2015 – Maestro Strategies

Next Generation Clinical Integration Networks: Lessons Learned

Rob York is a Senior Vice President of Kaufman, Hall & Associates, LLC, and leader of the Population Health Management division in the firm’s Strategy practice. He provides strategic services for a range of healthcare industry clients, including payers, physician organizations, academic health centers, large healthcare systems, public/safety-net providers, and community hospitals.

Mature clinical integration networks (CINs) are moving beyond basic performance improvement activities to develop contracting strategies with multiple payers, achieve scale across larger populations and geographies, and assume greater financial risks for outcomes. These advanced value networks or “Super-CINs” are also moving beyond many commonly held beliefs. As more CINs come on board, lessons learned by startup and early stage CINs are propelling the conversation to focus on care delivery transformation. Three of those lessons learned along the journey to population health follow.

Adopting a Successful Case Study Isn’t Enough: What has succeeded in one market will not necessarily succeed in your market. In some cases, the approach of pioneering CINs such as Advocate, along with FTC requirements, have been used as blueprints. What we have learned, however, is that business and clinical readiness, state laws, payer role and agreements, partner responsibilities, information and technology capabilities and many other factors vary significantly by market and CIN. Many of the “Super-CINs” are operating across a variety of regions and must develop unique approaches in each market. Requirements for payer contracting strategies, care standardization and care management infrastructure will look very different depending on the progress of clinical integration and the specifics of the local market.

No One Can Do it Alone: While there continue to be stand-alone hospitals and independent physician practices, most are creating partnerships at some level. Historic views of the payer-provider relationship are changing on both sides. There is more willingness to have an open conversation because payers and providers need each other to make population health management work. The relationship varies by market – in some, payers are driving the design of the value network, and in others providers are taking the lead. Rather than staying in their traditional siloed roles, both are coming to the table to design new approaches to care management. Payers have tools and information sets, and providers need to enhance care management. In addition, nontraditional players are becoming part of the landscape, such as DaVita HealthCare Partners, which operates medical groups and specializes in care management, and which has sought to partner with payers for population health management.

This Is More than an Experiment; Success Means Making a Commitment to Go the Distance: Many of the more advanced value networks are recognizing that upside, shared savings are short lived and that the real opportunity is associated with the assumption of risk. Early on, some providers chose not to assume risk because of challenges such as capital requirements and the need for cultural change. However, the urgency has been ramped up by external forces such as the intention of the Centers for Medicare & Medicaid Services (CMS) to move 50 percent of its payments into value-based arrangements by 2018. CINs and accountable-care organizations entering the market today must realize that a commitment to go the distance is essential. For example, organizations need to develop a contracting strategy that encompasses a variety of commercial, CMS and direct-to-employer agreements; define a care management model; and invest in a care management platform with key partners. Success will be driven by hyper focus based on your market characteristics and your organization’s capabilities, chosen role in population health management, and level of clinical integration.

Physician Satisfaction with EHRs: Finding Balance in a Digital World

Dr. Howard Landa, MD, CMIO Vice Chairman of AMDIS

As Vice Chairman of the Association of Medical Directors of Information Systems (AMDIS), Howard Landa frequently discusses with CMIOs the challenges and opportunities they face in leading informatics and analytics initiatives at their health systems. We asked Dr. Landa to address physician satisfaction with EHRs and the emerging technologies that may help improve the value of these systems.

While we have succeeded in providing healthcare systems with a plethora of health information technology pathways designed to improve the efficiency and quality of care, we have also managed to make patient care much more complex. At a recent AMDIS symposium on the evolving role of the CMIO in physician leadership, a discussion regarding the impact of the Electronic Health Record (EHR) on medical practice yielded interesting results. When polled, many front-line clinicians will tell you that they have a love-hate relationship with the EHR. They don’t want to give it up completely and return to the ‘old school’ days of paper, but the way it has impacted their workflows has simultaneously improved efficiency and caused a complete shift in the care paradigm.

What are the issues causing the physicians and clinicians to feel this way? One is the transition from Clinician created prose to standardized and structured documentation. EHR templates structure the documentation process by capturing data in drop-down boxes, checked or unchecked boxes and prefilled templates. The templates provide consistent documentation methods, speed up documentation time and allow rapid analysis of large groups of patients via automatic analytics tools. Yet they leave little room for interpretation regarding the nuances of the patient’s specific case. In the analog world, a physician would dictate findings which would later be transcribed and become part of the record. The dictation process allowed the clinician to share why certain decisions were made, the timing of the care process and “if/then” statements which could guide steps in clinical decision making. As other care team members provided care to the patient, these aspects of the story were often useful in providing clinical context and understanding. While the structured data provided by the usage of the EHR is very valuable from a data analytics side, we have lost the physician’s intellectual input into those notes making it difficult to “individualize” the patient. One patient’s notes-over-time may be almost indistinguishable from each other, raising both cognitive and coding concerns.

So what can we do to swing the pendulum back toward the middle and find a balance between free prose “storytelling” and the high value of structured data? Natural Language Processing (NLP) is one option. NLP is a practical application which can process free text that is entered or dictated into the record. NLP enables physicians to extract the data in a more evolutionary and biologic way – i.e., the way a human brain would work as opposed to a computer. When NLP is combined with nomenclature codification schemas such as SNOMED, structured data can be extracted incorporated into the patient’s record. Leveraging the “OpenNotes” patient engagement/empowerment movement and applying analytics to this data, clinicians will be able to improve the accuracy of the patient story and connect what the patient says with what the physician hears. The patient engagement with the process makes the requirement of clear and individualized information all the more important.

So to find balance and truly deliver the promise of EHRs, NLP and other tools will allow the care team the ability to read the notes and extract data while keeping track of the nuances of patient care due to the specificity of prose. We will also be able to ask the systems to categorize, store, prioritize, codify, and place structured extracted data where it can be redelivered when needed while still retaining the physician’s intellectual thought processes. Health systems can then use the findings to improve weaknesses in clinical documentation or care processes, further stratify population health risks and outcomes, provide input into clinical research and more.

Dr. Howard Landa, MD is an accomplished CMIO with a proven record of leveraging innovation, technical expertise and operational knowhow to deliver HIT solutions. Industry recognition including 20 years as Vice-Chair of the Association of Medical Directors of Information Systems; two years as the chairman of the HIMSS Physician Community, and recipient of Modern Healthcare’s Top 25 Medical Informaticists Award in 2010, 2011 and 2012.

Beware Best Practices

Almost twenty years ago, in 1996 after publishing “America’s Health in Transition: Protecting and Improving Quality” the Institute of Medicine launched a long term, ongoing concerted effort on assessing and improving the quality of healthcare. “To Err is Human” further galvanized the national movement to improve the quality and safety of our healthcare practices by putting the spotlight on how tens of thousands of Americans die each year from medical errors. The “Quality Chasm” report underscored the importance of a dramatically improved information technology infrastructure to support a 21st century health system. Building blocks for such a system include an electronic health record system and national standards. Progress has been made, the federal government has paid out over 30 billion dollars in Meaningful Use incentives as of March 2015 and impressive examples of quality improvements are frequently quoted in the literature. Yet, most would agree that the results to-date have been underwhelming.

It is important to recognize that most implemented EHRs with a “check-the-box” mentality order to comply with Meaningful Use. When Meaningful Use was initially launched, our team suggested that we were “enabling the dinosaur”. And while not prehistoric, the design of today’s healthcare system does have ancient roots. The Romans constructed buildings called valetudinaria for the care of sick slaves, gladiators, and soldiers around 100 B.C. (Heinz E Müller-Dietz, Historia Hospitalium, 1975). In the U.S., the number of hospitals reached 4400 in 1910, when they provided 420,000 beds (U.S. Bureau of the Census, Historical Statistics of the United States 1976). So clinical information technology was about automating existing clinical processes in hospitals (Stead 2005) rather than transforming clinical decision-making and work processes across the care continuum” (Brown, Patrick, Pasupathy 2013).

Separately, quality and performance improvement departments focused on deploying best practice – a method or technique that has consistently shown results superior to those achieved with other means, and that is used as a benchmark. (Wikipedia). While best practices have their place, it is important to recognize the risks associated with emulating others when the practice depends on an antiquated business model such as hospital care.

As health systems transition from 1.0 – Bricks and Mortar Healthcare to 3.0 – Digital, Value Driven Connected Health and Healthcare, we encourage a focus on emerging practice. A concept born in “systems thinking”, emerging practice assumes:

We cannot copy other organizations, use it in our organization and expect it to work given the number of variables at play
Intentional design of care management and business models will result in disruption of today’s best practices
Collaboration and integration of clinical teams, business leaders, information technology experts and data analyst will create new value
Big bang, long term projects are giving way to agile, experimentation where we learn to work in new and different ways
Rather than using our intuition or past experience to drive improvement, data driven innovation can often have more remarkable results and new practice will emerge

So, the next time someone mentions “best practice” challenge their thinking.

Health Care 2.0 and Beyond

In a recent article in Trustee magazine, Pam Arlotto begins the discussion of how a three stage transformational framework can guide boards as they identify information technology priorities and evolve to value-based care models.

Hospitals and systems now fall into one of three stages:

Health Care 1.0

(EHR implementation, patient portals)

Health Care 2.0

(Interoperable systems; mHealth and telemedicine; business intelligence; cloud-based technologies; cybersecurity; social media

Health Care 3.0

(Care management platforms; biosensors; predictive and prescriptive data mining; precision medicine)

Each health system will have strategic imperatives that drive the digital discussion. Boards need to know what stage their institution is in and determine how they can prepare to move to the next stage.

Read the full article here.

The Value of Health Information Exchange: Creation of a Health Information Ecosystem

Dr. Jan Lee, CEO, Delaware Health Information Network

The Delaware Health Information Network (DHIN) is the first live, statewide health information network in the nation. Among its significant accomplishments are financial self-sustainability, near universal participation in core services, connectivity beyond the Delaware state boarders and Stage 7 of 7 on the eHealth Initiative HIE Maturity Model. In 2011, Maestro conducted “a rigorous evaluation of the value DHIN’s data exchange program to assess the nature and extent to which DHIN had impact on important patient, safety, quality, processes and outcomes within the state”. Recently, we invited Jan Lee, MD, CEO of DHIN to share the broader Vision, lessons learned and value of health information exchange.

Over time, I’ve come to define HIE less as a health information exchange and more as a ‘health information eco-system.’ While many in healthcare view the benefit of health information exchange from a cost savings perspective, I view HIEs as a biosphere, where everyone contributes and everyone receives value. Now it certainly doesn’t happen overnight. As an early pioneer, there wasn’t a playbook. We had one chance to get it right, no chance for a do-over. We were customer focused and tied our business model the needs of our market.

Delaware’s visionary leadership – at the state level and in its health systems started with an environment of collaboration not found in many other states. Participants focused on finding what is best for patients, even if that means giving away a perceived competitive advantage by sharing data. Leaders recognized they would have to find other ways to differentiate their organizations. Sadly, other communities have created their own market barriers by making data sharing difficult.

There was a large list of potential offerings we could provide our stakeholders. We focused initially on clinical results delivery on behalf of sending organizations and found a return on investment through cost reduction. We built critical mass, and the momentum grew from there. Over time the data exchange became the standard for the safe and secure delivery of clinical results (lab and pathology), reports (both radiology and transcribed), and face sheets (hospital admission, discharge, and transfer data, including demographic and billing information). DHIN has accomplished full participation of all acute care hospitals and skilled nursing facilities in the state. In addition, the number of providers enrolled as end users of the HIE now exceeds the number of practicing providers in Delaware. We have a number of practices with affiliations to Delaware hospitals across the Maryland and Pennsylvania borders who have enrolled. We also have the three Maryland hospitals closes to our borders enrolled as full up data senders, sending us data on both Delaware and Maryland patients. The value proposition to them comes from our ability to deliver the results to their affiliated practices, which is not a service offered by the Maryland HIE. Patients have come to expect local and regional organizations to use DHIN’s community health record and because of that, hospitals and other healthcare organizations feel the pressure to participate in the ecosystem or lose business.

We have a number of new initiatives on the drawing board including expanding the ability for ambulatory providers to contribute data, exploring ways to use the data beyond point of care decision making at the population level, developing quality measures and dashboards, and considering options to engage patients in data contribution. Each new effort is being designed to drive value from the perspective of key customers and stakeholders. We have learned patience is the key.

Many across the country are acquiring physicians and affiliates, and trying to put all the players on the same EHRs. The reality is that patients don’t stay in walled gardens, they are mobile and seek care where they choose to seek care. Even in Delaware, which is a small state, we have over 60 EHR vendors represented. Often patients cross state lines. We have found that about 13% of our ADTs come from Pennsylvania and 14% come from Maryland. Delaware healthcare organizations would be missing out on critical information if they didn’t link to entities outside their own systems.

Why is DHIN so successful? It’s important to note that DHIN was very deliberative in its development – Return on investment and value did not emerge on day one. Many, many meetings were held with the stakeholders. It took over 10 years for DHIN to reach the place where it could begin business and the road to get there was painful. Organizations approaching HIE today now have best practices available that can shorten the time – but it’s important to recognize that it will take time, there is no magic wand. Layer on activities, demonstrate their value and then add the next targeted offering.

Jan Lee, MD, currently serves as the Chief Executive Officer of the Delaware Health Information Network (DHIN). Dr. Lee is a board certified Family Practice physician with a Master of Medical Management degree and a wealth of leadership experience. Prior to joining DHIN, she was Vice President of Knowledgebase and Content for NextGen Healthcare, a leading vendor of health information technology products and services, where she was responsible for the development of clinical content in 26 medical specialty areas for the NextGen electronic health record.

Archive for year: 2015