A mature health system takes into account the increasing complexity in health care settings that make humans more prone to mistakes. For example, a patient in hospital might receive a wrong medication because of a mix-up that occurs due to similar packaging.\r\n In this case, the prescription passes through different levels of care starting with the doctor in the ward, then to the pharmacy for dispensing and finally to the nurse who administers the wrong medication to the patient. Had there been safe guarding\r\n processes in place at the different levels, this error could have been quickly identified and corrected. In this situation, a lack of standard procedures for storage of medications that look alike, poor communication between the different providers,\r\n lack of verification before medication administration and lack of involvement of patients in their own care might all be underlying factors that led to the occurrence of errors. Traditionally, the individual provider who actively made the mistake\r\n (active error) would take the blame for such an incident occurring and might also be punished as a result. Unfortunately, this does not consider the factors in the system previously described that led to the occurrence of error (latent errors). It\r\n is when multiple latent errors align that an active error reaches the patient.
Venous thromboembolism (blood clots) is one of the most common and preventable causes of patient harm, contributing to one third of the complications attributed to hospitalization. Annually, there are an estimated 3.9 million cases\r\n in high-income countries and 6 million cases in low- and middle-income countries (19).
Hospital Management Use Case Diagram Example 16.pdf
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14. Clinical transfusion process and patient safety: Aide-mémoire for national health authorities and hospital management. Geneva: World Health Organization; 2010 ( _use/who_eht_10_05_en.pdf?ua=1, accessed\r\n 26 July 2019).
A mature health system takes into account the increasing complexity in health care settings that make humans more prone to mistakes. For example, a patient in hospital might receive a wrong medication because of a mix-up that occurs due to similar packaging.In this case, the prescription passes through different levels of care starting with the doctor in the ward, then to the pharmacy for dispensing and finally to the nurse who administers the wrong medication to the patient. Had there been safe guardingprocesses in place at the different levels, this error could have been quickly identified and corrected. In this situation, a lack of standard procedures for storage of medications that look alike, poor communication between the different providers,lack of verification before medication administration and lack of involvement of patients in their own care might all be underlying factors that led to the occurrence of errors. Traditionally, the individual provider who actively made the mistake(active error) would take the blame for such an incident occurring and might also be punished as a result. Unfortunately, this does not consider the factors in the system previously described that led to the occurrence of error (latent errors). Itis when multiple latent errors align that an active error reaches the patient.
Venous thromboembolism (blood clots) is one of the most common and preventable causes of patient harm, contributing to one third of the complications attributed to hospitalization. Annually, there are an estimated 3.9 million casesin high-income countries and 6 million cases in low- and middle-income countries (19).
14. Clinical transfusion process and patient safety: Aide-mémoire for national health authorities and hospital management. Geneva: World Health Organization; 2010 ( _use/who_eht_10_05_en.pdf?ua=1, accessed26 July 2019).
Use case diagrams referred as a Behavior model or diagram. It simply describes and displays the relation or interaction between the users or customers and providers of application service or the system. It describes different actions that a system performs in collaboration to achieve something with one or more users of the system. Use case diagram is used a lot nowadays to manage the system.
The Meaningful Use program (see Chapter 1) has propelled the development of both EHR-linked and EHR-integrated registries. For example, EHR-integrated registries have expanded to meet EHR certification requirements and to help health systems meet requirements for workflow efficiency and quality improvement to achieve value-based criteria (e.g., improving population health). EHR-linked registries have grown as the Meaningful Use program specifically requires the reporting of EHR data to external registries (e.g., public health registries, quality reporting registries).4 Meaningful Use Stage-1 provided an optional objective (which became a mandatory objective in Meaningful Use Stage-2) for eligible hospitals and professionals to submit EHR-extracted electronic data to immunization registries.5 Meaningful Use Stage-2 further expanded EHR reporting to cancer registries and other specialized registries (e.g., birth defects, chronic diseases, and traumatic injury registries).6
Public health agencies have long used registries for surveillance and tracking purposes. For example, local and state public health departments usually maintain immunization registries that receive information from clinicians and other entities such as schools and pharmacies. Other common public health registries include syndromic surveillance and specialized registries such as birth defects, chronic diseases, and traumatic injury registries. In recent years, coincident with the rising EHR adoption among providers, public health entities began to link various registries with EHRs. A significant driver of increased EHR integration has been the Meaningful Use program, which incentivized clinicians to share EHR immunization and syndromic surveillance data with public health agencies.7 Other drivers have included the maturation of data standards (both semantic and syntactic) for automating and improving the transmission of EHR data to public health registries (e.g., distributed population queries),58 and the increased interest of value-based care provider organizations in assessing the needs and improving the health of the communities they serve (e.g., community health needs assessment).59 Most EHR-linked public health registries have relied on semi-automated processes; only recently have more automated mechanisms been introduced and adopted (e.g., vaccination registries). EHR-linked public health registries follow a similar architecture to that of EHR-linked research registries (Figure 4-2); however, the methods used to collect data from EHRs may vary as not all public health registries require patient-level data (e.g., counts are sufficient for some purposes). Methods used include but are not limited to: (1) semi-automated forms/templates to collect public health specific information about patients that fit a certain criteria (e.g., S&I Framework SDC);60 (2) data exchange protocols for receiving case reports from certified EHRs (e.g., MU public health reporting objectives);7 (3) tools to mine EHR and HIE data for signs and symptoms relevant to public health emergencies and outbreaks (e.g., ESSENCE Syndromic Surveillance System);61 and, (4) distributed data network queries to collect aggregated data from multiple providers when the identity of patients is not relevant (e.g., PopMedNet).62 2ff7e9595c
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