Original Paper
Abstract
Background: Poor data transfer and interoperability between electronic health record (EHR) systems has been a challenge hindering availability and usability of patient information in clinical practice and evidence-based decision-making. To improve data transfer and interoperability, patient information should be documented in a structured format. This also applies to medication-related patient information and results of the interventions, such as medication reviews (MRs), to individually optimize medication regimens, especially in older adults.
Objective: This study aimed to identify what information obtained from MRs should be documented in a structured form in EHRs at a national and organizational level.
Methods: The study was conducted as a 3-round Delphi consensus survey in 2020. The electronic survey was based on a comprehensive inventory of international and national MR procedures in various settings. Expert panelists (N=41) independently assessed which topics should be documented in a structured form in EHRs. The interprofessional panel (N=41) consisted of 12 physicians, 13 pharmacists, 10 nurses, and 6 information management professionals (participation rate 66%-76% in rounds 1-3; consensus limit set at 80%). The responses were analyzed quantitatively and qualitatively.
Results: Consensus was reached on 97.3% (108/111) of predetermined topics to be documented in a structured form in EHRs. Of these, 39 concerned the MR process, 25 related to potentially drug-induced symptoms, 11 related to burden of risks for adverse drug effects, 12 related to laboratory tests and other test results, 12 related to medication adherence, and 9 related to the use of intoxicants. The patient’s blood pressure (mean 4.85, SD 0.53; on a Likert scale 1-5), kidney function (mean 4.81, SD 0.56), and risk of bleeding (mean 4.81, SD 0.56) were ranked as the 3 most important topics to be documented in a structured form. The panel reached a consensus that the information obtained from MRs should be made available to all health care professionals in the national digital repository for patient data and to patients to some extent.
Conclusions: The interprofessional expert panel strongly agreed on the results of the MRs that should be documented in a structured form in EHRs and made available to both health professionals involved in care teams and patients themselves.
doi:10.2196/70133
Keywords
Introduction
Background
Health care across the world is undergoing digitalization with the goal of well-integrated systems leading to improved work efficiency and patient safety [,]. However, the transition phase toward well-functioning digital systems is characterized by fragmented, immature medical records that have become a major challenge and patient safety risk in various health care functions and settings [-]. The key issue is that patient information is collected and documented in numerous local and national data systems that do not communicate or enable data access or data transfer between social and health care organizations or even within an organization. This siloed, fragmented information is difficult to share, blurring the overall picture of the treatment and making it difficult for any care team member to take full responsibility for the patient’s care coordination [,]. Thus, standardized terminology and operating models are needed for documenting patient information in a structured format to enable data transfer and interoperability between health care units, regardless of the organization or electronic health record (EHR) system [-]. This would also enable the secondary use of patient data when estimating the effectiveness of care or future need for health care services.
The same kind of challenges with fragmented patient information apply to documenting patient information on medication regimens to EHRs which has led to shortcomings and safety risks in managing and obtaining up-to-date medication information []. In medication risk management, medication reviews (MRs), that is, a structured evaluation of a patient’s medication regimen with the aim of optimizing medicines use and improving health outcomes, are an important strategy for identifying and solving medication-related risks and problems [-]. Traditionally, MRs have been a physician’s duty, but practices where other care team members, including pharmacists, contribute to MRs have become more common globally [-]. Collaborative MRs have increased the need for a common electronic platform, where MR information can be documented in such a way that it is up to date and available to all health care professionals involved in the medication use process [,,].
Objective
Structured documentation offers a possible solution to these issues [-,]. To implement structured documentation of medication information, an understanding of what MR information should be available in a structured form is needed. However, no previous studies were found that defined MR information necessary to be documented in a structured form. Therefore, this study aimed at identifying what patient information obtained from MRs should be documented in a structured form in EHRs at a national and organizational level.
Methods
Context
The Finnish health care system serves a population of 5.5 million inhabitants and is mainly based on public health care, complemented by private and occupational health care []. The services are divided into primary and specialized health care services. The social and health care system is undergoing a major reform that officially started at the beginning of 2023 after a long preparatory phase []. Since then, 21 well-being services counties, the City of Helsinki, and the HUS Group (the joint authority for Helsinki and Uusimaa responsible for organizing specialized health care in the Uusimaa region) have been responsible for organizing public social and health care services. The key objective of the reform is improving the availability and accessibility of social and health services, for example, through digitalization of care pathways and patient information. The reform also concerns structures and processes needed for ensuring rational pharmacotherapy as part of patient care [,]. Availability of up-to-date electronic medication information and information transfer have been prioritized as the most important issues to be developed in this respect [-].
Use of information technology in prescribing medicines, processing prescriptions, and making medicines information available has been a routine practice in Finland since the 1980s when the first technology-based solutions were launched and nationally implemented [-]. The deployment of the national digital repository for electronic patient data Kanta since 2010 is one of the most prominent milestones toward electronic patient and medication information management in a closed-loop manner [,,,]. It enables electronic prescribing and centralized archiving of electronic patient data and data transfer between different health care providers regardless of local EHR. Electronic prescribing became mandatory by law in 2017 []. The Finnish Institute for Welfare and Health (THL) is nationally responsible for the definition, distribution, and harmonization of the structures of patient information [,]. Thus, it has played a crucial role in the development and harmonization of medication information management in EHRs by describing the target state of medication information documentation which has emphasized the importance of structured documentation. Structured documentation is also increasingly adopted in Kanta and EHRs to address shortcomings regarding data transfer and interoperability as patient and medication information is still stored in hundreds of separate systems [-].
Among the driving forces for the ongoing health and social services reform in Finland are the challenges in meeting the service needs of one of the fastest aging populations in the world [,]. Aging has increased multimorbidity and complexity of medication treatments, also increasing medication-related risks and problems [,,-]. Therefore, collaborative MR practices have been developed in Finland since 2005 as a measure to optimize medication treatments individually and to avoid preventable risks and harms [,,-]. As a result, the medication management process has become increasingly interprofessional, extending the need to share medication-related information from electronic prescriptions to follow-up information on the implementation of the medication regimen.
The Delphi Consensus Method
Overview
This study applied the Delphi consensus method, which is a qualitative survey-based method gathering views of experts with the aim of reaching consensus on the studied topic [-]. The expertise and anonymity of the expert panelists, the iteration of research arguments, and the feedback given to the experts on the results of the previous round are the method’s key characteristics. The method has been widely used in health services research for developing treatment recommendations, quality standards and indicators, risk-management tools, and integrating health service systems [,-]. For this study, 3 Delphi rounds were carried out as electronic surveys in September to December 2020 using the eDelphi software developed by Metodix Ltd []. The process was led by an 8-member research group consisting of experienced pharmacy professionals familiar with health care information systems, EHR development, IT architecture, and collaborative MRs in various operating environments, having also expertise in Delphi research methodology. The study is reported in alignment with the guidance on Conducting and REporting DElphi Studies (CREDES; ).
Expert Panel
The interprofessional expert panel consisted of the following 41 members recruited by the research group from different parts of Finland: 12 physicians, 13 pharmacists, 10 nurses, and 6 information management professionals. The recruitment had characteristics of snowball sampling, as the selected experts were invited to recommend other professionals as potential members of the expert panel. The primary criterion for the experts was MR expertise. The recruited experts needed to have experience of using patient and medication information in practice, enter MR information into data systems, and understand the possibilities and limitations of structured documentation in EHRs.
Another primary target group of the study were information management professionals (n=6) from different national authorities who had experience in developing EHR systems or other national health information systems. Many of them also had been working as health care professionals, and therefore, understood the importance of structured documentation in EHR systems, bringing invaluable insights to this study. The physicians (n=12) came from various health care organizations and specialties (eg, geriatrics, acute medicine, and oncology), national authorities, and organizations developing EHR systems. The pharmacists (n=13) came from various health care organizations, national authorities, universities, community and hospital pharmacies, and organizations specialized in developing EHR systems. Similarly, the nurses (n=10) were from different areas of health care, working in emergency and geriatric care, some having special expertise in patient safety as well as developing EHRs and closed-loop medication processes.
EHR vendors were excluded from this study as the researchers did not want commercial interests or conflict of interests influencing the results. Furthermore, this study was primarily aimed at representing the mindset of public-sector health care professionals who conduct MRs because public health care is the mainstay in Finland.
Identifying MR Topics for the First Delphi Round
MR topics for the first electronic Delphi round survey were identified by comprehensively reviewing literature on national and international MR definitions, procedures, practices, and inventories in various settings [,,-,,,-] (
Figure 1). In addition, internationally recognized and most widely used criteria of potentially inappropriate medications for older adults and drug-related problems (DRPs) were used [,,-]. A validated tool for assessing risks for DRPs to be used by practical nurses caring for home-dwelling older adults, and a validated checklist for medication-related risk factors (Lääkehoidon onnistumisen tarkistuslista LOTTA checklist) to be self-assessed by older adults were also used [,,]. The identified MR topics were inductively divided into six categories: (1) MR process topics, (2) potentially drug-induced symptoms, (3) the burden of risks for adverse drug effects, (4) laboratory tests and other test results, (5) medication adherence, and (6) the use of intoxicants.
The first Delphi round’s survey instrument was piloted by 18 experts other than panel members before the actual round to ensure the face and content validity and usability of the survey []. The results of the pilot were analyzed and compared by the 2 main researchers (TL and NL) who then presented their findings to the research group. On the basis of the pilot, a few minor changes were made to the survey. Examples of liver function tests (ALAT, ASAT, and GT), examples of electrolytes (potassium and sodium), and the orthostatic test were added to laboratory tests and other test results. In addition, the wording of 1 item was modified (“The medicine user is afraid of possible adverse effects” was modified into “The medicine user expresses concern about possible adverse effects”).
The panelists could choose from the following structured answer options when assessing each of the presented topics during rounds 1 and 2: (1) “Yes, as presented”; (2) “Yes, but modified”; (3) “Not at all”; and (4) “Cannot say.” In each round, the panelists were asked to justify their answer in an open comment field if they chose to answer with option 3, “Not at all.” The panelists were asked to comment and suggest changes if the presented topic was suitable but after modifications. The panelists were encouraged to provide comments and justifications for their choices in the open comment fields and to suggest new additional potentially missing topics.
Delphi Round 1
During the first Delphi round, the panelists were asked to assess which MR-related patient information and other patient data (N=104) should be documented in a structured form in EHRs (
Figure 2).
Delphi Round 2
The second Delphi round consisted of the topics for which consensus was not reached during the first round. New topics suggested by the panelists during the first round were also added. Thus, a total of 45-MR topics were presented to the expert panelists during the second round (Figure 2). In addition, the expert panelists were asked to assess if MR-related information should be available in the national Kanta and MyKanta services. MyKanta is a web-based part of Kanta through which citizens can access their health information, patient data, prescriptions, and laboratory test results documented by health care providers [,].
Delphi Round 3
During the third round, the expert panelists were asked to rate the importance of each of the topics for which consensus was reached during the first and second rounds (N=108) on a Likert scale from 1 to 5 (Figure 2). The importance of prioritization was emphasized, as not all topics can be structured at the same time. In addition, the expert panelists were asked to take the context into consideration, as not every topic is appropriate for every patient.
Data Analysis
The responses from each Delphi round were analyzed with Microsoft Excel by the 2 main researchers (TL and NL) who then compared their findings. The results were presented to and discussed with the whole research group that also resolved possible disagreements and approved the survey instrument to be sent for the next Delphi round. The results were reported using descriptive analysis with the main parameters being frequencies and percentages with SDs. Responses to the open-ended questions were analyzed qualitatively using inductive content analysis to modify the topics for the next round []. The consensus limit was set at 80% [,].
Ethical Considerations
The study was conducted in accordance with the national guidelines for responsible conduct of research and procedures for handling allegations of misconduct in Finland by the Finnish Advisory Board on Research Integrity []. The ethical principles of research with human participants and ethical review in the human sciences in Finland by the Finnish National Board on Research Integrity were followed []. According to the guidelines, a review by the research ethics committee and their approval were not required for this study. Participating in the expert panel was voluntary, and written informed consent was received from all expert panelists. The expert panelists were aware that their responses would be treated anonymously and used for research purposes only. The research material is stored in accordance with current regulations, considering the General Data Protection Regulation of the European Union [].
Results
Participation Rates
The results of the study consist of the MR topics for which consensus was reached during the 3 Delphi rounds. The response rates for all respondents (N=41) were 66% to 76% during all 3 Delphi rounds (
Table 1).
| Expert panel | Round 1 | Round 2 | Round 3 | |
| Experts participating in the study, n | ||||
| All professional groups | 41 | 41 | 41 | |
| Physicians | 12 | 12 | 12 | |
| Pharmacists | 13 | 13 | 13 | |
| Nurses | 10 | 10 | 10 | |
| Information management professionals | 6 | 6 | 6 | |
| Experts who answered in each round, n (%) | ||||
| All professional groups | 30-31 (73-76) | 27-29 (66-71) | 27-28 (66-68) | |
| Physicians | 8 (67) | 8 (67) | 6 (50) | |
| Pharmacists | 13 (100) | 12 (92) | 12 (92) | |
| Nurses | 5-6 (50-60) | 5 (50) | 6 (60) | |
| Information management professionals | 4 (67) | 2-4 (33-67) | 3-4 (50-67) | |
Consensus
Of the 111 topics, the expert panelists reached consensus on 108 (97.3%) topics during the 3 Delphi rounds as shown in 
Figure 3 and . During the first Delphi round, consensus was reached for 67 of 104 (64%) MR topics that the expert panelists assessed should be documented in a structured form in EHRs. Topics (n=37) for which consensus was not reached during the first Delphi round were modified and, if necessary, clarified based on the expert panelists’ comments. For consensus to be reached during the first Delphi round, it was determined based on the number of respondents (n=30-31) that 24 (77%) of the experts had to accept the presented MR topic. The expert panelists reached a consensus on 42 out of 45 (93%)-MR topics during the second Delphi round (; ). Depending on the varying response rate (n=27-29) for each question during the second Delphi round, it was determined that 21 to 22 (77%) of the experts had to accept the presented topic for consensus to be reached. A clear consensus was also reached regarding that the MR-related information should be available in the national Kanta (29/29, 100%) and MyKanta services (25/29, 86%).
Importance
During the final third round, the expert panelists rated the structured documentation of most of the topics for which consensus had been reached during the previous rounds as important or somewhat important with 92 of the 108 topics (85%) reaching a mean of at least 4.0 (; ). The 10 most important topics according to the experts are presented in .
| Medication review item | Ratings, mean (SD) |
| Blood pressure | 4.85 (0.53) |
| Kidney function tests | 4.81 (0.56) |
| Risk of bleeding | 4.81 (0.56) |
| Date of medication reconciliation | 4.78 (0.51) |
| Drug-drug interactions | 4.78 (0.51) |
| Inexplicable bruises, nose bleeds, or dark stools | 4.78 (0.58) |
| Blood glucose level | 4.78 (0.58) |
| International normalized ratio | 4.78 (0.58) |
| Sedative burden | 4.78 (0.58) |
| Renal toxicity burden | 4.78 (0.58) |
Discussion
Principal Findings
A large and committed interprofessional expert panel was obtained for this Delphi study, which enabled the identification and prioritization of MR topics that should be documented in a structured form in EHRs. To our knowledge, this is the first reported study aimed at systematically identifying these topics at the national level. Interprofessional studies involving professionals participating in patient care are essential when developing EHR systems and defining their contents. This approach ensures the views of different professional groups are integrated, enhancing the usability and compatibility of systems. The Delphi method proved to be suitable for this purpose. The structured documentation of MR topics in EHRs was perceived as important or somewhat important in most of the presented topics, including basic information about the patient’s health status, medication regimen, outcomes of the MR process, potentially drug-induced symptoms, burden of risks for adverse drug effects, results of laboratory tests and other tests, adherence, and the use of intoxicants, such as alcohol.
On the basis of the results, the patient’s blood pressure, kidney function, and risk of bleeding were clearly considered the 3 most important topics to be documented in a structured form (). Supported by previous research, the experts raised their concern that especially the estimated glomerular filtration rate (eGFR) value is often ignored even though it essentially affects the drug and dosage choices especially in older patients [-]. The structured documentation of the kidney function could also enable the use of electronic decision support systems in medication management in older adults [,]. Our results are in line with the increasing body of evidence indicating the importance of taking the kidney function into account in medicines optimization []. However, the eGFR value is not yet routinely and easily available to all care team members involved in the implementation of the drug therapy [,,].
Until now, a major portion of EHR data has consisted of unstructured elements [,]. Structured data has typically included patient demographics, vital signs, laboratory results, diagnostic codes, medication prescriptions, dosages, and administration methods, whereas elements such as clinical notes and discharge summaries have been unstructured. However, our results indicate a shift toward EHR systems that facilitate individual optimization of drug treatments. Updating standard terminology within coding systems, such as LOINC (Regenstrief Institute) and RxNORM (National Library of Medicine), so that they would enable embedding the identified MR items with Health Level 7 Fast Healthcare Interoperability Resources solutions, would thereby be essential [-]. Even though many of the clinical observations related to MRs and basic information about the patient and medicines in use are expressed and documented in standard terminology, there is still a lack of specific terminology for medication use aspects. Such aspects include confirming the patient specific therapeutic suitability and the appropriateness of medications, dosage regimen, administration route, and discontinuation of the medication (deprescribing). Once embedded within Fast Healthcare Interoperability Resources profiles, the exchange and use of more patient-specific MR data would be enabled and made electronically available to care team members, ideally also to community pharmacists while dispensing, counseling, and reviewing medications or contributing in any way to the appropriate and safe medication use [-]. This is particularly important considering aging populations leading to increased comorbidity, polypharmacy, and complex treatments that need to be managed in clinical practice [,-,-].
Medication adherence topics were rated slightly less important to be documented compared with other datasets. This may be explained by the fact that medication adherence can be considered difficult to measure as it is usually based on patient reporting or claims-based evaluations as proportion of days covered in comparison with more easily measured markers of clinical effect, such as blood pressure or blood coagulation risk [-]. On the other hand, adherence as a behavioral issue may be considered complicated to measure due to a lack of valid and reliable measures feasible to be used in routine clinical practice or to be integrated in EHRs or electronic care pathways [-]. The adherence items identified in this study address behavioral factors related to knowledge and skills in taking medication, beliefs about consequences in taking medication, and negative emotion and beliefs about capabilities in taking medication []. These items could serve as a short set of questions integrated into the EHR to help assess patients’ medication taking behaviors and screen for adherence status. This kind of integrated measure could help to identify contributing factors or even root causes to nonadherence and to help plan effective customized physician communication, which is one of the main factors influencing medication adherence []. Medication adherence is a significant factor affecting real-life effectiveness of drug therapies, as only about 50% of patients treat their long-term condition according to instructions [,]. It would be useful to integrate medication adherence items with other treatment-related adherence measures, such as diet, physical activity, or other lifestyle changes. This extension may provide a more holistic understanding of adherence and disease management problems, enabling also differentiation of medication adherence issues from other treatment adherence issues. In this respect, EHRs should be developed to enable the documentation and monitoring of adherence status and self-management of the treatment to identify problems that should be solved together with the patient [,,].
The expert panel strongly agreed on having structured MR information in the national Kanta patient information repository, while they commented on several aspects to be considered if the information was made accessible to patients in the MyKanta service. One of the concerns that emerged was the risk of the patients starting independently implementing suggested medication changes without consulting a physician. This concern is in line with physicians’ previous concerns that the patients’ access to their own health information, especially if there is not a physician available to interpret the information, may upset patients and cause wrong interpretations [-]. Therefore, previous studies have concluded that not all information should be real-time and that health care professionals should have time to interpret the obtained results and prepare the treatment plans [,,]. However, our results indicate that health care professionals have internalized the positive effects achieved by enabling patient access to their own information. The experts commented that the availability of information in MyKanta could increase the transparency of health care functions and increase a sense of trust. They recommended that the patient could see the final result or a summary of the MR in the MyKanta service but not the possible intermediate stages. These aspects need to be considered when further developing the Kanta and MyKanta services.
Structuring the identified MR topics could further promote the uniformity and standardization of the MR process and its documentation, which have been called for [,,-]. Organized and easily accessible documentation helps to create an overall picture of the patient’s situation so that those participating in the care provision can more easily make use of the previously collected essential information and notice changes in the patient’s condition making it easier to plan further treatment and discharge []. Enhancing the electronic communication between care providers has also proven to be crucial for the large-scale implementation of collaborative MRs [,]. Moreover, structured documentation of patient information could contribute to the secondary use: assessing reliably the effectiveness and cost-effectiveness of MRs, and thereby, possibly supporting their large-scale implementation into the routine clinical practice [,].
It is, however, important to recognize that although MR practices can benefit from standardization, it is still crucial to maintain flexibility in individualizing MRs according to the context, medical and patient needs, and available resources [,,]. As medication use seldom is black and white, the need for maintaining flexibility also applies to the documentation of MRs. Thus, a combination of freeform text and structured documentation has been called for [,]. To capture clinical and contextual information and interpretations about aspects, such as complexity, severity, or uncertainty, a text box for entering a freeform narrative of the clinical note might be included in an EHR to supplement the structured information [-]. This may apply to parts of MRs where a significant degree of variation occurs hindering the use of a predefined template. Such areas could be explaining the reasons behind nonadherence and self-management problems, describing how identified adherence issues have been resolved or describing the patient’s past medical history or the history of the present illness or treatment. To effectively structure the identified MR items, EHR design should focus on key aspects, such as clear labeling of structured fields for ease of use, alignment of data entry processes with clinical workflows, and optimization of user interfaces and interoperability [-].
Strengths and Limitations
Our research addresses a very current issue related to the shortcomings of electronic patient information management, particularly information related to medication treatments. The 2 main researchers (TL and NL) thoroughly reviewed previous literature, MR practices, and criteria when preparing for the first Delphi round survey to identify topics that should be documented in a structured form. This was important, because the comprehensiveness and quality of the first round’s survey is critical for a successful Delphi study [-]. The comprehensiveness of the preparatory work is supported by the fact that the expert panel proposed only a few new topics and found the presented topics appropriate. To avoid important items being excluded in the case of nonconsensus or the assumption that consensus would automatically imply the correct answer, the results of the study were continuously compared with scientific evidence and the clinical expertise of the research group that ultimately had the final say.
The expert panel was committed and large in number with a geographical and interprofessional representation. The participation rates remained high throughout the Delphi survey, reflecting commitment and interest in the subject. Of the health care professionals involved, pharmacists were most active, possibly making the results slightly pharmacist oriented. However, due to the strong consensus of the expert panelists, it can be assumed that no great distortion occurred. The lack of patients’ perspective can be considered a limitation of this study. However, this was a conscious choice made by the researchers at this point as patients cannot be expected to be able to assess the clinical relevance and importance of the MR items presented in the survey in its current form. As members of the research group who ultimately possessed the final say had experience in IT architecture and EHR development, we believe that the absence of EHR vendors in the expert panel did not affect the quality of our research. Even though the Delphi method has proven to be suitable for these kinds of medication safety and risk management studies, the typical methodological limitations of the Delphi method remain [-]. This means that the results represent the views of the expert panel and are dependent on the selection criteria and study process. As the panel consisted of Finnish experts working in the Finnish context, the results as such cannot be directly generalized beyond Finland, but they can be indicative for other countries and their EHR development.
Practical Implications
Digital patient information management applications play an increasingly important role in the planning, implementation, monitoring, and optimizing of pharmacotherapies among other health care services. In this study, a carefully built comprehensive list of MR topics was developed based on international literature. This gives EHR developers and clinicians a starting point for further prioritization of topics suitable for different operating settings for both primary and secondary use, even though MR processes in different countries differ in terms of the available patient data, patient involvement, and the purpose of the MR. Such a prioritization has not yet been internationally conducted to any greater extent []. Our study can contribute to expanding the scope of the more traditionally reviewed MR topics toward a more comprehensive patient-centered direction as well as standardizing the MR process and its documentation.
Structuring the MR process could also contribute to the effectiveness of MRs and identifying patients benefitting from MRs, thus supporting the large-scale integration of MRs into the standard care []. The topics related to drug treatment monitoring could prove significant in this regard, as these often represent components that influence the outcomes of MRs []. This combined with the fast advances in integrating artificial intelligence (AI) tools for natural language processing of free text into EHRs would significantly enhance the MR process []. This will extend the function of the medication-related documentation in EHRs from a technical data repository toward a prospective clinical decision support system and medication risk management system. The results of this study clarify the issues encountered during the implementation of drug treatments, identify the components of MRs, and highlight which of these components represent critical measures that should be monitored in the patients’ condition during treatment. In a well-organized information system, these identified factors are quite likely to improve therapeutic outcomes, reduce risks and problems, and increase the efficiency of drug treatment implementation processes.
Further Research
In this study, a strong consensus emerged for the structured documentation of a large number of MR topics. The next step in ensuring the clinical feasibility and practical implementation of structured documentation is to define how the information identified in this study should be structured in practice so that the documentation does not become too laborious and time-consuming. Therefore, automated clinical documentation and AI applications should be developed in such a way that compiling and interpreting the information is automated, reliable, and covers the essential information regarding medication treatments [,]. Since not all information can be structured at once, further prioritization is needed. This would enable the use of the structured information for secondary purposes such as identifying patients at risk of developing DRPs and thus benefit from MRs by developing alerts and using AI in automatic screening. Starting with the most prioritized information related to blood pressure, eGFR and the risk of bleeding would seem logical. Involving patients and EHR vendors is an essential prerequisite to ensure that the perspectives and priorities of patients, especially what comes to adherence items, are taken into account in the further development and practical implementation of the structured documentation of MR items. Furthermore, it must be defined which MR information should be made available to patients and what information the patients themselves could document in electronic patient information systems. However, pilots are needed to test new kinds of digital documentation and their use in the medication management system.
Conclusions
The committed interprofessional expert panel had a strong consensus on a wide range of MR-related information that should be structurally documented in electronic patient information systems. Further prioritization of the information identified in this study is needed. The expert panel also had a consensus that the MR information should be available to all health care professionals involved in a care team and the patients themselves with some reservations.
Acknowledgments
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Open access funded by Helsinki University Library.
Data Availability
The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.
Authors' Contributions
TL was responsible for study concept and design, data analysis, data interpretation, and drafting and revision of the manuscript for important intellectual content. NL was responsible for study concept and design, data analysis, data interpretation, and revision of the manuscript for important intellectual content. KK, ARH, TT, MU, HN and MA were responsible for study concept and design, data interpretation, and revision of the manuscript for important intellectual content. All authors read and approved the final manuscript.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Guidance on Conducting and Reporting of Delphi Studies.
PDF File (Adobe PDF File), 456 KBMultimedia Appendix 2
The identified medication review (MR) topics (N=108) that should be documented in a structured form in the electronic health record and the MR topics (n=3) for which consensus was not reached.
PDF File (Adobe PDF File), 411 KBReferences
- Keller ME, Kelling SE, Cornelius DC, Oni HA, Bright DR. Enhancing practice efficiency and patient care by sharing electronic health records. Perspect Health Inf Manag. 2015;12(Fall):1b. [FREE Full text] [Medline]
- Delice E, Polatlı L, Jbara KA, Tozan H, Ertürk A. Digitalization in healthcare: a systematic review of the literature. Proceedings. 2023;85(1):26. [FREE Full text] [CrossRef]
- Kallio S, Kumpusalo-Vauhkonen A, Järvensivu T, Mäntylä A, Pohjanoksa-Mäntylä M, Airaksinen M. Towards interprofessional networking in medication management of the aged: current challenges and potential solutions in Finland. Scand J Prim Health Care. Dec 2016;34(4):368-376. [FREE Full text] [CrossRef] [Medline]
- Kaipio J, Lääveri T, Hyppönen H, Vainiomäki S, Reponen J, Kushniruk A, et al. Usability problems do not heal by themselves: national survey on physicians' experiences with EHRs in Finland. Int J Med Inform. Jan 2017;97:266-281. [FREE Full text] [CrossRef] [Medline]
- Quinn M, Forman J, Harrod M, Winter S, Fowler KE, Krein SL, et al. Electronic health records, communication, and data sharing: challenges and opportunities for improving the diagnostic process. Diagnosis (Berl). Aug 27, 2019;6(3):241-248. [FREE Full text] [CrossRef] [Medline]
- Payne TH, Zhao LP, Le C, Wilcox P, Yi T, Hinshaw J, et al. Electronic health records contain dispersed risk factor information that could be used to prevent breast and ovarian cancer. J Am Med Inform Assoc. Jul 01, 2020;27(9):1443-1449. [FREE Full text] [CrossRef] [Medline]
- Warren L, Clarke J, Darzi A. Measuring the scale of hospital health record system fragmentation in england. Health Serv Res. Aug 20, 2020;55(S1):43-44. [CrossRef]
- Li E, Clarke J, Ashrafian H, Darzi A, Neves AL. The impact of electronic health record interoperability on safety and quality of care in high-income countries: systematic review. J Med Internet Res. Sep 15, 2022;24(9):e38144. [FREE Full text] [CrossRef] [Medline]
- Steinkamp J, Kantrowitz JJ, Airan-Javia S. Prevalence and sources of duplicate information in the electronic medical record. JAMA Netw Open. Sep 01, 2022;5(9):e2233348. [FREE Full text] [CrossRef] [Medline]
- Atasoy H, Greenwood BN, McCullough JS. The digitization of patient care: a review of the effects of electronic health records on health care quality and utilization. Annu Rev Public Health. Apr 01, 2019;40(1):487-500. [CrossRef] [Medline]
- Häyrinen K, Saranto K, Nykänen P. Definition, structure, content, use and impacts of electronic health records: a review of the research literature. Int J Med Inform. May 2008;77(5):291-304. [CrossRef] [Medline]
- Kalra F, Fernando B, Morrison Z, Sheikh A. A review of the empirical evidence of the value of structuring and coding of clinical information within electronic health records for direct patient care. Inform Prim Care. 2012;20(3):171-180. [FREE Full text] [CrossRef] [Medline]
- Wells BJ, Chagin KM, Nowacki AS, Kattan MW. Strategies for handling missing data in electronic health record derived data. EGEMS (Wash DC). 2013;1(3):1035. [FREE Full text] [CrossRef] [Medline]
- Forsvik H, Voipio V, Lamminen J, Doupi P, Hyppönen H, Vuokko R. Literature review of patient record structures from the physician's perspective. J Med Syst. Feb 27, 2017;41(2):29. [CrossRef] [Medline]
- Vuokko R, Mäkelä-Bengs P, Hyppönen H, Lindqvist M, Doupi P. Impacts of structuring the electronic health record: results of a systematic literature review from the perspective of secondary use of patient data. Int J Med Inform. Jan 2017;97:293-303. [CrossRef] [Medline]
- Ferrão JC, Oliveira MD, Janela F, Martins HM, Gartner D. Can structured EHR data support clinical coding? A data mining approach. Health Syst (Basingstoke). Mar 01, 2020;10(2):138-161. [FREE Full text] [CrossRef] [Medline]
- Fennelly O, Cunningham C, Grogan L, Cronin H, O'Shea C, Roche M, et al. Successfully implementing a national electronic health record: a rapid umbrella review. Int J Med Inform. Dec 2020;144:104281. [FREE Full text] [CrossRef] [Medline]
- Manskow US, Kristiansen TT. Challenges faced by health professionals in obtaining correct medication information in the absence of a shared digital medication list. Pharmacy (Basel). Feb 22, 2021;9(1):46. [FREE Full text] [CrossRef] [Medline]
- Hepler CD, Strand LM. Opportunities and responsibilities in pharmaceutical care. Am J Hosp Pharm. Mar 01, 1990;47(3):533-543. [CrossRef]
- Leikola S, Tuomainen L, Peura S, Laurikainen A, Lyles A, Savela E, et al. Comprehensive medication review: development of a collaborative procedure. Int J Clin Pharm. Aug 2012;34(4):510-514. [CrossRef] [Medline]
- Dimitrow SM. Development and validation of a drug-related problem risk assessment tool for use by practical nurses working with community-dwelling aged. Dissertation. University of Helsinki; 2016. URL: https://helda.helsinki.fi/items/185e2d7a-36e5-46f3-85e6-3c95374d9170 [accessed 2024-10-09]
- Griese-Mammen N, Hersberger KE, Messerli M, Leikola S, Horvat N, van Mil JW, et al. PCNE definition of medication review: reaching agreement. Int J Clin Pharm. Oct 2018;40(5):1199-1208. [CrossRef] [Medline]
- Schepel L, Aronpuro K, Kvarnström K, Holmström AR, Lehtonen L, Lapatto-Reiniluoto O, et al. Strategies for improving medication safety in hospitals: evolution of clinical pharmacy services. Res Soc Adm Pharm. Jul 2019;15(7):873-882. [CrossRef]
- Bulajeva A, Labberton L, Leikola S, Pohjanoksa-Mäntylä M, Geurts MM, de Gier JJ, et al. Medication review practices in European countries. Res Social Adm Pharm. 2014;10(5):731-740. [CrossRef] [Medline]
- Kiiski A, Airaksinen M, Mäntylä A, Desselle S, Kumpusalo-Vauhkonen A, Järvensivu T, et al. An inventory of collaborative medication reviews for older adults - evolution of practices. BMC Geriatr. Nov 21, 2019;19(1):321. [FREE Full text] [CrossRef] [Medline]
- Imfeld-Isenegger TL, Soares IB, Makovec UN, Horvat N, Kos M, van Mil F, et al. Community pharmacist-led medication review procedures across Europe: characterization, implementation and remuneration. Res Soc Adm Pharm. Aug 2020;16(8):1057-1066. [CrossRef] [Medline]
- Kallio SE, Kiiski A, Airaksinen MS, Mäntylä AT, Kumpusalo-Vauhkonen AE, Järvensivu TP, et al. Community pharmacists' contribution to medication reviews for older adults: a systematic review. J Am Geriatr Soc. Aug 2018;66(8):1613-1620. [CrossRef] [Medline]
- Mercer K, Burns C, Guirguis L, Chin J, Dogba MJ, Dolovich L, et al. Physician and pharmacist medication decision-making in the time of electronic health records: mixed-methods study. JMIR Hum Factors. Sep 25, 2018;5(3):e24. [FREE Full text] [CrossRef] [Medline]
- Keskimäki I, Tynkkynen LK, Reissell E, Koivusalo M, Syrjä V, Vuorenkoski L, et al. Finland: health system review. Health Syst Transit. 2019;21(2):1-166. [FREE Full text]
- Ministry of Social Affairs and Health. National service reform: reform of the content and operating methods of health and social services. URL: https://stm.fi/en/national-service-reform [accessed 2024-11-13]
- Ministry of Social Affairs and Health. Reports and Memorandums of the Ministry of Social Affairs and Health 19/2018. Rational Pharmacotherapy Action Plan. Final report. 2018. URL: http://urn.fi/URN:ISBN:978-952-00-3930-1 [accessed 2024-05-03]
- Ministry of Social Affairs and Health. Points of views on Need for Changes in Medication and Distribution system of Medicines Memorandum. Sosiaali- ja Terveysministeriö Helsinki. 2019. URL: https://julkaisut.valtioneuvosto.fi/bitstream/handle/10024/161340/STM_Rap_5_2019.pdf?sequence=1&isAllowed=y [accessed 2024-08-19]
- Jormanainen V. Large-scale implementation and adoption of the Finnish national Kanta services in 2010–2017: a prospective, longitudinal, indicator-based study. Fin J EHealth EWelfare. Dec 04, 2018;10(4):381-395. [CrossRef]
- Mononen N. From paper to cyber: medicines information as a strategic goal in Finland and the European Union. Dissertation. University of Helsinki; 2020. URL: https://helda.helsinki.fi/items/6ad9f259-5bcb-4b4f-9b56-6cab7e73f59c [accessed 2024-08-02]
- Kallio S. Community pharmacists’ contribution to prospective medication risk management for older adults in the context of network theory. Dissertation. University of Helsinki; 2021. URL: https://helda.helsinki.fi/items/eedbeeb8-e242-4f8e-881b-23501f908b39 [accessed 2024-09-14]
- Heponiemi T, Hyppönen H, Vehko T, Kujala S, Aalto AM, Vänskä J, et al. Finnish physicians' stress related to information systems keeps increasing: a longitudinal three-wave survey study. BMC Med Inform Decis Mak. Oct 17, 2017;17(1):147. [FREE Full text] [CrossRef] [Medline]
- Kanta homepage. Kanta. URL: https://www.kanta.fi/en/ [accessed 2024-05-30]
- Act on electronic prescriptions 61/2007. Finlex. URL: https://www.finlex.fi/fi/lainsaadanto/2007/61 [accessed 2024-12-17]
- Hyppönen H, Vuokko R, Doupi P, Mäkelä-Bengs P. Structuring of the Electronic Patient Record. Methods, Assessment Practices and Impacts. Helsinki, Finland. National Institute for Health and Welfare; 2014. URL: https://urn.fi/URN:ISBN:978-952-302-381-9 [accessed 2024-05-27]
- Virkkunen H, Palvimo J. The concept of medication treatment information management. The Finnish Institute for Health and Welfare. Dec 2024. URL: https://www.julkari.fi/bitstream/handle/10024/150221/L%c3%a4%c3%a4kehoidon%20tiedonhallinnan%20konsepti-v2-20241216.pdf?sequence=1&isAllowed=y [accessed 2024-12-16]
- Kaipio J, Kuusisto A, Hyppönen H, Heponiemi T, Lääveri T. Physicians' and nurses' experiences on EHR usability: comparison between the professional groups by employment sector and system brand. Int J Med Inform. Feb 2020;134:104018. [FREE Full text] [CrossRef] [Medline]
- Statistical yearbook on social welfare and health care 2021. Finnish Institute for Health and Welfare. 2021. URL: https://www.julkari.fi/handle/10024/143537 [accessed 2024-08-18]
- Pitkala KH, Juola AL, Hosia H, Teramura-Gronblad M, Soini H, Savikko N, et al. Eight-year trends in the use of opioids, other analgesics, and psychotropic medications among institutionalized older people in Finland. J Am Med Dir Assoc. Nov 01, 2015;16(11):973-978. [CrossRef] [Medline]
- Juola AL, Pylkkanen S, Kautiainen H, Bell JS, Bjorkman MP, Finne-Soveri H, et al. Burden of potentially harmful medications and the association with quality of life and mortality among institutionalized older people. J Am Med Dir Assoc. Mar 01, 2016;17(3):276.e9-276.14. [CrossRef] [Medline]
- Auvinen K, Räisänen J, Merikoski M, Mäntylä A, Kumpusalo-Vauhkonen A, Enlund H, et al. The Finnish Interprofessional Medication Assessment (FIMA): baseline findings from home care setting. Aging Clin Exp Res. Oct 2019;31(10):1471-1479. [FREE Full text] [CrossRef] [Medline]
- Jalava SE, Pohjanoksa-Mäntylä M, Puustinen J, Airaksinen M, Dimitrow MS. Psykoosilääkkeiden käyttö iäkkäillä : järjestelmällinen katsaus [Use of antipsychotics among older adults in Finland: a systematic review]. Suomen lääkärilehti. 2018;73(33):1743-1749. [FREE Full text]
- Kurko T, Saastamoinen LK, Tuulio-Henriksson A, Taiminen T, Tiihonen J, Airaksinen M, et al. Trends in the long-term use of benzodiazepine anxiolytics and hypnotics: a national register study for 2006 to 2014. Pharmacoepidemiol Drug Saf. Jun 2018;27(6):674-682. [CrossRef] [Medline]
- Toivo T, Airaksinen M, Dimitrow M, Savela E, Pelkonen K, Kiuru V, et al. Enhanced coordination of care to reduce medication risks in older home care clients in primary care: a randomized controlled trial. BMC Geriatr. Nov 27, 2019;19(1):332. [FREE Full text] [CrossRef] [Medline]
- Dimitrow MS, Mykkänen SI, Leikola SN, Kivelä SL, Lyles A, Airaksinen MS. Content validation of a tool for assessing risks for drug-related problems to be used by practical nurses caring for home-dwelling clients aged ≥65 years: a Delphi survey. Eur J Clin Pharmacol. Aug 2014;70(8):991-1002. [CrossRef] [Medline]
- The National Coordination Group of Professional Development of Pharmacy Services (AATE). Medication review competence recommendations for pharmacists working in community pharmacies and other health care settings (English summary). Dosis. 2017;33(3):199-209. [FREE Full text]
- Dalkey N, Helmer O. An experimental application of the DELPHI method to the use of experts. Manag Sci. Apr 1963;9(3):458-467. [CrossRef]
- Campbell SM, Cantrill JA. Consensus methods in prescribing research. J Clin Pharm Ther. Feb 15, 2001;26(1):5-14. [CrossRef] [Medline]
- Okoli C, Pawlowski SD. The Delphi method as a research tool: an example, design considerations and applications. Inf Manag. Dec 2004;42(1):15-29. [CrossRef]
- Hsu CC, Sandford BA. The Delphi technique: making sense of consensus. Pract Assess Res Eval. 2007;12(1):10. [FREE Full text]
- Beers MH, Ouslander JG, Rollingher I, Reuben DB, Brooks J, Beck JC. Explicit criteria for determining inappropriate medication use in nursing home residents. Arch Intern Med. Sep 01, 1991;151(9):1825-1832. [CrossRef]
- Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. Arch Intern Med. Jul 28, 1997;157(14):1531-1536. [CrossRef]
- McLeod PJ, Huang AR, Tamblyn RM, Gayton DC. Defining inappropriate practices in prescribing for elderly people: a national consensus panel. CMAJ. Feb 01, 1997;156(3):385-391. [FREE Full text] [Medline]
- Naugler CT, Brymer C, Stolee P, Arcese ZA. Development and validation of an improving prescribing in the elderly tool. Can J Clin Pharmacol. 2000;7(2):103-107. [Medline]
- Fick DM, Cooper JW, Wade WE, Waller JL, Maclean JR, Beers MH. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch Intern Med. Dec 08, 2003;163(22):2716-2724. [CrossRef] [Medline]
- Gallagher P, Ryan C, Byrne S, Kennedy J, O'Mahony D. STOPP (Screening Tool of Older Person's Prescriptions) and START (Screening Tool to Alert doctors to Right Treatment). Consensus validation. Int J Clin Pharmacol Ther. Feb 2008;46(2):72-83. [CrossRef] [Medline]
- Rognstad S, Brekke M, Fetveit A, Spigset O, Wyller TB, Straand J. The Norwegian General Practice (NORGEP) criteria for assessing potentially inappropriate prescriptions to elderly patients. A modified Delphi study. Scand J Prim Health Care. Sep 09, 2009;27(3):153-159. [FREE Full text] [CrossRef] [Medline]
- Maaskant JM, Eskes A, van Rijn-Bikker P, Bosman D, van Aalderen W, Vermeulen H. High-alert medications for pediatric patients: an international modified Delphi study. Expert Opin Drug Saf. Nov 10, 2013;12(6):805-814. [CrossRef] [Medline]
- Pouliot A, Vaillancourt R, Stacey D, Suter P. Defining and identifying concepts of medication literacy: an international perspective. Res Social Adm Pharm. Sep 2018;14(9):797-804. [CrossRef] [Medline]
- Penm J, Vaillancourt R, Pouliot A. Defining and identifying concepts of medication reconciliation: an international pharmacy perspective. Res Social Adm Pharm. Jun 2019;15(6):632-640. [FREE Full text] [CrossRef] [Medline]
- Watson KE, Singleton JA, Tippett V, Nissen LM. Defining pharmacists' roles in disasters: a Delphi study. PLoS One. Dec 26, 2019;14(12):e0227132. [FREE Full text] [CrossRef] [Medline]
- Delphi Method Software eDelphi. Metodix Ltd. URL: https://www.edelphi.org/ [accessed 2024-08-12]
- Burns A. Medication therapy management in pharmacy practice: core elements of an MTM service model (version 2.0). J Am Pharm Assoc. May 2008;48(3):341-353. [FREE Full text] [CrossRef]
- Clyne W, Blenkinsopp A, Seal R. A guide to medication review 2008. National Health Service. 2008. URL: https://www.cff.org.br/userfiles/52%20-%20CLYNE%20W%20A%20guide%20to%20medication%20review%202008.pdf [accessed 2024-10-15]
- LaMantia MA, Scheunemann LP, Viera AJ, Busby-Whitehead J, Hanson LC. Interventions to improve transitional care between nursing homes and hospitals: a systematic review. J Am Geriatr Soc. Apr 2010;58(4):777-782. [FREE Full text] [CrossRef] [Medline]
- Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. Mar 2011;40(2):150-162. [CrossRef] [Medline]
- Blenkinsopp A, Bond C, Raynor DK. Medication reviews. Br J Clin Pharmacol. Oct 05, 2012;74(4):573-580. [FREE Full text] [CrossRef] [Medline]
- Kwint HF, Bermingham L, Faber A, Gussekloo J, Bouvy ML. The relationship between the extent of collaboration of general practitioners and pharmacists and the implementation of recommendations arising from medication review: a systematic review. Drugs Aging. Feb 16, 2013;30(2):91-102. [CrossRef] [Medline]
- Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. Oct 07, 2014;10(10):CD008165. [CrossRef] [Medline]
- National Institute for Health and Care Excellence. Medicines optimisation: the safe and effective use of medicines to enable the best possible outcomes. Mar 4, 2015. URL: https://nice.org.uk/guidance/ng5 [accessed 2024-05-26]
- Chen TF. Pharmacist-led home medicines review and residential medication management review: the Australian model. Drugs Aging. Mar 9, 2016;33(3):199-204. [CrossRef] [Medline]
- Jokanovic N, Tan EC, van den Bosch D, Kirkpatrick CM, Dooley MJ, Bell JS. Clinical medication review in Australia: a systematic review. Res Social Adm Pharm. May 2016;12(3):384-418. [CrossRef] [Medline]
- Kiiski A, Kallio S, Pohjanoksa-Mäntylä M, Kumpusalo-Vauhkonen A, Järvensivu T, Airaksinen M, et al. Reports and memorandums of the Ministry of Social Affairs and Health 19/2018. Rationalization of Pharmacotherapy for the Elderly as an Inter-Professional Collaboration. Systematic Review (in Finnish). 2018. URL: https://julkaisut.valtioneuvosto.fi/bitstream/handle/10024/74808/RAP-2016-12-iakkaiden-l%c3%a4%c3%a4kehoidon-j%c3%a4rkeist%c3%a4minen.pdf?sequence=1&isAllowed=y [accessed 2024-05-26]
- Duncan P, Cabral C, McCahon D, Guthrie B, Ridd MJ. Efficiency versus thoroughness in medication review: a qualitative interview study in UK primary care. Br J Gen Pract. Feb 11, 2019;69(680):e190-e198. [CrossRef]
- Rose O, Cheong VL, Dhaliwall S, Eislage K, Erzkamp S, Jorgenson D, et al. Standards in medication review: an international perspective. Can Pharm J (Ott). Jul 14, 2020;153(4):215-223. [FREE Full text] [CrossRef] [Medline]
- Lias N, Lindholm T, Pohjanoksa-Mäntylä M, Westerholm A, Airaksinen M. Developing and piloting a self-assessment tool for medication review competence of practicing pharmacists based on nationally set competence criteria. BMC Health Serv Res. Nov 25, 2021;21(1):1274. [FREE Full text] [CrossRef] [Medline]
- Hanlon JT, Schmader KE, Samsa GP, Weinberger M, Uttech KM, Lewis IK, et al. A method for assessing drug therapy appropriateness. J Clin Epidemiol. Oct 1992;45(10):1045-1051. [CrossRef] [Medline]
- By the 2019 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2019 Updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. Apr 2019;67(4):674-694. [CrossRef] [Medline]
- Strand LM, Morley PC, Cipolle RJ, Ramsey R, Lamsam GD. Drug-related problems: their structure and function. DICP. Nov 01, 1990;24(11):1093-1097. [CrossRef] [Medline]
- Cipolle RJ, Strand LM, Morley PC. Pharmaceutical Care Practice: The Clinician's Guide, Second Edition. New York, NY. McGraw-Hill Education; 2004.
- Cipolle RJ, Strand LM, Morley PC. Pharmaceutical Care Practice: The Patient Centered Approach to Medication Management. 3rd Edition. New York, NY. McGraw-Hill Education; 2012.
- Pharmaceutical Care Network Europe Association. Classification for drug related problems. 2019. URL: https://www.pcne.org/upload/files/410_PCNE_classification_V9-0m.pdf [accessed 2024-05-05]
- Kanninen JC, Puustinen J, Airaksinen M, Kautiainen H, Koivisto AL, Hietasalo P, et al. Self-assessed medication risk factors as part of comprehensive health screening in home-dwelling older adults. Health Sci Rep. Apr 13, 2023;6(4):e1196. [FREE Full text] [CrossRef] [Medline]
- Ranganathan P, Caduff C, Frampton CM. Designing and validating a research questionnaire - part 2. Perspect Clin Res. 2024;15(1):42-45. [FREE Full text] [CrossRef] [Medline]
- Jormanainen V, Lindgren M, Keskimäki I, Kaila M. Use of My Kanta in Finland 2010-2022. Stud Health Technol Inform. Jun 29, 2023;305:448-451. [CrossRef] [Medline]
- MyKanta. Kanta. URL: https://www.kanta.fi/en/my-kanta-pages [accessed 2024-09-07]
- Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs. Apr 2008;62(1):107-115. [CrossRef] [Medline]
- Diamond IR, Grant RC, Feldman BM, Pencharz PB, Ling SC, Moore AM, et al. Defining consensus: a systematic review recommends methodologic criteria for reporting of Delphi studies. J Clin Epidemiol. Apr 2014;67(4):401-409. [CrossRef] [Medline]
- Finnish Advisory Board on Research Integrity. Responsible conduct of research and procedures for handling allegations of misconduct in Finland. 2012. URL: http://www.tenk.fi/sites/tenk.fi/files/HTK_ohje_2012.pdf [accessed 2024-05-15]
- Finnish National Board on Research Integrity TENK. The ethical principles of research with human participants and ethical review in the human sciences in Finland. Finnish National Board on Research Integrity TEKN Guidelines. 2019. URL: https://tenk.fi/sites/default/files/2021-01/Ethical_review_in_human_sciences_2020.pdf [accessed 2024-05-15]
- Office of a Data Protection Ombudsman. Scientific research and data protection. 2020. URL: https://tietosuoja.fi/en/scientific-research-and-data-protection [accessed 2024-05-15]
- Elinder CG, Bárány P, Heimbürger O. The use of estimated glomerular filtration rate for dose adjustment of medications in the elderly. Drugs Aging. Jul 6, 2014;31(7):493-499. [CrossRef] [Medline]
- Dörks M, Allers K, Schmiemann G, Herget-Rosenthal S, Hoffmann F. Inappropriate medication in non-hospitalized patients with renal insufficiency: a systematic review. J Am Geriatr Soc. Apr 27, 2017;65(4):853-862. [CrossRef] [Medline]
- Tesfaye WH, Castelino RL, Wimmer BC, Zaidi ST. Inappropriate prescribing in chronic kidney disease: a systematic review of prevalence, associated clinical outcomes and impact of interventions. Int J Clin Pract. Jul 23, 2017;71(7):e12960. [CrossRef] [Medline]
- Ibrahim J, Hazzan A, Mathew AT, Sakhiya V, Zhang M, Halinski C, et al. Medication discrepancies in late-stage chronic kidney disease. Clin Kidney J. Aug 2018;11(4):507-512. [FREE Full text] [CrossRef] [Medline]
- Koskela T, Sandström S, Mäkinen J, Liira H. User perspectives on an electronic decision-support tool performing comprehensive medication reviews - a focus group study with physicians and nurses. BMC Med Inform Decis Mak. Jan 22, 2016;16(1):6. [FREE Full text] [CrossRef] [Medline]
- Alagiakrishnan K, Wilson P, Sadowski C, Rolfson D, Ballerman M, Ausford A, et al. Physicians’ use of computerized clinical decision supports to improve medication management in the elderly – the Seniors Medication Alert and Review Technology intervention. Clin Interv Aging. Jan 2016;11:73-81. [CrossRef]
- Modig S, Lannering C, Ostgren CJ, Mölstad S, Midlöv P. The assessment of renal function in relation to the use of drugs in elderly in nursing homes; a cohort study. BMC Geriatr. Jan 11, 2011;11(1):1. [FREE Full text] [CrossRef] [Medline]
- Kallio S, Eskola T, Pohjanoksa-Mäntylä M, Airaksinen M. Medication risk management in routine dispensing in community pharmacies. Int J Environ Res Public Health. Nov 05, 2020;17(21):8186. [FREE Full text] [CrossRef] [Medline]
- Ellinger LK, Bursua A, Galanter W, Schiff GD, Lambert BL. Empowering pharmacists with data: steps toward proactive medication safety and quality improvement. J Am Coll Clin Pharm. Jun 27, 2024;7(8):824-831. [CrossRef]
- Bush RA, Kuelbs C, Ryu J, Jiang W, Chiang G. Structured data entry in the electronic medical record: perspectives of pediatric specialty physicians and surgeons. J Med Syst. May 21, 2017;41(5):75. [CrossRef] [Medline]
- Shah SM, Khan RA. Secondary use of electronic health record: opportunities and challenges. IEEE Access. 2020;8:136947-136965. [CrossRef]
- LOINC. Regenstrief Institute. URL: https://loinc.org/ [accessed 2025-03-01]
- RxNORM. National Institutes of Health National Library of Medicine. URL: https://www.nlm.nih.gov/research/umls/rxnorm/index.html [accessed 2025-02-28]
- Welcome to FHIR®. HL7® FHIR® Foundation. URL: https://www.hl7.org/fhir/index.html [accessed 2025-03-02]
- Salgado TM, Correr CJ, Moles R, Benrimoj SI, Fernandez-Llimos F. Assessing the implementability of clinical pharmacist interventions in patients with chronic kidney disease: an analysis of systematic reviews. Ann Pharmacother. Nov 27, 2013;47(11):1498-1506. [CrossRef] [Medline]
- Pourrat X, Sipert AS, Gatault P, Sautenet B, Hay N, Guinard F, et al. Community pharmacist intervention in patients with renal impairment. Int J Clin Pharm. Dec 18, 2015;37(6):1172-1179. [CrossRef] [Medline]
- Mongaret C, Aubert L, Lestrille A, Albaut V, Kreit P, Herlem E, et al. The role of community pharmacists in the detection of clinically relevant drug-related problems in chronic kidney disease patients. Pharmacy (Basel). May 22, 2020;8(2):89. [FREE Full text] [CrossRef] [Medline]
- Gao L, Maidment I, Matthews F, Robinson L, Brayne C, Medical Research Council Cognitive Function and Ageing Study. Medication usage change in older people (65+) in England over 20 years: findings from CFAS I and CFAS II. Age Ageing. Mar 01, 2018;47(2):220-225. [FREE Full text] [CrossRef] [Medline]
- Young EH, Pan S, Yap AG, Reveles KR, Bhakta K. Polypharmacy prevalence in older adults seen in United States physician offices from 2009 to 2016. PLoS One. Aug 3, 2021;16(8):e0255642. [FREE Full text] [CrossRef] [Medline]
- Delara M, Murray L, Jafari B, Bahji A, Goodarzi Z, Kirkham J, et al. Prevalence and factors associated with polypharmacy: a systematic review and meta-analysis. BMC Geriatr. Jul 19, 2022;22(1):601. [FREE Full text] [CrossRef] [Medline]
- Tarn DM, Mattimore TJ, Bell DS, Kravitz RL, Wenger NS. Provider views about responsibility for medication adherence and content of physician-older patient discussions. J Am Geriatr Soc. Jun 2012;60(6):1019-1026. [CrossRef] [Medline]
- Kjeldsen LJ, Nielsen TR, Olesen C. The challenges of outcome research. Int J Clin Pharm. Jun 2, 2016;38(3):705-708. [CrossRef] [Medline]
- Berra E, Azizi M, Capron A, Høieggen A, Rabbia F, Kjeldsen SE, et al. Evaluation of adherence should become an integral part of assessment of patients with apparently treatment-resistant hypertension. Hypertension. Aug 2016;68(2):297-306. [CrossRef]
- Kekäle M, Talvensaari K, Koskenvesa P, Porkka K, Airaksinen M. Chronic myeloid leukemia patients' adherence to peroral tyrosine kinase inhibitors compared with adherence as estimated by their physicians. Patient Prefer Adherence. 2014;8:1619-1627. [FREE Full text] [CrossRef] [Medline]
- Nieuwlaat R, Wilczynski N, Navarro T, Hobson N, Jeffery R, Keepanasseril A, et al. Interventions for enhancing medication adherence. Cochrane Database Syst Rev. Nov 20, 2014;2014(11):CD000011. [FREE Full text] [CrossRef] [Medline]
- Lam WY, Fresco P. Medication adherence measures: an overview. Biomed Res Int. 2015;2015:217047. [FREE Full text] [CrossRef] [Medline]
- Bokhour BG, Berlowitz DR, Long JA, Kressin NR. How do providers assess antihypertensive medication adherence in medical encounters? J Gen Intern Med. Jun 2006;21(6):577-583. [FREE Full text] [CrossRef] [Medline]
- Curtis JR, Cai Q, Wade SW, Stolshek BS, Adams JL, Balasubramanian A, et al. Osteoporosis medication adherence: physician perceptions vs. patients' utilization. Bone. Jul 2013;55(1):1-6. [CrossRef]
- Heeb RM, Kreeuzberg V, Grossmann V. Physicians' assessment of medication adherence: a systematic review. J Pharm Care Health Sys. 2019;06(01). [CrossRef]
- Tran VD, Vo TM, Vo QL, Nguyen MT, Nguyen MC, Dewey RS, et al. Behavioral factors associated with medication adherence among hypertensive patients using the theoretical domains framework. Explor Res Clin Soc Pharm. Dec 2024;16:100510. [FREE Full text] [CrossRef] [Medline]
- Kvarnström K, Westerholm A, Airaksinen M, Liira H. Factors contributing to medication adherence in patients with a chronic condition: a scoping review of qualitative research. Pharmaceutics. Jul 20, 2021;13(7):1100. [FREE Full text] [CrossRef] [Medline]
- World Health Organization. Medication without harm: WHO global patient safety challenge. 2017. URL: https://iris.who.int/bitstream/handle/10665/255263/WHO-HIS-SDS-2017.6-eng.pdf;jsessionid=7101003388F62C8E9B433E7D11C77940?sequence=1 [accessed 2024-05-23]
- Mohammed MA, Moles RJ, Chen TF. Medication-related burden and patients' lived experience with medicine: a systematic review and metasynthesis of qualitative studies. BMJ Open. Feb 02, 2016;6(2):e010035. [FREE Full text] [CrossRef] [Medline]
- Bailey SC, Wallia A, Wright S, Wismer GA, Infanzon AC, Curtis LM, et al. Electronic health record-based strategy to promote medication adherence among patients with diabetes: longitudinal observational study. J Med Internet Res. Oct 21, 2019;21(10):e13499. [FREE Full text] [CrossRef] [Medline]
- Blecker S, Schoenthaler A, Martinez TR, Belli HM, Zhao Y, Wong C, et al. Leveraging electronic health record technology and team care to address medication adherence: protocol for a cluster randomized controlled trial. JMIR Res Protoc. Jul 07, 2023;12:e47930. [FREE Full text] [CrossRef] [Medline]
- Beard L, Schein R, Morra D, Wilson K, Keelan J. The challenges in making electronic health records accessible to patients. J Am Med Inform Assoc. Jan 01, 2012;19(1):116-120. [FREE Full text] [CrossRef] [Medline]
- Davis Giardina T, Menon S, Parrish DE, Sittig DF, Singh H. Patient access to medical records and healthcare outcomes: a systematic review. J Am Med Inform Assoc. 2014;21(4):737-741. [FREE Full text] [CrossRef] [Medline]
- de Lusignan S, Mold F, Sheikh A, Majeed A, Wyatt JC, Quinn T, et al. Patients' online access to their electronic health records and linked online services: a systematic interpretative review. BMJ Open. Sep 08, 2014;4(9):e006021. [FREE Full text] [CrossRef] [Medline]
- Mold F, de Lusignan S, Sheikh A, Majeed A, Wyatt JC, Quinn T, et al. Patients' online access to their electronic health records and linked online services: a systematic review in primary care. Br J Gen Pract. Mar 2015;65(632):e141-e151. [FREE Full text] [CrossRef] [Medline]
- D'Costa SN, Kuhn IL, Fritz Z. A systematic review of patient access to medical records in the acute setting: practicalities, perspectives and ethical consequences. BMC Med Ethics. Mar 02, 2020;21(1):18. [FREE Full text] [CrossRef] [Medline]
- Grossman LV, Choi SW, Collins S, Dykes PC, O'Leary KJ, Rizer M, et al. Implementation of acute care patient portals: recommendations on utility and use from six early adopters. J Am Med Inform Assoc. Apr 01, 2018;25(4):370-379. [FREE Full text] [CrossRef] [Medline]
- Hammer A, Wagner A, Rieger MA, Manser T, WorkSafeMed Project Consortium#. Assessing the quality of medication documentation: development and feasibility of the MediDocQ instrument for retrospective chart review in the hospital setting. BMJ Open. Nov 18, 2019;9(11):e034609. [FREE Full text] [CrossRef] [Medline]
- Armistead LT, Cruz A, Levitt JM, McClurg MR, Blanchard CM. Medication therapy problem documentation and reporting: a review of the literature and recommendations. J Am Coll Clin Pharm. Jul 30, 2021;4(10):1337-1347. [CrossRef]
- Al-Diery T, Freeman H, Page AT, Cross AJ, Hawthorne D, Lee K. What types of information do pharmacists include in comprehensive medication management review reports? A qualitative content analysis. Int J Clin Pharm. Jun 17, 2023;45(3):712-721. [FREE Full text] [CrossRef] [Medline]
- Elliott RA, Tan Y, Chan V, Richardson B, Tanner F, Dorevitch MI. Pharmacist-physician collaboration to improve the accuracy of medication information in electronic medical discharge summaries: effectiveness and sustainability. Pharmacy (Basel). Dec 30, 2019;8(1):2. [FREE Full text] [CrossRef] [Medline]
- Craske ME, Hardeman W, Steel N, Twigg MJ. Components of pharmacist-led medication reviews and their relationship to outcomes: a systematic review and narrative synthesis. BMJ Qual Saf. Nov 20, 2024;33(12):808-822. [CrossRef] [Medline]
- Husband A, Robinson-Barella A. Integration and connection: the key to effectiveness of large-scale pharmacist-led medication reviews? BMJ Qual Saf. Nov 20, 2024;33(12):765-768. [CrossRef] [Medline]
- Saranto K, Kinnunen UM, Liljamo P, Mykkänen M, Kuusisto A, Kivekäs E. Interprofessional structured data: supporting the primary and secondary use of patient documentation. In: Hübner UH, Mustata Wilson G, Morawski TS, Ball MJ, editors. Nursing Informatics. Cham, Switzerland. Springer; 2022.
- Toivo T, Dimitrow M, Puustinen J, Savela E, Pelkonen K, Kiuru V, et al. Coordinating resources for prospective medication risk management of older home care clients in primary care: procedure development and RCT study design for demonstrating its effectiveness. BMC Geriatr. Mar 16, 2018;18(1):74. [FREE Full text] [CrossRef] [Medline]
- Toivo T. Prospective medication risk management in primary care: enhancing coordination of care and community pharmacists' participation. Dissertation. University of Helsinki; 2020. URL: https://helda.helsinki.fi/items/c4551dee-6d6e-4a72-9c8e-aacf23fa5515 [accessed 2024-11-02]
- Johnson SB, Bakken S, Dine D, Hyun S, Mendonca E, Morrison F, et al. An electronic health record based on structured narrative. J Am Med Inform Assoc. Jan 01, 2008;15(1):54-64. [CrossRef]
- Tayefi M, Ngo P, Chomutare T, Dalianis H, Salvi E, Budrionis A, et al. Challenges and opportunities beyond structured data in analysis of electronic health records. WIREs Comput Stat. Feb 14, 2021;13(6):13. [FREE Full text] [CrossRef]
- de Lusignan S, Wells SE, Hague NJ, Thiru K. Managers see the problems associated with coding clinical data as a technical issue whilst clinicians also see cultural barriers. Methods Inf Med. Feb 08, 2018;42(04):416-422. [CrossRef]
- Ebbers T, Kool RB, Smeele LE, Dirven R, den Besten CA, Karssemakers LH, et al. The impact of structured and standardized documentation on documentation quality; a multicenter, retrospective study. J Med Syst. May 27, 2022;46(7):46. [FREE Full text] [CrossRef] [Medline]
- Kazi S, Handley JL, Milicia AP, Ratwani RM, Adams KT, Jones R, et al. Free text as part of electronic health record orders: context or concern? Patient Safety. 2024;6(1). [CrossRef]
- Skentzos S, Shubina M, Plutzky J, Turchin A. Structured vs. unstructured: factors affecting adverse drug reaction documentation in an EMR repository. AMIA Annu Symp Proc. 2011;2011:1270-1279. [FREE Full text] [Medline]
- Ebbers T, Takes RP, Smeele LE, Kool RB, van den Broek GB, Dirven R. The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden. Int J Med Inform. Apr 2024;184:105344. [FREE Full text] [CrossRef] [Medline]
- Cahill M, Cleary BJ, Cullinan S. The influence of electronic health record design on usability and medication safety: systematic review. BMC Health Serv Res. Jan 06, 2025;25(1):31. [FREE Full text] [CrossRef] [Medline]
- Khosravi B, Rouzrokh P, Erickson BJ. Getting more out of large databases and EHRs with natural language processing and artificial intelligence: the future is here. J Bone Joint Surg Am. Oct 19, 2022;104(Suppl 3):51-55. [CrossRef] [Medline]
- Falcetta FS, de Almeida FK, Lemos JC, Goldim JR, da Costa CA. Automatic documentation of professional health interactions: a systematic review. Artif Intell Med. Mar 2023;137:102487. [CrossRef] [Medline]
Abbreviations
| AI: artificial intelligence |
| CREDES: Conducting and REporting DElphi Studies |
| DRP: drug-related problem |
| eGFR: estimated glomerular filtration rate |
| EHR: electronic health record |
| MR: medication review |
Edited by J Sarvestan; submitted 19.12.24; peer-reviewed by A Myrka, L Wreyford; comments to author 24.02.25; revised version received 17.03.25; accepted 03.04.25; published 06.05.25.
Copyright©Tanja Lindholm, Noora Lias, Kirsi Kvarnström, Anna-Riia Holmström, Terhi Toivo, Marjo Uusitalo, Harri Nurmi, Marja Airaksinen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.05.2025.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.