In December, states had to let the Department of Health and Human Services know whether they would set up their own state-operated health insurance exchanges. The deadline was not a surprise, although several states protested they didn’t have enough time to consider the issue. The mandate originates with the 2010 Accountable Care Act. What is surprising is the number of states who declined the opportunity to create their own insurance exchanges.
Federal health law requires states to establish health insurance marketplaces to serve individuals and small businesses that need access to affordable health benefits. HHS outlined a federal model, which was intended as a default option, fully expecting most states to choose local control and operation of their exchanges. Continue reading
Two weeks ago, the Centers for Medicare & Medicaid Services posted hospital readmission rates for three conditions in the Hospital Compare database. Almost immediately, critics pointed out the lack of improvement—only a 0.1 point decrease across the board. While that is true, the ensuing debate misses the real story.
An article in The Washington Post, published online July 19, was titled “Hospitals’ readmission rates still too high, government says.” It quotes a Harvard professor saying, “Either we have no idea how to really improve readmissions, or most of the readmissions are not preventable and the efforts being put on it are not useful.” That is an easy conclusion in light of the Medicare data. But it isn’t correct.
Several Medicaid programs currently are demonstrating widespread innovation at the state level to reduce hospital readmissions. According to an NAMD policy brief, published the day after the WP article, these programs have found effective methods of identifying preventable readmissions and focusing efforts where they can improve patient outcomes. Continue reading
Guest blog by Lisa Lyons, RN Product Marketing Manager with 3M Health Information Systems
As the industry transitions to pay-for-performance, there are persistent myths about its potential impact. One myth that needs to be dispelled is how pay-for-performance will affect total revenue. Critics of new payment models argue that healthcare revenue will go down with more efficient care and more effective patient outcomes. In reality, with preventable complication reduction, revenues will stay the same, margins will improve, and most importantly, patients will have safer care.
For example, consider a hospital patient who undergoes a surgical procedure and gets an infection in the area of surgery. When a complication occurs as a result of the process of care, the hospital has to do additional procedures, and the patient has a longer hospital stay because of the event. This creates more cost, not just for the patient and the payer, but also for the hospital. Continue reading
Echoing Paul Cerrato’s post on EHRs and Pay For Performance, which cites a study by Jonathan Weiner, et. al., at Johns Hopkins University titled New Paradigms for Measuring Clinical Performance Using Electronic Health Records, there are many shortcomings in current EHR support for a shift to Pay For Performance (P4P). Cerrato particularly calls out statistics showing very small fractions of ambulatory care encounters fully documented in EHRs and interoperable across providers – necessary to meaningfully impact quality of care across provider organizations.
There are two issues at work here: the capture and the use of data. When two provider EHRs cannot adequately share data for a single patient, this is an issue of the usage of the data. If the data cannot be effectively used across provider organizations, there is little chance of using the EHRs to drive improved quality, and thus succeeding at P4P. Continue reading
On June 5, 2012, CMS announced another new data initiative. If you are a provider, this one should be important to you – CMS intends to transform its approach to data analytics: “The initiative will help guide the agency’s evolution from a fee-for-service based payer to a ‘value-based purchaser of care’ that links payments to quality and efficiency of care, rather than sheer volume of services.” To run the initiative, CMS created an oversight group titled the Office of Information Products and Data Analysis. The goal of the new entity is making data management and information sharing a core CMS function. CMS is charging this new data-savvy group with oversight of current data functions, including the Chronic Condition Warehouse (CCW), the Medicare Current Beneficiary Survey, the Medicaid Analytic Extract, the Research Data Assistance Center, and other important initiatives. Read the CMS Fact Sheet for more. Continue reading
There is a transformation occurring in health care. What traditionally had been the responsibility of payers is now shifting to providers. Providers and health systems haven’t been responsible for comparing the total cost of care against total health outcomes. As part of this transformation, health systems will increasingly be held accountable for total costs of care.
My concern about putting the “accountable” in “accountable care” is measurement. What will be measured? How does a provider or health system that traditionally has billed for services now assume responsibility for the total cost of care? Continue reading
By: Sandeep Wadhwa
There is a big shift occurring in the way we measure the efficiency and effectiveness of health care. The shift is moving beyond process measures toward patient-satisfaction measures, such as CAHPS surveys and outcomes measures, including hospital-acquired conditions and hospital readmissions. These new measures are quickly becoming the foundation of new payment systems.
For example, the CMS hospital readmissions reduction program will penalize excessive hospital readmissions. This provides a huge incentive for hospitals to improve protocols and procedures to lower readmission rates. However, it isn’t just a clinical care issue. It’s a measurement issue, too, as pointed out by the Healthcare Financial Management Association (HFMA) in their letter to CMS. HFMA argues for CMS to provide data on readmissions and to change how they are defined and calculated. (They also made an unsolicited endorsement of 3M classification methodologies. Thanks, HFMA!)
Traditionally our industry has focused on quality process measures such as whether a medicine was delivered or not on time. Process measures are important. That’s a critical step in an equality hierarchy, but they’re not a measurement of the outcome of interest. If you’re trying to measure infection rates after surgery or a lung puncture or aspiration pneumonia, that’s the outcome.
Poor ICD-10, it has such an image problem. It needs a good makeover, someone who would be willing to conduct a serious spin campaign against all these silly accusations against it.
I am tempted to take it on, but I am frankly tired of the whole thing and could not pursue it with any gusto. It would be spectacular if some physician somewhere would take up the ICD-10 image problem as a fun cause. Think of it: an ICD-10 spin doctor doctor. Definitely too cool to happen.
If anyone else out there is interested in the job, here is an ICD-10 spin doctor starter kit, consisting of three popular accusations against ICD-10, followed by three counteroffensive positions an ICD-10 spin doctor could use. Continue reading
By: Jeremy Zasowski
What happens when clinical documentation strategies to meet Meaningful Use requirements don’t line up with an organization’s strategies to improve clinical documentation for coding and profiling?
In my interactions with our customers, we’re seeing an increasing number of hospitals moving to increase their physicians’ adoption of template-based EHR documentation workflows. The primary reasons include: the need to move away from hand-written, paper-based notes; the need to leverage the huge investment made in an EHR; and, the requirement to meet Meaningful Use criteria for their EHR.
By: Ron Mills
A well-understood maxim among software developers states that there is generally a difference between:
- what users say they want
- what users want
- what users need
The difference between the first two is one of communication and is easily solved by quickly prototyping what they say they want, so they can say “that isn’t what I want” and start pointing.
The chasm between want and need is much harder to bridge. In the short term, you can make plenty of money giving people what they want, but if you are in the game for the long haul, you ignore the difference at some peril to your reputation. When the system you build fails to solve their problem, are they more likely to come back and say “let’s try again” or will they go somewhere else?
Knowing what the user needs isn’t so easy, of course.