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Medication decision-making for patients with renal insufficiency in inpatient and outpatient care at a US Veterans Affairs Medical Centre: a qualitative, cognitive task analysis
  1. Nervana Elkhadragy1,2,
  2. Amanda P Ifeachor3,
  3. Julie B Diiulio4,
  4. Karen J Arthur3,
  5. Michael Weiner5,
  6. Laura G Militello4,
  7. Peter A Glassman6,
  8. Alan J Zillich2,
  9. Alissa L Russ1,2
  1. 1 Centre for Health Information and Communication, Health Service Research and Development, Department of Veterans Affairs, Roudebush VA Medical Centre, Indianapolis, Indiana, USA
  2. 2 Department of Pharmacy Practice, College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
  3. 3 US Department of Veterans Affairs (VA), Veterans Health Administration, Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA
  4. 4 Applied Decision Science, Dayton, Ohio, USA
  5. 5 Centre for Health Information and Communication, U.S. Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Centre; Regenstrief Institute, Inc;, Indiana University, Indianapolis, Indiana, USA
  6. 6 Internal Medicine, Department of Veterans Affairs, Greater Los Angeles Healthcare System, and David Geffen School of Medicine at UCLA, Los Angeles, California, USA
  1. Correspondence to Dr. Alissa L Russ; aruss{at}purdue.edu

Abstract

Background Many studies identify factors that contribute to renal prescribing errors, but few examine how healthcare professionals (HCPs) detect and recover from an error or potential patient safety concern. Knowledge of this information could inform advanced error detection systems and decision support tools that help prevent prescribing errors.

Objective To examine the cognitive strategies that HCPs used to recognise and manage medication-related problems for patients with renal insufficiency.

Design HCPs submitted documentation about medication-related incidents. We then conducted cognitive task analysis interviews. Qualitative data were analysed inductively.

Setting Inpatient and outpatient facilities at a major US Veterans Affairs Medical Centre.

Participants Physicians, nurses and pharmacists who took action to prevent or resolve a renal-drug problem in patients with renal insufficiency.

Outcomes Emergent themes from interviews, as related to recognition of renal-drug problems and decision-making processes.

Results We interviewed 20 HCPs. Results yielded a descriptive model of the decision-making process, comprised of three main stages: detect, gather information and act. These stages often followed a cyclical path due largely to the gradual decline of patients’ renal function. Most HCPs relied on being vigilant to detect patients’ renal-drug problems rather than relying on systems to detect unanticipated cues. At each stage, HCPs relied on different cognitive cues depending on medication type: for renally eliminated medications, HCPs focused on gathering renal dosing guidelines, while for nephrotoxic medications, HCPs investigated the need for particular medication therapy, and if warranted, safer alternatives.

Conclusions Our model is useful for trainees so they can gain familiarity with managing renal-drug problems. Based on findings, improvements are warranted for three aspects of healthcare systems: (1) supporting the cyclical nature of renal-drug problem management via longitudinal tracking mechanisms, (2) providing tools to alleviate HCPs’ heavy reliance on vigilance and (3) supporting HCPs’ different decision-making needs for renally eliminated versus nephrotoxic medications.

  • nephrology
  • medical education and training
  • health and safety
  • qualitative research

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Contributors NE participated in data analysis, interpretation, model development, drafted the initial manuscript and led the finalisation of manuscript content. AI participated in review of cognitive task analysis interviews for trends, assisted with drafting pieces of the initial manuscript, provided critical edits/input to the manuscript and approved of the final manuscript. JD participated in data analysis, interpretation, model development, provided critical edits/input to the manuscript and approved of the final manuscript. KJA screened submitted cases for clinical appropriateness/interview selection, participated in review of cognitive task analysis interviews for trends, provided critical edits/input to the manuscript and approved of the final manuscript. MW contributed to study conception and design, data interpretation, provided critical edits/input to the manuscript and approved of the final manuscript. LGM contributed to the design of the study, aided in interpreting findings, provided critical edits/input to the manuscript and approved of the final manuscript. PAG contributed to study conception and design, data interpretation, provided critical edits/input to the manuscript and approved of the final manuscript. AJZ contributed to the design of the study, aided in interpreting findings, provided critical edits/input to the manuscript and approved of the final manuscript. AR conceived and designed the study, wrote the funded grant, conducted all cognitive task analysis interviews, aided in data analysis and interpretation, provided critical edits/input to the manuscript and approved of the final manuscript.

  • Funding This work was supported by VA HSR&D Career Development Award 11-214 (PI: Russ), along with the Centre for Health Information and Communication, US Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service, CIN 13-416.

  • Disclaimer Views expressed in this article are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs or the US government. Rachel Dismore assisted with IRB paperwork, participant recruitment, incident card collection, descriptive statistics and data in Tables 1 and 2. Dr Weiner is Chief of Health Services Research and Development at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana. We would like to thank all of the physicians, nurses and pharmacists who participated.

  • Competing interests LGM is co-owner of Applied Decision Science, LLC, a company that studies decision-making in complex environments and utilises the critical decision method. MW has stock in Allscripts and Express Scripts Holding Company. All other authors report that they have no competing interests.

  • Ethics approval This study was approved by the Indiana University Institutional Review Board and the Richard L. Roudebush VA Research and Development Committee (IRB study #1301010433).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement A sample of the qualitative data from participants' interviews is available in the online supplemental document. For additional inquiries, please contact the Principal Investigator, Dr. Alissa L. Russ.

  • Patient consent for publication Not required.

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