Improving Primary Care Medication Processes by Using Shared Electronic Medication Plans in Switzerland: Lessons Learned From a Participatory Action Research Study

Designing and Implementation of a Digitalized Intersectoral Discharge Management System and Its Effect on Readmissions: Mixed Methods Approach

BACKGROUND

Digital transformation offers new opportunities to improve the exchange of information between different health care providers, including inpatient, outpatient and care facilities. As information is especially at risk of being lost when a patient is discharged from a hospital, digital transformation offers great opportunities to improve intersectoral discharge management. However, most strategies for improvement have focused on structures within the hospital.

OBJECTIVE

This study aims to evaluate the implementation of a digitalized discharge management system, the project "Optimizing instersectoral discharge management" (SEKMA, derived from the German Sektorübergreifende Optimierung des Entlassmanagements), and its impact on the readmission rate.

METHODS

A mixed methods design was used to evaluate the implementation of a digitalized discharge management system and its impact on the readmission rate. After the implementation, the congruence between the planned (logic model) and the actual intervention was evaluated using a fidelity analysis. Finally, bivariate and multivariate analyses were used to evaluate the effectiveness of the implementation on the readmission rate. For this purpose, a difference-in-difference approach was adopted based on routine data of hospital admissions between April 2019 and August 2019 and between April 2022 and August 2022. The department of vascular surgery served as the intervention group, in which the optimized discharge management was implemented in April 2022. The departments of internal medicine and cardiology formed the control group.

RESULTS

Overall, 26 interviews were conducted, and we explored 21 determinants, which can be categorized into 3 groups: "optimization potential," "barriers," and "enablers." On the basis of these results, 19 strategies were developed to address the determinants, including a lack of networking among health care providers, digital information transmission, and user-unfriendliness. On the basis of these strategies, which were prioritized by 11 hospital physicians, a logic model was formulated. Of the 19 strategies, 7 (37%; eg, electronic discharge letter, providing mobile devices to the hospital's social service, and generating individual medication plans in the format of the national medication plan) have been implemented in SEKMA. A survey on the fidelity of the application of the implemented strategies showed that 3 of these strategies were not yet widely applied. No significant effect of SEKMA on readmissions was observed in the routine data of 14,854 hospital admissions (P=.20).

CONCLUSIONS

This study demonstrates the potential of optimizing intersectoral collaboration for patient care. Although a significant effect of SEKMA on readmissions has not yet been observed, creating a digital ecosystem that connects different health care providers seems to be a promising approach to ensure secure and fast networking of the sectors. The described intersectoral optimization of discharge management provides a structured template for the implementation of a similar local digital care networking infrastructure in other care regions in Germany and other countries with a similarly fragmented health care system.

Exploring strategies for building a sustainable healthcare system in Africa: lessons from Japan and Switzerland

Strengthening healthcare infrastructure is an important strategy for building a sustainable healthcare system in Africa. This involves investing in facilities, equipment, and supplies, as well as training and retaining skilled healthcare workers. Additionally, improving healthcare infrastructure and investing in healthcare education and training can lead to significant improvements in health outcomes, such as reducing maternal and child mortality. This is critical for building a sustainable healthcare system. Through a literature review, we assessed the approaches to building a sustainable healthcare system in Africa from the perspectives of Japan's and Switzerland's healthcare systems. It was discovered that Japan currently has the highest life expectancy, which can be attributed to insurance policies, healthcare policies, and the integration of emerging technologies and clinical research into their healthcare system. Lessons that Africa must emulate from the Japanese healthcare system include ensuring universal healthcare coverage, improving the workforce, improving primary healthcare, prioritizing the aging population, and investing in technology, infrastructure, and research. Japans healthcare system is also sustainable thanks to its stable workforce and primary healthcare. Switzerland also has an exceptional healthcare system globally, with technical and socioeconomic advancements leading to increased life expectancy and population aging through a worldwide health policy approach, programs tackling professional responsibilities and interprofessional cooperation, and initiatives to support family medicine. By learning from Japan's and Switzerland's approaches, Africa will gradually achieve the Sustainable Development Goals and build a sustainable healthcare system.

A systems approach to the safety and efficiency of prescribing at the primary-secondary care interface

The interface between primary and secondary care represents a highly complex and heterogeneous system that continues to pose risks to the safety and quality of care. Many issues relate to prescribing activities, and suboptimal information sharing between stakeholders can lead to avoidable harm events and system inefficiencies that increase workload. The framework of a systems approach is used to structure four key interface issues: medicines reconciliation, prescribing at secondary care outpatient appointments, shared records, and quality of communication. We outline opportunities for improved safety and efficiency, and identify key barriers that need to be addressed. Significant further development is required for the measures discussed. We recommend the use of a systems approach to methodologically support this process, particularly due to the inherent system-wide understanding of problems that it generates. We argue such understanding is essential to ensure that risks and workload are not shifted around a system, without overall gain.

Patients' Use of a Standardized Medication List - A Mixed Methods Study

Purpose

A medication list (ML) is a document listing the patient's entire medication, instructions for use, and indications. In Germany, a national standard was established in 2016 by law. However, data on patients' use of this standardized ML are scarce. We investigated (i) patients' practical use of the ML, (ii) patients' understanding of the ML, (iii) completeness and correctness of the current ML version, and (iv) reasons why patients did not adhere to their ML.

Patients and Methods

Community pharmacists recruited patients possessing a standardized ML with ≥5 medications. Information sources to evaluate the ML were: (a) brown bag analysis, (b) practical demonstration, (c) patient interview, and (d) patient file. Data were analyzed using qualitative and quantitative methods.

Results

Two hundred and eighty-eight patients (median age: 76 years, range: 27-95) were enrolled. (i) 38.5% of the patients used their ML regularly to prepare their medication and 73.3% to inform their physician. (ii) Overall, patients' understanding of the ML was good, with >80% of the patients being able to identify all relevant information. (iii) While n = 2779 medications were actually taken, n = 2539 were documented on the ML. No ML was fully correct and complete. Regarding particularly relevant items, ie, active ingredient, strength, dosage, medication missing or listed but not taken, 79.2% of ML were incorrect or incomplete. Handwritten modifications on the ML were frequent. (iv) Almost 60% of all patients did not follow their ML with "fear of adverse drug reactions" being the most frequently (n = 50) mentioned reason.

Conclusion

Completeness and correctness of the current ML version was poor with handwritten modifications being frequent. Additionally, most of the patients did not adhere to their ML. This indicates that measures that lead to correct and up-to-date ML and improvements in patient counseling about their medication should be developed and implemented into routine practice.

Discrepancies in patients' medication lists from pharmacies in Sweden: an interview study before the implementation of the Swedish National Medication List

BACKGROUND

Discrepancies in medication lists are common and can contribute to drug-related problems. This study was performed before the implementation of the National Medication List in Sweden, an intervention expected to improve the accuracy of medication lists.

AIM

The aim of the study was to examine the number and type of discrepancies in the medication list from pharmacies in Sweden. The secondary aim was to describe the information sources Swedish patients used as their medication lists and how confident they were with the information.

METHOD

Structured interviews were conducted with patients at 13 community pharmacies in Sweden during the period October 5, 2020, to April 16, 2021. The printed medication list was reviewed together with the patient to identify any discrepancies and missing information.

RESULTS

A total of 327 patients were included in the study (response rate 51%). The printed medication list from pharmacies was the most common information source for patients to know which medications to use. Two thirds (n  =  215) of the patients had at least one discrepancy among their prescriptions and 32% (n  =  106) were missing at least one prescription medication. Among all prescriptions (n  =  2567) 10% (n  =  264) were non-current prescriptions, 9% (n  =  238) were duplicates and 3% (n  =  88) had the wrong dose. The proportion of prescriptions with discrepancies differed between drug-groups.

CONCLUSION

The discrepancies described in this study can have serious consequences, and results provide a baseline for studies after the implementation of the National Medication List.

Healthcare professionals' perceptions of a web-based application for using the new National Medication List in Sweden

Objective

During the first stage of implementing the National Medication List in Sweden, a web-based application called Förskrivningskollen (FK) was launched. FK includes information about a patient's prescribed and dispensed medications, and it works as a backup system until the healthcare electronic health record (EHR) systems are fully integrated. The aim of this study was to examine the healthcare professionals' experiences and perceptions of FK.

Methods

The study applied a mixed methods approach, with statistics about the use of FK and a survey with open and closed questions. The respondents (n  =  288) were healthcare professionals who were users or potential users of FK.

Results

Overall there was little knowledge about FK and uncertainty regarding working routines and the regulations connected to the application. Lack of interoperability with the EHRs made FK time-consuming to use. Respondents said that the information in FK was not updated, and they were concerned that using FK could lead to a false sense of security about the accuracy of the list. Most clinical pharmacists thought FK added benefit to their clinical work, while as a group, physicians were more ambivalent about FK's benefit.

Conclusions

The concerns of healthcare professionals give important insights for future implementation of shared medication lists. Working routines and regulations linked to FK need to be clarified. In Sweden, the potential value of a national shared medication list will probably not be realized until it is fully integrated into the EHR in a way that supports healthcare professionals' desired ways of working.

Digital Exclusion During the COVID-19 Pandemic

During the COVID-19 pandemic, the reliance on digital services increased in most developed countries leaving many communities who are digitally excluded cut-off from vital services such as health and social care. Globally, digital exclusion is proposed to be one of the largest issues on discrimination within countries where smart cities and digital-by-default policies have been promoted, preventing certain groups of society from having access to public services. Addressing why people are being digitally excluded is important in improving the access people have to healthcare and other services that improve a person’s quality of life. Through a focused review of literature and publicly available secondary information, this paper examines the impact of Covid-19 on digital exclusion in Europe, Scandinavia, North America and Asia Pacific region and the methods that have been successful in limiting digital exclusion. Results show that while some countries handled the COVID 19 pandemic well, other countries’ attempts widened the gap with more people becoming digitally excluded.

Electronic transmission of prescriptions in primary care: transformation, timing and teamwork

INTRODUCTION During the coronavirus disease 2019 (COVID-19) pandemic lockdown in New Zealand in March 2020, there was a rapid shift to virtual consultations in primary care. This change was supported by system adjustments to enable electronic transmission of prescriptions without a handwritten signature if they met certain security criteria. International research suggests potential for unintended consequences with such changes, so it is important to understand the effect on professional practice in New Zealand general practice and community pharmacy. AIM The purpose of this study was to undertake a preliminary exploration of the experiences of New Zealand general practitioners and community pharmacists when prescriptions are transmitted electronically directly from prescriber to pharmacy. METHODS Semi-structured interviews with a purposive sample of four pharmacists and four general practitioners gathered qualitative data about their experiences of the shift to electronic transmission of prescriptions. Participants' perceptions of effect on professional workflow, interprofessional interactions between general practitioners and pharmacists, and interactions with patients were explored. Interviews were audio-recorded, and the data analysed thematically using an inductive approach. RESULTS Four themes were identified: workflow transformation; mixed impact on interactions with patients; juggling timing and expectations; and new avenues for interprofessional communication (with some cul-de-sacs). DISCUSSION Both general practitioners and pharmacists experienced transformational changes to workflow. This was positive for general practitioners due to saved time and increased work flexibility. Pharmacists noted potential benefits but also some challenges. To fully reap teamwork benefits, more work is needed on managing the timing issues and patient expectations, and to refine the new modes of communication between health-care practitioners.

Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers

BACKGROUND

With the rapid adoption of electronic medical records (EMRs), there is an ever-increasing opportunity to collect data and extract knowledge from EMRs to support patient-centered stroke management.

OBJECTIVE

This study aims to compare the effectiveness of state-of-the-art automatic text classification methods in classifying data to support the prediction of clinical patient outcomes and the extraction of patient characteristics from EMRs.

METHODS

Our study addressed the computational problems of information extraction and automatic text classification. We identified essential tasks to be considered in an ischemic stroke value-based program. The 30 selected tasks were classified (manually labeled by specialists) according to the following value agenda: tier 1 (achieved health care status), tier 2 (recovery process), care related (clinical management and risk scores), and baseline characteristics. The analyzed data set was retrospectively extracted from the EMRs of patients with stroke from a private Brazilian hospital between 2018 and 2019. A total of 44,206 sentences from free-text medical records in Portuguese were used to train and develop 10 supervised computational machine learning methods, including state-of-the-art neural and nonneural methods, along with ontological rules. As an experimental protocol, we used a 5-fold cross-validation procedure repeated 6 times, along with subject-wise sampling. A heatmap was used to display comparative result analyses according to the best algorithmic effectiveness (F1 score), supported by statistical significance tests. A feature importance analysis was conducted to provide insights into the results.

RESULTS

The top-performing models were support vector machines trained with lexical and semantic textual features, showing the importance of dealing with noise in EMR textual representations. The support vector machine models produced statistically superior results in 71% (17/24) of tasks, with an F1 score >80% regarding care-related tasks (patient treatment location, fall risk, thrombolytic therapy, and pressure ulcer risk), the process of recovery (ability to feed orally or ambulate and communicate), health care status achieved (mortality), and baseline characteristics (diabetes, obesity, dyslipidemia, and smoking status). Neural methods were largely outperformed by more traditional nonneural methods, given the characteristics of the data set. Ontological rules were also effective in tasks such as baseline characteristics (alcoholism, atrial fibrillation, and coronary artery disease) and the Rankin scale. The complementarity in effectiveness among models suggests that a combination of models could enhance the results and cover more tasks in the future.

CONCLUSIONS

Advances in information technology capacity are essential for scalability and agility in measuring health status outcomes. This study allowed us to measure effectiveness and identify opportunities for automating the classification of outcomes of specific tasks related to clinical conditions of stroke victims, and thus ultimately assess the possibility of proactively using these machine learning techniques in real-world situations.