Category Archives: complex adaptive systems

business, complex adaptive systems, data saving lives, entrepreneurship, health market quality, healthcare, management and leadership, policy, rapid learning health systems

McKinsey: Feeding consumer decisions…

Will be useful to plug this into our health market quality explorations…

PDF: Digitizing the consumer decision journey McKinsey

http://www.mckinsey.com/Insights/Marketing_Sales/Digitizing_the_consumer_decision_journey?cid=DigitalEdge-eml-alt-mip-mck-oth-1406

Digitizing the consumer decision journey

In a world where physical and virtual environments are rapidly converging, companies need to meet customer needs anytime, anywhere. Here’s how.

June 2014 | byEdwin van Bommel, David Edelman, and Kelly Ungerman

Many of the executives we speak with in banking, retail, and other sectors are still struggling to devise the perfect cross-channel experiences for their customers—experiences that take advantage of digitization to provide customers with targeted, just-in-time product or service information in an effective and seamless way.

Video

How consumer behavior keeps changing

McKinsey’s David Edelman explains how purchasing decisions are made in a digital world.

This quest for marketing perfection is not in vain—during the next five years or so, we’re likely to see a radical integration of the consumer experience across physical and virtual environments. Already, the consumer decision journey has been altered by the ubiquity of big data, the Internet of Things, and advances in web coding and design.1 Customers now have endless online and off-line options for researching and buying new products and services, all at their fingertips 24/7. Under this scenario, digital channels no longer just represent “a cheaper way” to interact with customers; they are critical for executing promotions, stimulating sales, and increasing market share. By 2016, the web will influence more than half of all retail transactions, representing a potential sales opportunity of almost $2 trillion.2

Companies can be lulled into thinking they’re already doing everything right. Most know how to think through customer search needs or have ramped up their use of social media. Some are even “engineering” advocacy—creating easy, automatic ways for consumers to post reviews or otherwise characterize their engagement with a brand.

Yet tools and standards are changing faster than companies can react. Customers will soon be able to search for products by image, voice, and gesture; automatically participate in others’ transactions; and find new opportunities via devices that augment their reality (think Google Glass). How companies engage customers in these digital channels matters profoundly—not just because of the immediate opportunities to convert interest to sales but because two-thirds of the decisions customers make are informed by the quality of their experiences all along their journey, according to research by our colleagues.3

To keep up with rapid technology cycles and improve their multiplatform marketing efforts, companies need to take a different approach to managing the consumer decision journey—one that embraces the speed that digitization brings and focuses on capabilities in three areas:

  • Discover. Many of the executives we’ve spoken with admit they are still more facile with data capture than data crunching. Companies must apply advanced analytics to the large amount of structured and unstructured data at their disposal to gain a 360-degree view of their customers. Their engagement strategies should be based on an empirical analysis of customers’ recent behaviors and past experiences with the company, as well as the signals embedded in customers’ mobile or social-media data.
  • Design. Consumers now have much more control over where they will focus their attention, so companies need to craft a compelling customer experience in which all interactions are expressly tailored to a customer’s stage in his or her decision journey.
  • Deliver. “Always on” marketing programs, in which companies engage with customers in exactly the right way at any contact point along the journey, require agile teams of experts in analytics and information technologies, marketing, and experience design. These cross-functional teams need strong collaborative and communication skills and a relentless commitment to iterative testing, learning, and scaling—at a pace that many companies may find challenging.

Let’s consider what an optimized cross-channel experience could look like when companies target improved capabilities in these three areas.

A new normal …

Imagine that a couple has just bought its first home and is now looking to purchase a washer and a dryer. Mike and Linda start their journey by visiting several big-box retailers’ websites. At one store’s site, they identify three models they are interested in and save them to a “wish list.” Because space in their starter home is limited—and because it is a relatively big purchase in their eyes—they decide they need to see the items in person.

Under an optimized cross-channel experience, the couple could find the nearest physical outlet on the retailer’s website, get directions using Google Maps, and drive over to view the desired products. Even before they walk through the doors, a transmitter mounted at the retailer’s entrance identifies Mike and Linda and sends a push alert to their cell phones welcoming them and providing them with personalized offers and recommendations based on their history with the store. In this case, they receive quick links to the wish list they created, as well as updated specs and prices for the washers and dryers that they had shown interest in (captured in their click trails on the store’s website). Additionally, they receive notification of a sale—“15 percent off selected brand appliances, today only”—that applies to two of the items they had added to their wish list.

When they tap on the wish list, the app provides a store map directing Mike and Linda to the appliances section and a “call button” to speak with an expert. They meet with the salesperson, ask some questions, take some measurements, and close in on a particular model and brand of washer and dryer. Because the store employs sophisticated tagging technologies, information about the washer and dryer has automatically been synced with other applications on the couple’s mobile phones—they can scan reviews using their Consumer Reports app, text their parents for advice, ask Facebook friends to weigh in on the purchase, and compare the retailer’s prices against others. Mike and Linda can also take advantage of a “virtual designer” function on the retailer’s mobile app that, with the entry of just a few key pieces of information about room size and decor, allows them to preview how the washer and dryer might look in their home.

All the input is favorable, so the couple decides to take advantage of the 15 percent offer and buy the appliances. They use Mike’s “smartwatch” to authenticate payment. They walk out of the store with a date and time for delivery; a week later, on the designated day, they receive confirmation that a truck is in their area and that they will be texted within a half hour of arrival time—no need to cancel other plans just to wait for the washer and dryer to arrive. Three weeks after that, the couple gets a message from the retailer with offers for other appliances and home-improvement services tailored toward first-year home owners. And the cycle begins again.

… requires new capabilities

As this example makes clear, the forces enabling consumers to expect real-time engagement are unstoppable. Across the entire customer journey, every touchpoint is a brand experience and an opportunity to engage the consumer—and digital touchpoints just keep multiplying. To maximize digital channels, companies need to focus on improving their “3-D” capabilities.

Discover: Build an analytic engine

Even in this era of big data and widespread digitization of customer information, some companies still lack a 360-degree view of the people who buy their products and services. They typically measure the performance of direct sales activities such as product pitches and encourage downloads using “last-action attribution” analyses, which assess campaigns in isolation rather than in the context of the entire cross-channel consumer decision journey. Usually these data will have been stored in disparate locations and legacy systems rather than in a central server. Complicating matters further is the range and quantity of unstructured data out there—information about consumers’ behaviors and preferences that is, for instance, captured in online reviews and social-media posts. In our experience, this type of data is usually the least understood and therefore the least utilized by companies.

To get the full customer portrait rather than just a series of snapshots, companies need a central data mart that combines all the contacts a customer has with a brand: basic consumer data plus information about transactions, browsing history, and customer-service interactions (for an illustrative example of how companies can lose potential customers by failing to optimize digital channels, see exhibit). Tools like Clickfox and Teradata can help marketers gather these data and begin to pinpoint opportunities to engage more effectively with consumers across the decision journey. This collection effort requires input from people across multiple functions—a complex undertaking, to be sure, but the payoff can be big. Our work in this area suggests that the growth rate of earnings before interest, tax, depreciation, and amortization of grocers that focus on customer analytics is 11 percent, compared with just 3 percent on average for their main competitors. For big-box retailers, the difference is 10 percent compared with 2 percent.4

Exhibit

Failure to optimize digital channels may result in underperformance.

With a comprehensive data set in hand, companies can undertake the sort of quick-hit “shop diagnostics” that many tell us is lacking in their marketing and e-commerce programs. Using analytic applications such as SAS and R, and by applying various algorithms and models to longitudinal data, companies can better model the cost of their marketing efforts, find the most effective journey patterns, spot potential dropout points, and identify new customer segments. Based on its analysis of click-through behaviors, for instance, one regional retailer saw that a particular set of customers preferred digital shopping over physical and always read e-mail on Saturdays, and so the retailer altered its e-mail campaign to send this cohort online offers only on Saturdays.

Additionally, by using business-process software and services from vendors such as Adobe Systems, ExactTarget, Pegasystems, and Responsys, companies can identify in real time the basic “triggers” for what individual customers need and value—regardless of the product or service—and personalize their approach when making cross- or up-sell offers. They can also use these tools to generate automated reports that track customer trends and key performance indicators. For instance, the regional retailer’s analytics suggested that two of the customers who read their e-mail only on Saturdays were in the midst of a career change; both had revised their profiles on LinkedIn within the past three days. Based on its analytics efforts, the company was able to create targeted offers for each—one received information about laptop bags (based on her previous purchases) while the other received information about suits (based on his previous purchases).

Already, the companies employing these types of advanced analytics have seen significantly improved click-through rates and higher conversion rates (between three and ten times the average). Additionally, McKinsey analysis shows that using data to make better marketing decisions can increase marketing productivity by between 15 and 20 percent—that’s as much as $200 billion given the average annual global marketing spend of $1 trillion.5

Design: Create frictionless experiences

Careful orchestration of the consumer decision journey is incredibly complex given the varying expectations, messages, and capabilities associated with each channel. According to published reports, 48 percent of US consumers believe companies need to do a better job of integrating their online and off-line experiences. There is a premium for getting this right. One major bank unlocked more than $300 million in additional margins by making better use of digital channels. It tapped into underutilized customer data and delivered targeted marketing messages at various points in the purchase-decision process. The bank used the data, plus various personalization and testing tools, to inform changes in marketing campaigns for certain product lines; every next step for every customer was progressively tailored to help the customer take the best action.

Digital natives such as Amazon, eBay, and Google have been leading the pack in resetting consumers’ expectations for cross-channel convenience. (Think of eBay’s Now mobile app, which provides one-touch ordering from any of eBay’s retail partners and same-day delivery in some US cities, or Amazon’s recent incorporation of a help button in the company’s latest-generation Kindle Fire tablet, linking users to a live help-desk representative.) These players have perfected the ability to test new user experiences and constantly evolve their offers—often for segments of one.

This lean, start-up approach might sound counterintuitive to large, entrenched marketing organizations in which decisions are made at a snail’s pace, but test-and-learn methods can help companies decide how best to optimize (and customize) critical design attributes of the consumer decision journey at various points along the way. In the appliances example discussed earlier, the retailer’s customer analytics allowed it to design an experience for the couple that was completely customized to their context—from their initial online searches to their physical and virtual interactions at the store and to their follow-up with the company postpurchase. Rather than push what could be construed as intrusive (even creepy) messaging, the retailer provided Mike and Linda with the most useful information at every point in their decision journey and offered the easiest possible path to purchase and delivery.

To create similarly frictionless experiences, some companies have created 24/7 digital “window shops” to test product ideas and customer interactions and collect rapid feedback without the need for additional labor or inventory. Several companies that offer inherently complex products or services have incorporated “gaming” elements into their experiences—tweaking the navigation, content architecture, and visual presentation to allow consumers to trade off and test various options and prices associated with a product before making a decision. One financial-services firm redesigned its mobile app for collecting credit-card applications to incorporate the customer context. Previously it had a one-size-fits-all interface; in the redesigned version, various elements of the mobile app’s interface—such as pricing, stage of process, and designated credit limits—are dynamically generated based on existing customer information. And the app’s page layout and navigation are rendered simply, allowing for easy completion within just a few clicks. The result has been a significant uptick in online applications.

Deliver: Build a more agile organization

In our experience, too many companies are afraid to launch “good enough” campaigns—ones that are continually refined as customers’ purchase behaviors and stated preferences change. Under the direction of conservative senior leaders, teams tend to launch campaigns that take too long to get off the ground and end up revealing few new insights. Instead, they must be willing to conduct lots of small-scale experiments with cloud or proxy website services to pilot new designs and prove their value for investment.

These types of agile, data-driven activities must be supported by an organization that has the right people, tools, and processes. Many companies will have some of the talent required, but not all, and executives will inevitably face resistance when it comes to introducing lean tools and techniques into their sales, marketing, and IT processes. The most successful omnichannel marketers we’ve seen have established centers of excellence in both analytics and digital marketing, and they practice end-to-end management of microcampaigns. Their campaign-building processes typically include systematic calendaring, brainstorming, and evaluation sessions to allow for one-week and two-week turnaround times. And roles and responsibilities are clearly defined. Far from creating a rigid, hierarchical process, this model frees up individuals to iterate quickly—what is sometimes called “failing fast forward” in the world of high tech.

At one bank, for instance, business-unit leaders gather each month to talk about their progress in improving different consumer journeys. As new products and campaigns are launched, the team places a laminated card illustrating the journey at the center of the conference-room table and discusses its assumptions about the flow of the experience for different segments and about how the various functional groups need to contribute: Where does customer data need to be captured and reused later? How will the design of the campaign flow from mass media to social media and then on to the website? What is the follow-up experience once a customer sets up an account? The team has also appointed dedicated mobile and social-media executives to become evangelists for strengthening the omnichannel experience, helping business units raise their game along a range of consumer interactions. The company’s first wave of fixes and new programs generated tens of millions of dollars in the first six months, and the team expects it to continue scaling beyond $100 million in added annual margins.

Building an agile marketing organization will take time, of course. Companies should start by assembling a “scrum team” that will bring the right people together to test, learn, and scale. The team should incorporate cross-functional perspectives (marketing, e-commerce, IT, channel management, finance, and legal), and its members must adopt a war-room mentality—for instance, making tough calls about which campaigns are working and which aren’t, and which messages should take priority for which segments; launching new tests every week rather than every six months; and mustering the IT and design resources to create content for every possible type of interaction.

Companies likely will need to hire people with skills that differ from the ones they rely on now. Some organizations have developed innovative, venture capital–like strategies for finding and recruiting the people they need. Staples, for instance, has built an e-commerce innovation center in Cambridge, Massachusetts, to better recruit technology talent from nearby Harvard University and MIT, and it recently bought conversion-marketing start-up Runa to act as a talent hub on the West Coast.

New types of information systems may also be required. The best technology solutions will vary according to a company’s starting point and objectives. Generally, though, companies will get the best results from tools that enable large-scale data management and the integration of databases; the generation of next-best-action and other types of advanced analyses; and simpler campaign testing, execution, and metrics.

Companies need to make strategic decisions about the best pathways to build customer value. Many cite digital as one of their top three priorities in this regard, but few have taken the time to measure the level of digital maturity their organization has achieved. A company’s digital quotient (DQ) is a function of how well defined its long-term digital strategy is, its effectiveness in implementing that strategy, and the strength of its organizational infrastructure and information technologies. The companies that incorporate the notion of DQ into their short list of performance metrics can more effectively monitor their progress across the digital capabilities we’ve outlined here, enabling more targeted investments and accelerated rates of digital growth.

Indeed, the companies that ultimately succeed in omnichannel marketing and sales will likely resemble tech companies and, interestingly, publishers—effectively using big data and digital touchpoints to drive growth and reduce costs, while producing and managing a variety of content (catalogs, coupons, web pages, mobile apps, and user-generated content) in real time across multiple platforms to create breakthrough customer experiences. This means rethinking the analytics that inform their segmentation strategies, the flow of the experiences they design, and the way they set up their internal operations for faster iteration and delivery of service.

About the authors

Edwin van Bommel is a principal in McKinsey’s Amsterdam office, David Edelman is a principal in the Boston office, and Kelly Ungerman is a principal in the Dallas office. They are leaders in McKinsey’s revenue enhancement through digital (RED) initiative, which redesigns the consumer decision journey to encompass all commercial levers, across all channels and touchpoints, thereby creating growth in revenue and profits.

business, complex adaptive systems, data saving lives, health market quality, healthcare, healthy habits, musings, nutrition, policy, politics, quantified self, quotes & aphorisms, rapid learning health systems

The Hospital of the Future is not a Hospital

Great insights into where capital is being invested in US healthcare…

http://www.healthleadersmedia.com/print/LED-305089/The-Hospital-of-the-Future-is-Not-a-Hospital

The Hospital of the Future is Not a Hospital

Philip Betbeze, for HealthLeaders Media , May 30, 2014

Pursuing expensive inpatient volume in the traditional sense is a strategic dead end. Any new construction undertaken by hospitals and health systems should be based on adaptability, patient flow, and efficiency gains—not bed count.

I’ve spent a good deal of time the past several weeks interviewing senior healthcare leaders for my story in the May issue of HealthLeaders magazine about the hospital of the future. But in truth, that headline might be a bit of a tease.

As it turns out, the hospital of the future doesn’t look much like a hospital at all. Instead, it’s a cohesive amalgamation of plenty of outpatient modalities that represent growth in healthcare. Inpatient care, increasingly, represents stagnation and shrinkage, in the business sense.

In the past, a story about the hospital of the future has meant investigating healthcare organizations’ access to capital, and their ability to fund expensive new patient bed towers with all-private rooms and top technologies, in a race to grab volume from competitors.

Under that operating scenario, the sky was the limit, in terms of what organizations were willing to do to attract volume.

That calculus has changed drastically.

In a recent survey on healthcare design trends conducted by Minneapolis-based Mortenson Construction, 95% of the healthcare organizations surveyed said most of the projects they are undertaking are predominantly ambulatory in nature.

“If, in theory, the [Patient Protection and Affordable Care Act] has now got 7 million people engaged in healthcare insurance who didn’t have that previously, the inrush of patients will be outpatient-based,” says Larry Arndt, general manager of healthcare in the company’s Chicago offices. “What’s not needed is bed space or heavy procedural space.”

A Strategic Dead End
The PPACA, employers, and commercial health plans have made clear that pursuing expensive inpatient volume in the traditional sense is a strategic dead end. That doesn’t mean new patient towers won’t go up, but it does mean their construction will be based on adaptability, patient flow, and efficiency gains, not bed count.

As few as five to seven years ago, says Arndt, a healthcare leadership team would take a capital improvement project through a planning and programming phase in which they followed a traditional approach. The team would utilize widely standardized metrics and program their building based on what they’re doing now, with no consideration of the future, Arndt says.

By contrast, within the last five years, more leaders have been embracing the concept of lean operational improvement.

In order to be competitive in a limited amount of reimbursements, they have had to become more efficient. So instead of the traditional approach of programming new construction based on how the organization operates today, instead, it attempts to map out its current patient flows and discover how to become more efficient. Only then will the team look at how to build around that improved and more efficient model.

Indeed, a whopping 22% of respondents to Mortenson’s February survey said they were “doing nothing” construction-related right now, and only 5% were planning for a traditional replacement hospital.

Instead, a majority said they are focusing new construction on building clinics that can feature just about any outpatient modality except surgery, Arndt says.

Healthcare Shifts to Outside
They’re focusing on combining dialysis, radiology and other treatments that can be provided in one location. And they’re funneling more of their capital budget to items that are outside the realm of new construction, like home health and what Arndt calls e-home healthcare—in other words, technological solutions that help patients access their caregivers outside of any facility.

“Our customer understands that healthcare is moving more toward healthcare outside a facility,” says Arndt. “That means more money is being invested in health information technology. Also, you see more constellation or satellite projects, for example, a small 15,000-20,000 square-foot clinic in a neighborhood. That allows patients to travel a shorter distance to a less congested environment, but yet allows connection to the bigger facility if needed.”

Modular construction is a trend that Arndt sees developing quickly. It’s in the process of designing a clinic for a client that will feature modular walls, to make it more flexible for the changes in care protocols that are assured, but that healthcare’s leaders aren’t sure how will ultimately affect their competitive offerings.

In one clinic, doctors want to be able to meet with patients in groups, for example. Modular walls mean physicians can occasionally meet with groups of patients instead of individually, or vice-versa. Their space is less limiting.

“The clinic can adapt,” says Arndt.

Prefabricating buildings is also gaining steam in healthcare, he says.

“Money is being invested much more wisely than it has been in the past,” he says. “For the design/construction field, we have to be more lean too.”

Part of that lean attitude means offering customers 3-D modeling that starts with design partners, such as the people who will be staffing the building, to optimize work flow.

Adapting Takes Time
“We can prefab things we couldn’t years ago,” he says. An example might be a bathroom “pod” that can be built offsite and installed on site. Full exam rooms can be prepared the same way, and models can be constructed to test care protocols with the team that will be working there.

Arndt’s customers, he says, can be categorized two ways. Either they’re thinking broadly about adapting to the future without knowing exactly what it’s going to bring, or they’re standing idly on the sideline until they understand better how the PPACA and other drastic changes in how healthcare is provided and paid for will affect their bottom lines.

Neither approach is necessarily better than the other, but waiting just puts off the action that needs to be taken. It can be a prudent approach, but even in healthcare, what works can change quickly. Designing, building, and adapting still takes time.

Don’t wait too long.

Philip Betbeze is senior leadership editor with HealthLeaders Media. 

complex adaptive systems, health market quality, healthcare, rapid learning health systems

Economist: US Medicare Fraud

 

New word: A Pill Mill

http://www.economist.com/news/united-states/21603078-why-thieves-love-americas-health-care-system-272-billion-swindle

Health-care fraud

The $272 billion swindle

Why thieves love America’s health-care system

INVESTIGATORS in New York were looking for health-care fraud hot-spots. Agents suggested Oceana, a cluster of luxury condos in Brighton Beach. The 865-unit complex had a garage full of Porsches and Aston Martins—and 500 residents claiming Medicaid, which is meant for the poor and disabled. Though many claims had been filed legitimately, some looked iffy. Last August six residents were charged. Within weeks another 150 had stopped claiming assistance, says Robert Byrnes, one of the investigators.

Health care is a tempting target for thieves. Medicaid doles out $415 billion a year; Medicare (a federal scheme for the elderly), nearly $600 billion. Total health spending in America is a massive $2.7 trillion, or 17% of GDP. No one knows for sure how much of that is embezzled, but in 2012 Donald Berwick, a former head of the Centres for Medicare and Medicaid Services (CMS), and Andrew Hackbarth of the RAND Corporation, estimated that fraud (and the extra rules and inspections required to fight it) added as much as $98 billion, or roughly 10%, to annual Medicare and Medicaid spending—and up to $272 billion across the entire health system.

Federal prosecutors had over 2,000 health-fraud probes open at the end of 2013. A Medicare “strike force”, which was formed in 2007, boasts of seven nationwide “takedowns”. In the latest, on May 13th, 90 people, including 16 doctors, were rounded up in six cities—more than half of them in Miami, the capital city of medical fraud. One doctor is alleged to have fraudulently charged for $24m of kit, including 1,000 power wheelchairs.

Punishments have grown tougher: last year the owner of a mental-health clinic got 30 years for false billing. Efforts to claw back stolen cash are highly cost-effective: in 2011-13 the government’s main fraud-control programme, run jointly by the Department of Health and Human Services (HHS) and the Department of Justice, recovered $8 for every $1 it spent.

As fraud-fighting has intensified, dodgy billing has tumbled in areas that were most prone to abuse, such as durable medical kit and home visits (see chart). Home-health fraud—such as charging for non-existent visits to give insulin injections—got so bad that the CMS, which runs the programmes, called a moratorium on enrolling new providers in several large cities last year. Since tighter screening was introduced under Obamacare, the CMS has stripped 17,000 providers of their licence to bill Medicare. Thousands of suppliers also quit after being required to seek accreditation and to post surety bonds of $50,000.

Economist_HealthcareFraud_20140531_USC154

Yet the sheer volume of transactions makes it easier for miscreants to hide: every day, for instance, Medicare’s contractors process 4.5m claims. In this context the $4.3 billion recovered by fraud-busters in 2013, though a record, looks paltry.

Better than cocaine

Fraud migrates. Take one popular scam: overbilling for HIV infusion, an outdated therapy that Medicare still covers despite the existence of cheaper, better alternatives. This scam waned in Florida after a crackdown, only to pop up in Detroit, run by relatives of the original perpetrators.

Fraud mutates, too. As old hustles are rumbled, fraudsters invent new ones. “We’ve taken out much of the low-hanging fruit,” says Gary Cantrell, an investigator at HHS—an example being the thousands of bogus equipment suppliers registered to empty shopfronts. Scams now need to be more sophisticated to succeed, he argues. Doctors, pharmacies, and patients act in league. Scammers over-bill for real services rather than charging for non-existent ones. That makes them harder to spot.

Some criminals are switching from cocaine trafficking to prescription-drug fraud because the risk-adjusted rewards are higher: the money is still good, the work safer and the penalties lighter. Medicare gumshoes in Florida regularly find stockpiles of weapons when making arrests. The gangs are often bound by ethnic ties: Russians in New York, Cubans in Miami, Nigerians in Houston and so on.

Stealing patients’ identities is lucrative. Medical records are worth more to crooks than credit-card numbers. They contain more information, and can be used to obtain prescriptions for controlled drugs. Usually, it takes victims longer to notice that their details have been pinched. The Government Accountability Office has recommended that the CMS remove Social Security numbers from Medicare cards to prevent fraud. It has yet to do so.

In one fast-growing area of fraud, involving pharmacies and prescription drugs, federal investigators have seen caseloads quadruple over the past five years. Elderly patients may receive kickbacks to sell their details to a pharmacist. He will then provide them with drugs they need while billing Medicare for costlier ones.

Paid recruiters scour nursing homes for accomplices. Some pharmacies also pay wholesalers to produce phoney invoices. Others bribe medical workers for leftover pills: in April a pharmacy-owner in Louisiana admitted to paying nursing-home staff a few hundred dollars a time to bring her unused drugs, which she repackaged and sold as new, billing Medicare $2.2m for the recycled meds between 2008 and 2013.

Another scam is to turn a doctor’s clinic into a prescription-writing factory for painkillers (or “pill mill”) and resell them on the street. A clinic in New York was recently charged with fraudulently producing prescriptions for more than 5m oxycodone tablets, which were sold locally for $30-$90 each. The alleged conspirators included doctors and traffickers who ran crews of “patients” so large that long queues sometimes formed outside the clinic. The doctors charged $300 per large prescription. One raked in $12m. To cover their backs they would ask for scans or urine samples purporting to show injuries. The fake patients typically obtained these from the traffickers at the clinic door.

False billing by pharmacies is rife. New York’s Medicaid sleuths have stepped up spot checks to see if the drugs in the back room square with invoices. But this is a lot of work, so most outlets are never checked.

Dozens of operators of ambulances and ambulettes (vans designed to take wheelchairs) have been caught offering kickbacks to patients to pretend they can’t walk. This lets them qualify for “emergency” pick-ups, for which the company can charge $400 per patient. New York has clamped down with roadside checks. But in one case, word that a checkpoint had been set up spread so quickly—as drivers called each other and a local Russian-language radio station put out a warning—that the number of ambulettes on the main street “went from several to none in a few minutes as they re-routed down side streets”, says Chris Bedell, who took part.

This sort of pavement-pounding investigative work remains important. Another approach is the “desk audit”, where possible overpayment is identified but the only way to ascertain losses is to sift through heaps of records manually. Florida’s Agency for Health Care Administration (AHCA) has recovered up to $50m a year solely from hospitals billing for treatment of illegal aliens that is wrongly coded as “emergency care”. But the work is labour-intensive. Data-crunching technologies are increasingly being used to complement the human eye. “When I started in 1996 we had little access to data,” says HHS’s Mr Cantrell. “It had to be requested ad hoc from CMS contractors.” Now a central database houses near-real-time information for Medicare. This helps the 300 workers at the inspector-general’s office who are trained in data analytics to “triage” the tips that flow in. “We receive far more than we can investigate closely,” says Mr Cantrell.

The CMS is still getting to grips with a new predictive-analysis system, which was introduced in 2011 to catch Medicare fraud earlier and is modelled on tools used by credit-card firms. This identified $115m of dodgy payments in 2012, its first full year. (The number for the second year has yet to be released.) Another useful tool is voice-recognition technology. In Florida, health workers who conduct home visits have to call in from the patient’s phone during each appointment to have their voice pattern matched against the one stored electronically. This has greatly reduced billing for non-visits.

Technology is no panacea, however. Medicare’s computers were pumping out thousands of payments a year for patients who had been struck off the programme before receiving their treatment, until human hands began to intervene this year. The electronification of patient records can allow “cloning”, in which treatments automatically trigger excessive billing codes by defaulting to set templates.

This is the medical world’s “dirty secret”, says John Holcomb of the Texas Medical Association. Everyone talks about it in the doctor’s lounge, but few complain. (What doctors do complain about is the complexity of the bill-coding system: see article.) Moreover, there are gaps in the data picture—some of which could grow. Federal investigators complain that there is no proper national repository for Medicaid information, which is held state-by-state.

A bigger worry is that, as ever more Medicare and Medicaid beneficiaries move to “managed  care” (privately administered) plans, government sleuths will have access to less data. This could lead to lower fraud-related recoveries.

Efforts have been made to improve information-sharing between government and private insurers, including the creation of a public-private forum, the National Health Care Anti-Fraud Association (NHCAA). But some insurers are reluctant to take part, fearing that being too open with their data would invite lawsuits over privacy. Fraudsters bank on public and private payers not working together to connect the dots, said Louis Saccoccio, the head of the NHCAA, at a recent hearing.

The NCHAA is pushing for federal immunity guarantees for insurers that share fraud-related information. On May 20th a bipartisan group of senators introduced a bill to make it easier for insurers to share data with Medicare. It would also require Medicare to check new providers for links to firms that have previously swindled the taxpayer (which you might have thought it was already doing).

Obamacare has had a big impact, says Shantanu Agrawal of the CMS. One thing it requires is that when a state kicks out a dodgy Medicaid provider, it shares that information with Medicare, and vice versa. Previously there were legal impediments to doing this, for some reason.

Resources are tight for investigators. New York has a Medicaid investigations division of 110 souls (including support staff) to scrutinise $55 billion of annual payments and 137,000 providers. Gloria Jarmon, an auditor with the HHS, told a recent hearing that budget cuts will probably force it to cut its oversight of Medicare and Medicaid by 20% in this fiscal year. “Everyone [in Congress] is excited that we bring in eight times more than we cost, but that hasn’t translated into more funding,” laments Mr Cantrell.

This squeeze makes it all the more important to enlist help. More than 5,000 old folk have joined “Medicare patrols”, which hold local meetings to raise awareness of common scams. A crucial part of the anti-fraud effort is the new, simpler Explanation of Benefits (summary statement) that lets recipients see who has billed the programme with their identification numbers. This is “a landmark change”, a CMS executive told Congress last year, adding: “Our best weapon in fighting fraud is our 50m Medicare beneficiaries.”

From the print edition: United States

complex adaptive systems, musings

Parenthood = Stockholm Syndrome

Was watching Philomena on the plane to Singapore surrounded by 2 families each with 3 children under three. Let’s just say I was luck to have remembered my Seinnheisser DJ Headphones that blocked most of the noise out.

Anyway, it struck me that the relationship between children and their parents, orphans and their churches is similar to Stockholm Syndrome… Wikipedia seems all across it:

Stockholm syndrome, or capture-bonding, is a psychological phenomenon in which hostages express empathy and sympathy and have positive feelings toward their captors, sometimes to the point of defending and identifying with them. These feelings are generally considered irrational in light of the danger or risk endured by the victims, who essentially mistake a lack of abuse from their captors for an act of kindness.[1][2] The FBI‘s Hostage Barricade Database System shows that roughly 8% of victims show evidence of Stockholm syndrome.[3]

Stockholm syndrome can be seen as a form of traumatic bonding, which does not necessarily require a hostage scenario, but which describes “strong emotional ties that develop between two persons where one person intermittently harasses, beats, threatens, abuses, or intimidates the other.”[4] One commonly used hypothesis to explain the effect of Stockholm syndrome is based on Freudian theory. It suggests that the bonding is the individual’s response to trauma in becoming a victim. Identifying with the aggressor is one way that the ego defends itself. When a victim believes the same values as the aggressor, they cease to be a threat.[5]

Battered-person syndrome is an example of activating the capture-bonding psychological mechanism, as are military basic training and fraternity bonding byhazing.[dubious – discuss].[6][7][8]

Stockholm syndrome is sometimes erroneously referred to as Helsinki syndrome.[9][10] Helsinki syndrome is more of a case of group think and inattentional blindnessto the negative in order to achieve some perceived benefit, a reference to the non-binding Helsinki Accords that attempted to settle post WWII Cold War tensions.

 

complex adaptive systems, data saving lives, facts & data points, healthcare, healthy habits, nutrition, policy, politics, rapid learning health systems

Economist Daily Chart: Peak Fat

Worryingly, the study—led by the Institute of Health Metrics and Evaluation at the University of Washington—showed that children are fattening at a faster pace than adults. Last week the World Health Organisation set up a new commission to curb child obesity. But it will be some time yet before the world reaches peak fat.

http://www.economist.com/blogs/graphicdetail/2014/05/daily-chart-19?fsrc=scn/fb/wl/dc/peakfat

Daily chart

Peak fat

20140531_gdc156_0 Economist Peak Fat

WAISTLINES are widening everywhere. The percentage of adults who are overweight or obese has swelled from 29% in 1980 to 37% in 2013, according to a new study in the Lancet. People in virtually all nations got larger, with the biggest expansions seen in Africa, the Middle East and New Zealand and Australia. The chunkiest nations overall are found in the tiny Pacific islands and Kuwait, where over three-quarters of adults are overweight and over half are obese. And the world is unlikely to slim down soon. While the rate of increase has slowed in the rich world, it is still rising in poorer countries, where two-thirds of the world’s 2.1 billion overweight adults live. China is home to the largest number anywhere—335m, more than the population of America. This is not just because of its sheer size, but also because economic growth led to cellulite growth: a quarter of adults are now overweight compared with one in ten in 1980.Mexicans just outweigh neighbouring Americans. In both countries, two-thirds of people could lose a pound or two, though more Americans are obese. Agreeing on how to combat the problem is tricky, given that experts continue to bicker on what, precisely, makes us fat. Worryingly, the study—led by the Institute of Health Metrics and Evaluation at the University of Washington—showed that children are fattening at a faster pace than adults. Last week the World Health Organisation set up a new commission to curb child obesity. But it will be some time yet before the world reaches peak fat.

complex adaptive systems, health market quality, healthcare, policy, politics, rapid learning health systems

Deeble Inst: Jury still out on P4P

 

PDF: deeble_issues_brief_no_6_partel_k_can_we_improve_the_health_system_with_performance_reporting

The jury is still out on pay-for-performance and other financial incentive mechanisms

Date:

Wed, 28/05/2014

Spokesperson:

Australian Healthcare and Hospitals Association (AHHA)

Can we improve the health system with pay-for-performance? is the latest Health Policy Issues Brief released by the Australian Healthcare and Hospitals Association’s Deeble Institute for Health Policy Research. Outlining Australian and international experiences with pay-for-performance, the brief unpacks the latest research evidence and implications for policymakers.

“The healthcare system is moving toward greater efficiency, transparency and accountability, and this trend is not likely to change,” Alison Verhoeven, Chief Executive of the AHHA said today. “To meet these goals, a number of financing reforms have been implemented across its health system, but it is unclear where the reform process is now headed.”

“We need to remember there is no single fix to improve service delivery and patient outcomes, to ensure financial sustainability and to increase accountability and transparency in a health system,” said Krister Partel, Policy Analyst with the AHHA’s Deeble Institute. “The jury is still out on whether financial incentive mechanisms, such as pay-for-performance, work as intended and deliver value for money, but if we want to go down that route then the research literature is rich in lessons to keep in mind when developing and rolling out pay-for-performance programs.”

“Regardless of how health financing is structured in the future, governments must ensure that changes strengthen the health system and improve public confidence in it,” said Alison Verhoeven.

“The AHHA is proud to support independent research to inform evidence-based policy development, and we look forward to furthering this discussion to maximise the use of health resources and enhance patient care.”

The Australian Healthcare & Hospitals Association represents Australia’s largest group of health care providers in public hospitals, community and primary health sectors and advocates for universal high quality healthcare to benefit the whole community.

Media inquiries:
Alison Verhoeven, Chief Executive, Australian Healthcare and Hospitals Association 0403 282 501

 

complex adaptive systems, health market quality, healthcare, policy, politics, rapid learning health systems

US healthcare costs are rising again and no one knows why (yet)

Cogent analysis of Obamacare and impacts on spending…

http://www.newrepublic.com/article/117452/rising-health-care-costs-what-it-means-economy-obamacare

Cause for Concern: Health-care costs are rising—and the experts aren’t sure why

By 

Last week’s news about Obamacare enrollment was great. But health care policy wonks have something else on their mind now: the cost of health care. It’s starting to rise more quickly than before. That could be a problem.

For the last four years or so, national health care expenditures—that is, all the money that Americans spend on medical services and supplies—has been growing at historically low rates. It’s gone up every year, as it almost always does, but only by 3 or 4 percent. That’s just a little bit more than inflation. Typically health care spending has risen more quickly. Sometimes, in the 1980s and again in the early 2000s, it’s risen much more quickly. Keep in mind that when national health care spending rises much more quickly than the economy is growing, you feel the impact—as relatively higher insurance premiums, higher out-of-pocket costs, and higher taxes to support government insurance programs. You may not have noticed it, but the recent slowdown has been good for your finances.

Rising health care costs via Altarum

Now the respite may be ending. You can see it in the latest monthly reports from the Altarum Institute, an Ann Arbor-based think-tank that monitors national health care spending. These reports, based on government data, are the equivalent of an early warning system for medical costs. They are one of the first places a spending spike would show up. According to Altarum, expenditures started to rise more quickly in the middle of 2013. Since then, the rate has gone up even more. Reports of rising costs have already gotten the attention of savvy health care observers in the media, like Philip Klein and Sarah Kliff. The question now is how long the trend will continue, how quickly spending will accelerate, what should be done about it—and, of course, what it means for Obamacare.

 

First economists have to figure out whether the recent reports are accurate. They may not be. The key evidence of accelerating health costs comes from monthly government statistics, particularly those produced by the Bureau of Economic Analysis. There’s a reasonable chance, three or four months from now, BEA will announce that costs haven’t been rising so quickly—in much the same way government sometimes revises unemployment statistics, upon learning there were more jobs than the initial data suggested. If that happens, analysts like those at Altarum will have to redraw that graph above and the outlook might look more encouraging.

But most experts I know are betting against that. For some time, they have expected health care costs to rise, because the primary factor in the slowdown was the economy. When unemployment is high and wages aren’t rising, you are less likely to consume more health care for the same reason that you are less likely to consume other goods—it costs money you might not have. You can’t avoid treatment for a heart attack, obviously. But the pills you take for a chronic condition? Getting somebody to look at a nagging, but tolerable pain? You might push that off until you had a little more cushion to pay for the co-pays and deductibles. That’s what people did during the recession. And now that the recession is over, they’re almost certainly starting to spend more again, partly to take care of those problems that they allowed to linger.

In fact, exactly one year ago Monday, an op-ed in the Washington Postpredicted that health care spending would start rising about now. The op-ed was from Drew Altman and Larry Levitt of the Kaiser Foundation, based on work they and their colleagues had done with the analysts at Altarum. Historically, they noted, health care spending followed economic growth, albeit with a time lag. So pretty soon after the economy picked up again, people would start spending more money on health care—until it was rising at about 7 percent rather than 4 percent. Sure enough, according to the latest Altarum analysis, annual growth in health care spending as of February was 6.7 percent. That would be the highest rate since late 2007, just before the recession started.

But the recession wasn’t the only reason health care spending stopped rising so quickly, which means there’s reason to think the long-term trajectory on medical spending really has come down—at least a little. The whole health care industry is in the midst of some pretty significant transformations right now. One of them is a change in the design of health plans, which are transferring more and more out-of-pocket costs onto individuals. That change has tended to slow down health care spending for the same reason that the recession did: It makes people more cost-conscious, because every bill is another direct hit on their wallets. Conservatives and economists tend to think this is a good thing, because it gives people “more skin in the game.” Liberals and public health experts tend to think this is a bad thing, because it gives people incentive not to get medical care they might need. Either way, it’s been happening.

Read More: Obamacare’s Very, Very Good DayAnother change is one taking place in the places where people get medical care, particularly hospitals. It’s a vast re-engineering project, one that attempts simultaneously to make systems run more smoothly and to pay closer attention to the issues that make people sick (or, at least, prevent them from getting better). One sign of this progress is a dramatic drop in hospital “readmissions” across the country—that is, patients going back to the hospital shortly after discharge, for the same reason they were admitted previously. (See the graph below.) This is no accident. It’s a product of “transitional care” programs that hospitals like Mount Sinai in New York started a few years ago. Basically, the hospitals identify which patients are at high risk for readmission, educate them while they are still in hospital, and then provide follow-up outpatient care once the patients have left.

Readmissions via Cutler

How real are these changes? And how widespread? Nobody is sure. But one encouraging sign is the trajectory of spending within the Medicare program. Seniors’ consumption of health care doesn’t track the economy so closely, since their fixed incomes vary less and Medicare (with supplemental policies) provides such comprehensive insurance. Sure enough, Medicare’s cost trajectory fell a few years ago—and it has stayed low even as the economy has recovered. As Peter Orszag, the economist and former Obama Administration official, noted recently at Bloomberg View, “Even though copayments and deductibles in Medicare are usually small, Medicare beneficiaries, too, seem to be having fewer elective procedures and unnecessary doctor visits. This year, for example, Medicare has seen a reduction in the number of costly hip, knee and other major joint replacements, which are sometimes more a choice than a necessity.”

One reason for this progress is the Affordable Care Act. The law’s critics predicted that it would make health care more expensive. And there’s one sense in which that’s certainly true. Because of Obamacare, more people will have insurance and more people who already had insurance will have more comprehensive coverage. All else equal, that means people are going to get more medical care, at least initially. That’s particularly true for people with medical problems that, for years, they deferred treating because they lacked the ability to pay their bills.

But Obamacare also has provisions that push costs in the other direction. There are cuts to what Medicare pays doctors, hospitals, and insurers who provide alternative private coverage. There are financial incentives that reward providers for becoming more efficient: Pretty much everybody agrees that hospitals wouldn’t be working so hard to reduce readmissions if Medicare didn’t penalize them for each patient readmitted. And then there is the “Cadillac tax”—which gradually reduces the financial advantages of very pricey health insurance. The tax doesn’t start for a few years but, already, employers are talking about readjusting their insurance plans to avoid hitting the threshold that would trigger the tax.

So what does that mean for the future? Over the last few weeks I’ve consulted a number of respected experts—including those at Altarum and the Kaiser Foundation, as well as leading economists like Amitabh Chandra and David Cutler. I’ve also consulted reports from the Congressional Budget Office. Their predictions vary, particularly when it comes to the effects of Obamacare. Chandra, for example, thinks the law has done very little to restructure medical care—he calls hopes for its success at cost control “aspirational.” Cutler, by contrast, thinks the law is having an effect already and is likely to have an even bigger one in the future. (The White House, naturally, has adopted the optimistic view as its own.) But pretty much all of these authorities agree on the general shape of things to come. Health care spending will acclerate for a little while, partly because of Obamacare’s coverage expansion but mostly because of the economic recovery. Then it will subside. It will, in other words, be like a wave: Spending will go up, crest, and then return to a lower level.

The good news is that, once the wave is done, year-to-year increases in health care spending should be significantly lower than the historical average. Economists like to talk about “excess growth”—that’s the difference between how quickly health care costs are rising and how fast the economy, measured as Gross Domestic Product, is growing. Over the last 50 years, excess growth has been about 2.6 percent. But the average in the last 20 years has been down to 1.6 percent, thanks to structural changes, some of which date back to the 1990s when insurers first started using managed care. There’s every reason to think that, once the economy fully recovers and Obamacare’s expansion is in place, health care spending will be back to rising at something like the level it was before.

Projected cost growth via KFF

The Kaiser-Altarum projection, for example, assumes excess growth will revert right back to 1.6 percent. (See graph above.) But that would still require some combination of signficantly higher taxes, higher deficits, or higher health insurance premiums in the future. Knocking even a tenth of a percentage point off of that would make a difference. Knocking a few tenths of a percentage point would make a big difference. Is that possible? Sure. But it would mean, first and foremost, standing by the Affordable Care Act’s cost cutting provisions. And the evidence on that front so far has been mixed.

Cuts to hospitals are taking place, for example. But the insurance industry recently won a reprieve on cuts for its Medicare plans. This is why conservative economists think Obamacare is likely to drive up government health spending—and, eventually, everybody’s health spending—no matter what the projections say. They are convinced Congress will never let the tough, cost-cutting provisions take effect, since those parts of the law inevitably take money out of the pockets of powerful special interests. This isn’t a crazy argument. Medicare’s official actuary has warned, repeatedly, that proposed Medicare cuts may be too harsh for the political system to sustain.

One challenge, then, is showing the mettle it takes to stand by those cuts. But it will take more than that to significantly reduce spending on medical care. The health care industry would have to find new ways to be more efficient—and consumers would have to become more intelligent shoppers—ideally in ways that don’t compromise the quality of care. The Affordable Care Act can be a catalyst for these changes: Among other things, it created a new “Center for Medicare and Medicaid Innovation” for introducing new ways of paying for treatments and supplies. But it’s not so hard to imagine such efforts failing to take hold—and leaving future generations with a huge bill.

One final note: It’s not always the case that spending more on health care is a bad thing. New or more treatments might alleviate suffering, reduce disability, or extend life—all of which have value. Providing insurance to more people, so that they are more secure financially, also has value. The reason to worry about high health care spending is that the extra money America spends doesn’t actually seem to buy America better health care. But, over the long run, the real goal of health care reforms should be a combination of restraining costs and improving quality.

Sometime this spring, Sylvia Burwell will have confirmation hearings to be Secretary of Health and Human Services. Republicans are sure to use those hearings as a chance to highlight everything they think is wrong with Obamacare. That’s fine. The purpose of confirmation hearings, after all, is to establish some democratic accountability. But it would be great if senators from both parties used the moment to ask her about what’s happening with health care costs and what, if anything, the government plans to do about it. As Cutler said a year ago, in an interview with the Harvard Gazette. “We have a lot of control over this, through policies in the Affordable Care Act and Medicare and Medicaid. It’s not easy—no change is ever easy—but if we continue to do the right things, like stressing efficiency and helping people choose less expensive alternatives, then we can make sure this trend continues.”