Your Role as a Program Manager in Pit Production Mission Integration (PPMI-DO)

Background: Stroke care evolution has been remarkable since 2000, when the Brain Attack Coalition published their recommendations for Primary Stroke Centers. For the first time, hospitals had evidence-based standards to improve patient outcomes. Today, many states require emergency responders to take suspected stroke patients only to certified stroke centers. As a result, many hospitals have established the role of stroke coordinator to oversee the myriad facets of stroke care. Coordinators are overwhelmed with the opportunities - and responsibilities - to improve care processes. Method: In 2009, the stroke program manager at a Magnet academic medical center established a regional stroke coordinators’ group. Eight coordinators met and established milestones for success. Information has been shared and nurses have traded services, providing education for each other’s organization. The group of now 28 coordinators meets every other month. Results: Positive outcomes of membership in this dynamic group include a 65% increase in professional membership in American Association of Neuroscience Nurses. In addition, the coordinators report confidence and empowerment to impact change in their own organization that improved care and outcomes. Aggregate group data demonstrates improvement in the following measures: thrombolytic administration 44%; door-to-needle time 16%; & patient education 12%. Nine additional hospitals (from 6 to 17, a 183% increase) have attained Advanced Primary Stroke certification and the host organization achieved Comprehensive Stroke certification. Conclusion: Neuroscience nurses are influential leaders - not just within their own organization. These outcomes demonstrate the mutual benefit of stroke coordinator colleagues working together and sharing best practice strategies. Through multi-organizational collaboration, they have become empowered to establish programs and become experts within their organization, able to guide and improve the care provided by their own direct-care nurses.

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Interview with:Antonio FernandezSenior Program Manager Supersaver.com

Journal of Information Privacy and Security ◽

10.1080/15536548.2010.10855894 ◽

2010 ◽

Vol 6 (3) ◽

pp. 72-73

Author(s):

Choton Basu

Keyword(s):

Program Manager

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Analisis Pola Masa Studi Mahasiswa Fakultas Teknik Universitas Darma Persada Menggunakan Metode Clustering

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2020741001 ◽

2020 ◽

Vol 7 (4) ◽

pp. 861

Author(s):

Ayu Hardianti ◽

Dewi Agushinta. R

Keyword(s):

Grade Point Average ◽

Clustering Analysis ◽

Study Program ◽

Grade Point ◽

Program Manager ◽

Knowledge Analysis ◽

Initial Stage ◽

Study Programs ◽

Result Interpretation ◽

Cluster 2

Penelitian ini bertujuan menganalisis pola lama studi mahasiswa fakultas teknik universitas Darma Persada daridata akademik. Metode yang digunakan adalah clustering algoritma K-Means. Variabel yang dianalisis adalah jurusan, daerah asal, umur, jenis kelamin, Indeks Prestasi Komulatif (IPK), Satuan Kredit Semester (SKS), tahun masuk, lama studi. Analisis dilakukan menggunakan perangkat lunak WEKA. Penelitian dilakukan melalui pengumpulan data dari arsip atau database biro Administrasi Akademik yaitu berupa data akademik mahasiswa fakultas teknik Universitas Darma Persada angkatan 2009 sampai 2014. Tahapan selanjutnya adalah preprocessing data yang dilakukan melalui analisis metode clustering menggunakan algoritma K-Means dengan terlebih dahulu menentukan jumlah cluster menggunakan metode Elbow dan interpretasi hasil. Berdasarkan hasil metode Elbow, jumlah cluster sebanyak 4 cluster. Berdasarkan hasil proses K-Means clustering, pembagian data pada masing-masing cluster adalah cluster 1 berjumlah 556 data (26%), cluster 2 berjumlah 414 data (19%), cluster 3 berjumlah 189 data (9%) dan cluster 4 berjumlah 1010 data (46%). Selanjutnya, yang memiliki lama studi lebih dari 4 tahun (lebih dari 8 semester) berada pada cluster 2, cluster 3, cluster 4 sedangkan mahasiswa yang memiliki masa studi 4 tahun (8 semester) berada pada cluster 1. AbstractThe duration of student study is one of the factors that influence the completing students' timeliness. Based on the policy of the National Accreditation Board of Higher Education (BAN-PT) in Regulation No. 4 of 2017 concerning the Policy for Preparing Accreditation Instruments, the duration of study is one of the benchmarks and evaluation elements in accreditation of study programs. From the Faculty of Engineering academic data, Darma Persada University, many students take more than four years of study. The duration of study is one of the problems of the study program manager in terms of academic performance. This study aims to analyze the old patterns of study by students of the Faculty of Engineering, Darma Persada University from academic data. K-Means algorithm clustering technique is used with the variables are majors, the area of origin, age, gender, Grade Point Average (GPA), Semester Credit Unit (SKS), year of entry and study duration. The Waikato Environment for Knowledge Analysis (WEKA) software is used as an analytic tool. The initial stage of research is through collecting data from archives or Academic sections, namely academic data from students of the Faculty of Engineering, Darma Persada University, 2009 to 2014. The next stage is preprocessing data through K-Means algorithm clustering analysis by first calculating many clusters using the Elbow method and result interpretation. From the Elbow method result, the number of clusters used is 4 (four) clusters. Based on the results of the K-Means clustering process, the data sharing in each cluster is cluster 1 (one) totaling 556 data (26%), cluster 2 (two) totaling 414 data (19%), cluster 3 (three) totaling 189 data (9%) and cluster 4 (four) totaling 1010 data (46%). Furthermore, those who have more than 4 years of study are in cluster 2, cluster 3, cluster 4 and students who have a 4-year study period are in cluster 1.

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”Side effects--part of the package”: A mixed methods approach to adverse events among patients being programmatically treated for DR-TB in Gujarat, India

10.21203/rs.3.rs-16303/v2 ◽

2020 ◽

Author(s):

Arjunkumar Hardas Jakasania ◽

Kalpita shringarpure ◽

Dixit Kapadia ◽

Radhika Sharma ◽

Kedar Mehta ◽

...

Keyword(s):

Mixed Methods ◽

Adverse Events ◽

Medical Officer ◽

Treatment Seeking ◽

Tb Treatment ◽

Program Manager ◽

Resistant Tuberculosis ◽

Initial Treatment Period ◽

Unsuccessful Treatment ◽

Depth Interviews

Abstract Background Unsuccessful treatment outcomes among patients with drug resistant tuberculosis (DR-TB) are due to high rates of adverse events (AEs). However, information related to AEs is not systematically collected and managed under programmatic setting. The present study assessed the a) incidence and pattern of adverse events in first three months of DR-TB treatment initiation; b) treatment seeking behaviour for AE management; and c) explore the challenges in seeking treatment and reporting AEs.Methods This mixed methods study included all patients diagnosed and initiated on treatment under RNTCP during July-September 2018 at Ahmedabad DR-TB centre. The patients were interviewed telephonically and assessed for all AEs experienced by them. In-depth interviews and key-informant interviews were conducted among patients, DOTS supervisors and programme staffs (treatment supervisors, medical officer and district program manager). Results Total 207 AEs were reported by the 74 DR-TB patients. All patients experienced at least one AE during initial treatment period. Incidence rate of AEs (experienced) was 3.11 (1st month-4.6, 2nd month-2.7, 3rd month-2.02) per 100 person days. Of the 207 AEs, gastro-intestinal (59, 28.3%), ophthalmic (32, 15.4%) and otolaryngology (25, 11.9%) system related AEs were commonly experienced. Treatment was not sought in two-fifths of the AEs. Themes and sub-themes related to challenges in treatment seeking or reporting of AEs were 1) Patient related-Misconceptions, accessibility and affordability of management, lack of counselling support, stigma and discrimination, and past treatment experience; 2) Health system related- lack of guidelines and training for AE management, 3) Poor coordination between hospital and tuberculosis centre. Conclusion The incidence of AEs was high among patients with DR-TB in the first three months of treatment and treatment seeking/reporting was low. Adequate health education and counselling of the patient and orientation of the health systems are the need of the hour. An efficient real-time reporting and management of AE can be developed and tested for effective DR-TB control.

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Pentingnya Membangun Platform Kolaborasi Multi-Stakeholder sebagai Key Enabling Factor dalam Membangun Ekosistem Inovasi Industri 4.0 di Era New Normal

Jurnal Informatika Universitas Pamulang ◽

10.32493/informatika.v6i1.8142 ◽

2021 ◽

Vol 6 (1) ◽

pp. 67

Author(s):

Satrio Utomo ◽

Agus Nugroho Harjono

Keyword(s):

Industry 4.0 ◽

Industrial Development ◽

Industrial Revolution ◽

Transformation Process ◽

Point Of View ◽

Industrial Transformation ◽

Program Manager ◽

National Priority ◽

Industry Policy ◽

Multi Stakeholder

Industry 4.0 is an era of technological disruption or industrial revolution 4.0 because it puts more emphasis on system automation and connectivity which will make the mobility of the industrial world movement and job competition non-linear . The use of digital technology is one of the keys. Industry opportunities for industrial development 4.0 are an effort to increase industrial competitiveness, but many industries do not yet understand the concept and how to start the stages. One of the ways proposed as a policy in preparing industry 4.0 should be taken a multi-stakeholder collaborative approach to facilitate development, including gathering digital transformation initiatives so that limited resources can be optimal. As a form of soft industry policy, a platform organization is also needed as a sustainable program manager and provides technical facilities. From a technical point of view, it is necessary to prepare enabling technology that can be utilized by all actors in the cross-sectoral digital economy in an affordable manner. The Ecosystem Platform becomes a medium to be able to build synergy and collaborative across industries with all stakeholders in an effort to accelerate the transformation of industry 4.0 according to the national priority program of Making Indonesia 4.0. In line with that, coordination was carried out between parties in the industrial transformation 4.0 process, as well as building networks to develop positive cooperation, including government, academics or R&D, industry players / associations, technical providers, consultants and of course financial actors in accelerating the industrial transformation process 4.0.

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