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Predefined Headings in a Multi-professional Electronic Health Record : Professionals’ Application, Aspects of Health and Health Care and Correspondence to Legal RequirementsTerner, Annika January 2014 (has links)
The overall aim of this thesis was to investigate predefined headings in a Swedish county council multi-professional EHR system in terms of their shared application, what aspects of health and health care they reflected, and their correspondence to legal requirements. An analysis of 3 596 predefined headings, applied to 20 398 104 occasions by eight professional groups, was conducted. Less than 2% of the predefined headings were applied by all eight professional groups, whereas 60% were not shared at all between the professional groups. A classification of the predefined headings revealed that 13% were “Specialist terms”, which were the least ambiguous predefined headings, 46% were “Terms for specific purposes”, which are less ambiguous than the “Common words” (28%), which were the most ambiguous predefined headings according to the sociolinguistic method employed. The remaining predefined headings (13%) were sorted into “Unclassified headings”. A qualitative content analysis of the predefined headings yielded 23 subcategories grouped into five categories: Description of the patient, Health care process, Resources employed, Administrative documentation, and Development and research. A comparison of the 23 subcategories to the Patient Data Act showed, first, that 15 of 23 subcategories corresponded to four legal requirements, second, that there were legal requirements with a focus on patient rights that were not being met, and third, that there were eight subcategories of predefined headings that could not be attributed to the legal provisions of the Patient Data Act. In conclusion, the proportion of shared predefined headings in the EHRs was limited. The predefined headings in the multi-professional EHRs did not constitute a joint language for specific purposes. A meaningful structure comprising categories and subcategories of different aspects of health and health care as reflected in the applied predefined headings was identified. The structure reflected a wide range of health and health care. No subcategory corresponded to the three legal requirements concerning patient rights. Future research should include professionals’ and patients’ understanding of predefined headings, the correspondence of documented notes to predefined headings and how the documentation in the EHR has had an impact on patient safety.
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Patient Data Management System (PDMS) : Anestesi- och intensivvårdspersonalens upplevelser av implementering och arbete med PDMS / Patient Data Management System (PDMS) : Anesthesia- and intensive care staff experiences of implementation and work with PDMSOrtscheid, Julius, Jensen, Thomas January 2017 (has links)
Titel: Patient Data Management System (PDMS) – Anestesi- och intensivvårdspersonalens upplevelser av implementering och arbete med PDMS. Bakgrund: Dagens och framtidens sjukvård innebär en ökande användning av digitala system i omvårdnaden. Patient Data Management System (PDMS) är ett kliniskt informationssystem och beslutsstöd som implementeras allt mer på svenska sjukhus. Tidigare forskning visar på skilda upplevelser av digitala systems påverkan på omvårdnaden, arbetsbelastning och tidsåtgång. Syfte: Syftet är att beskriva anestesi- och intensivvårdspersonalens upplevelser av implementering och arbete med PDMS. Metod: Studien genomfördes som en intervjustudie med kvalitativ ansats. Resultat: I resultatet framträder fyra teman, införandeprocessen, användarvänlighet, informationsöverföring samt patientsäkerhet. Dessa fyra teman skildrar vårdpersonalens upplevelser av införandet och arbetet med PDMS. Konklusion: PDMS implementeras på allt fler sjukhus i Sverige. Vårdpersonalen anser att det är mycket viktigt med information och utbildning inför implementeringen av PDMS. Helhetssynen på sjukhusets datasystem är viktigt då det framkommer att olika system inte alltid kommunicerar med varandra. Det leder till ökad arbetsbelastning och ökad risk för patientsäkerheten. Mer forskning om PDMS påverkan på omvårdnadsarbetet och patientsäkerheten behövs. / Title: Patient Data Management System (PDMS) – Anesthesia- and intensive care staff experiences of implementation and work with PDMS. Background: Todays and future healthcare means an increasing use of digital systems in nursing care. Patient Data Management System (PDMS) is a clinical information system and clinical decision support which is implemented in swedish hospitals. Previous research shows different experiences of digital systems impact on nursing care, workload and patient safety. Aim: The purpose was to describe anesthesia- and intensive care unit staff experiences of implementation and work with PDMS. Method: The study was conducted by interviews with a qualitative approach. Results: In the result four themes appear, process of introduction, serviceability, transfer of information and patient safety. The four themes depict the anesthesia- and intensive care unit staff experiences of the implementation and work with PDMS. Conclusion: PDMS is implemented in an increasing number of swedish hospitals. The anesthesia- and intensive care unit staff consider it very important with information and education before implementation of PDMS. The comprehensive view on the hospitals computer system is important due to the fact that these systems appear not to always be in synchronization with each other. That leads to an increased workload and also an increased risk regarding patient safety. More research on the PDMS impact on nursing and patient safety are needed.
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"PDMS skapar flera nyanser av patientsäkerhet" : En kvalitativ intervjustudie om intensivvårdssjuksköterskors erfarenheter av att arbeta med ett Patient Data Management System. / "PDMS creates many shades of patient safety" : A qualitative interview study on intensive care nurse's experience of working with a Patient Data Management System.Nilsson, Johanna, Roos, Helena January 2018 (has links)
Bakgrund: PDMS, Patient Data Management System, är ett kliniskt informationssystem som är speciellt utvecklat för intensivvård som genererar stora mängder patientdata. Systemet samlar automatiskt in patientdata från övervakning och medicinskteknisk apparatur och presenterar informationen på ett överskådligt sätt. Tidigare forskning belyser framförallt användbarheten, den minskade dokumentationstiden samt fördelar med läkemedelshanteringen men visar motsägelsefulla resultat vad gäller vad den frigjorda tiden används till. Syfte: att belysa intensivvårdssjuksköterskors erfarenhet av att använda PDMS i vårdarbetet. Metod: kvalitativ intervjustudie med intensivvårdssjuksköterskor som analyserats med hjälp av en kvalitativ innehållsanalys. Resultat: i resultatet framträder fem kategorier; patientnära vårdande, evidensbaserad vård, olika former av kvalitetsutveckling, säker vård och informatik. Dessa kategorier återger intensivvårdssjuksköterskornas erfarenheter av att arbeta med PDMS och resultatet visar tydligt att PDMS ökar patientsäkerheten på flera sätt. Konklusion: Ökad vårdkvalitet, minskad dokumentationstid, mer lättförståeligt kontinuerligt lärande för personalen, möjlighet till uppföljning och forskning samt säkrare läkemedelshantering anses vara de största vinsterna med PDMS. Sammantaget bidrar samtliga faktorer till en ökad patientsäkerhet. / Background: PDMS, Patient Data Management System, is a clinical information system specially developed for intensive care which generates a large amount of patient data. The system automatically collects patient data from monitoring and medical equipment and presents the information in a clear overall view. Previous research highlights especially usability of the system, reduced time spent on documentation and benefits with handling medications but shows contradictory results in terms of what the released time is used for. Aim: to highlight intensive care nurses experiences of using PDMS in nursing. Method: qualitative interview-study with intensive care nurses which was analyzed with qualitative content analysis. Results: five categories came forward in the result; close-to-patient care, evidece-based care, different forms of quality developement, safe care and informatics. These categories reflects the experiences of working with PDMS among intensive care nurses and the results clearly demonstrate that PDMS increases patient safety for several reasons. Conclusion: increased quality of care, reduced documentation time, more easy-to-understand continuous learning for the staff, opportunity to follow-up and posibility for reasearch and safer handling with medications are considered the biggest gains with PDMS. Overall, all factors contribute to increased patient safety.
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Systematically Missing Subject-Level Data in Longitudinal Research SynthesisKline, David January 2015 (has links)
No description available.
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Clinicians' demands on monitoring support in an Intensive Care Unit : A pilot study, at Capio S:t Görans Hospital / Sjukvårdspersonals krav på övervakningssuport på en intensivvårdsavdelning : Förstudie på Capio S:t Görans SjukhusCallerström, Emma January 2017 (has links)
Patients treated at intensive care units (ICUs) are failing in one or several organs and requireappropriate monitoring and treatment in order to maintain a meaningful life. Today clinicians inintensive care units (ICUs) manage a large amount of data generated from monitoring devices.The monitoring parameters can either be noted down manually on a monitoring sheet or, for some parameters, transferred automatically to storage. In both cases the information is stored withthe aim to support clinicians throughout the intensive care and be easily accessible. Patient datamanagement systems (PDMSs) facilitate ICUs to retrieve and integrate data. Before managinga new configuration of patient data system, it is required that the ICU makes careful analysis ofwhat data desired to be registered. This pilot study provides knowledge of how the monitoringis performed in an Intensive Care Unit in an emergency hospital in Stockholm.The aim of this thesis project was to collect data about what the clinicians require and whatequipment they use today for monitoring. Requirement elicitation is a technique to collectrequirements. Methods used to collect data were active observations and qualitative interviews.Patterns have been found about what the assistant nurses, nurses and physicians’ require of systems supporting the clinician’s with monitoring parameters. Assistant nurses would like tobe released from tasks of taking notes manually. They also question the need for atomized datacollection since they are present observing the patient bed-side. Nurses describe a demanding burden of care and no more activities increasing that burden of care is required. Physicians require support in order to see how an intervention leads to a certain result for individual patients.The results also show that there is information about decision support but no easy way to applythem, better than the ones used today. Clinicians state that there is a need to be able to evaluatethe clinical work with the help of monitoring parameters. The results provide knowledge about which areas the clinicians needs are not supported enough by the exciting tools.To conclude results show that depending on what profession and experience the clinicians have the demands on monitoring support di↵ers. Monitoring at the ICU is performed while observing individual patients, parameters from medical devices, results from medical tests and physical examinations. Information from all these sources is considered by the clinicians and is desired to be supported accordingly before clinicians commit to action resulting in certain treatment,diagnosis and/or care. / Patienter som vårdas på intensivvårdsavdelningar har svikt i ett eller flera organ. Övervakning sker av patienterna för att kunna bidra till den vård som behövs för att upprätthålla ett meningsfullt liv. Idag hanterar sjukvårdpersonal en stor mängd data som genereras från övervakningsutrustning och system förknippade med övervakningsutrustning. Övervakningsparameterar kan antecknas förhand på ett övervakningspapper eller direkt sparas i digitalt format. Parameterarna sparas med syfte att vara ett lättillgängligt underlag under hela intensivvårdsprocessen. Patient data management systems (PDMSs) förenklar hämtning och integrering av data på exempelvis intensivvårdsavdelningar. Innan en ny konfiguration av ett patientdatasystem erhålls, är det eftersträvnadsvärt att intensivvårdsavdelningen analyserar vilken datasom skall hanteras. Detta examensarbete bidrog till kunskap om hur övervakning utförs på en intensivvårdsavdelning, på ett akutsjukhus i Stockholm. Målet med detta examensarbete var att insamla data om vad klinikerna behöver och vilken utrustning och system som de använder idag för att utföra övervakning. Behovsframkallning är en teknik som kan användas för att insamla krav. I detta projekt insamlades data genom aktivaobservationer och kvalitativa intervjuer. Mönster har hittats bland undersköterskornas, sjuksköterskornas och läkarnas behov av teknisksupport från system och utrustning som stödjer sjukvårdspersonalen under övervakningen av en patient. Undersköterskor uttrycker ett behov av att bli avlastade från uppgifter så som att manuellt skrivaner vitala parametervärden. De ifrågasätter behovet av automatiserad datahämtning eftersom de ständigt är närvarande bredvid patienten. Sjuksköterskor beskriver en hög vårdtyngd och önskaratt inte bli tillägnade fler aktiviteter som ökar den vårdtyngden. Läkare beskriver ett behov av ökat stöd för hur en interversion leder till resultat för individuella patienter. Resultaten visar attdet finns information om möjliga kliniska beslutsstöd utan givet sätt att applicera dessa, bättre än de sätt som används idag. Sjukvårdspersonalen hävdar att det det finns ett behov av att utvärdera det kliniska arbetet med hjälp av övervakningsparametrar. Resultaten utgör kunskap om vilka områden som sjukvårdpersonalens behov inte har stöd av nuvarnade verktyg. Resultaten visar att beroende på vilken profession och erfarenhet som sjukvårdspersonalen har, är behoven olika. På intensivvårdsavdelningen sker övervakning då enskilda patienter visuellt observeras såväl som övervakningsparametrar från medicintekniska produkter, resultat från medicinska tester och fysiska examinationer. Det finns behov att integrera och presenterainformation från dessa källor givet kunskap om att sjukvårdpersonalen fattar beslut på dessa som resulterar i behandling, diagnostik och/eller vård.
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Short-Term Occupancy Prediction at the Ottawa Hospital Using Time-Series Data for Admissions and Longitudinal Patient Data for DischargeArbuckle, Lon Michel Luk 11 January 2012 (has links)
The Ottawa Hospital cancels hundreds of elective surgeries every year due to a lack of beds, and has an average weekday occupancy rate above 100%. Our approach to addressing these issues, by way of informing administrators of resource needs, was to model the flow of patients coming and going from the hospital.
We used administrative data from the Ottawa Hospital to build a time-series model of emergency department admissions, and studied models that would predict next-day discharge of patients currently taking up hospital beds. In the latter, we considered population-averaged models for groups of patients based on their primary medical condition, as well as subject-specific models. We included the random effects from subject-specific variation to improve on predictive accuracy over the population- averaged approach. The result was a model that provided more realistic probabilities of discharge, and stable predictive accuracy over patient length of stay.
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Short-Term Occupancy Prediction at the Ottawa Hospital Using Time-Series Data for Admissions and Longitudinal Patient Data for DischargeArbuckle, Lon Michel Luk 11 January 2012 (has links)
The Ottawa Hospital cancels hundreds of elective surgeries every year due to a lack of beds, and has an average weekday occupancy rate above 100%. Our approach to addressing these issues, by way of informing administrators of resource needs, was to model the flow of patients coming and going from the hospital.
We used administrative data from the Ottawa Hospital to build a time-series model of emergency department admissions, and studied models that would predict next-day discharge of patients currently taking up hospital beds. In the latter, we considered population-averaged models for groups of patients based on their primary medical condition, as well as subject-specific models. We included the random effects from subject-specific variation to improve on predictive accuracy over the population- averaged approach. The result was a model that provided more realistic probabilities of discharge, and stable predictive accuracy over patient length of stay.
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Short-Term Occupancy Prediction at the Ottawa Hospital Using Time-Series Data for Admissions and Longitudinal Patient Data for DischargeArbuckle, Lon Michel Luk 11 January 2012 (has links)
The Ottawa Hospital cancels hundreds of elective surgeries every year due to a lack of beds, and has an average weekday occupancy rate above 100%. Our approach to addressing these issues, by way of informing administrators of resource needs, was to model the flow of patients coming and going from the hospital.
We used administrative data from the Ottawa Hospital to build a time-series model of emergency department admissions, and studied models that would predict next-day discharge of patients currently taking up hospital beds. In the latter, we considered population-averaged models for groups of patients based on their primary medical condition, as well as subject-specific models. We included the random effects from subject-specific variation to improve on predictive accuracy over the population- averaged approach. The result was a model that provided more realistic probabilities of discharge, and stable predictive accuracy over patient length of stay.
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Short-Term Occupancy Prediction at the Ottawa Hospital Using Time-Series Data for Admissions and Longitudinal Patient Data for DischargeArbuckle, Lon Michel Luk January 2012 (has links)
The Ottawa Hospital cancels hundreds of elective surgeries every year due to a lack of beds, and has an average weekday occupancy rate above 100%. Our approach to addressing these issues, by way of informing administrators of resource needs, was to model the flow of patients coming and going from the hospital.
We used administrative data from the Ottawa Hospital to build a time-series model of emergency department admissions, and studied models that would predict next-day discharge of patients currently taking up hospital beds. In the latter, we considered population-averaged models for groups of patients based on their primary medical condition, as well as subject-specific models. We included the random effects from subject-specific variation to improve on predictive accuracy over the population- averaged approach. The result was a model that provided more realistic probabilities of discharge, and stable predictive accuracy over patient length of stay.
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MOBILE PHONE TEXT MESSAGING FOR ADHERENCE TO ANTIRETROVIRAL THERAPY: APPROACHES TO EVIDENCE GENERATION AND SCALE UPMbuagbaw, Lawrence January 2014 (has links)
Background and Objectives:
HIV in a major public health problem in many countries of the world. Recent advances in care for people living with HIV such as the use of antiretroviral medication have reduced the mortality and morbidity associated with HIV infection. However, many people receiving antiretroviral therapy do not take it as prescribed and still experience sub-optimal health outcomes. Mobile phone text messaging is emerging as an important tool in health care, and HIV in particular. Our objectives were to explore the determining factors for adherence to antiretroviral therapy, test text messaging as an adherence enhancement tool, develop a framework for community ownership of a text messaging program and describe strategies for transfer of evidence in HIV to other conditions.
Methods:
This research is primarily based in Yaoundé, Cameroon, and employs a variety of methodologies, including a systematic review, two cross- sectional surveys, a randomized controlled trial, an individual patient data meta-analysis, a mixed methods study and a systematic review of systematic reviews.
Results and Conclusions:
Two-way weekly text messaging is an effective strategy in improving adherence to antiretroviral therapy and enhancing provider-client communication. People living with HIV in Yaoundé, Cameroon like receiving text messages, and are willing to own and run a text messaging program. Text messaging interventions may be transferred to other conditions by integrating services or by copying what works in HIV. Further research on potential harms, cost effectiveness and text messaging for other chronic conditions is warranted. / Thesis / Doctor of Philosophy (PhD)
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