7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK
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7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK
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'Dirty' data in EHRs could cause unnecessary expenses

'Dirty' data in EHRs could cause unnecessary expenses | 7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK | Scoop.it

The health IT landscape is changing at a rapid pace, and with this change there is critical work to be done to enhance data integrity and prevent unnecessary expense.

 

With the urgent need for telemedicine some vendors have had to change their course abruptly; some stayed the course but are working faster and harder to get their product to market.

 

Prior to the COVID-19 outbreak, there were physician practices in the middle of implementing new EHR systems.

 

These projects slowed down during the stay at home mandates, and hopefully project managers took that time to rethink implementation strategies and reengineer system configuration for the physicians’ upcoming workflow changes.

 

Researchers and data scientists, while still aggregating clinical data, have been forced to learn how to improve data accuracy and ultimately patient outcomes in a production environment.

 

No matter where you are in the health IT ecosystem during this birth of the new normal, there is one thing that everyone should be doing right now: It is absolutely imperative to clean up registration procedures.

 

Data that is stored in EHR, registration system, and ancillary systems is most likely dirty – and could well have a financial impact on health systems and physician practices.

 

A large group of physicians most likely uses different EHRs and registration systems across the healthcare system.

 

One registration system could have one field for "Street Address" where another could have "Address 1" and "Address 2" for "Street Address." This can cause an inconsistency in the address data and has caused mail to go to the wrong address.

 

Likewise, "Primary Care Physician" should be labeled correctly in the registration system. Data from the doctor table should be verified and adjusted as many times it is incorrect. Even if it is only the suite number that is incorrect, it still will cause snail mail to go to the wrong person.

 

This is where the expense begins:

  • One of the more common HIPAA violations is sending PHI to the wrong patient/address. This includes snail mail, email, and faxing and it can be information regarding a patient sent to the wrong patient address or sending patient information to the wrong physician address, fax number, or email address. While this is considered an accidental HIPAA violation, there is a defined course of action which must be followed or there will be fines. There also could be fines if this violation is repeated. 
  • The second area negatively impacted by the wrong address is patient billing. If the information is sent to the wrong address the out-of-pocket fees will not get paid on time, if at all. The billing companies may fix the error in their system after the payment becomes overdue and goes into collections. Now, the problem is compounded: there is also a patient who is getting calls from collections and they did not receive the bill in the first place. The next time the patient visits the physician it is quite likely that the registration system will send the same bad address data and it will overwrite the billing company changes, causing mail to once again be sent to the wrong address.

 

When working with big data, small inconsistencies in data entry matter.

 

Leaving the task of cleaning up your registration or demographic data to your data scientists or IT staff will be expensive. This is most likely what is happening now prior to and during research projects.

 

The first step to fix this downward spiral of dirty data and financial drain is to take an export from each registration system the practice uses.

 

Each systems export should contain a large list of patients, addresses, and demographic data to expose the most frequent and most disruptive data entry errors.

 

Based on the output, education should be given, and educational materials should be documented and distributed making sure to leave a cheat sheet at each registration desk.

 

The last and most difficult step is monitoring the data after registration to ensure the new procedures are being adopted.

 

If data is intended for improvement activities or research, and if an IT team is available, it may be helpful to have a separate database at the core of the healthcare system or larger practice to take in, electronically scrub, and store a clean copy of data. Just remember: garbage in, garbage out.

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Who Owns The Data In Your EHR ?

Who Owns The Data In Your EHR ? | 7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK | Scoop.it

The concept of healthcare and EHR data ownership carries many implications for patients, providers, and medical practices. While experts agree that EHR vendors do not own the data, this has not prevented vendors from winning court disputes that resulted in serious financial losses for medical providers.

 

These considerations make the discussion of data ownership critical for any physician or medical practice that utilizes electronic health records.

 

Defining Data and Data Ownership

 

Healthcare data comes from a variety of sources. One is the patient themselves, who individually provide data to platforms such as patient portals. Another is the physician or healthcare team in the form of examination findings and clinical observations. Results from laboratory studies or radiology, along with data from other external healthcare providers or practices, also contribute to EHRs.

 

The number of parties who lay claim to healthcare data makes grappling with EHR data ownership even more complicated. Patients, providers, vendors, and the medical practice itself all have aninvestment in healthcare data, and there is often uncertainty over EHR data ownership. Amazingly both of these groups report that 20% simply don’t know who owns the data.

 

Establishing Data Ownership

 

The best method of minimizing disputes over EHR data ownership is prevention. Measures such as establishing data ownership early, defining terms, and enforcing guidelines are critical to minimizing trouble down the road. With EHR vendors, defining conditions of data exportation in the event the practice wishes to end a business relationship is critical.

 

For all parties, the concept of access must also be clearly defined. Terms include practice or provider access to data from the vendor’s servers, as well as patient access to healthcare data via portals or other mechanisms. The most common source of disputes is when a party wishes to leave the relationship; either the practice decides to select a different EHR vendor, or a patient wishes to port their data to a new provider.

 

Vendor Red Flags

 

For a medical practice, establishing terms of EHR data ownership must begin at the time of vendor selection. Identifying warning signs during this process can help providers avoid much larger issues in the future.

 

When choosing an EHR, keep an eye out for red flags such as unstructured data formatting (i.e. PDF instead of CCDA), an inability to meet the National Coordinator for Health Information Technology’s certification requirements,or restrictive contracts thatdemand exorbitant financial charges to port data in the event of a vendor switch.

 

Establishingproductive EHR data ownership for a healthcare organization takes careful planning.

 

The ZH Healthcare HITaaS (Health IT as a Service) architecture is designed with the needs of medical professionals and their patients in mind, meaning, among other things, that you own your data, and have complete administrative control.

 

 

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Healthcare providers to control all clinical content of the patient record #hcsmeufr #esante

Healthcare providers to control all clinical content of the patient record #hcsmeufr #esante | 7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK | Scoop.it

Turn health data into actionable, cost-saving strategies

oday’s healthcare challenges are no mystery. Hospitals and health systems are navigating the transition to value-based care while continuing to rely on traditional fee-for-service reimbursement models. Uncertainty about the future of health care in the United States is making this shift even more complex as organizations seek a path forward that conquers both known (and unknown) challenges ahead.

 

The standard advice heard across the industry is to “leverage data,” but how does a health system do this? Every healthcare delivery network in the country is rich with data, but how can this resource be applied for each of your care settings, clinicians and provider groups, payers and reimbursement models, and shifting populations?

 

Ensuring high quality patient care and outcomes while balancing financial realities in an evolving market requires a robust data analytics solution—one that can handle the breadth and complexity of health care today without an army of data analysts to make it work.


The 3M Performance Matrix Platform is a data analytics and performance management solution that combines 3M Health Information Systems’ decades of coding and risk-adjustment experience with the data processing power of Verily, an Alphabet company. The platform simultaneously analyzes performance in managing populations throughout your network across all visits, episodes of care and disease cohorts to:

 

  • Automatically identify the root causes of quality issues and excess costs to strengthen performance
  • Prioritize system-wide problem areas using advanced intelligent data processing power
    Work with experienced professionals to drive sustainable behavior change and process improvement

With Verily’s big data computing power, the Performance Matrix platform applies 3M’s risk adjustment methodologies and performance measures to all available data. It then mines this enriched data to identify and prioritize key problem areas. Rather than deploying teams of data analysts, the technology does the work for you.

 

Using Verily’s analytics engine and 3M’s real-world, proven methodologies, the platform helps improve performance by focusing on areas and interdependencies of preventable clinical and financial issues that stem from:

  • Under- and over-utilization of services or care settings
  • Avoidable care, such as readmissions and complications
  • Unnecessary costs
  • Post-acute services

 

3M Performance Matrix analyzes aggregated data against dozens of performance measures to identify and describe the most impactful problem areas. This combination of problem prioritization and analysis helps you focus on what can be fixed, and done differently, going forward. 3M Health Information Systems

Hyland Healthcare’s enterprise imaging

Hyland Healthcare’s suite of enterprise imaging solutions allow healthcare providers to control all clinical image content—including images from specialty departments. When integrated with a clinical imaging system or EHR, clinicians and staff can view medical images in the context of the patient record from within those familiar systems.

 

Eliminating departmental imaging silos improves clinical workflows, strengthens security of protected health information (PHI), enhances disaster recovery, and eases the burden of building and supporting multiple clinical imaging interfaces to the EHR. The following are core components of Hyland Healthcare’s enterprise imaging portfolio.

Acuo VNA

The Acuo Vendor Neutral Archive (VNA) provides standards-based enterprise access to medical images regardless of viewing application, offering independence from proprietary archives, and streamlining clinical workflows.

 

The solution leverages technologies to support the management and sharing of medical images across the enterprise and beyond, allowing providers to assemble a comprehensive image-enabled patient record.

 

With on-site, cloud, and hybrid deployment options, Acuo VNA supports business continuity and disaster recovery strategies while providing a platform for clinical content integration, interoperability, and exchange.

NilRead

NilRead, a multi-specialty, zero-footprint enterprise viewer, provides a universal vendor-independent platform for accessing a full range of DICOM and non-DICOM image data. Integrating seamlessly with most EHR, PACS, or VNA, NilRead identifies and ingests images from virtually any departmental archiving solution—whether dermatology JPEGs, data-intensive virtual pathology slides, or radiology DICOM files.

 

This scalable solution is based on a zero footprint, web-based architecture, meaning only a browser is needed to launch the application. There is no software or plug-ins and images never reside on the workstation. NilRead runs on any web-enabled mobile device, tablet, or PC, providing clinicians with constant access to medical images and remarkable tools to enable collaboration across the enterprise.

PACSgear

PACSgear solutions complete the enterprise imaging framework by allowing providers to capture a variety of documents, film, photos, video, and other media and integrate them with any EHR, VNA, or PACS. Hyland Healthcare’s ModLink software uses DICOM Structured Report or HL7 measurement data from ultrasound, DEXA, and CT devices to auto-populate reports in voice recognition systems. Meanwhile, ImageLink worklist solution manages HL7 to DICOM MWL mappings, facilitating Integrating the Healthcare Enterprise (IHE) workflow for interoperability with existing PACS.

PACSgear connectivity offerings:

PACS Scan, PACS Scan Mobile, PACS Scan Film, PACS Scan Web, EHR Gateway, ModLink, Media Writer, Gear View QC, MDR Video – Touch, ScopeCap, DICOM Box, and Image Link.
Hyland Healthcare

Alliance Community Hospital first MEDITECH customer to deploy CommonWell Services

MEDITECH, an Enterprise Health Record (EHR) vendor and Contributor Member of CommonWell Health Alliance, has deployed CommonWell interoperability services at Alliance Community Hospital (ACH). The capabilities will enable ACH, a non-profit hospital serving the residents of Alliance, OH, to exchange patient information seamlessly for improved patient care and quality outcomes.

 

MEDITECH is the first EHR vendor in CommonWell to deploy the Argonaut Project’s FHIR specifications to customers for the purpose of document exchange, providing near real-time access to a participating patient’s data. Embedded directly into the MEDITECH EHR, these CommonWell services include patient enrollment capabilities and C-CDA exchange, opening the door for more comprehensive sharing of discrete segments of data in the future, such as medication and allergy data.

 

Today, more than 9,300 provider sites are Live on CommonWell services across the nation, and more than 30 million individuals are enrolled..

 

Accelerate and improve patient care anytime, anywhere with secure mobile app AlertView

AlertView, the mobile application developed by Novarad Healthcare Enterprise Imaging, was created to accelerate healthcare by notifying physicians via text message that reports and findings are ready for review.

 

AlertView makes healthcare more efficient by eliminating unnecessary delays in the review of imaging reports. The AlertView app instantly sends a text message to referring physicians, radiologists, or cardiologists alerting them that a report is ready for review. No matter where they are, they can review with one click on the text message, and have this instantly shared with other medical care professionals. This type of mobile communication and collaboration improves patient outcomes while minimizing disruptions for primary care physicians and hospital staff.

 

The app’s features include secure login with TouchID, a dynamic patient list to enable quick searches, extensive filtering including modality and time filters, a convenient basic report view along with an in-depth full report view, display of all key images in the study, and enhanced data security through deep linking

NeXus Portal Solutions's curator insight, April 2, 2019 4:19 PM

Health Cost Saving Strategies