Impact of electronic health record systems on quality of primary care within essential public health function framework
https://doi.org/10.24412/2790-1289-2025-2-109-124
Abstract
Quality healthcare is the primary objective of any healthcare system. An effective electronic health record system is a crucial tool for achieving this goal. Its objectives are to improve the quality of medical care by automating the work of doctors and medical personnel in all areas of activity.
The purpose of this study. To explore the impact of electronic health records systems in primary health care facilities on improving the quality of care to ensure a sustainable organizational structure as an essential public healthcare function.
Materials and methods. The search was conducted in the MEDLINE, EMBASE, CINAHL, and Cochrane Central Register of Controlled Trials databases. The search strategy was based on the PICO Framework. The studies selected for the meta-analysis were published between January 1, 2010, and May 1, 2023. Two authors independently reviewed article titles and abstracts for eligibility. Information from the search was deduplicated using EndNote X9 and imported into the Covidence Systematic Review for review. Statistical processing was performed in RStudio 2023.03.1 Build 446 (Posit Software, PBC).
Results. A literature search identified 640 publications; 11 of them were included in the review. Meta-analysis showed that the use of electronic health records (EHRs) helps to reduce the time to complete medical records by 33.4 % (95% CI = 0.8 % to 1.2 %; p < 0.007), promotes adherence to clinical recommendations (RR 1.30; 95 % CI = 1.04 to 1.79; p = 0.05) and reduces prescribing errors (RR 0.44; 95 % CI = 0.34 to 0.53; p < 0.001), which undoubtedly improves the quality of medical care.
Conclusion. This study validates the positive influence of EHRSs on enhancing care quality in PHC settings, primarily by streamlining documentation, reducing prescription errors, and aligning workflow with clinical guidelines. These findings can help healthcare and public health professionals make informed decisions about EHRS adoption.
About the Authors
N. S. YussupovaKazakhstan
Yussupova Nargiza Saidakhmetovna – master of Medical sciences, Manager of international cooperation; graduate of the doctoral program in the specialty «Public Health»
Almaty
B. S. Turdaliyeva
Kazakhstan
Turdaliyeva Botagoz Saitovna – doctor of Medical Sciences, Professor, Deputy Director of Science and Strategic Development
Almaty
V. V. Koikov
Kazakhstan
Koikov Vitaliy Viktorovich – doctor of Medical Sciences, Vice-Rector
Astana
I. M. Son
Russian Federation
Son Irina Mikhailovna – Doctor of Medical Sciences, Professor, Deputy Director of Science and Education
Moscow
Z. Y. Аtalykova
Kazakhstan
Аtalykova Zhupar Yermekovna – master of Humanitarian Knowledge, Chief Specialist of the Department of Publication Activity
Almaty
References
1. Pronovost, P. J. (2017). High-performing health care delivery systems: High performance toward what purpose? Joint Commission Journal on Quality and Patient Safety, 43(9), 448-449, DOI: https://doi.org/10.1016/j.jcjq.2017.06.001
2. Jedwab, R. M., Franco, M., Owen, D., Ingram, A., Redley, B., & Dobroff, N. (2022). Improving the quality of electronic medical record documentation: Development of a compliance and quality program. Applied Clinical Informatics, 13(4), 836– 844. DOI: https://doi.org/10.1055/s-0042-1756369.
3. World Health Organization (2018). Essential public health functions, health systems and health security: Developing conceptual clarity and a WHO roadmap for action. World Health Organization, 67 p.
4. World Health Organization (2016). Sixty-ninth World Health Assembly: WHA69.1. Resolution adopted by the World Health Assembly. World Health Organization, 450 p.
5. Slabkij, G. A., & Parhomenko, G. Ja. (2012). Mіzhnarodnі pіdhodi do rozvitku gromads'kogo zdorov’ja. Ukraine. Health of the nation, 21(1), 7.
6. Strengthening public health services in the European Region – Brief overview of source documents for the European action plan. World Health Organization [website]. Retrieved February 6, 2025, from http://www.euro.who.int/__data/assets/pdf_file/0007/172681/RC62-id05-final-Rus.pdf?ua=1.
7. Forrest, G. N., et al. (2014). Use of electronic health records and clinical decision support systems for antimicrobial stewardship. Clinical Infectious Diseases, 59, 122-133. DOI:https://doi.org/10.1093/cid/ciu565
8. Joynt, K. E., Bhatt, D. L., Schwamm, L. H., Xian, Y., Heidenreich, P. A., Fonarow, G. C., Smith, E. E., Neely, M. L., Grau-Sepulveda, M. V., & Hernandez, A. F. (2015). Lack of impact of electronic health records on quality of care and outcomes for ischemic stroke. Journal of the American College of Cardiology, 65(18), 1964-1972. DOI: https://doi.org/10.1016/j.jacc.2015.02.059.
9. Kee, K. W., Char, C. W., & Yip, A. Y. (2018). A review on interventions to reduce medication discrepancies or errors in primary or ambulatory care setting during care transition from hospital to primary care. Journal of Family Medicine and Primary Care, 7, 501-506.
10. Tsai, C. H., Eghdam, A., Davoody, N., Wright, G., Flowerday, S., & Koch, S. (2020). Effects of electronic health record implementation and barriers to adoption and use: A scoping review and qualitative analysis of the content. Life (Basel), 10(12), 327. DOI: https://doi.org/10.3390/life10120327.
11. Agoritsas, T., Merglen, A., Courvoisier, D. S., Combescure, C., Garin, N., Perrier, A., & Perneger, T. V. (2012). Sensitivity and predictive value of 15 PubMed search strategies to answer clinical questions rated against full systematic reviews. Journal of Medical Internet Research, 14(3), 85. DOI: https://doi.org/10.2196/jmir.2021.
12. Kwon, Y., Lemieux, M., McTavish, J., & Wathen, N. (2015). Identifying and removing duplicate records from systematic review searches. Journal of the Medical Library Association, 103(4), 184-188. DOI: https://doi.org/10.3163/1536-5050.103.4.004.
13. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, 71. DOI: https://doi.org/10.1136/bmj.n71
14. Janett, R. S., & Yeracaris, P. P. (2020). Electronic medical records in the American health system: Challenges and lessons learned. Ciência & Saúde Coletiva, 25(4), 1293-1304. DOI: https://doi.org/10.1590/1413-81232020254.28922019.
15. Koper, D., Kamenski, G., Flamm, M., & Böhmdorfer, B. (2013). Frequency of medication errors in primary care patients with polypharmacy. Family Practice, 30(3), 313-319. DOI: https://doi.org/10.1093/fampra/cms070.
16. Säfholm, S., Bondesson, Å., & Modig, S. (2019). Medication errors in primary health care records: A cross-sectional study in Southern Sweden. BMC Family Practice, 20, 110. DOI: https://doi.org/10.1186/s12875-019-1001-0.
17. Al Alawi, S., Al Dhaheri, A., Al Baloushi, D., et al. (2014). Physician user satisfaction with an electronic medical records system in primary healthcare centers in Al Ain: A qualitative study. BMJ Open, 4(11), e005569. DOI: https://doi.org/10.1136/bmjopen-2014-005569.
18. Wetterneck, T. B., Walker, J. M., Blosky, M. A., Cartmill, R. S., Hoonakker, P., Johnson, M. A., Norfolk, E., & Carayon, P. (2011). Factors contributing to an increase in duplicate medication order errors after CPOE implementation. Journal of the American Medical Informatics Association, 18(6), 774-782. DOI: https://doi.org/10.1136/amiajnl-2011-000255.
19. Shabbir, S. A., Ahmed, L. A., Sudhir, R. R., Scholl, J., Li, Y. C., & Liou, D. M. (2010). Comparison of documentation time between an electronic and a paper-based record system by optometrists at an eye hospital in South India: A time-motion study. Computer Methods and Programs in Biomedicine, 100(3), 283-288. DOI: https://doi.org/10.1016/j.cmpb.2010.04.003.
20. Banerjee, D., Thompson, C., Kell, C., Shetty, R., Vetteth, Y., Grossman, H., DiBiase, A., & Fowler, M. (2017). An informatics-based approach to reducing heart failure all-cause readmissions: The Stanford heart failure dashboard. Journal of the American Medical Informatics Association, 24(3), 550-555. DOI: https://doi.org/10.1093/jamia/ ocw150.
21. Armor, B. L., Wight, A. J., & Carter, S. M. (2016). Evaluation of adverse drug events and medication discrepancies in transitions of care between hospital discharge and primary care followup. Journal of Pharmacy Practice, 29(2), 132-137. DOI: https://doi.org/10.1177/0897190014549836.
22. Chen, J., Cutrona, S. L., Dharod, A., Bunch, S. C., Foley, K. L., Ostasiewski, B., Hale, E. R., Bridges, A., Moses, A., Donny, E. C., Sutfin, E. L., & Houston, T. K. (2023). Monitoring the implementation of tobacco cessation support tools: Using novel electronic health record activity metrics. JMIR Medical Informatics, 11, e43097. DOI: https://doi.org/10.2196/43097.
23. Pohlmann, S., Kunz, A., Ose, D., Winkler, E. C., Brandner, A., Poss-Doering, R., Szecsenyi, J., & Wensing, M. (2020). Digitalizing health services by implementing a personal electronic health record in Germany: Qualitative analysis of fundamental prerequisites from the perspective of selected experts. Journal of Medical Internet Research, 22(1), e15102. DOI: https://doi.org/10.2196/15102
24. Robinson, K. E., & Kersey, J. A. (2018). Novel electronic health record (EHR) education intervention in large healthcare organization improves quality, efficiency, time, and impact on burnout. Medicine, 97(38), e12319. DOI: https://doi.org/10.1097/MD.0000000000012319.
25. Shafi, S., Collinsworth, A. W., Copeland, L. A., Ogola, G. O., Qiu, T., Kouznetsova, M., Liao, I. C., Mears, N., Pham, A. T., Wan, G. J., & Masica, A. L. (2018). Association of opioid-related adverse drug events with clinical and cost outcomes among surgical patients in a large integrated health care delivery system. JAMA Surgery, 153(8), 757-763. DOI: https://doi.org/10.1001/jamasurg.2018.1039
26. Liao, P. J., Mao, C. T., Chen, T. L., Deng, S. T., & Hsu, K. H. (2019). Factors associated with adverse drug reaction occurrence and prognosis, and their economic impacts in older inpatients in Taiwan: A nested case-control study. BMJ Open, 9(5), e026771. DOI: https://doi.org/10.1136/bmjopen-2018-026771.
27. Yagi, M., Shindo, Y., Mutoh, Y., Sano, M., Sakakibara, T., Kobayashi, H., Matsuura, A., Emoto, R., Matsui, S., Nakagawa, T., & Ogawa, K. (2023). Factors associated with adverse drug reactions or death in very elderly hospitalized patients with pulmonary tuberculosis. Scientific Reports, 13(1), 6826. DOI: https://doi.org/10.1038/s41598-023-33967-6.
28. de Hoon, S. E. M., Hek, K., van Dijk, L., & Verheij, R. A. (2017). Adverse events recording in electronic health record systems in primary care. BMC Medical Informatics and Decision Making, 17(1), 163. DOI: https://doi.org/10.1186/s12911-017-0565-7.
29. Zarrinpar, A., Cheng, T. Y. D., & Huo, Z. (2020). What can we learn about drug safety and other effects in the era of electronic health records and big data that we would not be able to learn from classic epidemiology? Journal of Surgical Research, 246, 599-604. DOI: https://doi.org/10.1016/j.jss.2019.09.053.
30. Hui, C., Vaillancourt, R., Bair, L., Wong, E., & King, J. W. (2016). Accuracy of adverse drug reaction documentation upon implementation of an ambulatory electronic health record system. Drugs – Real World Outcomes, 3(2), 231-238. DOI: https://doi.org/10.1007/s40801-016-0071-8.
31. Kern, L. M., Barron, Y., Dhopeshwarkar, R. V., Edwards, A., & Kaushal, R. (2013). Electronic health records and ambulatory quality of care. Journal of General Internal Medicine, 28(4), 496-503. DOI: https://doi.org/10.1007/s11606-012-2237-8.
32. Personal Electronic Health Records: A Review of Clinical Effectiveness, Cost-Effectiveness, and Guidelines (2016). Ottawa (ON): Canadian Agency for Drugs and Technologies in Health CADTH Rapid Response Reports [website]. Retrieved February 10, 2025, from https://www.ncbi.nlm.nih.gov/books/NBK355652/.
33. 21st century health challenges: Can the essential public health functions make a difference? (2021). World Health Organization [website]. Retrieved February 12, 2025, from https://www.who.int/publications/i/item/9789240038927.
34. van Fenema, E. M. (2017). Meten van naleving van richtlijnen en behandelkwaliteit met data van routine outcome monitoring [Assessment of guideline adherence and quality of care with routine outcome monitoring data]. Journal of Psychiatry, 59(3), 159-165.
35. Cowppli-Bony, A., Tretarre, B., Marrer, E., Defossez, G., Daubisse-Marliac, L., Coureau, G., Minicozzi, P., Woronoff, A. S., Delafosse, P., & Molinié, F. (2019). Compliance with clinical guidelines for breast cancer management: A population-based study of quality-of-care indicators in France. PLOS ONE, 14(10), e0224275. DOI: https://doi.org/10.1371/journal.pone.0224275.
36. Nijor, S., Rallis, G., Lad, N., & Gokcen, E. (2022). Patient safety issues from information overload in electronic medical records. Journal of Patient Safety, 18(6), 999-1003.
37. Fennelly, O., Cunningham, C., Grogan, L., Cronin, H., O’Shea, C., Roche, M., Lawlor, F., & O’Hare, N. (2020). Successfully implementing a national electronic health record: A rapid umbrella review. International Journal of Medical Informatics, 144, 104281. DOI https://doi.org/10.1016/j.ijmedinf.2020.104281
38. Holmes, J. H., Beinlich, J., Boland, M. R., Bowles, K. H., Chen, Y., Cook, T. S., Demiris, G., Draugelis, M., Fluharty, L., Gabriel, P. E., Grundmeier, R., Hanson, C. W., Herman, D. S., Himes, B. E., Hubbard, R. A., Kahn, C. E., Kim, D., Koppel, R., Long, Q., Mirkovic, N., Morris, J. S., Mowery, D. L., Ritchie, M. D., Urbanowicz, R., & Moore, J. H. (2021). Why is the electronic health record so challenging for research and clinical care? Methods of Information in Medicine, 60(1-2), 32-48. DOI: https://doi.org/10.1055/s-0041-1731784.
Review
For citations:
Yussupova N.S., Turdaliyeva B.S., Koikov V.V., Son I.M., Аtalykova Z.Y. Impact of electronic health record systems on quality of primary care within essential public health function framework. Actual Problems of Theoretical and Clinical Medicine. 2025;(2):109-124. https://doi.org/10.24412/2790-1289-2025-2-109-124