The Journey of a thousand miles towards an ACO begins with one step.

Healthcare organizations are coming to realize that the programs stimulated by the ARRA – HITECH Act, Meaningful Use (MU) and Accountable Care Organizations (ACO), require something that they don’t have in sufficient quantities, the desired type or in the right format: “Data”.

In this post we’re going to focus primarily on the ACO analytics side of things although some of the same principles are applicable to Meaningful Use at its various stages.

The Little Data We Do Have

Historically hospitals have focused on managing their data from the financial perspective. They are very good at submitting claims and receiving the reimbursements, or denials, and reconciling these. They are also very good at dealing with myriad payers which each have unique and complex processes and workflows to embrace. Government payers such as Medicare and Medicaid are very different to deal with because of complex rules that each of them has; Medicaid differs from state to state; private payers also have their disparities. Most healthcare organizations have created value based purchasing strategies that have nothing to envy the mammoth retailers. But all this data generated, stored and mined is similar to that of any other industry vertical. It’s business as usual here.

Hospital organizations have been relying on claims data for most of their financial and operational needs.

The current trend in healthcare is far beyond this type of data. Managing a patient’s health requires relevant clinical data. This is the data that is hundredfold more complex than any other industry has to deal with.

Folks that are, for the first time, entering the Healthcare Information Technology (Health IT) domain are a little perplexed and seem to perceive that we are years behind other domains. This is far from the truth. In the other verticals such as the banking, investment, retail or telecommunications ones, most of the data is of financial, logistic and operational nature. In healthcare we have to deal with this type of data as was indicated and with the other types that are not measurable with fingers alone, or an abacus.

Where’s the BIG Data

Laboratory information results are value and range based (e.g., normal, high, low), or binary (e.g., positive, negative), resulting from the chemical analysis and measurement of specimens (e.g., blood, urine, tissue); anatomical pathology results consist of the same in addition to complex interpretation narratives.

Medicines are discrete units that are being dispensed and administered (e.g., Metformin ER 500 mg tablet, Mupirocin Ointment USP, 2%) but also within a time frame, finite or infinite, and at precise intervals. And to add to the complexity; dosages may vary during the episode of care or an encounter in response to the patient’s reactions; allergies have to be taken into account; medicines may be changed; drug-to-drug interactions are evaluated prior to administering; diet has to be tracked and recorded; follow-up procedures or treatments have to be accounted for.

Imaging results from radiology contain images, discrete data, metadata and non-discrete narratives combined and packaged as a study. The non-discrete narrative is contained in report that is created by the radiologist while “reading” the images and recording into a transcription device or software which is converted from voice to text. A study can contain 1 or hundreds of images; a simple chest x-ray may contain 1-4 images (e.g., Posterior-Anterior (PA), Anterior-Posterior (AP), lateral (LAT)); a CT study may contain as many as 500 images each representing a slice.

We have complex coding systems: ICD-9 (currently migrating to ICD-10) for the classification of diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases; LOINC for the classification of laboratory and clinical observations; SNOMED as an organized categorization of clinical terms, codes, synonyms and definitions of diseases, diagnosis and procedures; RxNorm provides normalized names for clinical drugs and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software; etc.

Hospitals also have their own reference coding systems that have evolved throughout the years.

When a patient arrives at a provider facility and the clinicians begin with the anamnesis, many events, manual or automated, may start occurring: insurance or Medicare/Medicaid eligibility is verified; laboratory, radiology and pharmacy orders are entered; laboratory and radiology results are generated; medications are ordered, dispensed and administered, sometimes with CPOE and sometimes not; scheduling is processed and resource availability is verified; registration, admission and transfer events are triggered; billing details are validated and recorded. Behind the scenes there are disparate systems “talking” to each other in several healthcare lingos: HL7, X12 and DICOM. Hundreds or thousands of messages containing data are going from here to there and vice-versa. All these messages are sending data that is being consumed by other systems or even other external organizations.

Then, if there is so much data why is there little data?

The answer is simple: an enormous amount of data or information generated that spans from the beginning of a patient’s anamnesis, through the evolution of the episode of care and until the end of the catamnesis, is not being collected, and if it is being collected then it’s being recorded in a format that is inadequate, difficult or impossible to mine (or extract).

But didn’t we just say in one of the above paragraphs that hundreds or thousands of messages containing data are being exchanged during an encounter?

The answer is yes, but the data that is being collected is only the tip of the iceberg of what is required for many of the use cases being envisioned and which are required to manage the population’s health that belong to an ACO.

For example, from the anamnesis the clinician obtains the chief complaint and tons more of information provided entirely by the patient that may have motivated the visit or encounter. The majority of the information being provided by the patient is subject to the interpretation of the physician or the nurse. Have you ever gone to two different doctors with the same ailment and received the same interpretation? I haven’t.

The physician and nursing notes are not being transcribed into the Electronic Health Record (EHR) of the patient mostly because many providers don’t have an Electronic Medical Record (EMR) system. Maybe the provider has an EMR but the EMR doesn’t capture the information in a discrete way. These documents might be scanned and stored in an image format.

You’ve mentioned it a few times, what in the world is an anamnesis? Good question, the anamnesis is the combination of the verbal narration and written information the patient provides initially during the first encounters and it may continue throughout the entire episode of care; and since the care of a patient can depend on other people than him/herself abundant data or information may come from a heteroanamnesis, that is where relatives or caregivers narrate and provide written information about chief complaint, family history, present illness, etc.

Thinking from the End

An ACO requires the following capabilities among many others:

• Population Health Management (PHM)
• Chronic Disease Management (CDM)
• Disease Registries
• Health Information Exchanges

These capabilities require tons of data or BIG data that should be collected by clinicians and other trained healthcare professionals and not by mere source systems communicating messages between themselves.

Most of the healthcare organizations have a very difficult time knowing what the Average Length of Stay (ALOS) isf for their patients at each one of their facilities. Needless to say they believe that a re-admissions management system is something required to operate effectively. Do you have to manage re-admissions or do you just have to count them? You don’t manage re-admissions you avoid them!

How much data do you need to obtain results for these two trivial indicators? All you need is the patient identifying information and the admission and discharge dates for each episode of care. Of course, you could also get fancier and try to obtain the ALOS that corresponds to a particular physician or department. But still, this data is easily obtainable.

On the other hand the capabilities listed above require data that is not easily obtainable since many times it’s not even collected. In order to succeed you would have to determine what data elements would be required for each of the capabilities and then try to map these to the origins or source systems. Not too long ago I performed a mapping for Coronary Artery Disease (CAD) and it was a daunting task. My team and myself had discovered that 80% of the data elements had to be manually abstracted since they were contained almost entirely in scanned notes or even paper notes that had never been scanned.

Yet, thinking from the end and mapping to the source will help you discover the gaps in data that is required for each use case.

The Heterogeneous Curse

Most healthcare organizations choose the “Best of Breed” model for their various systems. What this means is that each application has its own database and typically they don’t share information among each other.

Even those healthcare organizations that have chosen a single vendor for most of their needs face a similar dilemma in that the vendors generally grow their offerings by acquisition of other smaller software companies. The end result is that although the systems are under one vendor’s umbrella they generally implement different technologies and interoperability among them is as challenging as in the “Best of Breed” model.

HL7 messaging, as explained above, has been able to get most of these applications to “talk” to each other. “Talking” alone doesn’t solve the problem of “actionable” data. “Actionable” data is a requirement for many of an ACO’s requirements.

The BIG Challenge Ahead

Getting to “actionable” data is key to overcoming the heterogeneous curse. This is the BIG challenge ahead.

Taking on this challenge one step at a time can help overcome the paralysis.

The most crucial step is creating an Operational Data Store (ODS) and an Atomic Data Store (ADS) from all the available historic data, whether archived or extracted from the source systems databases. Those organizations that have taken this step have been the ones that succeeded with Business Intelligence (BI), Clinical Intelligence (CI) and near real-time use cases.

The ODS/ADS combo will help aggregate the patients data. They will also be the precursors for the Extract, Transform and Load (ETL) layer.

Unfortunately, most hospitals treat the messages that are exchanged by the myriad of systems in a “consume and discard” fashion. Most of the messages navigate through the healthcare system going through a broker or interface engine. These messages get transformed or mapped and are pushed to the consuming systems which ingest the information they need. The messages may stay in the interface engine’s data store for a short period of time; typically between 15 to 30 days before they are deleted.

The next step is fomenting a cultural shift of the clinical staff. Clinicians have been reluctant to be data clerks and many have valid reasons. Fomenting the cultural shift is not changing mindsets of the clinicians. Enabling them with novel technologies to capture a patient’s health status at all critical points of the workflows will be the real game changer. Mobile technology, natural language processing (NLP) and voice recognition should become ubiquitous in the healthcare settings.

Leverage the CCD and other CDA based documents at each point of transfer of care. This requirement alone will be the major force to put in place all the necessary gear to get to an interoperable state.

Indirect requirements will start popping up: data governance will be mandatory, and so will coming up with well-defined terminologies and coding systems. Don’t let these dissuade you since they are all good.

Conclusion

To succeed in the future healthcare paradigm you must start immediately. Take one step at a time, have a BIG strategic picture of the future but act tactically now. You will get there, eventually.

CCD is an acronym that stands for “Continuity of Care Document”. The CCD is a file that uses Extensible Markup Language (XML) format, which could have one of 3 different structure levels. I will explain the various structure levels in Part III of this blog series. A CCD contains patient related information that could be electronically exchanged between healthcare providers, as well as, shared with the patients themselves.

The CCD template, derived from the American Society for Testing and Materials (ASTM) Continuity of Care Record template or ASTM E2369-05 Standard Specification, or simply stated the CCR. The CCD is constrained by the HL7 (Health Level Seven) Clinical Document Architecture (CDA). The CDA adheres to the HL7 V3.0 Reference Information Model or RIM.

The ASTM CCR was created to provide a snapshot in time that contains a summary of relevant and pertinent encounters information (e.g., demographic, clinical, financial) of a patient.

Health Level Seven International partnered with ASTM to create an HL7 version of the CCR for institutions that preferred using the CDA model, hence the birth of the CCD. The CCD maps the CCR elements into the CDA structure.

The CCD is a template based on the principles of the HL7 CDA. The characteristics of a clinical document based on the CDA are the following:

• Persistent
• Authenticable
• Human readable
• Self-context
• Thorough and complete
• Stewarding

Although one of the characteristics of a CCD is to be human-readable this does not mean that there isn’t a tool involved for the readability. A CCD could be rendered with a simple web browser in order to comply with the human-readability qualification.

The CCD is structured as a CDA document. For those of you familiar with XML documents the following line-by-line depiction will be easily understood:

• Document
  • Header
    • Body
      • Sections
        • Optional narrative block
          • Entries

A CCD includes the following 16 sections:

1. Family history
2. Social history
3. Functional status
4. Allergies
5. Immunizations
6. Medications
7. Vital signs
8. Medical equipment
9. Support
10. Encounters
11. Problems
12. Procedures
13. Results
14. Plan of care
15. Payers
16. Advance directives

Many Electronic Health Record (EHR) vendors are starting to implement the CCD to share patient information across Health Information Exchanges(HIEs), outpatient centers and other clinical providers.

The CCD is not alone. There are many other CDA based templates:

• Discharge summaries,
• History and Physical (H&P)
• Procedure Note
• Progress Note
• Operative Note
• Consultation Note
• Diagnostic Imaging Report

In the next Part II of this series we will explore a “real-world” example of a CCD.

In the first post of this 2 part blog we explored the big challenges with the demands that the ARRA HITECH and other compliance and regulatory impositions have impacted Healthcare IT: HIPAA’s Version 5010 conversion, ICD-10 migrations, Meaningful Use of EHRs and their Attestation and Accountable Care Organizations. We also briefly touched the popular topic of the imminent end of the world in 2012 according to the Mayan calendar prediction.

If you read carefully you would have noticed that my predictions, well, they have some small glitches now and then, or you may call them “bugs” due to my software developer background. So at the end of this blog we’ll have to revisit the end of the world prediction. Sorry folks.

The ICD-10 deadline, as of last week, was announced by the HHS Secretary Kathleen G. Sebelius the intent to delay the compliance date. Hopefully the delay will not be such that it has a big impact on healthcare interoperability projects. ICD-10 would help the way healthcare data is stored and exchanged between systems. One of the drawbacks of ICD-9 is that since it lacked codes to describe many diagnosis or procedures clinicians and related clerical staff would use the code that closely matched the reimbursement amount expected. Pro-active healthcare organizations should move forward with their ICD-10 conversion projects since it solves many inherent problems contained in their data that hinders interoperability in a meaningful way.

Data Aggregation and Mining for Successful Quality Measurement Reporting and Performance Improvement Requirements

Going back to the topics we left off in our previous post, I would like to dive a little into data aggregation. Healthcare data is contained in many source systems inside a hospital organization and more frequently it can be found outside of the organization. I have been in several projects where I’ve had to aggregate data located in 3 different states in the US!

If your organization plans to successfully meet Meaningful Use stages 1, 2 and 3 then getting control of your data is of paramount importance. Meaningful Use stage 1 may appear to be trivial to many organizations but don’t let this mislead you as to the growing complexities of stages 2 and 3. Albeit we don’t know the details of the requirements for stage 2, which are to be announced shortly, what we do know is that they will require more data from the different source systems.

Health BI, as an aggregation platform, can receive healthcare data from myriad sources; whether it’s from the inpatient Health Information System (HIS) , the outpatient Electronic Medical Record (EMR) or the Laboratory Information System (LIS) it can all come together in a single repository from which up to 600 Clinical Quality Measures can be reported! Health BI is modeled after the HL7 v3.0 RIM.

Health BI can accept data in various formats: HL7 v2.x, text files, ftp, HL7 v3.0 CDA documents (e.g., CCD) and HITSP C32 among others. Our approach is to create accelerators or connectors to the most common Healthcare Source Systems in the domain.

For more information on how Perficient’s health BI (Business Intelligence) solution can assist you with your 44 Eligible Professional (EP) or 15 Eligible Hospital (EH), depending on your particular case, of the Meaningful Use (MU) Clinical Quality Measures (CQM) – refer to the Meaningful Use Measure sheets for Eligible Professionals or Eligible Hospitals.

CPOE Implementations

Meaningful Use requires a scalable approach to the implementation of a Computerized Physician Order Entry system or as it is known by its acronym ‘CPOE’. For MU stage 1 it is required that more than 30 percent of all unique patients with at least one medication in their medication list being treated by the Eligible Professional have at least one medication order entered using CPOE. There is an exclusion for an EP that writes less than 100 prescriptions during the EHR reporting period. For Meaningful Use stages 2 and 3 it will be required that 60% and 80% of all unique patients, respectively, under the same criteria as stage 1, have at least one medication order entered using CPOE. The stage one bar is low in order to get the eligible professionals started but as the bar raises more automation and interoperability should be put in place by using certified electronic health record products.

CDA and the CCD template based document generation

The Continuity of Care Document, or CCD, is a CDA based constrained template derived from ASTM’s Continuity of Care Record. The Clinical Document Architecture, or CDA, is based on the HL7 RIM.

Exchanging healthcare information has been one of the main premises of implementing certified Electronic Health Records for Meaningful Use.

The CCD was designed to provide a human readable and electronically consumable document that contained a snapshot of the relevant healthcare information of a patient after an encounter with a healthcare professional or provider.

It is estimated that many organizations will start exchanging CCDs or CCRs to meet Meaningful Use criteria during stages 2 and 3. It is probable that your organization would have to embark on a project revolving around a CCD.

Health BI is capable of ingesting and aggregating data from myriad source systems in order to produce a CCD document that can be exchanged with other source systems or HIEs.

To learn more about the HL7 CCD you can visit this wiki: http://wiki.hl7.org/index.php?title=Product_CCD (Note: Some sections may require membership privileges.)

Natural Language Processing (NLP)

In every project of aggregating data to be leveraged for various use cases the valuable and relevant clinical data is hidden in transcriptions, nursing notes, scanned forms and documents and many other non-structured formats.

This is what has been the major blocker in true interoperability in healthcare. Over and over again I witness IT professionals from other domains enter the healthcare vertical believing that they have the silver bullet for interoperability but they all end up dismayed and disheartened when they run into the reality.

NLP is a promising Artificial Intelligence technology that will ease some of the pains of abstracting this hidden data. Today, most of this data has to be manually abstracted which takes its toll on specialized resources and time.

IBM is investing a lot of money and energy into Watson. Microsoft Research is also working on NLP applied to healthcare.

If you are in a larger healthcare organization, expect to be encountering this technology soon. It’s probably the only way to overcome interoperability hurdles that will be encountered while trying to meet many meaningful use criteria.

You can learn more about IBM’s Watson technology here: http://www-03.ibm.com/innovation/us/watson/

Private Health Information (PHI) in the Cloud

The cloud is here to stay and exchanging information nationwide has to be able to traverse artificial barriers that IT departments have created in their healthcare organizations. These barriers to protect PHI were put in place much before technology that is extremely secure had matured.

Many organizations, like Amazon, already provide cloud-based spaces that can protect PHI data even better than most healthcare organizations can!

Expect to be involved in many cross-organizational projects where healthcare data has to be sent to and received from the cloud. Learn the new security and privacy protocols that cloud technology is creating or improving.

Internal demand for emerging technologies

Tablets and smartphones have become ubiquitous in the healthcare realm. Physicians have really been eager adopters of this new technology. I’ve been in a few projects where the biggest scope creep requirement has been to make tablets browsers compatible with the Internet or Intranet solution being deployed enterprise wide in the healthcare organization.

The pressure for providing support to mobile technology will grow and especially from the point of care use cases and workflows. Mobile technology in healthcare is probably the hottest theme after MU and ACOs.

This endeavor entails a lot of coordination between the vendors and the IT security department. Little portable devices are prone to get lost a lot easier than bigger laptops or stationed devices.

The Mayan prediction of the end of the world

I’m just hoping that NASA won’t change their mind like CMS HHS did with regard to the intent to delay the implementation of ICD-10. But just in case I’ll provide once again their doomsday link in this second part of the blog to see if we have to embark on a project to sail away from planet Earth before 2012 ends.

What do you think are the biggest challenges in Health IT?

Background

Healthcare providers and eligible primary physician practices are undergoing analysis paralysis because of all the government impositions on improving healthcare with the following list of complex problems to solve: HIPAA’s Version 5010 conversion, ICD-10 migrations, Meaningful Use (MU) of EHRs and Attestation , Accountable Care Organizations (ACOs) , Data Aggregation and mining for successful Quality Measurement Reporting and Performance Improvement Requirements, CPOE implementations, CDA and the CCD template based document generation for sharing patient information between health providers, Natural Language Processing (NLP), Private Health Information (PHI) in the Cloud, internal demand for emerging technologies, the Mayan prediction of the end of the world, Et cetera, Et cetera, Et cetera.

The list above is not a bloated aggregation of current buzz-words, terms, solutions and a potential world event, but actually projects (challenges) that most healthcare providers, large and small, have had to embark on or are getting ready to do so beginning the first quarter of this year; yes indeed, that is NOW!

The aforementioned list isn’t exhaustive either, because there are other very specialized areas that the ARRA/HITECH and the Affordable Care Act have intentionally or unintentionally triggered off as well. We will leave a discussion of this topic to another blog in the near future.

Those organizations that have been proactive and early starters or pioneers have a clear advantage over the others but yet they’ll still face their own challenges and probably very similar to the late bloomers.

Any of these challenges (which are also projects by nature) involve not only unique but also many common complexities such as:

Format: Challenge ^{Level of Effort (1 = Least – 5 = Most)}

• Stakeholder alignment ²
• Project Management ² (communication, charter, schedule, resources, Et cetera)
• Multiple vendor selection ⁴
• Heterogeneous vendor alignment ⁵
• Multiple potential software system and hardware upgrades ⁴
• Reliance on Subject Matter Experts (SMEs) ⁴
• Managing Disruptive Emerging technologies (e.g., mobile apps, tablets) ³
• Workflow and process re-engineering ⁴
• Compliance with HIPAA and possibly the FDA ³
• Individual State laws regarding patient privacy that go beyond HIPAA requirements and constraints ³
• Testing, Verification and Validation ³
• Documentation ²
• Training ²
• Et cetera^?

Average LOE Result: If we average the weights of the various LOEs (excluding Et cetera) the result is 3.15. An average LOE of 3.15 can bring some unexpected surprises during the execution of a project.

Version 5010

For those HIPAA covered entities that were unable to meet the January 1st, 2012, deadline for the ASC X12 Version 5010 conversion their focus on other projects may be substantially distracted until March 31st, 2012 which will be the trigger date for compliance enforcement by the Centers for Medicare & Medicaid Services’ (CMS) Office of E-Health Standards and Services (OESS). Only 90 days were allotted for the Enforcement Discretion period; that is the three month grace period after which the CMS will start penalizing those that are lagging.

The covered providers must use Version 5010 when conducting electronic transactions including but not limiting to: eligibility queries, claims and claims queries, referral queries and other transactions.

Some common Version 5010 message transactions are: 270/271 for eligibility requests/eligibility responses, 278 for healthcare services and 837 for healthcare claims.

For further information regarding ASC X12 Version 5010 please visit the following links:

http://www.cms.gov/Versions5010andD0/

http://www.x12.org/x12org/subcommittees/x12n/n0221_wedi-x12-v5010_file.pdf

ICD-10

The Meaningful Use and Healthcare Reform evolution had somewhat eclipsed ICD-10 conversions during 2010 and 2011. Many US providers decided to drag their feet with the ICD-9 to ICD-10 conversion projects using many excuses around the complexity and lack of benefits it brought, which were then highly mitigated by the successful transitions experienced by European countries, Australia, New Zealand and others.

The ICD-10 conversion timeline and the October 1^st, 2013, firm deadline seems to be generous at first, but don’t let it mislead you and not only because the end of the world may occur first! Changing a coding system will potentially impact almost every one of your source systems database schemas, stored procedures, views, Et cetera. If you use the coding system in your HL7 or transactional messages there may be some significant modifications required here as well. There are two sets of ICD codes; the ICD-10-CM for diagnosis coding and the ICD-10-PCS for inpatient procedure coding. Almost all types of healthcare providers will have to convert from ICD-9-CM to ICD-10-CM with the introduction of 2 additional digits in the coding system in a subset of cases. The ICD-9-PCS to ICD-10-PCS, which only applies to inpatient settings, will introduce 3 additional digits to a subset of the coding system. Even though it’s for some cases a good designer will account for all possibilities. Also, ICD-9 being decades old has the typical implementation inconsistencies of older technologies, standards and vocabularies which should be fixed before the transition is rolled out to production. If you have custom mappings and other software artifacts of components that are designed around the older coding system than these may have to be refactored as well.

Something to be aware of is that October 1^st, 2013, is a firm deadline and there are no plans for an extension.

For further reading of how Perficient Healthcare can assist your organization with your HIPAA ASC X12 Version 5010 and/or ICD-10 Conversion projects please refer to the following links:

Regulatory Compliance in Healthcare

http://www.healthcare.perficient.com/RegulatoryCompliance.aspx,

Solution Insights:

http://www.healthcare.perficient.com/docs/4010ICD10/SolutionSheets/4010-5010_Solution_Sheet.pdf,

http://www.healthcare.perficient.com/docs/4010ICD10/SolutionSheets/ss_ICD_10.pdf,

Case Studies:

http://www.healthcare.perficient.com/docs/systeminteroperability/CaseStudies/BISOA_BCBS_mass.pdf

http://www.healthcare.perficient.com/docs/systeminteroperability/CaseStudies/TuftsICD10.pdf

Videos:

https://blogs.perficient.com/2011/05/17/bcbs-massachusetts-hipaa-5010-and-next-generation-capabilities/

Meaningful Use (MU) of Electronic Health Records (EHRs) – Stage 1 and its Attestation

According to information published by Robert Anthony, Health Insurance Specialist of the CMS Office of e-Health Standards and Services, almost $2 Billion had been paid out during the year 2011 for those who have been able to successfully complete the MU Stage 1 attestation of their Electronic Health Record (EHR). Payments to date, January 2012, have also been quite onerous.

Proactive organizations, anticipating the challenges of Version 5010 and ICD-10, worked steadily on EHR Meaningful Use attestation during 2011. During 2012 they have more bandwidth to focus on the upcoming stage 2 requirements.

If your practice or organization hasn’t received your share of the big carrot, well then, you simply fall in the late bloomer’s category.

In order to receive the Medicare and/or Medicaid incentives you must perform the three following steps:

• Successfully register for the Medicare EHR Incentive Program;
• Meet meaningful use criteria using certified EHR technology; and
• Successfully attest, using CMS’ Web-based system, that you have met meaningful use criteria using certified EHR technology.

For further information regarding EHR MU attestation please follow the following link: https://www.cms.gov/EHRIncentivePrograms/32_Attestation.asp

If you are a typical provider, whether a hospital or an ambulatory entity, you rely mostly on vendors to get the job done and this is the BIG CHALLENGE. Health IT vendors are currently stretched and their growth rate is limited by the low availability of qualified or expert Health IT folks and Subject Matter Experts (SMEs).

Even though the MU Stage 1 bar was set quite low it can still be a huge endeavor for most physician practices and to a lesser degree to a hospital setting organization. Choosing the right vendor, customizing the EHR, testing, implementing to a successful go-live, training staff and finally obtaining attestation require expert project management skills, technical skills, and several Subject Matter Experts (SMEs).

For more information on how Perficient’s health BI (Business Intelligence) solution can assist you with your 44 Eligible Professional (EP) or 15 Eligible Hospital (EH), depending on your particular case, of the Meaningful Use (MU) Clinical Quality Measures (CQM) – refer to the Meaningful Use Measure sheets for Eligible Professionals or Eligible Hospitals.

This video, presented by Martin Sizemore of Perficient, a Microsoft Gold Certified Partner, discusses how to successfully create a meaningful solution in your EMR environment–a solution built on the Microsoft BI stack, including SQL Server and SharePoint.

For more information regarding CMS Meaningful Use, please visit the following page https://www.cms.gov/EHRIncentivePrograms/30_Meaningful_Use.asp.

Accountable Care Organizations (ACOs)

Although in its pioneer stage ACOs will gather quite some traction this year. The ACO final rule was highly applauded by the medical community by the end of 2011.

Many organizations that have embraced this model (e.g., Partners Healthcare) albeit under different names and slightly different approaches are among the 32 pioneers selected by CMS. For a detailed list of the Pioneers please follow this link: http://innovations.cms.gov/documents/pdf/PioneerACO-Generall_Fact_SheetFINAL_12_19_11.pdf

An ACO will be required to report on 33 Clinical Quality Measures in order to be able to measure their performance. The 33 CQMs are classified by domains:

• Patient/Caregiver Experience (e.g., timely care, appointments, communication)
• Care Coordination / Patient Safety (e.g., readmissions, medication reconciliation)
• Preventive Health (e.g., tobacco use, cancer screening)
• At Risk Population (e.g., diabetes, IVD, CAD)

For more information of the 33 ACO quality measures please refer to the following fact sheet: https://www.cms.gov/MLNProducts/downloads/ACO_Quality_Factsheet_ICN907407.pdf

Learn how Perficient Healthcare can IT-Enable your ACO by following this link.

In Regards to the End of the World

As for the rumor going around about the end of the world according to the end of the Mayan calendar or planet Nibiru colliding against Earth, I prefer to ask the experts opinion: http://www.nasa.gov/topics/earth/features/2012.html.

So please don’t let 2012 pass by without you getting expert advice for all of your EHR, meaningful use, attestation or Accountable Care Organization IT needs, because if not, what can be assured is that the late-bloomers will be paying hefty penalties to good ol’ Uncle Sam.

Part 2 of 2 Preliminary

In the next part of this blog we will be presenting valuable information and tips regarding the following topics: Data Aggregation and mining for successful Quality Measurement Reporting and Performance Improvement Requirements, CPOE implementations, CDA and the CCD template based document generation for sharing patient information between health providers, Natural Language Processing (NLP), Private Health Information (PHI) in the Cloud, internal demand for emerging technologies.

Thanks for reading!