posted Apr 7, 2011, 8:00 AM by Post Master
The OSCAR Vollies have released the version 2.0 of BC Billing module! this is a UI to rules and regulations announced by the government of British Columbia here:
A demo version is available here: https://rivercityclinic.net:13242/bcbilling/
and the project website can be found over here: http://oscarbcbilling.patesco.ca/
Way to go OSCAR Volunteers! Patesco is proud to be associated with this great team and project. We look forward to witnessing your continued success and accomplishments! |
posted Oct 14, 2009, 11:16 PM by Post Master
[
updated Apr 7, 2011, 7:55 AM
]
In the present era, data is one of the most important
factors for business survival of any industry, and healthcare is no exception.
In fact, the drive to reduce cost and the desire to improve patient care makes
the healthcare industry one of the most eager customers for clean and
integrated organizational data.
But this data needs to posses a number of characteristics if
it is to be used for decision-making and strategic operation. The government of
British Columbia defines the state of completeness, validity, consistency,
timeliness and accuracy that makes data appropriate for a specific use as data
quality
  To build a practical framework for achieving
desirable data quality, Strong et al. (2) suggest taking a customer focused view by treating
data processing as a data manufacturing system and to produce data that is “fit
to use by data customer”. They recognize three fundamental roles: data
producers, data custodians and data consumers. Fitness for use would mean that
the concept of data quality is relative; therefore dimensions need to be
defined to ensure fitness in an integrated health care environment.
Table 1: Perceived Data Quality Dimensions
|
Information Quality Category
|
Information Quality Dimensions
|
Intrinsic
|
Accuracy, Objectivity, Believability, Reputation
|
Accessibility
|
Access, Security
|
Contextual
|
Value-added, Relevancy, Timeliness, Completeness, Amount
of Data
|
Representational
|
Interpretability, Ease of Understanding, Concise
Representation, Consistent Representation |
Organizations
select from these dimensions based on their own needs and special
circumstances. Examples include New Zealand Healthcare data quality framework
(6 dimensions), Statistics Canada’s
Quality Assurance Framework (6 dimensions), Ontario Data Quality
Management Framework (4 dimensions) , and CIHI Data Quality Framework, which
will be presented here in further detail.
CIHI has been publishing a framework for data quality since
2000. the latest revision, 2006, has selected five of these dimensions to
implement a data quality assessment tools (10).
CIHI selects Accuracy, Timeliness, Comparability, Usability,
and Relevance. They then divide these dimensions into characteristics, and
define a set of criteria for each characteristic. Using a ranking system of
met, unmet, and unkown or not applicable, the strengths and limitations of data
is assessed, and areas of intervention identified. To help prioritize those
intervention activities, some of the criteria follow another ranking system of
minimal, moderate and significant.
CIHI
defines the roles and responsibilities of data quality framework as follows:
- Senior Management
- Provide Resource, Support DQ in all new initiative
- Product Areas
- Evaluate data quality and address issues
- Document quality
- Conduct studies and identify ways of improvement
- Data Quality Section
- Provide guidance, review and report on compliance
- Assist in studies
- Conduct R&D on data quality
- Train and update framework annually
Full text article is available in the Resources section. |
posted Oct 14, 2009, 11:11 PM by Post Master
[
updated Apr 7, 2011, 8:00 AM
]
Process modeling measures, analyses,
improves and controls characteristics of the business process in an
organization. It demands the commitment of everyone in the organization,
particularly high-level management, to achieve sustainable quality improvement.
It reasons that business success depends on reduction of process variation,
with continuous effort to establish stable and predictable process results.
The historical success of organizations
that implemented correct process modeling has made this topic a common practice
for all organizations that wish to optimize their performance; and with
increasing demand on health care information and limited financial resources,
health care organizations have followed suite of the major industries and are
now increasingly implementing these concepts.
Six Sigma,
christened after the statistical process capability studies, was originally a
set of practices to improve manufacturing process developed by Bill Smith at
Motorola in 1986. However, it has expanded in the two subsequent decades to
extend to other types of business processes as one of the most popular quality
improvement strategies.
The paper is divided to two main parts. The
first part presents a review of current
literature, showing the facts and issues of each concept. It introduces the Six
Sigma strategy and the Lean Manufacturing approach, and describes how the
combination of these, Lean Six Sigma, is used as a methodology for business
process management.
The SIPOC diagrams are then described in
further detail, pointing out how should each part (Supplier, Input, Process,
Output, and Customer) should be documented and described. The Swim lane
diagrams that depict the processes are then introduced and their expected
layout and properties discussed.
Once the processes are defined correctly by
the SIPOC diagrams, they need to be analysed. Value Stream Mapping and Quality
Stream Mapping are two of these tools that are described here as the last
section of the first part of this document.
The second part defines the metadata for
SIPOC diagrams. Here, tables demonstrate each data element that should be
recorded about each part of the system, and an example or a description is
presented to help specify that element correctly. A set of graphic icons is
represented at the end of the document to be used in process maps so that they
would all follow a uniform visual presentation.
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