rank, B. H., & Margolis, K. L. (2016). Outpatient Diabetes Clinical Decision Support: current status and future directions. Diabetes Medicine, 33(6). https://doi.org/https://doi.org/10.1111/dme.13090
Ota, S., Mogushi, K., Hirai, A., Niimura, Y., & Tanaka, H. (2018). Improvements in Diabetic Patients’ Outcomes in a Clinical Decision Support System. European Journal of Biomedical Informatics, 14(1), 29–36. https://www.ejbi.org/scholarly-articles/improvements-in-diabetic-patients-outcomes-in-a-clinical-decision-support-system.pdf
Pérez-Gandía, C., García-Sáez, G., Subías, D., Rodríguez-Herrero, A., Gómez, E. J., Rigla, M., & Hernando, M. E. (2018). Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor. Journal of Diabetes Science and Technology, 12(2), 243–250. https://doi.org/10.1177/1932296818761457
Pichardo-Lowden, A. R. (2021). Clinical Decision Support for Diabetes Care in the Hospital: A Time for Change Toward Improvement of Management and Outcomes. Journal of Diabetes Science and Technology. https://doi.org/10.1177/1932296820982661
Pichardo-Lowden, A., Umpierrez, G., Lehman, E. B., Bolton, M. D., DeFlitch, C. J., Chinchilli, V. M., & Haidet, P. M. (2020). Clinical Decision Support to Improve Management of Diabetes and Dysglycemia in the Hospital: a path to optimizing practice and outcomes. BMJ Open Diabetes Research & Care, 9. https://doi.org/doi:10.1136/ bmjdrc-2020-001557
Robertson, L. A., Mclean, M.-A., Sardar, C. M., Bryson, G., & Kurdi, A. (2020). Evaluation of the prescribing decision support systemSynonymsin a primary care setting: a mixed-method study. International Journal of Pharmacy Practice, 28, 473–482.
Rodbard, D., & Vigersky, R. A. (2011). Design of a Decision Support System to Help Clinicians Manage Glycemia in Patients with Type 2 Diabetes Mellitus. Journal of Diabetes Science and Technologychnology, 5(2). https://doi.org/https://doi.org/10.1177/193229681100500230
Saeedi, P., Petersohn, I., Salpea, P., Malanda, B., Karuranga, S., Unwin, N., Colaguri, S., Guariguata, L., Motala, A. A., Ogurtsova, K., Shaw, J. E., Bright, D., & Williams, R. (2019). Global and Regional Diabetes Prevalence Estimatesfor 2019 and Projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practise, 157(107843). https://doi.org/https://doi.org/10.1016/j.diabres.2019.107843
Shahmoradi, L., Safdari, R., Ahmadi, H., & Zahmatkeshan, M. (2021). Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. In Medical Journal of the Islamic Republic of Iran (Vol. 35, Issue 1, pp. 1–16). https://doi.org/10.34171/mjiri.35.27
Shen, C., Jiang, B., Yang, Q., Wang, C., Lu, K. Z., Gu, M., & Yuan, J. (2021). Mobile Apps for Drug-Drug Interaction Checks in Chinese App Stores: Systematic Review and Content Analysis. JMIR MHealth and UHealth, 9(6). https://doi.org/10.2196/26262
Sim, L. L. W., Ban, K. H. K., Tan, T. W., Sethi, S. K., & Loh, T. P. (2017). Development of a Clinical Decision Support System for Diabetes Care: A pilot study. PLoS One, 12(2). https://doi.org/10.1371/journal.pone.0173021
Spat, S, Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Augustin, T., Chiarugi, F., Lichtenegger, K. M., Plank, J., & Pieber, T. R. (2017). A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients with Type 2 Diabetes Mellitus. Journal of Diabetes Science and Technology, 11(1), 20–28. https://doi.org/10.1177/1932296816676501
Spat, Stephan, Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Augustin, T., Chiarugi, F., Lichtenegger, K. M., & Plank, J. (2017). A mobile computerized decision support system to prevent hypoglycemia in hospitalized patients with type 2 diabetes mellitus: lessons learned from a clinical feasibility study. Journal of Diabetes Science and Technology, 11(1), 20–28.
Stultz, J. S., & Nahata, M. C. (2012). Computerized Clinical Decision Support for Medication Prescribing and Utilization in Pediatrics. Journal of the American Medical Informatics Association, 19(6). https://doi.org/10.1136/amiajnl-2011-000798
Wang, L., Wang, Y., Li, Z., Yu, B., & Li, Y. (2014). Unilateral Versus Bilateral Pedicle Screw Fixation of Minimally Invasive Transforaminal Lumbar Interbody Fusion (MIS-TLIF): a meta-analysis of randomized controlled trials. BMC Surgery, 14(87). https://bmcsurg.biomedcentral.com/articles/10.1186/1471-2482-14-87
Beauchemin, M., Murray, M. T., Sung, L., Hershman, D. L., Weng, C., & Schnall, R. (2020). Clinical decision support for therapeutic decision-making in cancer: A systematic review. International Journal Medical Informatics, 130. https://doi.org/10.1016/j.ijmedinf.2019.07.019
Bekele, F., Tsegaye, T., Negash, E., & Fekadu, G. (2021). Magnitude and Determinants of Drug-Related Problems among Patients Admitted to Medical Wards of Southwestern Ethiopian Hospitals: A multicenter prospective observational study. PloS One.
Berger, F. A., Van Der Sijs, H., Becker, M. L., Van Gelder, T., & Van Den Bemt, P. M. L. A. (2020). Development and validation of a tool to assess the risk of QT drug-drug interactions in clinical practice. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01181-3
Caballero-Ruiz, E., García-Sáez, G., Rigla, M., Villaplana, M., Pons, B., & Hernando, M. E. (2017). A web-based clinical decision support system for gestational diabetes: Automatic diet prescription and detection of insulin needs. International Journal of Medical Informatics, 102, 35–49. https://doi.org/10.1016/j.ijmedinf.2017.02.014
Centers for Disease Health and Human Services. (2020). National Diabetes Statistics Report.
Charpentier, G., Benhamou, P. Y., Dardari, D., Clergeot, A., Franc, S., Schaepelynck-Belicar, P., Catargi, B., Melki, V., Chaillous, L., Farret, A., Bosson, J. L., & Penfornis, A. (2011). The diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: A 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 study). Diabetes Care, 34(3), 233–239. https://doi.org/10.2337/dc10-1259
Chin, D. L., Wilson, M. H., Trask, A. S., Johnson, V. T., Neaves, B. I., Gojova, A., Hogarth, M. A., Bang, H., & Romano, P. S. (2020). Repurposing Clinical Decision Support System Data to MeasureDosing Errors and Clinician-Level Quality of Care. Journal of Medical Systems, 44.
Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Plank, J., Neubauer, K. M., Baumgartner, C., & Pieber, T. R. (2016). Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study. International Journal of Medical Informatics, 90, 58–67. https://doi.org/10.1016/j.ijmedinf.2016.03.007
Fleming, G. A., Petrie, J. R., Bergenstal, R. M., Holl, R. W., Peters, A. L., & Heinemann, L. (2020). Diabetes Digital App Technology: Benefits, Challenges, and Recommendations. A Consensus Report by the European Association for the Study of Diabetes (EASD) and the American Diabetes Association (ADA) Diabetes Technology Working Group. Diabetes Care, 43(1), 250–260.
Gibbs, J. R., Berger, K., & Falciglia, M. (2019). 1309-P: Utilizing a Clinical Decision Support System for Hypoglycemia Management. Diabetes Journal, 68. https://doi.org/https://doi.org/10.2337/db19-1309-P
Hardenbol, A. X., & Knols, B. (2020). Usability Aspects of Medication Related Decision Support Systems in the Outpatient Setting: A systematic literature review. Health Informatics Journal, 26(1), 72–87. https://doi.org/https://doi.org/10.1177/1460458218813732
International Diabetes Federation. (2017). IDF Diabetes Atlas, 8th ed.
International Diabetes Federation. (2021). Diabetes Around the World 2021. https://diabetesatlas.org/
Jadad, A. R., Moore, A., Carroll, D., Jenkinson, C., Reynolds, J. M., Gavaghan, D. J., & McQuay, H. J. (1996). Assessing the Quality of Reports of Randomized Clinical Trials: Is Blinding Necessary? Elsevier Science Inc, 17, 1–12. https://doi.org/https://doi.org/10.1016/0197-2456(95)00134-4
James, G., Kathrin, K., Turk, B., Chunshen, P., & Wenhui, M. (2019). Using Electronic Clinical Decision Support in Patient-Centered Medical Homes to Improve Management of Diabetes in Primary Care The DECIDE Study. Journal of Ambulatory Care Management, 42(2), 105–115. https://doi.org/10.1097/JAC.0000000000000267
Jia, P., Zhang, L., Chen, J., Zhao, P., & Zhang, M. (2016). The effects of clinical decision support systems on medication safety: An overview. In PLoS ONE (Vol. 11, Issue 12). https://doi.org/10.1371/journal.pone.0167683
Kart, Ö., Mevsim, V., Kut, A., Yürek, İ., Altın, A. Ö., & Yılmaz, O. (2017). A Mobile and Web-Based Clinical Decision Support and Monitoring System for Diabetes Mellitus Patients in Primary Care: a study protocol for a randomized controlled trial. BMC Medical Informatics and Decision Making, 17(154). https://doi.org/10.1186/s12911-017-0558-6
Kesavadev, J., Krishnan, G., & Mohan, V. (2021). Digital health and diabetes: experience from India. Therapeutic Advances in Endocrinology and Metabolism, 12, 1–13. https://doi.org/https://doi.org/10.1177/20420188211054676
Kim, B. Y., Sharafoddini, A., Tran, N., Wen, E. Y., & Lee, J. (2018). Consumer Mobile Apps for Potential Drug-Drug Interaction Check: Systematic Review and Content Analysis Using the Mobile App Rating Scale (MARS). JMIR MHealth and UHealth, 6(3). https://doi.org/10.2196/mhealth.8613
Kiyani, S., Abasi, S., Koohjani, Z., & Aslani, A. (2020). Technical Requirement of Clinical Decision Support System for Diabetic Patients. Frontiers in Health Informatics, 9(31). https://doi.org/http://dx.doi.org/10.30699/fhi.v9i1.217
Mazzaglia, G., Piccinni, C., Filippi, A., Sini, G., Lapi, F., Sessa, E., Cricelli, I., Cutroneo, P., Trifirò, G., & Cricelli, C. (2016). Effects of a computerized decision support system in improving pharmacological management in high-risk cardiovascular patients: A cluster-randomized open-label controlled trial. Health Informatics Journal, 22(2), 232–247.
Mazzaglia, G., Piccinni, C., Filippi, A., Sini, G., Lapi, F., Sessa, E., Cricelli, I., Cutroneo, P., Trifirò, G., Cricelli, C., & Caputi, A. P. (2016). Effects of a computerized decision support system in improving pharmacological management in high-risk cardiovascular patients: A cluster-randomized open-label controlled trial. Health Informatics Journal, 22(2), 232–247. https://doi.org/10.1177/1460458214546773
Moghadam, S. T., Sadoughi, F., Velayati, F., Ehsanzadeh, S. J., & Poursharif, S. (2021). The Efects of Clinical Decision Support System for Prescribing Medication on Patient Outcomes and Physician Practice Performance: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making, 21(98). https://doi.org/https://doi.org/10.1186/s12911-020-01376-8
Murphy, M. E., McSharry, J., Byrne, M., Boland, F., Corrigan, D., Gillespie, P., Fahey, T., & Smith, S. M. (2020). Supporting Care for Suboptimally Controlled Type 2 Diabetes Mellitus in General Practice with a Clinical Decision Support System: a mixed methods pilot cluster randomised trial. BMJ Open, 10. https://doi.org/doi. org/10.1136/bmjopen-2019- 032594
Neubauer, K. M., Mader, J. K., Höll, B., Aberer, F., Donsa, K., Augustin, T., Schaupp, L., Spat, S., Beck, P., & Fruhwald, F. M. (2015). Standardized glycemic management with a computerized workflow and decision support system for hospitalized patients with type 2 diabetes on different wards. Diabetes Technology & Therapeutics, 17(10), 685–692. https://pubmed.ncbi.nlm.nih.gov/26355756/
O’Connor, P. J., Sperl-Hillen, J. M., Fazio, C. J., Averbeck, B. M., Rank, B. H., & Margolis, K. L. (2016). Outpatient Diabetes Clinical Decision Support: current status and future directions. Diabetes Medicine, 33(6). https://doi.org/https://doi.org/10.1111/dme.13090
Ota, S., Mogushi, K., Hirai, A., Niimura, Y., & Tanaka, H. (2018). Improvements in Diabetic Patients’ Outcomes in a Clinical Decision Support System. European Journal of Biomedical Informatics, 14(1), 29–36. https://www.ejbi.org/scholarly-articles/improvements-in-diabetic-patients-outcomes-in-a-clinical-decision-support-system.pdf
Pérez-Gandía, C., García-Sáez, G., Subías, D., Rodríguez-Herrero, A., Gómez, E. J., Rigla, M., & Hernando, M. E. (2018). Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor. Journal of Diabetes Science and Technology, 12(2), 243–250. https://doi.org/10.1177/1932296818761457
Pichardo-Lowden, A. R. (2021). Clinical Decision Support for Diabetes Care in the Hospital: A Time for Change Toward Improvement of Management and Outcomes. Journal of Diabetes Science and Technology. https://doi.org/10.1177/1932296820982661
Pichardo-Lowden, A., Umpierrez, G., Lehman, E. B., Bolton, M. D., DeFlitch, C. J., Chinchilli, V. M., & Haidet, P. M. (2020). Clinical Decision Support to Improve Management of Diabetes and Dysglycemia in the Hospital: a path to optimizing practice and outcomes. BMJ Open Diabetes Research & Care, 9. https://doi.org/doi:10.1136/ bmjdrc-2020-001557
Robertson, L. A., Mclean, M.-A., Sardar, C. M., Bryson, G., & Kurdi, A. (2020). Evaluation of the prescribing decision support systemSynonymsin a primary care setting: a mixed-method study. International Journal of Pharmacy Practice, 28, 473–482.
Rodbard, D., & Vigersky, R. A. (2011). Design of a Decision Support System to Help Clinicians Manage Glycemia in Patients with Type 2 Diabetes Mellitus. Journal of Diabetes Science and Technologychnology, 5(2). https://doi.org/https://doi.org/10.1177/193229681100500230
Saeedi, P., Petersohn, I., Salpea, P., Malanda, B., Karuranga, S., Unwin, N., Colaguri, S., Guariguata, L., Motala, A. A., Ogurtsova, K., Shaw, J. E., Bright, D., & Williams, R. (2019). Global and Regional Diabetes Prevalence Estimatesfor 2019 and Projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practise, 157(107843). https://doi.org/https://doi.org/10.1016/j.diabres.2019.107843
Shahmoradi, L., Safdari, R., Ahmadi, H., & Zahmatkeshan, M. (2021). Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. In Medical Journal of the Islamic Republic of Iran (Vol. 35, Issue 1, pp. 1–16). https://doi.org/10.34171/mjiri.35.27
Shen, C., Jiang, B., Yang, Q., Wang, C., Lu, K. Z., Gu, M., & Yuan, J. (2021). Mobile Apps for Drug-Drug Interaction Checks in Chinese App Stores: Systematic Review and Content Analysis. JMIR MHealth and UHealth, 9(6). https://doi.org/10.2196/26262
Sim, L. L. W., Ban, K. H. K., Tan, T. W., Sethi, S. K., & Loh, T. P. (2017). Development of a Clinical Decision Support System for Diabetes Care: A pilot study. PLoS One, 12(2). https://doi.org/10.1371/journal.pone.0173021
Spat, S, Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Augustin, T., Chiarugi, F., Lichtenegger, K. M., Plank, J., & Pieber, T. R. (2017). A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients with Type 2 Diabetes Mellitus. Journal of Diabetes Science and Technology, 11(1), 20–28. https://doi.org/10.1177/1932296816676501
Spat, Stephan, Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L., Augustin, T., Chiarugi, F., Lichtenegger, K. M., & Plank, J. (2017). A mobile computerized decision support system to prevent hypoglycemia in hospitalized patients with type 2 diabetes mellitus: lessons learned from a clinical feasibility study. Journal of Diabetes Science and Technology, 11(1), 20–28.
Stultz, J. S., & Nahata, M. C. (2012). Computerized Clinical Decision Support for Medication Prescribing and Utilization in Pediatrics. Journal of the American Medical Informatics Association, 19(6). https://doi.org/10.1136/amiajnl-2011-000798
Wang, L., Wang, Y., Li, Z., Yu, B., & Li, Y. (2014). Unilateral Versus Bilateral Pedicle Screw Fixation of Minimally Invasive Transforaminal Lumbar Interbody Fusion (MIS-TLIF): a meta-analysis of randomized controlled trials. BMC Surgery, 14(87). https://bmcsurg.biomedcentral.com/articles/10.1186/1471-2482-14-87
Published
2024-09-25
How to Cite
Larasati, N., Satibi, S., Kristina, S. A., & Lazuardi, L. (2024). Clinical Decision Support Systems to Identify Drug-Related Problems in Diabetes Mellitus Patients: A Systematic Review. Indonesian Journal of Pharmacy, 35(3), 392–408. https://doi.org/10.22146/ijp.6209
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Section
Review Article
