Development of Diabetes Register

Development of Diabetes Register The national DEMS aims to support diabetic health professionals in providing real-time information when and where it is required. Electronic medical records (EMRs) are an important means of enhancing patient wellbeing through inaccuracy reduction and to enhance clinical care quality (Lester, Zai et al. 2008). EMRs have previously been effective in refining diabetes management and enhancing organizing of care among multi disciplinary teams (Lester, Zai et al. 2008). Accomplishing interoperability between EHRs and registries will be progressively more vital as the utilisation of registries and EHRs develops considerably (Gliklich and Dreyner 2010). The typical viewpoint regarding establishing a diabetes register is by assembling electronic patient files held by GPs medical centre’s of diabetic patients (Morris, Boyle et al. 1997). Another alternative is to gather patient records electronically from multi sources to a central source in order to achieve a more comprehensive register (Morris, Boyle et al. 1997). When setting up a diabetes register it should be carried out according to NICE guidelines which include: â€Å"Patients demographics adjustable risk factors medicine prescribed Attendance at practice or diabetes outpatient clinic† (OKelly, Foy et al. 2008). The set of accessible data sources is the most important factor in determining the capabilities of disease surveillance system. The purposed Irish diabetes register will utilise information from PCRS and NCSS data sources. PCRS contains information regarding prescribed drugs and medicines typically taken by diabetics such as statins (cholesterol lowering medications) this information is gotten from the General Medical Services Scheme. T2D patients can be identified by their need to use oral diabetes prescriptions such as oral anti-hyperglcaemic which can be taken on their own or with insulin (OShea, Teeling et al. 2013). The scheme affords entitled persons access to free health care as well as prescription medication (OShea, Teeling et al. 2013). The PCRS gathers the information on â€Å"dispensed prescribed medication† a monthly basis from the scheme, these medications† are coded using the WHO Anatomical Therapeutic Chemical (ATC) classification system† (OShea, Te eling et al. 2013). As well as checking these data sources, hospital diabetic clinics might contain patients not already on the national register. â€Å"Patients with medication treating T2D can be identified using the prescription of oral anti-hyperglycaemic agents alone or in combination with insulin as a proxy for disease diagnosis†. Diabetes register aids the identification and tracking of clinical outcome (Lester, Zai et al. 2008). The registry can be kept up-to-date in an automatic manner when run against laboratory results and GP practice EMR (Lester, Zai et al. 2008). The registry needs to up-to-date and not to contain stagnat data. Initially is it perceived that there will be two data sources: NCCS and PCRS. Hospital diabetes clinics – extracted to register Regarding the laboratory system, patient whose records contained information regarding glycated haemogloblin, plasma glucose, urinary microalbumin and serum creatinine were considered to be diabetes as well as oral glucose tolerance test confirming the diagnosis of diabetes or outpatient plasma glucose concentration of greater than 11.1 mmol/l (Morris, Boyle et al. 1997). All laboratory results applicable to diabetes care are available electronically; patients could be identified and included in the register. Registries typically gather information from various data sources, this is typically done by collecting information from various sources and linking the information across data sources, either with identifiers intended for linking or by recorded attributes of the patients to whom the information match up to (Gliklich and NA 2010). Most general method for record linkage typically depends on the presence of unique identifiers (Gliklich and Dreyner 2010). Once verified that the information is correct, it will be necessary to verify that the data can be uploaded correctly onto the Diabetes register. Look at hipe extract as an example Gathering of data from an assortment of data sources capitalizes on the available data on each diabetic patient and ensures comprehensiveness. The National Cancer Screening programme/ schemes provide data on . Data includes demographics, history of, treatment. This data is stored electronically on NCCS database whish a password protected designed database. The hospital system has a record of patients registered Duplicate patients records are avoided by the use of an report based on similar surnames, forenames and hospital numbers. Data of birth comparison. As data is collected from a number of sources it necessary to remove duplicate records. â€Å"Currently there is no unique number assigned to individuals accessing health and social care in Ireland which would enable the accurate identification of individuals†. â€Å"Therefore cases are cross-matched from the different data sources. A range of variables, including names, gender, county of residence, data of birth are used to match the data†. [dissertation Benefits realization information technology in a national surveillance system, Patient demographics download All systems to remain in sync. A patient enters a hospital is registered on the PIMS and that information is then sent to laboratory system. Healthlink server , the vendor provides the code handles how the file gets sent from nimis software suite The laboratory system requires an interface to PAS system to enable demographics and clinical information for common patients to be shared between the two systems. HL7 interface facilitates the transfer of demographic information between the PAS and laboratory systems. Information from PAS is extracted and formatted using iSoft Integration Engine. The laboratory system will communicate with the Integration Engine using HL7 messaging over TCP/IP sockets Patient information is entered or modified in PAS. The resultant transaction is recorded in PAS audit service. The audit service is continually monitored by iSoft Integration Engine which is configured to look for relevant transactions. For each transaction, the associated information is extracted from PAS and formed into the appropriate HL7 message for immediate onward transmission to laboratory system. The laboratory interface continually listens for HL7 messages from PAS. When a message is received it is analysed to check its purpose and check that the information is correct. If the patient number referenced in the message is unknown to laboratory system then the patient will be registered otherwise the patient details will be updated based on the contents of the message. Systolic blood pressure Diastolic blood pressure HbA1c Creatinine Microalbumin Patients attending Hospital diabetes clinics, Graphically representation on the main screen. Health care professionals perceive that there is not enough time in the day to carry out their workload. There needs to be effort made to ensure quick data review and efficient action (Lester, Zai et al. 2008). A graph will be generated to display on screen to demonstrate changes in weight and blood pressure to emphasize the importance of the data. The report function enables automatic printout of letters to GPs, episode details and annual review for filing in the patients case notes, referral letters to other specialities. Auditing All transactions within the system will be audited. This means that transactions will be recorded with a snapshot of the data and the user performing the action. The system needs an audit function to facilitate audit. Validation Data entry validation are used to minimize the risk of errors; duplication entries. Performance The system will be utilised on the National Health Network which will facilitate reliable and robust network on which the system to work on.