Accountable Care Analytics: A data-driven approach to achieving value-based healthcare

Edgewater’s Accountable Care Analytics application is comprehensive set of data integration and business intelligence capabilities for use by clinical, financial, and care management professionals that empower organizations to improve quality and reduce costs across a spectrum of care delivery settings.  The application streamlines many of the labor-intensive aspects of capturing and reporting quality and financial performance of accountable care, alternative quality contract, and similar risk-based arrangements operating in healthcare today.  It achieves this by enabling healthcare providers to take a data-driven approach to understanding the impact of quality, cost and outcomes on performance across the extended ACO enterprise.

In this podcast, Edgewater provides a high level overview of the Accountable Care Analytics application.

The Struggle to Define Quality Measures: Do You Have the Right People with the Right Skill Set Supporting This Effort?

Standardizing the definition of quality measures is hard enough when you have the right people. Unfortunately, it is too often the case that hospitals are not armed with the right people and skills sets to address this costly, complicated issue.

Over the past 2 years, we’ve heard a lot about the shortage of primary care physicians in this country, mostly due to the public debate about how to reform healthcare. What we haven’t heard nearly enough about is the even larger shortage of clinical analysts and informaticists. I would argue that right now, hospitals and healthcare organizations need this skill set more than almost anything else. Go to any large hospitals’ website and I’d be willing to bet there is a job posting related to these roles. Here’s why.

How many times has your healthcare IT or data related projects failed because of these two reasons (that I hear almost once a week)?

  • [IT Perspective] – “the users can’t tell us how they want to use the system, how they want to see the data, what they need out of their clinical applications…they don’t know how to ask the right questions!”
  • [Clinical Perspective] – “our people in IT don’t know the clinical world at all. Things aren’t as cut and dry as they try and make it. It’s not 0 or 1, or Yes or No – it’s more complicated than that. I wish they could just live a day in my life and see how I operate, things would be so much easier!”

And there you have it. The conundrum that almost every hospital deals with – an inefficient, ineffective relationship between their clinical users and supporting IT department/clinical decision support (CDS). I wrote previously about the difficulties IT Projects at hospitals face when the clinical and technical stakeholders don’t even know each other. “Dr. meet IT; IT meet Dr.” What I haven’t touched on, though, is the importance of what I like to call the “translators” that every hospital needs. These folks are the Clinical Systems Analysts, Clinical Decision Support Analysts, and Healthcare Informaticists who have a clinical education and real world experience with workflows and processes, but also have a strong understanding of information technology, clinical applications, and most importantly, the data. These resources are invaluable to institutions that finally understand this fundamental principle: the fastest, easiest way to improving patient outcomes and reducing the cost of delivering care is understanding ways to identify best practices and underperformers within your organization through the use of advanced analytics. How do you do that? You have someone who understands the data and can help directors and managers or clinical units/care settings understand where there are opportunities for improvement. It is essential these people “talk the clinical talk” when discussing data trends with nurses and clinicians; and “talk the IT talk” when relaying requirements and system improvements to the IT and CDS teams.

Without resources who can “straddle the fence” that sits between clinical users and CDS staff members, you’ll continue to have a disconnect between the people collecting the data and those trying to understand and report it. It’s time to find people who can play in both worlds. It’s not rocket science…even if calculating CMS Core Measures is.

Service Line Evolution: From Definition to Growth and Everything In Between

Are you a healthcare provider that is currently considering organizing your clinical service offerings around formally structured service lines? Have you already attempted to implement service lines in one area and come across some unforeseen difficulties, turf wars, and clinician pushback? Have you established a service line structure across your enterprise and are wondering how to grow particular lines to increase profitability or lower costs? These scenarios depict the various states of maturity that healthcare providers find themselves in as they struggle to define, implement, build, measure, plan/forecast and grow service lines. Regardless of where you sit in this Maturity Model, there are obstacles impeding your progress and growth.

There is no easy way to implement service lines. There are too many egos involved, too many possible hurt feelings, and not enough resources to go around. Why? Because when it comes down to it, you will be favoring one set of surgeons, or doctors, or nurses in a department and therefore giving them more attention, time, money, and other limited resources. And you’re doing this because you’ve determined that partnering with certain specialties or surgical teams or departments will reap greater financial reward, improve clinical outcomes and position your organization for greater potential growth. Hospitals are finally starting to realize that running healthcare like a business makes good cents. And aligning your organization around a defined set of service lines is exactly like maintaining a diversified portfolio of investments – some investments will be more profitable than others; some will have higher risk; some will receive greater scrutiny and public attention; and some will undoubtedly loose you money.  Regardless of the way you chose to do it, though, service lines are a great strategy for healthcare organizations to focus on what they’re best at, align their clinical services with that of their target markets, realize the best return on their marketing dollars, and position their institutions for the greatest possible growth both financially and clinically. In these tough economic times with rising healthcare costs and dwindling reimbursements, along with looming regulatory changes mandating bundled payments, service lines offer a framework for providers to align their clinical, financial, and operational objectives with dynamic markets and an aging population.

Over the past two years we have worked with institutions across the country, ranging from academic medical centers to integrated delivery networks, comprehensive cancer centers and multi-hospital organizations helping them progress along the Service Line Maturity Model. Similar obstacles continue to pop up including clinician buy-in and investments, incentives for progress and adaptation, cultural change management, and how to overcome the inherent data management challenges associated with defining, monitoring and measuring success and growth. In addition, there continue to be more technical challenges like, “how do I allocate individual patient visits to each service line?” We helped create business logic with hierarchies that include data points like DRG (and MS-DRG), ICD-9 diagnosis codes, discharge service, and others that help clearly define which patients go where. We’ve established goals for key performance indicators like Net Patient Revenue (NPR), Units of Service (UOS)/Rates, and patient/payer mix. In addition, there are frequently discussions about employee planning and how to determine where critical skill set deficiencies exists in the next 2, 5, and 10 years as the clinical workforce ages and retires. If it’s at the enterprise level dealing with strategic goals, or the department level dealing with tactical goals, a successful service line model requires a comprehensive, integrated, and coordinated mission from all levels of an organization. The worst thing you can do is try and go at this alone or in a silo, you’ll only soon find out not everyone agrees this is the best path forward…especially if you’re stepping on their turf.

Analyzing Clinical Documentation Requires Discrete Data

How many of your patients’ paper medical charts look something like this?  How many similar piles are on the front desk of the OR? The PACU managers office? The scheduling department? Your office?

I know it’s not pretty, it’s legible…barely, it’s written free hand, it’s clunky, it’s outdated, it’s like hearing your favorite song on an 8-track or cassette tape, it’s simply a thing of the past. Oh, and it takes a lot of time which means it costs a lot of money.

Doctors spend a lot of time and money going to school to become experts on the human body – that’s who I want taking care of me. Unfortunately, they are burdened by a system that requires they write specific phrases, terms, and codes just to get paid essentially becoming experts in understanding a set of reimbursement business rules – that’s not who I want taking care of me. Healthcare is an industry that’s core infrastructure, its backbone of information centered on diagnosis, procedure, and other treatment and care delivery codes, is broken. Why? Because all of that information is currently written down – not electronic!

I’m prepared to help fix a broken system. I have personally seen over 100 different ways for a physician to write down their observation after a routine visit with a patient. This includes the phrasing of the words, penmanship/legibility, abbreviations (only officially “accepted” abbreviations though), and interpretation.  The same thing goes for an appendectomy, blood work, an MRI, and an annual physical. This is unacceptable. The important information that a physician records must be entered as discrete data elements directly into a computer. This means that each piece of data has its own field – sorry circulating nurses who love free-text “case notes” sections at the end of surgery – and the time of free text and narrative documentation is over. Do you know how much time and money can be saved by avoiding the endless paper chasing and manual chart abstraction? Me either, but I know it’s a lot!

How do you fix it? I’m not going to lie and tell you it’s easy. Governance helps. You can guarantee that surgeons, anesthesiologists, hospitalists, specialists and the rest will all have their needs and comforts…and opinions. “If you want to perform surgery at this facility you need to document your information discretely, electronically, consistently and in a timely fashion.” Physicians are used to writing stuff down, its familiar, its comfortable, it’s home cooking. In order to change that comfortable behavior you must emphasize the benefits:  they will spend less time documenting, they will have faster clinical decision support, they will have automated and timely reporting capabilities, they will have near real time feedback on their performance, benchmarks against best standards, and opportunities for improvement. Doctors can appreciate an investment in an evidence-based approach. In order to automate the collection, reporting, and analysis of the mountain of information collected every day, on every patient, in every part of the hospital, it must be entered discretely. That or you waste more time and money than your competitor who just went all electronic. Do you really want to control costs and get paid faster?  Stop using paper and join the 21st century!

Clinical Alerts – Why Good Intentions Must Start as Good Ideas

As the heated debate continues about ways to decrease the costs of our healthcare system while simultaneously improving its quality, it is critical to consider the most appropriate place to start – which depends on who you are. Much has been made about the advantages of clinical alerts especially with their use in areas high on the national radar like quality of care, medication use and allergic reactions, and adverse events.   Common sense, though, says walk before you run; in this case its crawl before you run. 

Clinical alerts are most often electronic messages sent via email, text, page, and even automated voice to notify a clinician or group of clinicians to conduct a course of action related to their patient care based on data retrieved in a Clinical Decision Support System (CDSS) designed for optimal outcomes. The rules engine that generates alerts is created specifically for various areas of patient safety and quality like administering vaccines to children, core measure compliance, and preventing complications like venous thromboembolism (VTE) (also a core measure). The benefits of using clinical alerts in various care settings are obvious if the right people, processes, and systems are in place to consume and manage the alerts appropriately. Numerous studies have been done highlighting the right and wrong ways of implementing and utilizing alerts. The best criteria I’ve seen used consider 5 major themes when designing alerts: Efficiency, Usefulness, Information Content, User Interface, and Workflow (I’ve personally confirmed each of these from numerous discussions with clinicians ranging from ED nurses to Anesthesiologists in the OR to hospitalists on the floors). And don’t forget one huge piece of the alerting discussion that often gets overlooked…….the patient! While some of these may be obvious, all must be considered as the design and implementation phases of the alerts progress.

OK, Now Back to Reality

A discussion about how clinical alerting can improve the quality of care is one limited to the very few provider organizations that already have the infrastructure setup and resources to implement such an initiative. This means that if you are seriously considering such a task, you should already have:

  • an Enterprise Data Strategy and Roadmap that tells you how alerts tie into the broader mission;
  • Data Governance  to assign ownership and accountability for the quality of your data and implement standards (especially when it comes to clinical documentation and data entry);
  • standardized process flows that identify points for consistent, discrete data collection;
  • surgeon, physician, anesthesiology, nursing, researcher, and hospitalist champions to gather support from various constituencies and facilitate education and buy-in; and
  •  oh yeah, the technology and skilled staff to support a multi-system, highly integrated, complex rules-based environment that will likely change over time and be more scrutinized………

◊◊Or a strong relationship with an experienced consulting partner capable of handling all of these requirements and transferring the necessary knowledge along the way.◊◊

I must emphasize the second bullet for just a moment; data governance is critical to ensure that the quality of the data being collected passes the highest level of scrutiny, from doctors to administrators. This is of the utmost importance because the data is what forms the basis of the information that decision makers act on. The quickest way to lose momentum and buy in to any project is by putting bad data in front of a group of doctors and clinicians; trust me when I say it is infinitely more difficult to win their trust back once you’ve made that mistake. On the other hand, if they trust the data and understand the value of it in near real time across their spectrum of care, you turn them quickly into leaders willing to champion your efforts. And now you have a solid foundation for any healthcare analytics program.    

If you are like the majority of healthcare organizations in this country, you may have some pieces to this puzzle in various stages of design, development, deployment or implementation. In all likelihood, though, you are at the early stages of the Clinical Alerts Maturity Model


and with all things considered, should have alerting functionality in the later years of your strategic roadmap. Though, there are many  projects with low cost, fast implementations, quick ROIs, and ample examples to glean lessons learned from like, Computerized Physician Order Entry (CPOE), electronic nursing and physician documentation, Picture Archiving System (PACS), and a clinical data repository (CDR) to use alerting as a prototype or proof of concept to demonstrate the broader value proposition. Clinical alerting, to start, should be incorporated alongside projects that have proven impact across the Clinical Alerts Maturity Model before they are rolled out as stand-alone initiatives.