Systematic Review:The opportunities and challenges for digital health in pharmacy practice
Main Article Content
Keywords
Digital health, pharmacy practice, artificial intelligence (AI), patient engagement, medication management
Abstract
Background: Digital health technologies, including tele pharmacy, artificial intelligence (AI), mHealth, and electronic health records (EHRs), have all started to alter pharmacy practice by improving medication safety, adherence, workflow, and patient care. However, the unique impacts and challenges of these technologies in pharmacy practice necessitate more exploration. Objectives: The current systematic review explores the effectiveness of digital health interventions in pharmacy practice using evidence from recent studies. Method: A systematic review was performed on 50 studies published from 2019 to 2024, each assessing different digital health tools in pharmacy. Studies sourced from databases such as CINAHL, Cochrane Library, EMBASE, Google Scholar, PubMed, Scopus, and Web of Science. Primary outcomes included medication safety improvements, better clinical decision making, and operational factors like workflow efficiency and patient engagement. Results: Overall, the interventions yielded significant improvements in pharmacy practice activities among the surveyed 50 studies. Tele pharmacy service and AI - based decision support tools advanced medication, patient safety and care services over older technologies. On the contrary, key challenges identified included: issues of data privacy, regulations and standards, required infrastructure and IT support systems for tele pharmacy and AI - based technology systems, within underserved locations or lower - resourced pharmacy settings. Conclusion: The current systematic review concluded that while digital health technologies improve accessibility and medication management, addressing issues like regulatory limits and data security is critical for realizing their full potential. While digital health has shown promise, there is still a need for more research to demonstrate its effectiveness in pharmacy practice, especially regarding long-term patient outcomes.
References
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21. Bindler RJ. The Impact of Telepharmacy Services on the Identification of Medication Discrepancies, High-Alert Medications, and Cost Avoidance at Rural Healthcare Institutions. J Int Soc Telemed eHealth. 2020 Jul 2;8.
22. Deas C, Stockton K. Evaluation of Outcomes of a Pharmacist-Run, Outpatient Insulin Titration Telepharmacy Service. Innov Pharm [Internet]. 2019 May 6 [cited 2024 Oct 28];10(2):5.
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24. Santos MAD, Herbert J, Cinelli I, Burmann JAL, Soares V V., Russomano T. Development of a Digital Platform: A Perspective to Advance Space Telepharmacy. IEEE Open J Eng Med Biol. 2023;4:168–72.
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26. Yalçın N, Kaşıkcı M, Çelik HT, Allegaert K, Demirkan K, Yiğit Ş, et al. An Artificial Intelligence Approach to Support Detection of Neonatal Adverse Drug Reactions Based on Severity and Probability Scores: A New Risk Score as Web-Tool. Children 2022, Vol 9, Page 1826 [Internet]. 2022 Nov 26 [cited 2024 Oct 28];9(12):1826.
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28. Rafiei R, Williams C, Jiang J, Aungst TD, Durrer M, Tran D, et al. Digital health integration assessment and maturity of the United States biopharmaceutical industry: Forces driving the next generation of connected autoinjectable devices. JMIR Mhealth Uhealth [Internet]. 2021 Mar 1 [cited 2024 Oct 28];9(3):e25406.
29. Bazzari FH, Bazzari AH. Utilizing ChatGPT in Telepharmacy. Cureus [Internet]. 2024 Jan 16 [cited 2024 Oct 28];16(1).
30. Sheikh MS, Barreto EF, Miao J, Thongprayoon C, Gregoire JR, Dreesman B, et al. Evaluating ChatGPT’s efficacy in assessing the safety of non- prescription medications and supplements in patients with kidney disease. Digit Health [Internet]. 2024 Jan 1 [cited 2024 Oct 28];10.
31. Albogami Y, Alfakhri A, Alaqil A, Alkoraishi A, Alshammari H, Elsharawy Y, et al. Safety and quality of AI chatbots for drug-related inquiries: A real-world comparison with licensed pharmacists. Digit Health [Internet]. 2024 Jan 1 [cited 2024 Oct 28];10.
32. Ong JJ, Castro BM, Gaisford S, Cabalar P, Basit AW, Pérez G, et al. Accelerating 3D printing of pharmaceutical products using machine learning. Int J Pharm X [Internet]. 2022 Jun 9 [cited 2024 Oct 28];4:100120–100120.
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35. McCoubrey LE, Elbadawi M, Orlu M, Gaisford S, Basit AW. Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria. Pharmaceutics [Internet]. 2021 Jul 1 [cited 2024 Oct 28];13(7).
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37. Gonzales HM, Fleming JN, Gebregziabher M, Posadas-Salas MA, Su Z, McGillicuddy JW, et al. Pharmacist-Led Mobile Health Intervention and Transplant Medication Safety: A Randomized Controlled Clinical Trial. Clin J Am Soc Nephrol [Internet]. 2021 May 8 [cited 2024 Oct 28];16(5):776–84.
38. Kataria G, Dhyani K, Patel D, Srinivasan K, Malwade S, Syed Abdul S. The smart pill sticker: Introducing a smart pill management system based on touch-point technology. Health Informatics J [Internet]. 2021 Nov 1 [cited 2024 Oct 28];27(4).
39. Cobelli N, Chiarini A. Improving customer satisfaction and loyalty through mHealth service digitalization: New challenges for Italian pharmacists. TQM Journal. 2020 Nov 4;32(6):1541–60.
40. Alshehri N, Alanazi A. Pharmacists’ Perceptions on Safety Alerts of the Drug Utilization Review (DUR) in Electronic Health Records in a Tertiary Healthcare Hospital. Pharmacy (Basel) [Internet]. 2023 Jul 20 [cited 2024 Oct 28];11(4):119.
41. Balestra M, Chen J, Iturrate E, Aphinyanaphongs Y, Nov O. Predicting inpatient pharmacy order interventions using provider action data. JAMIA Open [Internet]. 2021 Jul 1 [cited 2024 Oct 28];4(3).
42. van der Nat DJ, Taks M, Huiskes VJB, van den Bemt BJF, van Onzenoort HAW. A comparison between medication reconciliation by a pharmacy technician and the use of an online personal health record by patients for identifying medication discrepancies in patients’ drug lists prior to elective admissions. Int J Med Inform. 2021 Mar 1;147:104370.
43. Aldughayfiq B, Sampalli S. Digital Health in Physicians’ and Pharmacists’ Office: A Comparative Study of e-Prescription Systems’ Architecture and Digital Security in Eight Countries. OMICS [Internet]. 2021 Feb 1 [cited 2024 Oct 28];25(2):102–22.
44. Peltoniemi T, Suomi R, Peura S, Lähteenoja MNY. Electronic prescription as a driver for digitalization in Finnish pharmacies. BMC Health Serv Res [Internet]. 2021 Dec 1 [cited 2024 Oct 28];21(1):1–9.
45. Foreman C, Smith WB, Caughey GE, Shakib S. Categorization of adverse drug reactions in electronic health records. Pharmacol Res Perspect [Internet]. 2020 Apr 1 [cited 2024 Oct 28];8(2):e00550.
46. Chapman AB, Peterson KS, Alba PR, DuVall SL, Patterson O V. Detecting Adverse Drug Events with Rapidly Trained Classification Models. Drug Saf. 2019 Jan 21;42(1):147–56.
47. Jungreithmayr V, Meid AD, Bittmann J, Fabian M, Klein U, Kugler S, et al. The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation-a before-and-after study. BMC Med Inform Decis Mak [Internet]. 2021 Dec 1 [cited 2024 Oct 28];21(1).
48. Aung MM, Maneetham D, Chawaphan P. Automatic Pill Dispenser for Pharmacy. International Journal of Engineering Trends and Technology. 2023 Dec 1;71(12):61–8.
49. Roh H, Shin S, Han J, Lim S. A deep learning-based medication behavior monitoring system. Math Biosci Eng [Internet]. 2021 Jan 1 [cited 2024 Oct 28];18(2):1513–28.
50. Manning SE, Wang H, Dwibedi N, Shen C, Wiener RC, Findley PA, et al. Association of multimorbidity with the use of health information technology. Digit Health [Internet]. 2023 Jan 1 [cited 2024 Oct 28];9.
51. Galozy A, Nowaczyk S, Sant’Anna A, Ohlsson M, Lingman M. Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation. Int J Med Inform. 2020 Apr 1;136:104092.
52. Manyazewal T, Woldeamanuel Y, Holland DP, Fekadu A, Blumberg HM, Marconi VC. Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial. Trials [Internet]. 2020 May 5 [cited 2024 Oct 28];21(1).
53. Chalasani SH, Syed J, Ramesh M, Patil V, Pramod Kumar TM. Artificial intelligence in the field of pharmacy practice: A literature review. Exploratory Research in Clinical and Social Pharmacy. 2023 Dec 1;12:100346.
2. Golder S, Xu D, O’Connor K, Wang Y, Batra M, Hernandez GG. Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review. Drug Saf. 2025 Apr;48(4):321-337. doi: 10.1007/s40264- 024-01505-6.
3. Yang X, Bian J, Gong Y, Hogan WR, Wu Y. MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes. Drug Saf [Internet]. 2019 Jan 21 [cited 2024 Oct 28];42(1):123–33.
4. Dandala B, Joopudi V, Devarakonda M. Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks. Drug Saf [Internet]. 2019 Jan 21 [cited 2024 Oct 28];42(1):135–46.
5. Segal G, Segev A, Brom A, Lifshitz Y, Wasserstrum Y, Zimlichman E. Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting. J Am Med Inform Assoc [Internet]. 2019 Nov 15 [cited 2024 Oct 28];26(12):1560–5.
6. Mohsen A, Tripathi LP, Mizuguchi K. Deep Learning Prediction of Adverse Drug Reactions in Drug Discovery Using Open TG–GATEs and FAERS Databases. Frontiers in Drug Discovery [Internet]. 2021 Oct 27 [cited 2024 Oct 28];1:768792. Available from: https://github.com/scikit-learn- contrib.
7. Nagata K, Tsuji T, Suetsugu K, Muraoka K, Watanabe H, Kanaya A, et al. Detection of overdose and underdose prescriptions-An unsupervised machine learning approach. PLoS One [Internet]. 2021 Nov 1 [cited 2024 Oct 28];16(11).
8. Patel J, Ladani A, Sambamoorthi N, Lemasters T, Dwibedi N, Sambamoorthi U. A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis. Int J Environ Res Public Health [Internet]. 2020 Jan 1 [cited 2024 Oct 28];18(1):1–16.
9. Xingwei W, Huan C, Mengting L, Lv Q, Jiaying Z, Enwu L, et al. A machine learning-based risk warning platform for potentially inappropriate prescriptions for elderly patients with cardiovascular disease. Front Pharmacol. 2022 Aug 11;13:804566.
10. Cho H, Flynn G, Saylor M, Gradilla M, Schnall R. Use of the FITT framework to understand patients’ experiences using a real-time medication monitoring pill bottle linked to a mobile-based HIV self-management app: A qualitative study. Int J Med Inform [Internet]. 2019 Nov 1 [cited 2024 Oct 28];131.
11. Zijp TR, Touw DJ, van Boven JFM. User Acceptability and Technical Robustness Evaluation of a Novel Smart Pill Bottle Prototype Designed to Support Medication Adherence. Patient Prefer Adherence [Internet]. 2020 [cited 2024 Oct 28];14:625–34.
12. Corny J, Rajkumar A, Martin O, Dode X, Lajonchère JP, Billuart O, et al. A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error. J Am Med Inform Assoc [Internet]. 2020 Nov 1 [cited 2024 Oct 28];27(11):1688–94.
13. Amkreutz J, Lenssen R, Marx G, Deisz R, Eisert A. Medication safety in a German telemedicine centre: Implementation of a telepharmaceutical expert consultation in addition to existing tele-intensive care unit services. J Telemed Telecare [Internet]. 2020 Jan 1 [cited 2024 Oct 28];26(1– 2):105–12.
14. Ilkić J, Obradović D, Georgiev AM, Marinković V, Tadić I. Implementation of Telepharmacy Services in Community Pharmacy – Pharmacists’ Perspective in Republic of Serbia. Indian Journal of Pharmaceutical Education and Research. 2023 Jan 1;57(1):286–94.
15. Jirjees F, Odeh M, Aloum L, Kharaba Z, Alzoubi KH, Al-Obaidi HJ. The rise of telepharmacy services during the COVID-19 pandemic: A comprehensive assessment of services in the United Arab Emirates. Pharm Pract (Granada) [Internet]. 2022 Apr 1 [cited 2024 Oct 28];20(2).
16. Abdulsalam Ali Asseri, Mohab Mohamed Manna, Iqbal Mohamed Yasin, Mashael Mohamed Moustafa, Fatmah Mousa Roubie, Salma Moustafa El-Anssasy, et al. Implementation and evaluation of telepharmacy during COVID-19 pandemic in an academic medical city in the Kingdom of Saudi Arabia: paving the way for telepharmacy. World Journal of Advanced Research and Reviews. 2020 Aug 30;7(2):218–26.
17. Farghali A, Borycki EM, Macdonald S. Pharmacist’s perception of the impact of electronic prescribing on medication errors and productivity in community pharmacies. Knowledge Management and E-Learning. 2021;13(4):536–58.
18. Lopez de Coca T, Moreno L, Alacreu M, Sebastian-Morello M. Bridging the Generational Digital Divide in the Healthcare Environment. J Pers Med [Internet]. 2022 Aug 1 [cited 2024 Oct 28];12(8).
19. Mohamed Ibrahim O, Ibrahim RM, Abdel-Qader DH, Al Meslamani AZ, Al Mazrouei N. Evaluation of Telepharmacy Services in Light of COVID-19. Telemed J E Health [Internet]. 2021 Jun 1 [cited 2024 Oct 28];27(6):649–56.
20. Peláez Bejarano A, Villar Santos P, Robustillo-Cortés MDLA, Sánchez Gómez E, Santos Rubio MD. Implementation of a novel home delivery service during pandemic. European Journal of Hospital Pharmacy [Internet]. 2020 Nov 1 [cited 2024 Oct 28];28(e1):e120.
21. Bindler RJ. The Impact of Telepharmacy Services on the Identification of Medication Discrepancies, High-Alert Medications, and Cost Avoidance at Rural Healthcare Institutions. J Int Soc Telemed eHealth. 2020 Jul 2;8.
22. Deas C, Stockton K. Evaluation of Outcomes of a Pharmacist-Run, Outpatient Insulin Titration Telepharmacy Service. Innov Pharm [Internet]. 2019 May 6 [cited 2024 Oct 28];10(2):5.
23. McGinnis B, Padilla E, Garret P, Aziz S. Using pharmacy technicians and telepharmacy to obtain medication histories in the emergency department. Journal of the American Pharmacists Association. 2019 May 1;59(3):390–7.
24. Santos MAD, Herbert J, Cinelli I, Burmann JAL, Soares V V., Russomano T. Development of a Digital Platform: A Perspective to Advance Space Telepharmacy. IEEE Open J Eng Med Biol. 2023;4:168–72.
25. Li H, Zheng S, Li D, Jiang D, Liu F, Guo W, et al. The Establishment and Practice of Pharmacy Care Service Based on Internet Social Media: Telemedicine in Response to the COVID-19 Pandemic. Front Pharmacol [Internet]. 2021 Oct 1 [cited 2024 Oct 28];12:707442.
26. Yalçın N, Kaşıkcı M, Çelik HT, Allegaert K, Demirkan K, Yiğit Ş, et al. An Artificial Intelligence Approach to Support Detection of Neonatal Adverse Drug Reactions Based on Severity and Probability Scores: A New Risk Score as Web-Tool. Children 2022, Vol 9, Page 1826 [Internet]. 2022 Nov 26 [cited 2024 Oct 28];9(12):1826.
27. Bu F, Sun H, Li L, Tang F, Zhang X, Yan J, et al. Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study. Front Pharmacol [Internet]. 2022 Nov 9 [cited 2024 Oct 28];13.
28. Rafiei R, Williams C, Jiang J, Aungst TD, Durrer M, Tran D, et al. Digital health integration assessment and maturity of the United States biopharmaceutical industry: Forces driving the next generation of connected autoinjectable devices. JMIR Mhealth Uhealth [Internet]. 2021 Mar 1 [cited 2024 Oct 28];9(3):e25406.
29. Bazzari FH, Bazzari AH. Utilizing ChatGPT in Telepharmacy. Cureus [Internet]. 2024 Jan 16 [cited 2024 Oct 28];16(1).
30. Sheikh MS, Barreto EF, Miao J, Thongprayoon C, Gregoire JR, Dreesman B, et al. Evaluating ChatGPT’s efficacy in assessing the safety of non- prescription medications and supplements in patients with kidney disease. Digit Health [Internet]. 2024 Jan 1 [cited 2024 Oct 28];10.
31. Albogami Y, Alfakhri A, Alaqil A, Alkoraishi A, Alshammari H, Elsharawy Y, et al. Safety and quality of AI chatbots for drug-related inquiries: A real-world comparison with licensed pharmacists. Digit Health [Internet]. 2024 Jan 1 [cited 2024 Oct 28];10.
32. Ong JJ, Castro BM, Gaisford S, Cabalar P, Basit AW, Pérez G, et al. Accelerating 3D printing of pharmaceutical products using machine learning. Int J Pharm X [Internet]. 2022 Jun 9 [cited 2024 Oct 28];4:100120–100120.
33. Naeem M, Coronato A. An AI-Empowered Home-Infrastructure to Minimize Medication Errors. Journal of Sensor and Actuator Networks 2022, Vol 11, Page 13 [Internet]. 2022 Feb 9 [cited 2024 Oct 28];11(1):13.
34. Takase T, Masumoto N, Shibatani N, Matsuoka Y, Tanaka F, Hirabatake M, et al. Evaluating the safety and efficiency of robotic dispensing systems. J Pharm Health Care Sci [Internet]. 2022 Dec 1 [cited 2024 Oct 28];8(1).
35. McCoubrey LE, Elbadawi M, Orlu M, Gaisford S, Basit AW. Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria. Pharmaceutics [Internet]. 2021 Jul 1 [cited 2024 Oct 28];13(7).
36. Subramanian G, SreekantanThampy A, Valbosco Ugwuoke N, Ramnani B. Crypto Pharmacy – Digital Medicine: A Mobile Application Integrated With Hybrid Blockchain to Tackle the Issues in Pharma Supply Chain. IEEE Open Journal of the Computer Society. 2021 Jan 5;2:26–37.
37. Gonzales HM, Fleming JN, Gebregziabher M, Posadas-Salas MA, Su Z, McGillicuddy JW, et al. Pharmacist-Led Mobile Health Intervention and Transplant Medication Safety: A Randomized Controlled Clinical Trial. Clin J Am Soc Nephrol [Internet]. 2021 May 8 [cited 2024 Oct 28];16(5):776–84.
38. Kataria G, Dhyani K, Patel D, Srinivasan K, Malwade S, Syed Abdul S. The smart pill sticker: Introducing a smart pill management system based on touch-point technology. Health Informatics J [Internet]. 2021 Nov 1 [cited 2024 Oct 28];27(4).
39. Cobelli N, Chiarini A. Improving customer satisfaction and loyalty through mHealth service digitalization: New challenges for Italian pharmacists. TQM Journal. 2020 Nov 4;32(6):1541–60.
40. Alshehri N, Alanazi A. Pharmacists’ Perceptions on Safety Alerts of the Drug Utilization Review (DUR) in Electronic Health Records in a Tertiary Healthcare Hospital. Pharmacy (Basel) [Internet]. 2023 Jul 20 [cited 2024 Oct 28];11(4):119.
41. Balestra M, Chen J, Iturrate E, Aphinyanaphongs Y, Nov O. Predicting inpatient pharmacy order interventions using provider action data. JAMIA Open [Internet]. 2021 Jul 1 [cited 2024 Oct 28];4(3).
42. van der Nat DJ, Taks M, Huiskes VJB, van den Bemt BJF, van Onzenoort HAW. A comparison between medication reconciliation by a pharmacy technician and the use of an online personal health record by patients for identifying medication discrepancies in patients’ drug lists prior to elective admissions. Int J Med Inform. 2021 Mar 1;147:104370.
43. Aldughayfiq B, Sampalli S. Digital Health in Physicians’ and Pharmacists’ Office: A Comparative Study of e-Prescription Systems’ Architecture and Digital Security in Eight Countries. OMICS [Internet]. 2021 Feb 1 [cited 2024 Oct 28];25(2):102–22.
44. Peltoniemi T, Suomi R, Peura S, Lähteenoja MNY. Electronic prescription as a driver for digitalization in Finnish pharmacies. BMC Health Serv Res [Internet]. 2021 Dec 1 [cited 2024 Oct 28];21(1):1–9.
45. Foreman C, Smith WB, Caughey GE, Shakib S. Categorization of adverse drug reactions in electronic health records. Pharmacol Res Perspect [Internet]. 2020 Apr 1 [cited 2024 Oct 28];8(2):e00550.
46. Chapman AB, Peterson KS, Alba PR, DuVall SL, Patterson O V. Detecting Adverse Drug Events with Rapidly Trained Classification Models. Drug Saf. 2019 Jan 21;42(1):147–56.
47. Jungreithmayr V, Meid AD, Bittmann J, Fabian M, Klein U, Kugler S, et al. The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation-a before-and-after study. BMC Med Inform Decis Mak [Internet]. 2021 Dec 1 [cited 2024 Oct 28];21(1).
48. Aung MM, Maneetham D, Chawaphan P. Automatic Pill Dispenser for Pharmacy. International Journal of Engineering Trends and Technology. 2023 Dec 1;71(12):61–8.
49. Roh H, Shin S, Han J, Lim S. A deep learning-based medication behavior monitoring system. Math Biosci Eng [Internet]. 2021 Jan 1 [cited 2024 Oct 28];18(2):1513–28.
50. Manning SE, Wang H, Dwibedi N, Shen C, Wiener RC, Findley PA, et al. Association of multimorbidity with the use of health information technology. Digit Health [Internet]. 2023 Jan 1 [cited 2024 Oct 28];9.
51. Galozy A, Nowaczyk S, Sant’Anna A, Ohlsson M, Lingman M. Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation. Int J Med Inform. 2020 Apr 1;136:104092.
52. Manyazewal T, Woldeamanuel Y, Holland DP, Fekadu A, Blumberg HM, Marconi VC. Electronic pillbox-enabled self-administered therapy versus standard directly observed therapy for tuberculosis medication adherence and treatment outcomes in Ethiopia (SELFTB): protocol for a multicenter randomized controlled trial. Trials [Internet]. 2020 May 5 [cited 2024 Oct 28];21(1).
53. Chalasani SH, Syed J, Ramesh M, Patil V, Pramod Kumar TM. Artificial intelligence in the field of pharmacy practice: A literature review. Exploratory Research in Clinical and Social Pharmacy. 2023 Dec 1;12:100346.
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Systematic Review:The opportunities and challenges for digital health in pharmacy practice. Pharm Pract (Granada) [Internet]. 2026 Jun. 22 [cited 2026 Jun. 22];24(2):1-17. Available from: https://pharmacypractice.org/index.php/pp/article/view/3542
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How to Cite
1.
Systematic Review:The opportunities and challenges for digital health in pharmacy practice. Pharm Pract (Granada) [Internet]. 2026 Jun. 22 [cited 2026 Jun. 22];24(2):1-17. Available from: https://pharmacypractice.org/index.php/pp/article/view/3542