Limits...
Graphical modeling and query language for hospitals.

Barzdins J, Barzdins J, Rencis E, Sostaks A - Health Inf Sci Syst (2013)

Bottom Line: They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset.The second step is to do evaluation of usability the proposed language and tool involving the physicians from several hospitals in Latvia and working with real data from these hospitals.Our third step is to develop an efficient implementation of the query language.

View Article: PubMed Central - PubMed

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia.

ABSTRACT

Background: So far there has been little evidence that implementation of the health information technologies (HIT) is leading to health care cost savings. One of the reasons for this lack of impact by the HIT likely lies in the complexity of the business process ownership in the hospitals. The goal of our research is to develop a business model-based method for hospital use which would allow doctors to retrieve directly the ad-hoc information from various hospital databases.

Methods: We have developed a special domain-specific process modelling language called the MedMod. Formally, we define the MedMod language as a profile on UML Class diagrams, but we also demonstrate it on examples, where we explain the semantics of all its elements informally. Moreover, we have developed the Process Query Language (PQL) that is based on MedMod process definition language. The purpose of PQL is to allow a doctor querying (filtering) runtime data of hospital's processes described using MedMod.

Results: The MedMod language tries to overcome deficiencies in existing process modeling languages, allowing to specify the loosely-defined sequence of the steps to be performed in the clinical process. The main advantages of PQL are in two main areas - usability and efficiency. They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset.

Conclusions: We are about to continue developing this project with three further steps. First, we are planning to develop user-friendly graphical editors for the MedMod process modeling and query languages. The second step is to do evaluation of usability the proposed language and tool involving the physicians from several hospitals in Latvia and working with real data from these hospitals. Our third step is to develop an efficient implementation of the query language.

No MeSH data available.


Filtering condition input form – data partitioning operation.
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Fig5: Filtering condition input form – data partitioning operation.

Mentions: The second filtering option is the data partitioning operations like getting Top or Bottom instances based on some attribute. Doctor may ask for 10 slices, where total expenses are the largest. She should select the corresponding activity and choose the data partitioning option. The filter input form is shown in Figure 5.Figure 5


Graphical modeling and query language for hospitals.

Barzdins J, Barzdins J, Rencis E, Sostaks A - Health Inf Sci Syst (2013)

Filtering condition input form – data partitioning operation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4340803&req=5

Fig5: Filtering condition input form – data partitioning operation.
Mentions: The second filtering option is the data partitioning operations like getting Top or Bottom instances based on some attribute. Doctor may ask for 10 slices, where total expenses are the largest. She should select the corresponding activity and choose the data partitioning option. The filter input form is shown in Figure 5.Figure 5

Bottom Line: They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset.The second step is to do evaluation of usability the proposed language and tool involving the physicians from several hospitals in Latvia and working with real data from these hospitals.Our third step is to develop an efficient implementation of the query language.

View Article: PubMed Central - PubMed

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia.

ABSTRACT

Background: So far there has been little evidence that implementation of the health information technologies (HIT) is leading to health care cost savings. One of the reasons for this lack of impact by the HIT likely lies in the complexity of the business process ownership in the hospitals. The goal of our research is to develop a business model-based method for hospital use which would allow doctors to retrieve directly the ad-hoc information from various hospital databases.

Methods: We have developed a special domain-specific process modelling language called the MedMod. Formally, we define the MedMod language as a profile on UML Class diagrams, but we also demonstrate it on examples, where we explain the semantics of all its elements informally. Moreover, we have developed the Process Query Language (PQL) that is based on MedMod process definition language. The purpose of PQL is to allow a doctor querying (filtering) runtime data of hospital's processes described using MedMod.

Results: The MedMod language tries to overcome deficiencies in existing process modeling languages, allowing to specify the loosely-defined sequence of the steps to be performed in the clinical process. The main advantages of PQL are in two main areas - usability and efficiency. They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset.

Conclusions: We are about to continue developing this project with three further steps. First, we are planning to develop user-friendly graphical editors for the MedMod process modeling and query languages. The second step is to do evaluation of usability the proposed language and tool involving the physicians from several hospitals in Latvia and working with real data from these hospitals. Our third step is to develop an efficient implementation of the query language.

No MeSH data available.