Implementering av IT-losningar i aldreomsorgen : Hur nystartade e-halsoforetag kan skapa en lonsam position med innovativa IT-losningar
Notice bibliographique
Résumé
The elderly care in Sweden needs to change because predictions states that proportion of elderly is expected to rise with 30 % between 2010 and 2050. This means that a quarter of the entire population in Sweden will be at the age of 65 years or older by 2050. With this background it is clear that the efficiency in the elderly care is an important issue. The Swedish government has therefore presented a report which states the goal of Sweden being the number one in e- health by the year of 2025. This will be achieved by letting entrepreneurs create tools to make the healthcare more efficient. Because of that, this project will investigate how a start- up company can create a lucrative position with e- health products for the elderly care market. This was done by conducting a qualitative research study based on 31 interviews and three focus groups with stakeholders in the elderly care. The stakeholders were elderly people, staff and head of divisions at retirement homes and Uppsala city officials. The study was conducted at the e-health start-up company Cenvigo which is located in the city of Uppsala. From the result it is shown that it exist a difference between how different healthcare providers implement IT. As of today there exist a lot of different IT- systems in the elderly care which are difficult to work with because they are poorly build and not compliant with other systems. The effect is that the systems are difficult to work with and that the staff needs to document the same data twice. Even though the reality looks like that our findings show that people working in the elderly care has a positive attitude towards IT solutions. But still, as an e-health company, it will be an good idea to make the product easy to use and compliant with other systems because it affects how it can perform on the market. The products also need to add value to the elderly care by for example make the working process more efficient. The findings show that staff put a lot of time in surveillance which probably can be digitalized. In order to gain a lucrative position a company also needs to identify customer groups. Potential customers are the elderly, the retirement homes or the government. The elderly has shown no interest in paying for e-health solutions themselves and they are also skeptical to use the product though they do not object to have them in the organizations. The government purchase routines are highly regulated by laws in contrast with privately driven retirement homes which do not have as strict routines. An e-health company therefore needs to be able to adapt to the demands of the market.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,004 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».