scholarly journals Translating Cochrane Reviews to Ensure that Healthcare Decision-Making is Informed by High-Quality Research Evidence

PLoS Medicine ◽  
2013 ◽  
Vol 10 (9) ◽  
pp. e1001516 ◽  
Author(s):  
Erik von Elm ◽  
Philippe Ravaud ◽  
Harriet MacLehose ◽  
Lawrence Mbuagbaw ◽  
Paul Garner ◽  
...  
Keyword(s):  
Decision Making ◽  
Research Evidence ◽  
Healthcare Decision ◽  
High Quality ◽  
High Quality Research ◽  
Quality Research ◽  
Cochrane Reviews ◽  
Healthcare Decision Making

scholarly journals Supplementing linked datasets with meaningful meta-data to enable high quality research

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Shivani Padmanabhan ◽  
Oliver Smith ◽  
Helen Strongman
Keyword(s):  
Decision Making ◽  
Linked Data ◽  
Applied Research ◽  
Care Practice ◽  
High Quality ◽  
High Quality Research ◽  
Meta Data ◽  
Quality Research ◽  
Methodological Research ◽  
Data Source

ABSTRACTObjectivesEnable high quality research using linked data sources whose membership and coverage change over time by providing clarity in applied processing steps and meaningful meta-data. ApproachOur organisations have developed a process that enables linkage of primary care practice data to several disparate data sets. Identifiers are submitted to the trusted third party (TTP) organisation by consenting practices and external data controllers. These include patient NHS number, post code, date of birth and gender. The TTP remove duplicates and clean the data received, and use a sequential eight stage deterministic algorithm to match patients based on all or some of the identifiers. The TTP provide the research organisation with meta-data; a match rank variable per linked dataset to indicate at which stage in the matching algorithm the patient was matched, as well as flags to indicate whether the identifiers submitted by the practice were valid. As part of the research organisation’s standard linked data provision, only patients that have a valid NHS number in the practice data, and therefore have the potential to be linked on NHS number are identified as eligible. A flag to indicate eligibility per individual linked data source is provided. Individual data source coverage periods allow users to define follow-up time for patients. Individuals that have contributed data to more than one practice are flagged. Records for patients that have not been matched on NHS number, or who have been linked to multiple individuals in the linked dataset are removed. This together with recommendations provided in the documentation simplifies decision making for applied research. Methodological research is supported through the option to access removed records. ResultsIn the latest linkage set, identifiers for 10,272,602 patients from 404 English GP practices were collected by the TPP. Of these, 8,213,068 (80%) had a valid NHS flag. A total of 7,401,948 patients were found to have one or more records in Hospital Episodes Statistics (HES) data: 7,152,194 (97%) were matched on NHS number and 6,661,453 (93%) were identified as unique HES patients. ConclusionTo maximise research benefit from linked data, study designs must account for linkage methodologies and potential errors. Data providers need to support informed decision making for applied research whilst enabling methodological research that explores linkage validity and related biases. The documentation and meta-data that we provide enables users to make informed decisions about their study based on its context and design.

Collaborative Partnership: Opening Doors Between Schools and Universities

2019 ◽  
Vol 42 (2) ◽  
pp. 74-80
Author(s):  
Yara N. Farah
Keyword(s):  
Decision Making ◽  
Educational Practices ◽  
Collaborative Partnership ◽  
High Quality ◽  
High Quality Research ◽  
Quality Research ◽  
K 12 ◽  
Successful School ◽  
Education Of Students

Although K-12 schools and universities are two separate and distinct systems, fundamentally both have the same broad goal: the education of students. This leads one to ponder, “How can these two entities work together to promote, foster, and support this goal?” In this article, I share and discuss the key elements for building a successful school–university collaborative partnership. A type of partnership that includes ongoing commitment founded on mutually beneficial goals, trust, equitable decision making, and communication. A partnership that produces high-quality research, improves educational practices in schools, and contributes to the field.

scholarly journals Nursing Home Staff’s Perceptions of Healthcare Decision Making for Unbefriended Residents

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 384-384
Author(s):  
Hyejin Kim ◽  
Molly Perkins ◽  
Thaddeus Pope ◽  
Patricia Comer ◽  
Mi-Kyung Song
Keyword(s):  
Decision Making ◽  
Geographic Area ◽  
Care Physician ◽  
Healthcare Decision ◽  
Do Not Resuscitate ◽  
Best Interest ◽  
Care Plans ◽  
Course Of Action ◽  
Healthcare Decision Making ◽  
Facility Level

Abstract ‘Unbefriended’ adults are those who lack decision-making capacity and have no surrogates or advance care plans. Little data exist on nursing homes (NHs)’ healthcare decision-making practices for unbefriended residents. This study aimed to describe NH staff’s perceptions of healthcare decision making on behalf of unbefriended residents. Sixty-six staff including administrators, physicians, nurses, and social workers from three NHs in one geographic area of Georgia, USA participated in a 31-item survey. Their responses were analyzed using descriptive statistics and conventional content analysis. Of 66 participants, eleven had been involved in healthcare decision-making for unbefriended residents. The most common decision was do-not-resuscitate orders. Decisions primarily were made by relying on the resident’s primary care physician and/or discussing within a facility interdisciplinary team. Key considerations in the decision-making process included “evidence that the resident would not have wanted further treatment” and the perception that “further treatment would not be in the resident’s best interest”. Compared with decision making for residents with surrogates, participants perceived decision making for unbefriended residents to be equally-more difficult. Key barriers to making decisions included uncertainty regarding what the resident would have wanted in the given situation and concerns regarding the ethically and legally right course of action. Facilitators (reported by 52 participants) included some information/knowledge about the resident, an understanding regarding decision-making-related law/policy, and facility-level support. The findings highlight the complexity and difficulty of healthcare decision making for unbefriended residents and suggest more discussions among all key stakeholders to develop practical strategies to support decision-making practices in NHs.

Perceived Financial Insecurity Impacts Healthcare Decision‐Making Among Patients With Sinusitis

2021 ◽  
Author(s):  
Vivek C. Pandrangi ◽  
Nyssa Fox Farrell ◽  
Jess C. Mace ◽  
Kara Y. Detwiller ◽  
Timothy L. Smith ◽  
...  
Keyword(s):  
Decision Making ◽  
Healthcare Decision ◽  
Healthcare Decision Making

scholarly journals 307 - Exploratory Study on Healthcare Decision-Making Capacity Assessment

2020 ◽  
Vol 32 (S1) ◽  
pp. 65-65
Author(s):  
Ana Saraiva Amaral ◽  
Rosa Marina Afonso ◽  
Mário R. Simões ◽  
Sandra Freitas
Keyword(s):  
Decision Making ◽  
Content Analysis ◽  
Focus Groups ◽  
Exploratory Study ◽  
Assessment Instrument ◽  
Funding Agency ◽  
Capacity Assessment ◽  
Healthcare Decision ◽  
Healthcare Decision Making ◽  
Decision Making Capacity

Mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) prevalence is expected to continue to increase, due to the population ageing. MCI and AD may impact patients’ decision-making capacities, which should be assessed through the disease course. These medical conditions can affect the various areas of decision-making capacity in different ways. Decision-making capacity in healthcare is particularly relevant among this population. Elders often suffer from multimorbidity and are frequently asked to make healthcare decisions, which can vary from consenting a routine diagnostic procedure to decide receiving highly risk treatments.To assess this capacity in elders with MCI or AD, we developed the Healthcare Decision-Making Capacity Assessment Instrument (IACTD-CS - Instrumento de Avaliação da Capacidade de Tomada de Decisão em Cuidados de Saúde). This project is funded by Portuguese national funding agency for science, research and technology, FCT (SFRH/BD/139344/2018). IACTD-CS was developed based on Appelbaum and Grisso four abilities model, literature review and review of international assessment instruments. After IACTD-CS first version development, an exploratory study with focus groups was conducted. This study included focus groups with healthcare professionals and nursing homes’ professionals.The focus groups main goals were: 1) understand the participants perception regarding healthcare decision-making capacity, 2) distinguish relevant aspects of decision-making, 3) discuss the abilities and items included in IACTD-CS and 4) identify new aspects or items to be added to IACTD-CS. A content analysis of the focus groups results, with resource to MAXQDA, was conducted afterwards. This exploratory study allowed to identify professionals’ perceptions on healthcare decision-making and its results were a significant contribute to IACTD-CS development. The proposed communication aims to describe the methodology used and present the results of content analysis.

Sign in / Sign up

Export Citation Format

Share Document