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| Name | Class |
|---|---|
| Wiener Rotes Kreuz- Rettungs-, Krankentransport-, Pflege- und Betreuungsgesellschaft m.b.H. | UNKNOWN |
| Volkshilfe Wien gemeinnützige Betriebs-GmbH | UNKNOWN |
| Volkshilfe Gesundheits- und Soziale Dienste GmbH |
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Linked Care aims to help healthcare professionals (nurses, doctors, pharmacists) interact efficiently and safely with IT support to improve patient information flows. It focuses on the medication ordering process, which currently involves time-consuming steps like calling doctors and traveling to get prescriptions. The project targets nursing staff, doctors, pharmacists, and patients, with indirect benefits for hospitals, social welfare organizations, and insurance bodies. This study evaluates the Linked Care solution by addressing the research question: Does an electronic ordering system improve the efficiency and quality of the regular medication process?
Background and rationale:
Linked Care aims to provide access to information relevant to care and support beyond the boundaries of the various care settings and primarily supports caregivers in the acquisition and transfer of information. The development of essential standards (e.g., a myCare Info) and the involvement of all affected target groups make it possible to develop practical IT tools for standardized networking in mobile care and nursing. The result will be an integrated, affordable, easy-to-use and well-connected IT system for care and support. The portal can be operated via mobile devices, PC, or tablets.
The McKinsey study demonstrates the significant potential of digitalization in the Austrian healthcare sector. According to this study, there is a 4.7-billion-euro opportunity for Austria. Approximately 70% of the potential benefits of increased productivity accrue to service providers, such as physicians and hospitals. The remaining 30% can be attributed to other players in the system, particularly health insurers, who benefit from reduced service utilization and improved care. Key factors in achieving these benefits include the implementation of the Austrian electronic health record (ELGA) and e-prescribing, which enable efficiency gains of EUR 690 million. Digitization is also sought after by regulators, patients, payers, and service providers in the Austrian healthcare system for improved efficiency and quicker access to data.
Helmcke et al. (2021) identify the following areas with the greatest potential for savings and benefits in the Austrian healthcare system:
Objectives:
This project aims to enable documenting healthcare professionals (such as nurses, general practitioners (GPs), and pharmacists) to interact efficiently, safely, and conveniently, with optimal IT support, to improve (or make more efficient) the patient-related information flows. The specific use cases studied are the process of ordering and in particular reordering medication. A significant time-saving potential has been identified in the transfer of medication information. The ordering process usually begins with nurses calling a GP as soon as they notice that a client has run out of medication and needs to be re-supplied when preparing the prescribed medication. The nurse then usually travels distances (e.g. by car) to obtain a prescription from the GP and collect the medication from the pharmacy. To do this, they need the client's insurance card, which has to be collected separately. The project is therefore aimed at four target groups: i) nursing staff who carry out the documentation, ii) GPs, and iii) pharmacists and finally iv) patients who make use of the care. In addition to the target groups studied in this trial, indirect beneficiaries include healthcare providers such as hospitals, social welfare organizations, rehabilitation clinics, public insurance bodies, etc. who ensure effective and efficient care. The trial aims to evaluate the entire process of data recording and data exchange via the newly created interfaces between the systems involved in practical use.
The primary research question of this study is: Does an electronic ordering system improve the efficiency and quality of the regular medication process?
Secondary research questions are:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention (using Linked Care system) | Experimental | All nurses and caregivers participating in the intervention group use the newly installed mynevaToGo app to reorder medication. Nurses and nursing assistant level 2 also use the myneva Care Center software to keep the medication list prescribed by the GP. The solution is installed in advance on the duty cell phones by the IT department of the relevant care organization. Participating nurses and caregivers in the intervention group are instructed to handle the medication ordering process electronically (i.e., medication orders will be sent to the GPs via the Linked Care platform). |
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| Control | Active Comparator | Care professionals in the convenience sampled control group continue to handle the usual medication process. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| medication management | Device | The test system consists of:
Functionally, the solution should, coordinate the medication requirements between pharmacies, GPs, and caregivers (subarea medication). |
| Measure | Description | Time Frame |
|---|---|---|
| Time spent on medication related processes | Measure of time efficiency recorded on a project-specific 14-day medication log. / Minimum value: 0 [minutes], maximum value: N/A. Higher scores mean a worse outcome. / Analysis metric: difference test vs. control, test group trend analysis. / Method of aggregation: mean. | Baseline, 3-month follow-up, 6-month follow-up |
| Measure | Description | Time Frame |
|---|---|---|
| Overall score from the "Survey on psychological stress in mobile care (BGW miab) | Self-reported indications on 6 subitems on a 5-point Likert pseudometric scale. / Minimum value: 1, maximum value: 5. Higher scores mean a worse outcome. / Analysis metric: Difference test vs. control & test group trend analysis. / Method of aggregation: mean score. | Baseline, 3-month follow-up, 6-month follow-up |
| Measure | Description | Time Frame |
|---|---|---|
| Sample Characteristic Affiliation | Affiliation to a care-providing organization (selection from 4 participating organizations GSD, VHW, WRK, JOHA). Scale: nominal. | Baseline |
| Sample Characteristic Profession |
Inclusion Criteria Caregivers:
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| Name | Affiliation | Role |
|---|---|---|
| Elisabeth Haslinger-Baumann, FH-Prof. Dr. | FH Campus Wien University of Apllied Sciences | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Volkshilfe Gesundheits- und Soziale Dienste GmbH | Linz | 4200 | Austria | |||
| Wiener Rotes Kreuz- Rettungs-, Krankentransport-, Pflege- und Betreuungsgesellschaft m.b.H. |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Background | Helmcke Stefan, Biesdorf Stefan, Bauer Florian, Berger Wernhard (2021). mckinseystudiedigitalisierung im gesundheitswesen die 47mrdeurochance fur Österreich. | ||
| Background | BGW miab für die Pflege und den stationären Wohnbereich der Behindertenhilfe Erstveröffentlichung 2002, Stand 01/2013 Hrsg. Berufsgenossenschaft für Gesundheitsdienst und Wohlfahrtspflege (BGW). Hamburg, Online: www.bgw-online.de |
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Because the trial deals with sensitive health-related data, neither person-identifiable nor coded raw data will be made publicly available or shared upon request from other researchers.
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| Johanniter Österreich Ausbildung und Forschung gem. GmbH | UNKNOWN |
Non-randomized controlled trial, with participants unequally allocated to test and control groups (factor 5) in clusters
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| Usual Care Group | Other | Usual care. |
|
| Overall score from a "Project-specific questionnaire on care-process quality". | Self-reported indications on 21 subitems on a 5-point Likert pseudometric scale. / Minimum value: 1, maximum value: 5. Higher scores mean a worse outcome. / Analysis metric: Difference test vs. control & test group trend analysis. / Method of aggregation: weighted mean score. | Baseline, 3-month follow-up, 6-month follow-up |
| Overall score from the "Usefulness, Satisfaction, and Ease of Use (PSSUQ) Questionnaire" | Self-reported indications on 16 subitems on a 7-point Likert pseudometric scale. / Minimum value: 1, maximum value: 7. Higher scores mean a worse outcome. / Analysis metric: Difference test vs. control & test group trend analysis. / Method of aggregation: mean score. | 3-month follow-up, 6-month follow-up |
| Overall score from the "Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Questionnaire" | Self-reported indications on a 7-point Likert pseudometric scale with subitems in 4 domains: i) performance expectancy, ii) effort expectancy, iii) social influence, and iv) facilitating conditions. / Minimum value: 1, maximum value: 7. Higher scores mean a worse outcome. / Analysis metric: Difference test vs. control & test group trend analysis. / Method of aggregation: mean score. | 3-month follow-up, 6-month follow-up |
Profession (selection from 5 options: certified nurse, specialist nursing assistant, nursing assistant level 1 or level 2 , home care assistant. Scale: nominal.
| Baseline |
| Sample Characteristic Age | Age (years). Scale: metric. | Baseline |
| Sample Characteristic Gender | Gender (selection from 3 options: male, female, divers). Scale: nominal. | Baseline |
| Sample Characteristic Employment Extent | Employment extent (weekly contractual hours). Scale: metric. | Baseline |
| Vienna |
| 1030 |
| Austria |
| Johanniter Österreich Ausbildung und Forschung gem. GmbH | Vienna | 1210 | Austria |
| Volkshilfe Wien gemeinnützige Betriebs-GmbH | Vienna | Austria |