scholarly journals A Proposal for an Austrian Nursing Minimum Data Set (NMDS)

2014 ◽  
Vol 05 (02) ◽  
pp. 538-547 ◽  
Author(s):  
W.O. Hackl ◽  
E. Ammenwerth ◽  
R. Ranegger
Keyword(s):  
Delphi Study ◽  
Medical Condition ◽  
Group Discussion ◽  
Minimum Data Set ◽  
Data Sets ◽  
Nursing Assessment ◽  
Data Set ◽  
Nursing Outcomes ◽  
Minimum Data ◽  
Data Elements

SummaryObjective: Nursing Minimum Data Sets can be used to compare nursing care across clinical populations, settings, geographical areas, and time. NMDS can support nursing research, nursing management, and nursing politics. However, in contrast to other countries, Austria does not have a unified NMDS. The objective of this study is to identify possible data elements for an Austrian NMDS.Methods: A two-round Delphi survey was conducted, based on a review of available NMDS, 22 expert interviews, and a focus group discussion.Results: After reaching consensus, the experts proposed the following 56 data elements for an NMDS: six data elements concerning patient demographics, four data elements concerning data of the healthcare institution, four data elements concerning patient’s medical condition, 20 data elements concerning patient problems (nursing assessment, nursing diagnoses, risk assessment), eight data elements concerning nursing outcomes, 14 data elements concerning nursing interventions, and no additional data elements concerning nursing intensity.Conclusion: The proposed NMDS focuses on the long-term and acute care setting. It must now be implemented and tested in the nursing practice.Citation: Ranegger R, Hackl WO, Ammenwerth E. A proposal for an austrian nursing minimum data set (NMDS): A Delphi study. Appl Clin Inf 2014; 5: 538–547 http://dx.doi.org/10.4338/ACI-2014-04-RA-0027

Minimum data and core outcomes for subacute rehabilitation: A scoping review

2021 ◽  
pp. 026921552110604
Author(s):  
Joshua R Lowe ◽  
Sarah J Wallace ◽  
Sonia Sam ◽  
Adrienne Young
Keyword(s):  
Core Outcome Set ◽  
Grey Literature ◽  
Minimum Data Set ◽  
Data Sets ◽  
Core Outcome ◽  
Data Set ◽  
Core Outcome Sets ◽  
Minimum Data ◽  
Global Quality ◽  
Global Quality Of Life

Objective In clinical practice and research, standardised sets of data and outcomes are routinely collected to facilitate data comparison, benchmarking and quality improvement. Most existing data sets are condition-specific and cannot be applied to all patients in a given clinical setting. This review aimed to determine whether the development of a minimum data set for subacute rehabilitation is feasible by collating and comparing existing rehabilitation minimum data sets and core outcome sets. Data sources Published literature was identified through database searches (Scopus, PubMed, EMBASE, CINAHL and the COMET Initiative) in September 2021. Additional data sets were identified through a grey literature search. Review methods This review was conducted in alignment with the PRISMA-ScR recommendations. Datasets were included if they were published in English, designed for adults, and intended for use in subacute rehabilitation. Data were extracted and taxonomically organised to identify commonalities. Items present in ≥50% of data sets were considered common. Results Twenty minimum data sets and seven core outcome sets were included. There were 29 common minimum data set domains, with 19 relating to Patient Information, seven relating to Outcomes, two relating to Service Delivery and one relating to Provider Demographics. Four common domains were identified within the Core Outcome Set analysis, which all related to Life Impact, specifically Physical Functioning (86%) , Emotional Functioning/Wellbeing (57%) , Social Functioning (86%) and Global Quality of Life (100%). Conclusion Common item domains in conditions requiring subacute rehabilitation have been identified, suggesting that development of a dataset for subacute rehabilitation may be feasible.

Towards a minimum data set to assess soil organic matter quality in agricultural soils

1994 ◽  
Vol 74 (4) ◽  
pp. 367-385 ◽  
Author(s):  
E. G. Gregorich ◽  
M. R. Carter ◽  
D. A. Angers ◽  
C. M. Monreal ◽  
B. H. Ellert
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Quality ◽  
Minimum Data Set ◽  
Data Sets ◽  
Data Set ◽  
Organic Matter Quality ◽  
Carbon And Nitrogen ◽  
Minimum Data ◽  
Soil Organic Matter Quality

Soil quality is a composite measure of both a soil’s ability to function and how well it functions, relative to a specific use. Soil quality can be assessed using a minimum data set comprising soil attributes such as texture, organic matter, pH, bulk density, and rooting depth. Soil organic matter has particular significance for soil quality as it can influence many different soil properties including other attributes of the minimum data set. Assessment of soil organic matter is a valuable step towards identifying the overall quality of a soil and may be so informative as to be included in minimum data sets used to evaluate the world’s soils.In this review, soil organic matter is considered to encompass a set of attributes rather than being a single entity. Included among the attributes and discussed here are total soil organic carbon and nitrogen, light fraction and macroorganic (particulate) matter, mineralizable carbon and nitrogen, microbial biomass, soil carbohydrates and enzymes. These attributes are involved in various soil processes, such as those related to nutrient storage, biological activity, and soil structure, and can be used to establish different minimum data sets for the evaluation of soil organic matter quality. Key words: Biological activity, minimum data set, nutrient storage, soil organic matter, soil quality, soil structure

scholarly journals Proposing a Minimum Data Set for Mass Gathering Health

2019 ◽  
Vol 34 (s1) ◽  
pp. s40-s41
Author(s):  
Malinda Steenkamp ◽  
Paul Arbon ◽  
Adam Lund ◽  
Sheila Turris ◽  
Jamie Ranse ◽  
...  
Keyword(s):  
Public Health ◽  
Minimum Data Set ◽  
Data Repository ◽  
Mass Gathering ◽  
Data Set ◽  
Mass Gatherings ◽  
Modified Delphi ◽  
Minimum Data ◽  
Safety Considerations ◽  
Data Elements

Introduction:There is currently no standardized approach to collecting mass gathering health data, which makes comparisons across or between events challenging. From 2013 onward, an international team of researchers from Australia and Canada collaborated to develop a Minimum Data Set (MDS) for Mass Gathering Health (MGH).Aim:The process of developing the MDS has been reported on previously at the 2015 and 2017 World Congresses on Disaster and Emergency Medicine, and this presentation will present a final MDS on MGH.Methods:This study drew from literature, including the 2015 Public Health for Mass Gatherings key considerations, previous event/patient registry development, expert input, and the results of the team’s work. The authors developed an MDS framework with the aim to create an online MGH data repository. The framework was populated with an initial list of data elements using a modified Delphi technique.Results:The MDS includes the 41 data elements in the following domains: community characteristics, event characteristics, venue characteristics, crowd characteristics, event safety considerations, public health considerations, and health services. Also included are definitions and preliminary metadata.Discussion:The development of an MGH-MDS can grow the science underpinning this emerging field. Future input from the international community is essential to ensure that the proposed MDS is fit-for-purpose, i.e., systematic, comprehensive, and rigorous, while remaining fluid and relevant for various users and contexts.

scholarly journals Essential Data Elements for Electronic Cardiovascular Medical Record Systems in Iran

2021 ◽  
Vol 10 (1) ◽  
pp. 54
Author(s):  
Abbas Sheikhtaheri ◽  
Farid Khorami ◽  
Hedyeh Mohammadzadeh
Keyword(s):  
Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Signs ◽  
Minimum Data Set ◽  
Nursing Interventions ◽  
Data Set ◽  
Minimum Data ◽  
Physical Examinations ◽  
Data Elements

Introduction: Electronic medical records play an important role in the management of patients. In order to develop cardiovascular electronic medical record systems, determining minimum data set is necessary. This study aimed to determine the essential data elements for electronic cardiovascular medical record systems.Methods: Medical records of patients with cardiovascular diseases and also the literature were reviewed to develop a questionnaire regarding the data elements.  87 cardiovascular specialists and residents as well as 50 nurses working in cardiovascular departments of hospitals affiliated with Iran University of Medical Sciences participated in the study. The data elements with at least 75% of agreement were considered essential for electronic medical records. Data were analyzed using descriptive statistics in SPSS software.Results: The essential  data elements were classified in 29 classes including admission, death, patients’ main complaints, clinical signs, observations, medications, cardiac surgery, risk factors, laboratory and pathology results, consultation, resuscitation, anesthetic, electrocardiography, blood transfusion or blood products, rehabilitation measures, angiography/venography, exercise testing, endoscopy/colonoscopy, medical imaging, echocardiography, nursing interventions, allergies and side effects, therapeutic implantations, cardiac examinations, physical examinations, angina, referrals, social backgrounds and history., Totally, out of 276 data elements, 245 elements were identified as the essential data elements for electronic cardiovascular medical record systems.Conclusion: In this study, essential data elements were defined for electronic cardiovascular medical records. Identifying cardiovascular minimum data set will be an effective step towards integrating and improving the management of these patients' information.

scholarly journals Developing a Minimum Data Set for a congenital abnormalities surveillance programme in Rwanda – a modified e-Delphi consensus study

F1000Research ◽  
2021 ◽  
Vol 8 ◽  
pp. 1037
Author(s):  
Annette Uwineza ◽  
Aline Muhorakeye ◽  
Janvier Hitayezu ◽  
Peter Thomas Cartledge
Keyword(s):  
Delphi Study ◽  
Congenital Anomalies ◽  
Congenital Abnormality ◽  
World Health ◽  
Minimum Data Set ◽  
Consensus Methods ◽  
Delphi Consensus ◽  
Data Set ◽  
Surveillance Programme ◽  
Minimum Data

Background: In 2015 it was reported that approximately 300,000 newborns die within four weeks of birth every year, worldwide, due to congenital anomalies.  This represents approximately 11% of neonatal deaths. This has led scientists, clinicians and public health authorities to establish congenital abnormality registries (CARs). There is currently no CAR in Rwanda. In establishing such a registry, it was determined that the first step was to identify the Minimum Data Set (MDS) of items/variables and outcomes for the registry to ensure that the final results are meaningful and employable. This study aimed to use Delphi consensus methods to identify a methodologically robust MDS for a congenital abnormality surveillance programme in Rwanda. Methods: A three-round, modified Delphi study was undertaken between April and June 2017. Round 1 was a literature and internet search followed by an open and closed question round with experts in Rounds 2 and 3, respectively. Results: An initial draft MDS of 134 items was created from a review of 15 African studies and 14 international repository tools including the European Surveillance of Congenital Anomalies and the World Health Organization surveillance guidance. In total, 36 and 34 eligible participants were included in Rounds 2 and 3, respectively. A total of 32 new items were added by participants in Round 2. 103 items met the pre-defined consensus criteria and made up the final MDS in Round 3. Conclusions: This is the first Minimum Data Set for a congenital abnormality surveillance programme in an African nation identified in the literature.  The next stage is to field-test the surveillance programme using passive case-finding in teaching hospitals in Rwanda.

scholarly journals A methodology for a minimum data set for rare diseases to support national centers of excellence for healthcare and research

2014 ◽  
Vol 22 (1) ◽  
pp. 76-85 ◽  
Author(s):  
Rémy Choquet ◽  
Meriem Maaroufi ◽  
Albane de Carrara ◽  
Claude Messiaen ◽  
Emmanuel Luigi ◽  
...  
Keyword(s):  
Data Collection ◽  
Rare Disease ◽  
Rare Diseases ◽  
Care Coordination ◽  
Minimum Data Set ◽  
National Plan ◽  
Data Set ◽  
Common Data Elements ◽  
Minimum Data ◽  
Data Elements

Abstract Background Although rare disease patients make up approximately 6–8% of all patients in Europe, it is often difficult to find the necessary expertise for diagnosis and care and the patient numbers needed for rare disease research. The second French National Plan for Rare Diseases highlighted the necessity for better care coordination and epidemiology for rare diseases. A clinical data standard for normalization and exchange of rare disease patient data was proposed. The original methodology used to build the French national minimum data set (F-MDS-RD) common to the 131 expert rare disease centers is presented. Methods To encourage consensus at a national level for homogeneous data collection at the point of care for rare disease patients, we first identified four national expert groups. We reviewed the scientific literature for rare disease common data elements (CDEs) in order to build the first version of the F-MDS-RD. The French rare disease expert centers validated the data elements (DEs). The resulting F-MDS-RD was reviewed and approved by the National Plan Strategic Committee. It was then represented in an HL7 electronic format to maximize interoperability with electronic health records. Results The F-MDS-RD is composed of 58 DEs in six categories: patient, family history, encounter, condition, medication, and questionnaire. It is HL7 compatible and can use various ontologies for diagnosis or sign encoding. The F-MDS-RD was aligned with other CDE initiatives for rare diseases, thus facilitating potential interconnections between rare disease registries. Conclusions The French F-MDS-RD was defined through national consensus. It can foster better care coordination and facilitate determining rare disease patients’ eligibility for research studies, trials, or cohorts. Since other countries will need to develop their own standards for rare disease data collection, they might benefit from the methods presented here.

scholarly journals Minimum data set development for a drug poisoning registry system

2019 ◽  
Vol 5 ◽  
pp. 205520761989715 ◽  
Author(s):  
Sadrieh Hajesmaeel-Gohari ◽  
Kambiz Bahaadinbeigy ◽  
Shahrad Tajoddini ◽  
Sharareh R Niakan Kalhori
Keyword(s):  
Healthcare Providers ◽  
Data Gathering ◽  
Initial Step ◽  
Minimum Data Set ◽  
Cross Sectional ◽  
Data Set ◽  
Drug Poisoning ◽  
Minimum Data ◽  
Registry System ◽  
Data Elements

Objective Drug poisoning is the most prevalent type of poisoning throughout the world that can occur intentional or unintentional. Standard way for data gathering with uniform definitions is a requirement for preventing, controlling and managing of drug poisoning management. The purpose of this study was to develop a minimum data set, as an initial step, for a drug poisoning registry system in Iran. Methods This was descriptive and cross-sectional study that was performed in 2019. As the first step a comprehensive literature review was performed to retrieve related resources in Persian and English languages. For the second step the medical records of drug poisoning patients at Afzalipour hospital affiliated to Kerman University of Medical Sciences were assessed. Related data from these two steps were gathered by a checklist. Finally, a questionnaire that was created based on the checklist data elements and had three columns of ‘essential,' ‘useful, but not essential', and ‘not essential' was used to reach a consensus on the data elements. Then the content validity ratio and the mean of experts’ judgments were calculated for each data element. The Cronbach’s alpha value for the entire questionnaire was obtained 0.9. Results The minimum data set of a drug poisoning registry system was categorised into the administrative part with three sections including 32 data elements, and clinical parts with six sections including 81 data elements. Conclusion This study provides a minimum data set for development of a drug poisoning registry system. Collecting this minimum data set is critical for helping policy makers and healthcare providers to prevent, control and manage drug poisoning.

scholarly journals The Minimum Data Set and Quality Indicators for National Healthcare-Associated Infection Surveillance in Mainland China: Towards Precision Management

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Hongwu Yao ◽  
Jijiang Suo ◽  
Yubin Xing ◽  
Mingmei Du ◽  
Yanling Bai ◽  
...  
Keyword(s):  
Quality Indicators ◽  
Surveillance System ◽  
Minimum Data Set ◽  
Healthcare Associated Infection ◽  
Process Data ◽  
Data Set ◽  
Minimum Data ◽  
Precision Management ◽  
Data Elements ◽  
Healthcare Associated

The magnitude and scope of the healthcare-associated infections (HCAIs) burden are underestimated worldwide, and have raised public concerns for their adverse effect on patient safety. In China, HCAIs still present an unneglected challenge and economic burden in recent decades. With the purpose of reducing the HCAI prevalence and enhancing precision management, China’s National Nosocomial Infection Management and Quality Control Center (NNIMQCC) had developed a Minimum Data Set (MDS) and corresponding Quality Indicators (QIs) for establishing national HCAI surveillance system, the data elements of which were repeatedly discussed, investigated, and confirmed by consensus of the expert team. The total number of data elements in MDS and QIs were 70 and 64, and they were both classified into seven categorical items. The NNIMQCC also had started two pilot projects to inspect the applicability, feasibility, and reliability of MDS. After years of hard work, more than 400 health facilities in 14 provinces have realized the importance of HCAI surveillance and contributed to developing an ability of exporting automatically standardized data to meet the requirement of MDS and participate in the regional surveillance system. Generally, the emergence of MDS and QIs in China indicates the beginning of the national HCAI surveillance based on information technology and computerized process data. The establishment of MDS aimed to use electronic health process data to ensure the data accuracy and comparability and to provide instructive and ongoing QIs to estimate and monitor the burden of HCAIs, and to evaluate the effects of interventions and direct health policy decision-making.

scholarly journals A study to design minimum data set of COVID-19 registry system

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Javad Zarei ◽  
Mohammad Badavi ◽  
Majid Karandish ◽  
Maryam Haddadzadeh Shoushtari ◽  
Maryam Dastoorpoor ◽  
...  
Keyword(s):  
Minimum Data Set ◽  
Second Phase ◽  
Data Set ◽  
Khuzestan Province ◽  
Minimum Data ◽  
Registry System ◽  
System Data ◽  
Southwestern Iran ◽  
Data Elements ◽  
Five Phases

Abstract Background From the beginning of the COVID-19 pandemic, the development of infrastructures to record, collect and report COVID-19‏ ‏data has become a fundamental necessity in the world. The disease registry system can help build an infrastructure to collect data systematically. The study aimed to design a minimum data set for the COVID-19 registry system. Methods A qualitative study to design an MDS for the COVID-19 registry system was performed in five phases at Ahvaz University of Medical Sciences in Khuzestan Province in southwestern Iran, 2020–2021. In the first phase, assessing the information requirements was performed for the COVID-19 registry system. Data elements were identified in the second phase. In the third phase, the MDS was selected, and in the four phases, the COVID-19 registry system was implemented as a pilot study to test the MDS. Finally, based on the experiences gained from the COVID-19 registry system implementation, the MDS were evaluated, and corrections were made. Results MDS of the COVID-19 registry system contains eight top groups including administrative (34 data elements), disease exposure (61 data elements), medical history and physical examination (138 data elements), findings of clinical diagnostic tests (101 data elements), disease progress and outcome of treatment (55 data elements), medical diagnosis and cause of death (12 data elements), follow-up (14 data elements), and COVID-19 vaccination (19 data elements) data, respectively. Conclusion Creating a standard and comprehensive MDS can help to design any national data dictionary for COVID-19 and improve the quality of COVID-19 data.

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