Not applicable.
The invention relates to the field of management information systems, and more particularly to a platform for managing medical operations by dynamically modeling clinical policies using best practices guidelines.
Management information systems have been commercially deployed which permit a medical director, chief information office or other managers to collect, track and analyze a variety of aspects of hospital and other clinical sites. For instance, packages exist which may track and capture diagnostic, outcomes, pharmaceutical and other clinically-related data from one or more hospitals, clinics or other facilities. A manager may then use data mining tools such as structured query language (SQL) engines to run reports off of the data store for their clinical operation. Managers and others may for instance run queries to see whether the number of patient bed-days has increased in the past year, or the cardiology department shows a positive profit trend. While these types of internal analytics may be helpful, there are limitations to the flexibility and sophistication of current clinical management systems in the medical arena. For one, while many packages permit the analysis of clinical operations by way of reports rolled up from raw clinical data, they may not permit a manager to model or simulate what would happen if various operational policies were changed. For instance, a data package might permit a chief cardiologist or others to determine how many shunt catheterizations were performed in the unit last year, but not allow that manager to forecast or project the effect on patient outcomes if more balloon angioplasties were substituted or combined with that surgical procedure.
As a further drawback, even if a medical information system permits a manager or other user to predict or simulate the resulting patient, financial or other outcomes from changes in various drug, surgical or other clinical policies, platforms today may do so today based only on the internally generated clinical data sets created by that operator. Whatever simulations may be performed may, in other words, be based upon empirical data but be unconstrained on the other side by other objective guidelines. Other problems and limitations exist.
The invention overcoming these and other problems in the art relates in one regard to a system and method for evidence-based modeling of clinical operations, in which a user may run predictive analytics off of clinical data stores, based on one side by empirical data captured from clinical sites but constrained on the other side by objective medical or clinical guidelines. In embodiments, an inference engine may access a data warehouse storing sets of clinical data related to hospital, clinic, research, government or other sites and also access a knowledge base of standardized or baseline clinical guidelines. The inference engine may compare the results on the ground from those clinical facilities to that objective set of guidelines or criteria, and model or project the estimated changes in operational outcomes if internal policies and procedures were to be changed, for instance to conform drug, surgery or other policies to recommended practice guidelines. The user may also re-model the clinical outcomes over time to determine how various factors contribute to changing clinical results and inter-relate to each other under shifting clinical scenarios and policies.
The clinically-related data may be communicated, for instance via a local area network (LAN), virtual private network (VPN), the Internet or other networks or connections to a data warehouse 104 for storage and manipulation on a clinical data store 106. The data warehouse 104 may include, for instance, a query engine such as a SQL engine or other resources to facilitate the maintenance, interrogation and transmission of the clinically-related data and other data stored on clinical data store 106. Clinical data store 106 may be or include a large-scale or other database hosting facility, such as a site including or interfacing to, for example, relational databases such as the Oracle™ relational database sold commercially by Oracle Corp. or others. Other storage or query formats, platforms or resources such as OLAP (On Line Analytical Processing), SQL, storage area networks (SANs), redundant arrays of independent disks (RAID) or others may also be used, incorporated or accessed by clinical data store 106, which may be supported by server or other resources.
The data warehouse 104 may likewise communicate with an inference engine 108 configured to execute or access a dynamic analytical module 112 which analyzes or models the content of clinically-related data. Inference engine 108 may for example execute on a local or remote workstation communicating via a communications link such as the Internet or other network or connection with data warehouse 104. Inference engine 108 may similarly communicate with a knowledge base 110 containing medical, clinical or other operational or other guidelines. The guidelines and other normative information contained in knowledge base 110 may for instance include recommended or best practices for different categories of diseases, patients or treatments as well as other clinical baseline or objective data. In embodiments the knowledge base 110 may include or access clinical guidelines published or released by Zynx Health Inc. Other sources of objective or evidence or research-based clinical guidelines may be assessed or incorporated, such as for example data published or provided by the Joint Commission on Accreditation of Healthcare Organizations. Other public or private sources or combinations of sources of clinically-related criteria or guidelines may be used.
As illustrated in
As illustrated another portlet in the dynamic analytical module 112 may present the user with the different categories of solution sets. Selecting one of those metrics may flex the listed solution set reports to display associated preconfigured reports. An accessible solution set of this type may be or include a collection of predefined report templates for a particular process in common healthcare settings. Illustratively those solution set offerings may include clinical outcomes, strategic outcomes and utilization outcomes. Other templates or metrics may be used. In embodiments of the invention in another regard, the data stored in clinical data store 106 and accessible via data warehouse 104 or otherwise may be or include data sets which have been processed to generate multidimensional extensions to the raw source data as described in the aforementioned U.S. Provisional Patent Application Ser. No. 60/498,283 and U.S. patent application Ser. No. 10/______, thereby extending the power and flexibility of queries and reports.
As further illustrated in
The user may then review the solution set entitled “AMI—Calcium Channel Blockers”, for instance by activating the embedded link. As illustrated in
As further illustrated in
The user may perceive that as a matter of clinical policy their organization's AMI patients should not be receiving short-acting nifedipine, while AMI patients actually received short-acting nifedipine 20% of the time in the illustrated year of 2002. The projective analysis 118 may quantify the opportunity for improvement if the evidence-based guidelines were followed. This may be done for instance by activating an embedded “Forecast” link, to display a projective analysis 118. The projective analysis 118 as shown demonstrates that if the pharmaceutical guideline were followed, in the user's clinical facility there is the potential to save approximately 49 lives as well as the costs of approximately $432,000 by adopting the policy or procedure of avoiding the use of short-acting nifedipine in AMI patients.
After establishing a quantified opportunity for improvement, the user may further analyze the clinical environment by generating additional reports, for instance using defined solution sets or additional custom queries. For example, as illustrated in
According to the invention in another regard, the dynamic analytical module 112 may help to identify an overall trend in the clinically-related data 116 at a high level from one or more key performance indicators 114, and drill further into the clinically-related data 116 to permit a user to assess further levels of detail, for instance to assess data at the level of individual patients or groups of patients or others.
As illustrated in
Overall analytic processing according to an embodiment of the invention is illustrated in
In step 608, clinical modeling and forecasting may be initiated, for instance by way of dynamic analytical module 112 or other resources. In step 610, the clinically-related data 116 may be compared against data in the knowledge base 110 in the inference engine 108, for instance to detect whether clinically driven or mandated guidelines, thresholds or limits have been reached or not for given recovery rates, drug delivery, patient readmittance or other variables or factors. In step 612, an operator such as a medical director, chief information officer or other user may manipulate the dynamic analytical module 112 to extract key performance indicators 114 such as drug delivery or prescription rates for identified pharmaceuticals, the frequency or elapsed time with which a surgical or other procedure is employed, or other clinical, diagnostic, financial or other data or variables.
In step 614, an operator may model the clinically-related data 116 to generate a predictive analysis 118 which projects revised clinical outcomes as a function of changed drug delivery, surgical, patient discharge or other procedures. In step 616, the clinically-related data 116 may be updated after a change in policy or procedures for those and other types of procedures, for instance to determine whether patient outcomes, costs or other factors have improved or declined. In step 618, the baseline improvements or other changes may be stored to clinical data store 106 or to other data stores or resources. In step 620, processing may terminate, repeat or return to a prior processing point.
The foregoing description of the invention is illustrative, and modifications in configuration and implementation will occur to persons skilled in the art. For instance, while the invention has generally been described in terms of a single inference engine 110 which communicates with a single knowledge base 110 to perform comparative analytics, in embodiments more than one distributed logic engines or modeling modules may access the clinical data and knowledge base independently or together. Likewise, in implementations more than one knowledge base 110, data warehouse 104 or other comparable data resources may supply raw clinical data and baseline clinical guidelines and other information for use in evidence-based analysis and forecasting of clinical operations.
Similarly, while the invention has in embodiments been described as extracting key performance indicators 114 to drive projective analytics, other variables or groups of variables may be selected or employed. Other hardware, software or other resources described as singular may in embodiments be distributed, and similarly in embodiments resources described as distributed may be combined. The scope of the invention is accordingly intended to be limited only by the following claims.
The subject matter of this application is related to the subject matter of U.S. Provisional Patent Application Ser. No. 60/498,283 filed Aug. 28, 2003 entitled “System and Method for Multidimensional Extension of Database Information”, to the subject matter of U.S. patent application Ser. No. 10/______ filed Sep. 22, 2003 entitled “System and Method for Multidimensional Extension of Database Information”, and to the subject matter of U. S. Provisional Patent Application Ser. No. 60/508,273 filed Oct. 6, 2003 entitled “System and Method for Management Interface for Clinical Environments”, each of which applications is assigned or under obligation of assignment to the same entity as this application, and each of which is incorporated in this application by reference.
Number | Date | Country | |
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60498283 | Aug 2003 | US | |
60508273 | Oct 2003 | US |