Suggested Minimum Data Set for Speech Therapy Centers Affiliated to Tabriz University of Medical Sciences

Damanabi, Shahla; Abdolnejad, Shawbo; Karimi, Gelavizh

doi:10.5455/aim.2015.23.243-247

Cited by 13 publications

(22 citation statements)

References 8 publications

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“…Some of the data elements were identified as important or highly important by the experts and organized in these 8 classes, which were quite similar to what had been found significant by the experts of other fields, e.g. for minimum datasets of speech therapy ( 20 ), Cystic Fibrosis ( 21 ), burns ( 22 ), breast cancer ( 23 ), nursing ( 24 ), hemodialysis adequacy information system ( 25 ), orthopedic injuries ( 26 ), and outpatient oncology clinical nursing ( 27 ). This similarity may indicate that these categories are highly important for many fields of health care system.…”

Section: Discussionsupporting

confidence: 59%

Development of a Minimum Data Set (MDS) for C-Section Anesthesia Information Management System (AIMS)

et al. 2017

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BackgroundCaesarean section, also known as C-section, is a very common procedure in the world. Minimum data set (MDS) is defined as a set of data elements holding information regarding a series of target entities to provide a basis for planning, management, and performance evaluation. MDS has found a great use in health care information systems. Also, it can be considered as a basis for medical information management and has shown a great potential for contributing to the provision of high quality care and disease control measures.ObjectivesThe principal aim of this research was to determine MDS and required capabilities for Anesthesia information management system (AIMS) in C-section in Iran.MethodsData items collected from several selected AIMS were studied to establish an initial set of data. The population of this study composed of 115 anesthesiologists was asked to review the proposed data elements and score them in order of importance by using a five-point Likert scale. The items scored as important or highly important by at least 75% of the experts were included in the final list of minimum data set.ResultsOverall 8 classes of data (consisted of 81 key data elements) were determined as final set. Also, the most important required capabilities were related to airway management and hypertension and hypotension management.ConclusionsIn the development of information system (IS) based on MDS and identification, because of the broad involvement of users, IS capabilities must focus on the users’ needs to form a successful system. Therefore, it is essential to assess MDS watchfully by considering the planned uses of data. Also, IS should have essential capabilities to meet the needs of its users.

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Section: Discussionsupporting

confidence: 59%

Development of a Minimum Data Set (MDS) for C-Section Anesthesia Information Management System (AIMS)

et al. 2017

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“…Although the developed data set for PFD is rather similar to most previous data sets in some sections such as demographic, surgical and outcome data elements, it contains details of specific data elements such as para clinic, prescription, voiding diary and PFMT which could provide comprehensive data elements required and can be useful in meeting the needs of the PFD data users. Classification of data elements into clinical and demographic groups is similar to the majority of categories of data determined as data sets for breast cancer, 14 traffic accidents, 15 thalassemia, 16 orthopedic injuries, 17 burn injuries, 9 schizophrenia, 18 speech therapy, 19 diabetes mellitus, 20 disability 13 and esophageal atresia 10 . However, since the minimal data set provided is specific to female PFDs, gender is not considered among our established data set.…”

Section: Discussionmentioning

confidence: 99%

Development of a core data set for pelvic floor disorder patients registry

Reyhan

Damanabi

Kalankesh

et al. 2020

LUTS

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Objectives: Pelvic floor disorders (PFDs) are important public health concerns due to their increasing prevalence. Hence, there is an increasing need for developing systematically collected quality data to assist appropriate clinical decision-making. This study aimed to develop a core data set for patients with PFDs based on the PFDs registry. Methods: A descriptive cross-sectional study was conducted in 2019. Data were retrieved from electronic databases including PubMed, Embase and Google scholar. Available documents and data systems in clinical centers were also assessed. The Delphi technique was applied to reach a consensus about the data elements using a questionnaire. A panel of experts evaluated the content validity of the questionnaire. Results: We developed a dataset for PFDs that included two classes of data (65 data items) identified from the related literature. In the Delphi survey, 74 data elements were determined by the experts and final data were divided into two demographic and clinical categories that included 12 and 62 data elements, respectively. Conclusions: This dataset has the potential for standardizing the data by providing accurate, consistent, complete and uniform data elements. Furthermore, it can provide valuable research facilities for clinicians and researchers in the healthcare system resulting in improvement of the quality of care and containment of costs.

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“…Administrative data, past medical history, sign and symptoms, physical examinations, and laboratory tests in similar studies are also an important part of MDS. [ 23 24 ]…”

Section: Discussionmentioning

confidence: 99%

Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health

Ehtesham

Safdari

Mansourian

et al. 2020

J Edu Health Promot

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BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus-based framework. METHODS: This research was conducted as a descriptive, cross-sectional study from April 2016 to January 2017, which has been performed in several steps: literature review, developing the initial draft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinions and creating version v.i, performing Delphi rounds, and creating the final framework. RESULTS: The administrative data category with 17 and the historical data category with 23 data elements were utilized in recording data elements in the diagnosis of all of the different oral diseases. In the paraclinical indicator and clinical indicator categories, the necessary data elements were considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket's Oral Medicine: ulcerative, vesicular, and bullous lesions; red and white lesions of the oral mucosa; pigmented lesions of the oral mucosa; benign lesions of the oral cavity and the jaws; oral and oropharyngeal cancer; and salivary gland diseases. CONCLUSIONS: The study achieved a consensus-based framework for the essential data element in the differential diagnosis of oral medicine using a comprehensive search with rich keywords in databases and reference texts, providing an environment for discussion and exchange of ideas among experts and the careful use of the Delphi decision technique.

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Suggested Minimum Data Set for Speech Therapy Centers Affiliated to Tabriz University of Medical Sciences

Cited by 13 publications

References 8 publications

Development of a Minimum Data Set (MDS) for C-Section Anesthesia Information Management System (AIMS)

Development of a Minimum Data Set (MDS) for C-Section Anesthesia Information Management System (AIMS)

Development of a core data set for pelvic floor disorder patients registry

Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health

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