Free Hospital EMR and EHR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to Hospital EMR and EHR for FREE!

EHR Alerts, Top 10 Health IT Topics, Gesture Based EHR, and Adverse Events

Posted on December 18, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I thought it might be valuable to highlight a few interesting tweets I’ve seen recently. Some of them come from the other Healthcare Scene blogs, but I think you’ll find interesting.


Have alerts helped your organization? Alert fatigue is a very real thing, but when calibrated effectively, I’ve seen them really benefit an organization.


This is a fun list of healthcare topics. Do you see any topics that should be added to the list?


We’ve heard about gesture based EHR many times before. Mostly in the surgery room and mostly as demonstration projects. I don’t think this will really go huge and mainstream in healthcare, but could likely get some pickup for very targeted use cases.


Carl does a really great job in this article talking about Adverse Events and the legislation that’s proposed around EHR adverse events. This is a really important topic that doesn’t get nearly enough attention.

ACOs Stuck In Limbo In Trying To Build HIT Infrastructure

Posted on September 26, 2014 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Though they try to present themselves differently, ACOs are paper tigers. While they may be bound together by the toughest contracts an army of lawyers can devise, they really aren’t integrated in a meaningful way.

After all, the hospitals and medical groups that make up the ACO still have their own leadership, they don’t generally hold assets in common other than funds to support the ACO’s operations, and they’re definitely not in a great position to integrate technically.

So it comes as no surprise that a recent study has found that ACOs are having a hard time with interoperability and rolling out advanced health IT functions.

The study, a joint effort by Premier and the eHealth Initative, surveyed 62 ACOs. It found that 86% had an EMR, 74% had a disease registry, 58% had a clinical decision support system, and 28% had the ability to build a master patient index.

Adding advanced IT functions is prohibitively difficult for many, researchers said. Of the group, 100% said accessing external data was difficult, 95% said it was too costly, 95% cite the lack of interoperability, 90% cite the lack of funding or return on investment and 88% said integration between various EMRs and other sources of data was a barrier to interoperability.

So what you’ve got here is groups of providers who are expected to deliver efficient, coordinated care or risk financial penalties, but don’t have the ability to track patients moving from provider to provider effectively. This is a recipe for disaster for ACOs, which are having trouble controlling risk even without the added problem of out of synch health IT systems.

By the way, if ACOs hope to make things easier by merging with some of the partners, that may not work either. The FTC — the government’s antitrust watchdog — has begun to take a hard look at many hospital and physician mergers. While hospitals say that they are acquiring their peers to meet care coordination goals, the FTC isn’t buying it, arguing that doctors and hospitals can generally achieve the benefits of coordinated care without a full merger.

This leaves ACOs in a very difficult position. If they risk the FTC’s ire by merging with other providers, but can’t achieve interoperability as separate entities, how are they going to meet the goals they are required to meet by health insurers? (I think there’s little doubt, at this point, that truly successful ACOs will have to find a way to integrate health IT systems smoothly.)  It’s an ugly situation that’s only likely to get uglier.

EMR Change Cuts Cardiac Telemetry Use Substantially

Posted on September 25, 2014 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Changing styles of medical practice can be really tough, even if major trade organization sticks its oar in to encourage new behavior from docs.

Such is the situation with cardiac telemetry, which is listed by the American Board of Internal Medicine Foundation as either unnecessary or overused in most cases. But a recent piece of research demonstrated that configuring an EMR to help doctors comply with the guideline can help hospitals lower needless cardiac monitoring substantially.

Often, it takes a very long time to get doctors to embrace new guidelines like these, despite pressure from payers, employers and even peers. (Physicians may turn on a dime and try out a new drug when the right pharmaceutical rep shows up, but that’s another story.) Doctors say they stick to their habits because of patient, institutional or personal preferences, as well as fear of lawsuits.

But according to a recent study appearing in JAMA Internal Medicine, reprogramming its Centricity EMR did the trick for Wilmington, Del.-based Christiana Care Health System.

To curb the use of cardiac telemetry that was unnecessary, Christiana Care removed the standard option for doctors to order cardiac monitoring outside of AHA guidelines, and required them to take an extra step to order this type of test.

Meanwhile, when the cardiac monitoring order did fall within AHA guidelines, Christiana Care added an AHA-recommended time frame for the monitoring. After that time passed, the EMR notified nurses to stop the monitoring or ask physicians if they believed it would be unsafe to stop.

The results were striking. After implementing the changes in the EMR, the health systems average daily not intensive care unit patients with cardiac monitoring fell by 70%. What’s more, Christiana Care’s average daily cost of administering  non-ICU cardiac monitoring held by 70%, from $18,971 to $5,772.

Christiana Care’s health IT presence is already well ahead of many hospitals — it’s reached Stage 6 of the HIMSS EMRAM scale — so it’s not surprising to see it leading the way in shaping physician behavior.

The question now is how the system builds on what it’s learned. Having survived a politically-sensitive transition without creating a revolution in its ranks, I’d argue the time is now to jump in and work on compliance with other clinical guidelines. With pressure mounting to deliver efficient care, it’d be smart to keep the ball rolling.

Can Big Data Do What Vendors Claim?

Posted on December 6, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

There’s no doubt about it — the air is ringing with the sounds of vendors promising big things from big data, from population health to clinical support to management of bundled payments. But can they really offer these blessings?  According to enterprise health IT architect Michael Planchart (known to many as @theEHRGuy), there’s a lot of snake oil sales going on.

In his experience, many of the experts on what he calls Big Bad Data either weren’t in healthcare or have never touched healthcare IT until the big data trend hit the industry. And they’re pitching the big data concept to providers that aren’t ready, he says:

  • Most healthcare providers haven’t been collecting data in a consistent way with a sound data governance model.
  • Most hospitals have paper charts that collect data in unstructured and disorganized ways.
  • Most hospitals — he asserts — have spent millions or even billions of dollars on EMRs but have been unable to implement them properly. (And those that have succeeded have done so in “partial and mediocre ways,” he says.)

Given these obstacles,  where is big data going to come from today? Probably not the right place, he writes:

Well, some geniuses from major software vendors thought they could get this data from the HL7 transactions that had been moving back and forth between systems.  Yes, indeed.  They used some sort of “aggregation” software to extract this data out of HL7 v2.x messages.  What a disaster!  Who in their sane mind would think that transactional near real time data could be used as the source for aggregated data?

As Planchart sees it, institutions need quality, pertinent, relevant and accurate data, not coarsely aggregated data from any of the sources hospitals and providers have. Instead of rushing into big data deals, he suggests that CIOs start collecting discrete, relevant and pertinent data within their EMRs, a move which will pay off over the next several years.

In the mean time, my colleague John Lynn suggests, it’s probably best to focus on “skinny data” – a big challenge in itself given how hard it can be to filter out data “noise” — rather than aggregate a bunch of high volume data from all directions.

EMRs Can Create New Malpractice Problems

Posted on October 9, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

In theory, EMRs have the capacity to improve patient care and avoid medical errors, but they also stand the chance of creating errors of their own, so users shouldn’t expect EMRs to lower their malpractice premiums, according to a story reported in FierceEMR.

In fact, the story suggests, EMRs can create new problems and make it harder to defend against lawsuits arising from some EMR-related problems, including the following, FierceEMR notes:

  • Disabled clinical decision support alerts that, if used, could have caught a problem
  • Auto complete functions that fill in data incorrectly
  • Sharing of passwords, so that physicians look like they’re viewing the chart when they really aren’t or in more than one place at the same time
  • Sloppy documentation, such as data entered incorrectly

What’s more, EMRs create audit trails which make it easier for plaintiff’s attorneys to find errors in care. And on top of that, legal costs for “e-discovery” — the collection of evidence from electronic systems — can raise the expense of a legal battle further, FierceEMR says.

Here’s an example of a situation in which an EMR-based error can create serious legal exposure. In one case lodged against the  University of Pittsburgh Medical Center, a 62-year old man died due to otherwise treatable bleeding in the brain because an intubation failed.

UPMC’s policy is that when a patient is a difficult intubation case, that must be noted directly in the EMR, which then displays a bright yellow banner nothing the problems at the top of the record. However, “difficult intubation” was not noted in his chart.  When his breathing tubes were later removed, he could not continue to breathe on his own. Attempts to re-intubate him failed, and he died.

As if that wasn’t bad enough, the defense alleges that after the patient’s death, a QA official from UPMC accessed the system and retroactively entered data labeling the deceased as a difficult intubaton. When that didn’t create the yellow banner, the defense claims, the official retracted the “diff intub” entry. Unfortunately for him, all of his actions were logged by the system.

The bottom line is that as it becomes apparent that EMRs come with their own set of safety issues, malpractice insurers who once offered premium discounts to those who use EMRs are dropping the idea. EMRs certainly have the potential to offer improved safety in some instances, but human error isn’t going away completely no matter what fixes EMRs offer.

EMRs Can Reduce ED Visits, Hospitalizations For Diabetics

Posted on September 16, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Using EMRs is associated with a drop in ED visits and hospitalizations among diabetics, according to a study covered in iHealthBeat.

The research, which appeared in the Journal of the American Medical Association, involved analyzing all of the 169,711 records for patients enrolled in Kaiser Permanente Northern California’s diabetes registry.

Researchers drew on data collected between 2004 and 2009. During this period, in 2005, KP began to stagger EMR implementations across the region’s 45 outpatient facilities, iHealthBeat reports.

The study found that EMR implementations were associated with the following results, according to iHealthBeat:

  • 10.50% decline in hospitalizations for preventable, ambulatory-care sensitive conditions, or about 7.08 fewer hospitalizations per 1,000 patients annually;
  • 6.14% decline in non-elective hospital admissions, or about 10.92 fewer admissions per 1,000 patients annually;
  • 5.54% decline in ED visits, from an expected 519.12 per 1,000 patients to 490.32 annually; and
  • 5.21% decline in hospital admissions, from an expected 251.6 per 1,000 patients to 238.5 annually

That being said, EMR implementation had no effect in certain areas. The number of physician office visits per year held steady at six; the frequency of times patients saw diabetic exacerbations remained level; and how often patients developed cardiovascular diseases remained the same, iHealthBeat noted.

The researchers concluded that these results represented not only an improvement in diabetes care, but also “the cumulative effect of EHRs across many different pathways and conditions.

This study is one of a growing body of evidence that effective EMR  use can reduce readmissions and improve outcomes.  For example, a recent study appearing in BMJ Quality & Safety recently concluded that EMRs can help reduce hospital readmissions of high-risk heart failure patients.

In that case, researchers used EMR-based software to sort high-risk from low-risk heart failure patients, using 29 clinical, social and behavioral factors within 24 hours of admission for heart failure. Using this tool, researchers were able to cut readmissions rates for the 1,700 adult inpatients study from 26.2 percent to 21.2 percent.

Epic Module Targets Patients For Care Coordination

Posted on May 15, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

At Gundersen Lutheran Health System, executives have put together a program to target the 1 to 2 percent of those most likely to be hospitalized, seen in the emergency department or face other complications. To manage the program, the La Crosse, Wis.-based system is leveraging a feature of their Epic EMR which sifts out the patients most in need of additional care coordination, reports Health Data Management.

Gundersen Lutheran is targeting complex patients with its program, but not just those with medically-complex conditions. They’re also hoping to find patients who, while they might have simpler conditions, live alone or have trouble following sometimes difficult medical care plans.  The system is using the EMR first to identify the patients, then to treat them, according to Health Data Management.

To find patients in need of extra care coordination services, Gundersen is using a “tiered scoring” module built in to the Epic platform which includes one component for medical complexity and another to measure psycho-social issues. When clinicians want to refer a patient to the care coordination program, physicians use the Epic scoring tool to see if  the patient qualifies. Clinicians can also notify the care coordination team using the Epic system, in three clicks or less, noted Beth Smith, R.N., executive director of patient and family-centered care at the health system.

The patients identified by the scoring model as in need of extra care coordination are farmed out to a group of 22 nurses and social workers, whose job it is to monitor the care of these complex patients who are more likely to face adverse events.

The workload the care coordinators face is intense.  Typically, care managers are supervising some 1,700 patients each, who not only stay in touch with patients but also attend office visits and follow through with specialists.  Epic plays a role here too, however.  Care coordinators get a special tab in the Epic EMR which pulls key elements of the patient’s history into a single view,  making it easier to get a sense of the whole patient.  Epic also notifies them via a message in the system if a patient shows up in the ED.

According to Health Data Management, this program has helped stabilize hypertensive and diabetic patients, with just under half showing sustained improvements over a two-year period.

Structuring for the Future of Clinical Decision Support (CDS)

Posted on May 10, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

The following is a guest post by Adam Lokeh, M.D., vice president of clinical development and informatics with Wolters Kluwer Health.

Clinical decision support tools (CDS) play an increasingly critical role in a healthcare organization’s overarching strategy to comply with federal incentive programs and succeed within the quality- and performance-based reimbursement landscape currently unfolding. When effectively aligned with physician documentation practices at the point of care, these tools can have a powerful impact on error reduction, the standardization of evidence-based practices, quality of care and ultimately saving lives.

Research reveals that a combination of advanced CDS technology working in tandem with computerized physician order entry (CPOE) solutions will be needed to successfully navigate the coming healthcare landscape. A number of CDS elements will need to be considered and integrated into existing systems to create this powerful collaboration including evidence-based order sets, alerting systems for medication management, ECA rules (event, condition, action), referential information including guidelines and care plans, smart documentation and surveillance technology to name a few. To fully leverage the advantages of these tools, it’s important to understand the different approaches to data and content and the inherent advantages and disadvantage of each.

Currently, there are two approaches to content when designing point-of-care IT infrastructures—structured and unstructured. While both have the potential to standardize care and improve decision-making, industry preference leans toward greater integration and use of structured content for its ability to lay a foundation of improved accuracy, efficiency and ability to drive clinical decision support and analytics.

Because structured content is tagged or coded data that resides in a fixed field, it can be easily located, identified and understood, simplifying the process of integrating content into existing systems and sharing between disparate systems. In contrast, unstructured content, such as free text, often results in irregularities and ambiguities that make it harder to interpret.

Unstructured data makes it more difficult for health IT systems to recognize shared data, requiring complex and largely manual conversion processes that are prone to errors, resulting in inaccurate data. When inaccurate patient information is then shared between systems, the potential for adverse events or care issues is only compounded.

While the premise of this discussion as it relates to the benefits of structured content would seem clear, it’s not that simple. Physicians want the ability to express themselves freely when documenting, and there is concern within the physician community that the full patient picture could get lost if the narrative is too highly structured. As a practicing physician, I understand the delicate balance that exists between the need for a technological foundation that promotes accurate information sharing and the desire to protect the individual patient story.

The truth is that there can be risk without allowing for flexibility in creation of narrative content.  Poorly-designed interfaces have clearly existed with some structured content frameworks historically—and still do today within some CDS and CPOE applications—that can cause pieces of the patient narrative to get lost. The use of applications lacking in flexible design and without trustworthy content that is thorough and exhaustive in nature has led to poor physician perception and even fear that the technology will marginalize patient care. Ultimately, the end result is poor physician adoption.

That is why it is so critical that vendors work with physicians to identify all essential elements as well as the factors that can hinder adoption.  The solution is new, thoughtful clinician-designed systems that are more intuitive and flexible, allowing some limited unstructured content to help flesh out the narrative.

When CDS technology is developed through this kind of high-level partnership and designed to accommodate the use of structured content where it is needed most, content can be indexed at a granular level, easing the process of mapping within systems.  It also lays a foundation for automated updating of content as industry evidence changes and provides a framework for more robust reporting due to extensive filtering capabilities.

The end result is more accurate and efficient integration of the best industry evidence at the point of care, delivering a framework for decision support that truly impacts care without compromising the patient narrative. It’s this kind of far-reaching potential—currently offered through some of the more advanced CDS and CPOE applications in the industry—that physicians need to witness to truly understand what can be accomplished. Unfortunately, the industry has not done a very good job of educating them to date.

Some are looking to the potential of natural language processing (NLP) to address the needs for mapping in free-text environments through data mining. While this path offers an alternative, it is not as powerful a foundation as structured content for improving decision making at the point of care. In fact, it’s retroactive. If data mining occurs after the patient narrative has already been input, decision support can, by definition, only be offered “after the fact.”

In essence, physician documentation that is completed in a structured-content environment —as opposed to a traditional dictation method—is, in itself, a form of CDS. Because documentation can be structured to guide and remind physicians to document important medical elements, it assures that nothing is overlooked.

Many industry initiatives point to greater incorporation of structured content into the design of IT applications for information exchange. Industry movements and organizations such as Meaningful Use, HL7, the Standards and Interoperability (S&I) Framework Health eDecisions Project and the CDS Consortium are working towards industry standards that will require use of more structured content.

The simple fact is that when data is shared, it has to be recognized across and between systems. Structured content within CDS applications allows data to be mapped to a standardized vocabulary to ensure accuracy.

That said, clinicians prefer free text. Until the industry properly educates physicians regarding the power inherent in structured content, the best approach will be a hybrid that includes avenues for both models. For maximum adoption, IT vendors should consider that critical components will need to be structured to drive CDS, reporting and quality metrics, but allowing for some amount of free text to smooth out the edges for more widespread adoption.

Survey: Confusion Slowing Meaningful Use Compliance

Posted on May 3, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

While Meaningful Use is likely to spur improvements in health IT, confusion over regulations — and the need to pursue other pressing HIT projects — are slowing down MU compliance, according to a new study.

The survey was conducted by Stoltenberg Consulting, which spoke with health IT managers, clinicians, HIT vendors and government agencies that attended this year’s HIMSS event.

Researchers asked which areas in which HIT will achieve the biggest improvements over the next 12 months.  The biggest group (35 percent) named Meaningful Use, while 19 percent said health information exchange, clinical integration and mobile health were due for the most growth.

When asked what might hold them back from meeting Meaningful Use requirements, 29 percent said confusion and/or ambiguity in the regulations were a challenge. Others named competing health IT projects (23 percent) and a lack of key resources such as funding, IT skills, talent and time (17 percent).

The survey also asked respondents what issues were likely to dominate HIT discussions this year.  Respondents favored health information exchange (62 percent), followed closely by mobile health (58 percent) and clinical analytics (54 percent).

As part of the survey, Stoltenberg also asked survey respondents which problems HIT executives would most likely attempt to solve with the help of a specialized IT consulting firm. The responses included ICD-10 (25 percent), Meaningful Use (25 percent), clinical and business intelligence (23 percent), cloud computing (21 percent) and CPOE/clinical systems implementation (20 percent).

Big Data Could Generate $450 Billion For Healthcare System

Posted on April 16, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Here’s some information that should give all of us something to chew on  this week, courtesy of the always-interesting Jane Sarasohn-Kahn at the HealthPopuli blog.  In a recent piece, Sarasohn-Kahn pulls data from McKinsey & Company suggesting that if big data is properly harnessed, it can produce nearly — wait for it — $450 billion in value for the healthcare system.

As always, however, there’s a catch. This value explosion can’t happen, McKinsey says, unless big data is leveraged across five dimensions of care. These dimensions, which McKinsey calls “new value pathways,” offer opportunities for better efficiencies and economies of scale for the health system, HealthPopuli notes.

The five dimensions include:

Right living, in which big data is used to help patients take an  active role in staying healthy, by such mechanisms as daily health reminders and getting patients to seek care early when problems do arise.

Right care, in which big data tools, particularly coordination of data across providers and settings, make sure that patients get the right care at the right time.

*  Right provider, in which data analytics matches patients with the ideal provider for their situation, sometimes to lower-cost providers that can provide appropriate care.

*  Right value, which uses big data analysis to reward providers who produce the best outcomes.

*  Right innovation, a pathway in which big data is mined to promote continuous improvement and productivity in healthcare processes as well as R&D.

Sounds great, doesn’t it?  Well, maybe not so much given what has to change. To travel down these pathways, McKinsey notes, it will take re-aligning several key forces in the healthcare system, including privacy and data security, a shift to  value-based reimbursement, partnerships across industry segments currently found in deep silos (such as payors and providers), and data analysis capabilities current lacking in the health IT workforce. Sigh. And  I was feeling hopeful there for a bit.

As Sarasohn-Kahn notes, one way McKinsey sees to meet some of these goals more quickly would be to promote transparency as a cultural norm. But honestly, the silos we see today exist for important institutional and competitive reasons. If we want key partners in the big data effort to cooperate, it’ll probably take a governmental club to that head. Hey, ONC, are you ready to get rough with those who don’t want to play in the same data sandbox?