Morbidity Data Quality Initiatives in Ireland

2005 ◽  
Vol 34 (2) ◽  
pp. 47-53 ◽  
Author(s):  
Michelle Bramley ◽  
Beth Reid
Keyword(s):  
Data Quality ◽  
Formative Evaluation ◽  
Reporting System ◽  
Training Programs ◽  
Social Research ◽  
Preceding Paper ◽  
Major Change ◽  
Quality Initiatives ◽  
Morbidity Data ◽  
Social Research Institute

In 2004, the Hospital In-Patient Enquiry and National Perinatal Reporting System (HIPE & NPRS) Unit of the Economic and Social Research Institute in Ireland requested a review of its coder training programs and data quality initiatives, primarily because of the decision to implement a major change in the morbidity classification in January 2005. In August 2004, the authors conducted a formative evaluation using qualitative methods to assess the Unit's programs. A number of opportunities for building on the solid framework the Unit has implemented were identified. The preceding paper focused on the Unit's coder training programs (Bramley & Reid 2005). In this paper, the Unit's data quality initiatives are examined.

Clinical Coder Training Initiatives in Ireland

2005 ◽  
Vol 34 (2) ◽  
pp. 40-46 ◽  
Author(s):  
Michelle Bramley ◽  
Beth Reid
Keyword(s):  
Qualitative Methods ◽  
Data Quality ◽  
Formative Evaluation ◽  
Reporting System ◽  
Training Programs ◽  
Social Research ◽  
Major Change ◽  
Subsequent Paper ◽  
Quality Initiatives ◽  
Social Research Institute

The Hospital In-Patient Enquiry and National Perinatal Reporting System (HIPE & NPRS) Unit of the Economic and Social Research Institute in Ireland requested a review of its coder training programs and data quality initiatives, primarily because of the decision to implement a major change in Ireland's morbidity classification in January 2005. In August 2004, a formative evaluation using qualitative methods was conducted to assess the Unit's programs and initiatives. A number of opportunities for building on the solid frameworks the Unit has implemented were identified. In this paper, we focus on the Unit's coder training programs. The Unit's data quality initiatives will be discussed in a subsequent paper (Bramley & Reid 2005).

Ri-scoprire l'analisi dei casi devianti. Una strategia metodologica di supporto dei processi teorico-interpretativi nella ricerca sociale di tipo standard

2009 ◽  
pp. 109-157
Author(s):  
Sergio Mauceri
Keyword(s):  
Data Quality ◽  
Social Research ◽  
Research Results ◽  
Columbia School ◽  
Depth Study ◽  
Procedural Strategy ◽  
Procedural Models

- This article contains a reflection that intends to assert the heuristic fertility of integrating common procedural models with analysis of deviant cases. This analysis was originally proposed by Paul F. Lazarsfeld and promoted between the '40s and the '60s at Columbia School, without much impact on quantitative social research circles. Deviant cases are cases that do not display expected behaviour or attitudes. Instead of considering deviant cases irrelevant because they are residual, this procedural strategy accentuates their importance and promotes an in-depth study to maximize data quality and support interpretation processes of research results.

Evaluation of the Clinical Professorship within a University TEC Model

1975 ◽  
Vol 157 (4) ◽  
pp. 40-53 ◽  
Author(s):  
William W. Wilen ◽  
Richard D. Hawthorne
Keyword(s):  
Teacher Preparation ◽  
Student Teaching ◽  
Professional Training ◽  
Formative Evaluation ◽  
Cooperating Teachers ◽  
Training Programs ◽  
Teaching Program ◽  
Major Purpose ◽  
Traditional Student ◽  
Data Analyses

Three years ago Kent State began making the transition from a traditional student teaching program to the Teacher Education Center approach. The major purpose was to bring together school and university people in a parity relationship to jointly plan, implement and evaluate the field-based components of professional training programs. As Kent State moved into the center approach, the responsibilities of student teaching supervisors began to change significantly. This prompted a redefinition of the role and title change to clinical professor. Last year the analysis of the data received from a comprehensive formative evaluation effort of our TEC program was completed. A major component of the assessment was the in-depth examination of the clinical professorship as perceived by TEC administrators, cooperating teachers, associate teachers and clinical professors. The data, analyses, and implications are reported in this manuscript. A major overall implication of the findings is that the clinical professor is the critical linkage between school and university in teacher preparation.

Using Technology in Providing Effective Training

2012 ◽  
pp. 138-153
Author(s):  
Ernest W. Brewer ◽  
Stephen D. Stockton ◽  
Tammi M. Basile
Keyword(s):  
Formative Evaluation ◽  
Training Programs ◽  
Clear Understanding ◽  
Training Methods ◽  
Implementation Phase ◽  
Evaluation Phase ◽  
Effective Training ◽  
Individualized Training ◽  
Learning With Technology ◽  
Goals And Objectives

The key to an organization’s abilities to provide effective training in the 21st century is by infusing technology into their training programs. Before technology infusion can occur, there must be a clear understanding of the dynamics of learning with technology and of the instructional culture of the organization. Developers of effective training programs infuse technology based on four phases—development, integration, implementation, and evaluation. The development phase involves the analysis of the organization, the creation of training goals and objectives, and the design of the training program. The integration phase determines the organization’s technology levels and allows developers and trainers to expedite training methods suitable for particular needs. The implementation phase consists of the actual delivery of the training. The evaluation phase is ongoing through formative evaluation, and it ends with a summative evaluation. Future trends of technology in training show promising models for effective individualized training in virtual environments.

Data quality initiatives: striving for continuous improvements

2007 ◽  
Vol 1 (4) ◽  
pp. 347 ◽  
Author(s):  
Sing What Tee ◽  
Paul L. Bowen ◽  
Peta Doyle ◽  
Fiona H. Rohde
Keyword(s):  
Data Quality ◽  
Quality Initiatives

Integrating the Pastoral Dimension into Pastoral Counselor Training Programs

1993 ◽  
Vol 47 (1) ◽  
pp. 56-64
Author(s):  
Marv Gardner
Keyword(s):  
Counselor Training ◽  
Formative Evaluation ◽  
American Association ◽  
Training Programs ◽  
Evaluation Research ◽  
Pastoral Counselor ◽  
Pastoral Counselors ◽  
Counselor Attitudes ◽  
Training Content ◽  
And Training

Reports on formative evaluation research designed to answer the following questions: “What is the pastoral dimension of pastoral counselor training?,” “What methods are in use to integrate the pastoral dimension into counselor training programs?,” and “What are the satisfaction levels of program participants with regard to this integration process?” Summarizes data gathered from 609 participants representing 26 training programs approved by the American Association of Pastoral Counselors. Analyzes and interprets the data on counselor attitudes, identity values, training content and training processes. Discusses the implications of the findings for training programs.

scholarly journals Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  
Keyword(s):  
Data Quality ◽  
Primary Healthcare ◽  
Reporting System ◽  
Health Management ◽  
Healthcare Facility ◽  
Data Accuracy ◽  
District Level ◽  
Management Information ◽  
District Office

Abstract Background: Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania. Methods: This cross-sectional study involved reviews of documents, systems and databases, and collection of primary data from facility registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system. Results: A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate=91.1%; interquartile range (IQR):66.7%-100%) and report forms (86.9%; IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR:35.6%-100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%. The availability rate at the district level was 65% (IQR:48%-75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers’ records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly. Conclusion: There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.

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