This webcast gives an overview of the reporting capabilities of ConnectR. In addition, it touches on ConnectR’s administrative capabilities such as merging message definitions and exporting translation tables and interface mappings for documentation purposes. The webcast concludes with the ConnectR Toolbelt, which is an imbedded, add-on reporting tool developed by Galen.
For more webcasts visit: http://www.galenhealthcare.com/calendar
This morning, Shahid Shah over at the The Healthcare IT Guy blog, published an article outlining why medical device data is the best way to fill meaningful use EHRs and conduct comparative effectiveness research (CER). What was of particular interest to me is the way in which Shahid elegantly broke down how unstructured and structured data is “sourced” today (scroll down in the blog article for the graphic).
As is evident by the table above, many of the existing MU incentives in Phase 1 (patient reported and healthcare professional entered especially) promote the wrong kinds of collection: unreliable, slow, and error prone. Accurate, real-time, data is only available from connected medical devices and labs / diagnostics equipment.
Given that meaningful Use and CER advocates are promoting (structured) data collection for reduction of medical errors, analysis of treatments and procedures, and research for new methods it’s important to see that we’re not going to get real gains until the medical device vendors are fully connected and providing data directly into EHRs or clinical data warehouses.
Shahid’s article brings to light a larger issue within the industry – a lot of meaningful data is captured in an unstructured fashion. Dr. John Halamka brought this to light in a blog article earlier in the year which addressed “Freeing the data.” In this article, Dr. Halamka suggests that businesses will always have a combination of structured and unstructured data and that businesses must find ways to leverage this unstructured data:
In healthcare, the HITECH Act/Meaningful Use requires that clinicians document the smoking status of 50% of their patients. In the past, many EHRs did not have structured data elements to support this activity. Today’s certified EHRs provided structured vocabularies and specific pulldowns/checkboxes for data entry, but what do we do about past data? Ideally, we’d use natural language processing, probability, and search to examine unstructured text in the patient record and figure out smoking status including the context of the word smoking such as “former”, “active”, “heavy”, “never” etc.
The value of unstructured patient narratives was addressed in detail in one of last year’s Health Management Technology articles – specifically the section which addressed Mining unstructured data:
As EHRs become increasingly widespread due to the billions of dollars in federal stimulus incentives, harnessing unstructured clinicians’ notes gives us the power to yield valuable patient data. With each year of data, more information will be gathered that could be used to find predictors for diseases or adverse effects of treatment that would otherwise have gone unnoticed by most traditional research studies. Though challenging, capturing and delving into this data will be worth the effort, and could potentially help healthcare institutions meet requirements for CMS reporting and for meaningful use, access funding and, most importantly, improve the health of entire populations.
At Galen, we have developed a solution that addresses current limitations with regards to extraction of structured note data within built-in Allscripts Enterprise EHR functionality. Galen’s NoteXML solution is designed to facilitate the querying of data contained within Allscripts Enterprise EHR v11 Structured Notes. These notes are not stored inside the EEHR as discrete data, but rather as XML documents that aren’t easily query-able. The solution has helped our clients extract pertinent MU reportable data that otherwise would not be discretely available.
Again, the aforementioned solution does not facilitate data mining of unstructured note data. However, companies such as Nuance are engaged in “‘unlocking’ unstructured clinical documentation, sometimes referred to as the ‘narrative blob’” Nuance’s NLP solutions assist in collecting and reporting on various diagnostic, quality and safety measures. I have yet to see this integrate directly to the Allscripts product line, but anticipate this possibility in the future months.
I’m curious as to how other groups and organizations are addressing the gap between unstructured data capture and discrete data extraction for MU and quality reporting? Are organizations relying on third-party solutions such as that offered by Nuance?
Our clients environments are both sophisticated and complex, often times with different vendors in the fold for the different healthcare information systems that are utilized by the organizations. For those clients that are Managed Service Organizations (MSOs) or have different sub-entities, this is even more pronounced. Consider for a moment a scenario where an Integrated Delivery Network (IDN) consists of four physician groups under its umbrella. Some of these physician groups were added via acquisition – and as such were using existing systems such as EHRs or PMs from vendors different than those of the organization they were joining. The following mosaic illustrates such a case:
Given the graphic above, one can appreciate the complexity involved with the following core enterprise organizational functions:
A recent presentation at a NEHIMSS last month illustrated these points above and did a great job of communicating how Partners Healthcare is addressing the Healthcare Information System (HIS) mosaic via their COMPASS project. The COMPASS project is an aggressive initiative which implements a common administrative system and processes to streamline revenue cycle management and help manage costs through a “holistic, patient-centric, workflow-driven approach.”
The efficiency of the mosaic of systems (ala Claude Shannon for those EE nerds out there) is subpar at best. But this is the environment organizations find themselves. The alternative would be to consolidate to utilize one vendor across all systems ala the COMPASS project. However, some vendor systems are better at functions than others and the cost for conversion may be prohibitive or in some instances not feasible. For those organizations seeking out advice or recommendations for healthcare information systems, check out the folks at Software Advice as they offer great resources.
Contact us today if your organization seeks assistance with data conversion or integration of healthcare information systems.
Organizations exploring Computerized Physician Order Entry (CPOE) might first pursue low-hanging fruit and implement an electronic workflow for results and keep a paper workflow for orders. Often times, electronic order entry can be cumbersome for end users and cause longer workflows. As alluded to in a previous blog article, the benefits of implementing a solicited result interface are compelling – reducing paper and scanning, and offers the capability for automated result tasking.
In the Allscripts Enterprise EHR (AE-EHR), results can tie back to existing orders, facilitating completion of the order. This functionality is enabled and configured within the results interface deployed at a particular group and can be achieved in one of two ways:
For some organizations, a paper order work flow may be utilized, in which a paper requisition is presented to the lab instead of an electronic order. However, the Laboratory Information System (LIS) may not allow for discrete capture of the Allscripts-generated order number or requisition number. For that matter, the LIS also may not have the capability to send back this number in the result interface (typically a HL7 ORU result message).
Additionally, most organizations encounter a percentage of solicited results that do not complete the order. In the latter scenario, a lab may manually enter the order introducing the possibility for human error and can cause issue with not only reconciliation of the order, but potentially patient or provider matching.
Furthermore, if a lab has to change an order for any reason (for instance, changing the orderable item), the corresponding result will likely not reconcile the order (with the AE-EHR, the correct protocol would be to cancel the order and place a new order with the desired changes).
This situation can cause nightmares for organizations that are trying to gain semblance as to where lab vendors stand in terms of order fulfillment. Additionally, order reconciliation reporting will likely be inaccurate.
This is especially pronounced in v11 AE-EHR, in which solicited results that are unable to reconcile to the original order create a “reported order.’ The original order is left unreconciled and a “duplicate” order renders in the patient chart:
We have resources available on our wiki to guide an organization through interfaced result-driven order reconciliation and can assist those organizations looking to gain control of order fulfillment and reconciliation. Please contact sales@galenhealthcare.com for more information.
Galen will be hosting another in Enterprise reporting workshop this coming March. This has been a popular course, so please sign up early!
What: A three-day course for report writers, DBAs and those in healthcare informatics on the Allscripts Enterprise EHR database.
When: March 1 – 3, 2010
Where: Boston, MA
Price: $2,500
The Galen Database Architecture and Reporting Workshop has furthered our understanding of the Allscripts Enterprise EHR database. The clear presentation and substantial hands-on time helped us to greatly accelerate our production of customized reports. And, the data dictionary documentation alone is invaluable.
– Chris Hyde, DBA, Albuquerque Health Partners
The attached announcement includes additional information regarding the course and suggested audience (report writers, DBAs, etc).
Please contact Mike Dow to register, or if you have any questions – mike.dow@galenhealthcare.com
There is quite a bit of buzz in the healthcare IT community surrounding the ONCHIT/CMS release of the Meaningful Use Interim Final Rule and the and the EHR certification requirements. The author of HISTalk kindly spent his New Year’s Eve poring over the documents to provide an excel worksheet summary of the actual criteria and thresholds and the author of the Medical Software Advice blog did a great job of outlining definition, features and measurement with his blog entry. I thought I would take it a step further and provide some meaningful information to CFOs and PMs by taking a stab at quantifying the effort involved with each measure. First some background information and disclaimers:
The meaningful use matrix with effort broken-out can be found on the Galen Healthcare Solutions Wiki.
Now that we have presented the effort involved, let’s delve into how EHR deployments – specifically AE-EHR deployements – are typically phased:
Phase I: Base, Document, Scan and Dictate
Description: Provide a baseline level of EHR functionality to all users. Real-time access to physician schedules, transcribed and scanned documents, facilitation of dictation. Data conversions, Scanned charts and documents, Base Deployment. This approach typically appeals to all providers regardless of technical aptitude and would not require significant workflow changes
Advantages: Clinical information access internal and external to the clinic, reduced level of change for physicians through the use of dictate, realized benefits of decreased errors and re-work.
*Phase II: Rx+, Note, Forms, Results
Description: Add medication management, structured note and results
Advantages: Ability to collect structured information facilitating use of panel queries. Additionally, formulary compliance, and prescription faxing/e-prescribing to pharmacies and ability to capture results as discrete data elements
Description: Facilitates charge capture and order transmission.
Advantages: Completes the access to centralized patient data and further enhances the quality of care and service to patients.
*Phase II and III can be combined based upon the organization requirements
In conclusion, one of the biggest questions that lingers for me is how the data is to be relayed to the government such that organizations can be evaluated as to whether or not they meet the thresholds to receive the incentives. Custom reporting comes to mind as precedent has been set here, specifically with PQRI and Medicare HCC. Galen Healthcare Solutions certainly can provide custom reporting specific to organizations needs in order to communicate meaningful use. Another solution is Allscripts Clinical Quality Solution powered by TeamPraxis. In the meantime, we wait for the rule to be finalized and anticipate announcement of how the meaningful use data is to be relayed.
If your organization is looking for assistance in exhibiting meaningful use, please contact sales@galenhealthcare.com and visit our website for more information regarding our technical and professional service offerings.
The requests for reports that we get runs the gamut. Most of the time, clients are looking to modify the existing canned reports that Allscripts offers with the Allscripts Enterprise Electronic Health Record (AE-EHR). Other times, clients envision a custom report that is unlike any of those currently offered and is unique to their particular organization. And still further, some organizations wish to fulfill reporting metrics to receive monetary incentives from initiatives such as the Physician Quality Reporting Initiatives (PQRI) and P4P (Pay for Performance) . Given the commonalities in the requests we receive, with our reporting solutions store, we have attempted to pick the most popular reports requested from clients and offer them via on-demand payment, download and installation.
We also receive a substantial amount of inquiries from clients as to what exactly goes into customizing existing reports and creating new reports. Clients are often curious as to what types of skill sets are needed. These organizations may feel that they are better suited to have their own personnel develop custom reports. For instance, the organization may have performed an return on investment (ROI) analysis and determined it makes the most financial sense to train their own staff to supply the multitude of administrative and “print” reports they require in the coming future.
That said, let’s get to answering the question of what goes into developing custom reports for the AE-EHR:
The most important ingredient to custom AE-EHR report recipes comes in the experience – specifically knowledge of the database schema. Knowing what tables to pull from, how tables are related, and what functions, stored procedures and existing custom reports can be utilized so as to not re-invent the wheel. Knowledge of advanced SQL querying is invaluable as well. If you would like to learn more, Galen is offering free EHR Reporting webcasts.
Let us know if we may assist your organization in developing and delivering custom AE-EHR reports. In addition to the reporting solutions store, we also offer training courses and reporting services for the Allscripts Enterprise EHR database, ETL database, Analytics and the ConnectR database. Please contact sales@galenhealthcare.com for more information regarding these courses and our reporting services.
Galen Healthcare Solutions will be hosting the second series of free webcasts covering Allscripts EHR Reporting. The purpose of these webcasts is to provide insight into reporting options within your EHR database. We will cover approaches to reporting, database structure, and hands-on querying of the EHR database.
These will be structured in a similar format to university courses – the initial three classes will be at 100, 300 and 500 levels. The list of the webcasts and their times may be found below.
100 Series – Introduction to the Allscripts EHR Database: Overview of the database, patient demographics and dictionary linking.
300 Series – v11 Order and Results: querying configuration and patient data.
500 Series – Advanced ConnectR Architecture and Querying
To attend, please contact Mike Dow, mike.dow@galenhealthcare.com. You must be an existing Allscripts Enterprise EHR client to attend.
We also offer training courses and reporting services for the Allscripts Enterprise EHR database, ETL database, Analytics and the ConnectR database. Please contact sales@galenhealthcare.com for more information regarding these courses and our reporting services.
Galen Healthcare Solutions will be hosting a series of free webcasts covering Allscripts EHR Reporting. The purpose of these webcasts is to provide insight into reporting options within your EHR database. We will cover approaches to reporting, database structure, and hands-on querying of the EHR database.
These will be structured in a similar format to university courses – the initial three classes will be at 100, 300 and 500 levels. The list of the webcasts and their times may be found below.
100 Series – Introduction to the Allscripts EHR Database: Overview of the database, patient demographics and dictionary linking.
300 Series – v11 Order and Results: querying configuration and patient data.
500 Series – Advanced ConnectR Architecture and Querying
Please contact Mike Dow, mike.dow@galenhealthcare.com, to sign up. You must be an existing Allscripts Enterprise EHR client to attend.
We also offer training courses and reporting services for the Allscripts Enterprise EHR database, ETL database, Analytics and the ConnectR database. Please contact sales@galenhealthcare.com for more information regarding these courses and our report writing services.
EHR Implementation Solutions Store