Published on in Vol 5, No 2 (2017): Apr-Jun

Applying STOPP Guidelines in Primary Care Through Electronic Medical Record Decision Support: Randomized Control Trial Highlighting the Importance of Data Quality

Applying STOPP Guidelines in Primary Care Through Electronic Medical Record Decision Support: Randomized Control Trial Highlighting the Importance of Data Quality

Applying STOPP Guidelines in Primary Care Through Electronic Medical Record Decision Support: Randomized Control Trial Highlighting the Importance of Data Quality

Journals

  1. Rogero-Blanco E, Lopez-Rodriguez J, Sanz-Cuesta T, Aza-Pascual-Salcedo M, Bujalance-Zafra M, Cura-Gonzalez I. Use of an Electronic Clinical Decision Support System in Primary Care to Assess Inappropriate Polypharmacy in Young Seniors With Multimorbidity: Observational, Descriptive, Cross-Sectional Study. JMIR Medical Informatics 2020;8(3):e14130 View
  2. Bloomfield H, Greer N, Linsky A, Bolduc J, Naidl T, Vardeny O, MacDonald R, McKenzie L, Wilt T. Deprescribing for Community-Dwelling Older Adults: a Systematic Review and Meta-analysis. Journal of General Internal Medicine 2020;35(11):3323 View
  3. Zhang Y, Koru G. Understanding and detecting defects in healthcare administration data: Toward higher data quality to better support healthcare operations and decisions. Journal of the American Medical Informatics Association 2020;27(3):386 View
  4. Mangin D, Lawson J, Adamczyk K, Guenter D. Embedding “Smart” Disease Coding Within Routine Electronic Medical Record Workflow: Prospective Single-Arm Trial. JMIR Medical Informatics 2020;8(7):e16764 View
  5. Monteiro L, Maricoto T, Solha I, Ribeiro-Vaz I, Martins C, Monteiro-Soares M. Reducing Potentially Inappropriate Prescriptions for Older Patients Using Computerized Decision Support Tools: Systematic Review. Journal of Medical Internet Research 2019;21(11):e15385 View
  6. Scott I, Pillans P, Barras M, Morris C. Using EMR-enabled computerized decision support systems to reduce prescribing of potentially inappropriate medications: a narrative review. Therapeutic Advances in Drug Safety 2018;9(9):559 View
  7. Doocy S, Paik K, Lyles E, Hei Tam H, Fahed Z, Winkler E, Kontunen K, Mkanna A, Burnham G. Guidelines and mHealth to Improve Quality of Hypertension and Type 2 Diabetes Care for Vulnerable Populations in Lebanon: Longitudinal Cohort Study. JMIR mHealth and uHealth 2017;5(10):e158 View
  8. Earl T, Katapodis N, Schneiderman S, Shoemaker-Hunt S. Using Deprescribing Practices and the Screening Tool of Older Persons’ Potentially Inappropriate Prescriptions Criteria to Reduce Harm and Preventable Adverse Drug Events in Older Adults. Journal of Patient Safety 2020;16(3):S23 View
  9. Meid A, Groll A, Heider D, Mächler S, Adler J, Günster C, König H, Haefeli W. Prediction of Drug-Related Risks Using Clinical Context Information in Longitudinal Claims Data. Value in Health 2018;21(12):1390 View
  10. Anfinogenova N, Trubacheva I, Popov S, Efimova E, Ussov W. Trends and concerns of potentially inappropriate medication use in patients with cardiovascular diseases. Expert Opinion on Drug Safety 2021;20(10):1191 View
  11. Shojania K, Jennings A, Ramsay C, Grimshaw J, Kwan J, Lo L. The effects of on-screen, point of care computer reminders on processes and outcomes of care. Cochrane Database of Systematic Reviews 2009;2021(6) View
  12. Hill J, Russ-Jara A, Campbell N, Holden R. The Case for Human-Centered Research on the Complex Patient Journey of Deprescribing. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2021;10(1):276 View
  13. Santoro S, Bartman T, Cua C, Lemle S, Skotko B. Use of Electronic Health Record Integration for Down Syndrome Guidelines. Pediatrics 2018;142(3) View
  14. Gangannagaripalli J, Porter I, Davey A, Ricci Cabello I, Greenhalgh J, Anderson R, Briscoe S, Hughes C, Payne R, Cockcroft E, Harris J, Bramwell C, Valderas J. STOPP/START interventions to improve medicines management for people aged 65 years and over: a realist synthesis. Health Services and Delivery Research 2021;9(23):1 View
  15. Beck A, Persaud N, Tessier L, Grad R, Kidd M, Klarenbach S, Korownyk C, Moore A, Thombs B, Mangin D, McCracken R, McDonald E, Sirois C, Kanji S, Molnar F, Nicholls S, Thavorn K, Bennett A, Shaver N, Skidmore B, Mitchelmore B, Avey M, Rolland-Harris E, Little J, Moher D. Interventions to address potentially inappropriate prescriptions and over-the-counter medication use among adults 65 years and older in primary care settings: protocol for a systematic review. Systematic Reviews 2022;11(1) View
  16. Fletcher E, Burns A, Wiering B, Lavu D, Shephard E, Hamilton W, Campbell J, Abel G. Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review. BMC Primary Care 2023;24(1) View
  17. Atmaja D, Yulistiani , Suharjono , Zairina E. Detection tools for prediction and identification of adverse drug reactions in older patients: a systematic review and meta-analysis. Scientific Reports 2022;12(1) View
  18. Rodrigues D, Plácido A, Mateos-Campos R, Figueiras A, Herdeiro M, Roque F. Effectiveness of Interventions to Reduce Potentially Inappropriate Medication in Older Patients: A Systematic Review. Frontiers in Pharmacology 2022;12 View
  19. Fernainy P, Cohen A, Murray E, Losina E, Lamontagne F, Sourial N. Rethinking the pros and cons of randomized controlled trials and observational studies in the era of big data and advanced methods: a panel discussion. BMC Proceedings 2024;18(S2) View
  20. Lampe D, Grosser J, Grothe D, Aufenberg B, Gensorowsky D, Witte J, Greiner W. How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review. BMC Medical Informatics and Decision Making 2024;24(1) View